diff --git a/.gitattributes b/.gitattributes new file mode 100644 index 000000000..8d9ad3005 --- /dev/null +++ b/.gitattributes @@ -0,0 +1,2 @@ +# Generated bundles may preserve whitespace inside dependency template literals. +frontend/dist/assets/*.js -whitespace diff --git a/.github/workflows/Benchmarks.yml b/.github/workflows/Benchmarks.yml index 381e2742d..cdaba191a 100644 --- a/.github/workflows/Benchmarks.yml +++ b/.github/workflows/Benchmarks.yml @@ -3,23 +3,109 @@ on: pull_request_target: branches: [ main ] workflow_dispatch: + inputs: + full_performance: + description: Run the complete downstream performance workflow + required: false + default: false + type: boolean permissions: pull-requests: write + contents: read jobs: bench: - name: Julia ${{ matrix.version }} - ${{ matrix.os }} - ${{ github.event_name }} + if: ${{ github.event_name != 'workflow_dispatch' || !inputs.full_performance }} + name: Julia ${{ matrix.version }} - ${{ matrix.os }} - ${{ matrix.arch }} - ${{ + github.event_name }} runs-on: ${{ matrix.os }} timeout-minutes: 60 + env: + PSE_BENCHMARK_INCLUDE_DOWNSTREAM: "false" strategy: fail-fast: false matrix: version: - - "1" + - "1.12.1" os: - ubuntu-latest + arch: + - x64 steps: - uses: MilesCranmer/AirspeedVelocity.jl@action-v1 with: julia-version: ${{ matrix.version }} bench-on: ${{ github.event.pull_request.head.sha }} - extra-pkgs: https://github.com/PalmStudio/XPalm.jl,https://github.com/VEZY/PlantBiophysics.jl \ No newline at end of file + + plantbiophysics: + if: ${{ github.event_name != 'workflow_dispatch' || !inputs.full_performance }} + name: PlantBiophysics multi-timestep + runs-on: ubuntu-latest + timeout-minutes: 30 + permissions: + contents: read + env: + JULIA_NUM_THREADS: "1" + JULIA_PKG_PRECOMPILE_AUTO: "0" + PSE_PLANTBIOPHYSICS_BENCHMARK_STEPS: "1000" + PSE_PLANTBIOPHYSICS_BENCHMARK_SAMPLES: "5" + PSE_PLANTBIOPHYSICS_FANOUT_SCENES: "20" + steps: + - name: Check out PlantSimEngine + uses: actions/checkout@v7 + with: + ref: ${{ github.event.pull_request.head.sha || github.ref }} + + - name: Check out PlantBiophysics + uses: actions/checkout@v7 + with: + repository: VEZY/PlantBiophysics.jl + ref: multi-plant + path: downstream/PlantBiophysics + + - name: Set up Julia + uses: julia-actions/setup-julia@v3 + with: + version: "1.12.1" + + - name: Cache Julia packages + uses: julia-actions/cache@v3 + + - name: Resolve the PlantBiophysics benchmark environment + shell: julia --project=benchmark --color=yes {0} + run: | + using Pkg + + benchmark_project = joinpath(pwd(), "benchmark", "Project.toml") + include(joinpath(pwd(), "benchmark", "prepare_full_performance_project.jl")) + prepare_plantbiophysics_performance_project!(benchmark_project) + Pkg.activate(joinpath(pwd(), "benchmark")) + Pkg.develop([ + PackageSpec(path=pwd()), + PackageSpec(path=joinpath(pwd(), "downstream", "PlantBiophysics")), + ]) + Pkg.resolve() + Pkg.instantiate() + Pkg.precompile() + + - name: Run the warmed multi-timestep benchmark + run: >- + julia --project=benchmark --color=yes + benchmark/test/runtests.jl + "PlantBiophysics benchmark (API smoke|performance)" + + - name: Persist measurements + if: always() + uses: actions/upload-artifact@v7 + with: + name: plantbiophysics-performance-${{ github.run_id }}-${{ github.run_attempt }} + path: benchmark/results/plantbiophysics-full-latest.csv + if-no-files-found: warn + retention-days: 30 + + full-performance: + if: ${{ github.event_name == 'workflow_dispatch' && inputs.full_performance }} + uses: ./.github/workflows/FullPerformance.yml + with: + xpalm_ref: codex/xpalm-release-regression + plantbiophysics_ref: multi-plant + plantgeom_ref: plantsimengine-multi-plant diff --git a/.github/workflows/FullPerformance.yml b/.github/workflows/FullPerformance.yml new file mode 100644 index 000000000..1a1afcac5 --- /dev/null +++ b/.github/workflows/FullPerformance.yml @@ -0,0 +1,139 @@ +name: Full downstream performance + +on: + schedule: + - cron: "17 2 * * *" + push: + tags: + - "v*" + workflow_dispatch: + inputs: + xpalm_ref: + description: XPalm branch, tag, or commit + required: true + default: main + type: string + plantbiophysics_ref: + description: PlantBiophysics branch, tag, or commit + required: true + default: master + type: string + plantgeom_ref: + description: PlantGeom branch, tag, or commit + required: true + default: plantsimengine-multi-plant + type: string + workflow_call: + inputs: + xpalm_ref: + description: XPalm branch, tag, or commit + required: false + default: main + type: string + plantbiophysics_ref: + description: PlantBiophysics branch, tag, or commit + required: false + default: master + type: string + plantgeom_ref: + description: PlantGeom branch, tag, or commit + required: false + default: plantsimengine-multi-plant + type: string + +permissions: + contents: read + +concurrency: + group: full-downstream-performance-${{ github.ref }} + cancel-in-progress: false + +jobs: + full-downstream-performance: + name: PlantBiophysics and XPalm + runs-on: ubuntu-24.04 + timeout-minutes: 45 + env: + JULIA_NUM_THREADS: "1" + JULIA_PKG_PRECOMPILE_AUTO: "0" + PSE_BENCHMARK_INCLUDE_DOWNSTREAM: "true" + PSE_PLANTBIOPHYSICS_BENCHMARK_STEPS: "8760" + PSE_PLANTBIOPHYSICS_BENCHMARK_SAMPLES: "10" + PSE_PLANTBIOPHYSICS_FANOUT_SCENES: "100" + steps: + - name: Check out PlantSimEngine + uses: actions/checkout@v6 + with: + ref: ${{ github.event.pull_request.head.sha || github.ref }} + + - name: Check out XPalm + uses: actions/checkout@v6 + with: + repository: PalmStudio/XPalm.jl + ref: ${{ inputs.xpalm_ref || 'main' }} + path: downstream/XPalm + + - name: Check out PlantBiophysics + uses: actions/checkout@v6 + with: + repository: VEZY/PlantBiophysics.jl + ref: ${{ inputs.plantbiophysics_ref || 'master' }} + path: downstream/PlantBiophysics + + - name: Check out PlantGeom + uses: actions/checkout@v6 + with: + repository: VEZY/PlantGeom.jl + ref: ${{ inputs.plantgeom_ref || 'plantsimengine-multi-plant' }} + path: downstream/PlantGeom + + - name: Set up Julia + uses: julia-actions/setup-julia@v3 + with: + version: "1.12.1" + + - name: Cache Julia packages + uses: julia-actions/cache@v3 + + - name: Resolve and instantiate the benchmark environment + shell: julia --project=benchmark --color=yes {0} + run: | + using Pkg + + benchmark_project = joinpath(pwd(), "benchmark", "Project.toml") + include(joinpath(pwd(), "benchmark", "prepare_full_performance_project.jl")) + prepare_full_performance_project!(benchmark_project) + Pkg.activate(joinpath(pwd(), "benchmark")) + Pkg.develop([ + PackageSpec(path=pwd()), + PackageSpec(path=joinpath(pwd(), "downstream", "XPalm")), + PackageSpec(path=joinpath(pwd(), "downstream", "PlantBiophysics")), + PackageSpec(path=joinpath(pwd(), "downstream", "PlantGeom")), + ]) + Pkg.resolve() + Pkg.instantiate() + Pkg.precompile() + + - name: Run the PlantBiophysics API and performance benchmark + run: >- + julia --project=benchmark --color=yes + benchmark/test/runtests.jl + "PlantBiophysics benchmark (API smoke|performance)" + + - name: Run the complete XPalm performance and correctness matrix + run: >- + julia --project=benchmark --color=yes + benchmark/test/runtests.jl + "XPalm staged performance profile full" + + - name: Persist measurements and the resolved environment + if: always() + uses: actions/upload-artifact@v4 + with: + name: downstream-full-performance-${{ github.run_id }}-${{ github.run_attempt }} + path: | + benchmark/results/plantbiophysics-full-latest.csv + benchmark/results/xpalm-full-latest.csv + benchmark/Manifest.toml + if-no-files-found: warn + retention-days: 90 diff --git a/.gitignore b/.gitignore index a7d1af9c5..9228d1f28 100644 --- a/.gitignore +++ b/.gitignore @@ -7,5 +7,8 @@ docs/Manifest.toml test/Manifest.toml docs/build/ benchmark/Manifest.toml -frontend/node_modules/ -docs/src/www/simple_dependency_graph.html +benchmark/results/ +/frontend/node_modules/ +/frontend/.vite/ +/frontend/test-results/ +/frontend/playwright-report/ diff --git a/AGENTS.md b/AGENTS.md index 119f35fd3..a660dda6a 100644 --- a/AGENTS.md +++ b/AGENTS.md @@ -1,340 +1,224 @@ # PlantSimEngine Agent And Developer Guide -This file is the maintainer-facing summary of how PlantSimEngine works internally. -It is meant for humans and coding agents making changes to the package. - -PlantSimEngine is a Julia engine for composing process models on either: - -- a single shared status (`ModelMapping{SingleScale}` / legacy `ModelList`) -- a multiscale MTG scene (`GraphSimulation`) - -The package is built around four ideas: - -1. Models declare `inputs_`, `outputs_`, and optionally `dep`. -2. The engine compiles a dependency graph from those declarations. -3. Runtime state is reference-based (`Status`, `RefVector`), so coupling is often aliasing, not copying. -4. Multiscale and multirate configuration can change where an input comes from, how it is transported, and when it is sampled. - -## What The Package Supports - -- Single-scale process composition with automatic soft-dependency inference. -- Hard dependencies declared explicitly and called manually from model code. -- MTG-based multiscale simulations with cross-scale variable mappings. -- Cross-scale scalar sharing through shared `Ref`s. -- Cross-scale multi-node sharing through `RefVector`s. -- Cross-scale writes, where a variable computed at one scale is materialized as an input at another scale. -- Same-scale variable aliasing and renaming. -- Cycle breaking through `PreviousTimeStep`. -- Multi-rate execution through `ModelSpec`, `ClockSpec`, and temporal policies. -- Explicit or inferred `InputBindings` between producers and consumers. -- Meteo resampling/aggregation per model in multi-rate MTG runs. -- Output routing (`:canonical` vs `:stream_only`) and online output export (`OutputRequest`). -- Parallel single-scale execution when model traits allow it. - -## Core Runtime Objects - -### Processes and models - -- All models subtype `AbstractModel`. -- `@process` creates an abstract process type such as `AbstractGrowthModel`. -- Process identity comes from the abstract process type, not the concrete model name. -- The model execution contract is: +PlantSimEngine composes process models over a unified composite-model/object registry. +The repository contains one scenario compiler and runtime: the composite-model/object +API. + +## Core Model Contract + +- Every model subtypes `AbstractModel`. +- `@process` defines the abstract process type. +- `process(model)` identifies the process. +- `inputs_(model)` and `outputs_(model)` declare status variables. +- `environment_inputs_(model)` and `environment_outputs_(model)` declare environment + variables. +- `dep(model)` optionally returns model-author defaults using `Input(...)` and + `Call(...)`. +- Kernels implement: ```julia -PlantSimEngine.run!(model, models, status, meteo, constants, extra) +PlantSimEngine.run!(model, status, environment, constants, context) ``` -- `inputs_(model)` and `outputs_(model)` are the authoritative declarations. -- `variables(model)` is `merge(inputs_(model), outputs_(model))`. -- Do not rely on a variable being both an input and an output under the same name: `merge` means the later declaration wins. - -### Status - -- `Status` is a wrapper around a `NamedTuple` of `Ref`s. -- Reading a field dereferences it. Writing a field mutates the underlying `Ref`. -- This aliasing behavior is intentional and is the basis of most coupling. -- In single-scale runs, vector-valued user inputs are flattened to one timestep value and updated per timestep with `set_variables_at_timestep!`. - -### RefVector - -- `RefVector` is an `AbstractVector` of `Base.RefValue`s. -- It is used when one model input must see a vector of references coming from many statuses. -- Reading a `RefVector` dereferences each underlying status cell. -- Writing into a `RefVector` mutates the source statuses. -- `RefVector` order follows MTG traversal order during initialization, not a semantic plant order. - -### Mapping wrappers - -- `MultiScaleModel` wraps one model plus a multiscale mapping declaration. -- `ModelSpec` wraps one model plus scenario-level runtime configuration: - `multiscale`, `timestep`, `input_bindings`, `meteo_bindings`, `meteo_window`, `output_routing`, and `scope`. -- `ModelMapping` is the normalized mapping container used by current entry points. -- Legacy `ModelList` still exists, but it is compatibility plumbing and should not be treated as the main abstraction for new work. - -### Simulation wrappers - -- `DependencyGraph` holds root dependency nodes plus unresolved dependencies. -- `GraphSimulation` holds the MTG, statuses, status templates, reverse mappings, dependency graph, models, model specs, outputs, and temporal state. - -## Dependency Graph Under The Hood +Read the current model's parameters directly from `model`. `context` is a +`RunContext` and provides `run_call!`, `call_targets`, and lifecycle access. -### Hard dependencies +## CompositeModel Structure -- Hard dependencies are declared with `dep(::ModelType)`. -- A hard dependency means: "this model directly calls another model from inside its own `run!` implementation." -- Hard dependencies are represented by `HardDependencyNode`. -- They are executed manually by the parent model. The runtime does not automatically recurse into hard dependencies. -- Hard dependencies can be same-scale or explicitly multiscale. +- `CompositeModel` owns a `ObjectRegistry`, model applications, instances, and an + environment. +- `Object` is one runtime entity with stable `ObjectId`, labels, parent, + geometry, and `Status`. +- Plant architecture is not prescribed. Users choose scales and topology. +- `CompositeModelTemplate` and `ObjectInstance` reuse the same model definitions across + several plants or objects. +- `Override` replaces one application model for selected objects without + splitting the logical application. +- `objects_from_mtg` and `CompositeModel(mtg; ...)` adapt MTG topology into the same + registry. -Important nuance: +## Model Applications -- A hard dependency does not become an independent soft-dependency node under the parent. -- But it still matters for graph construction, because the graph compiler aggregates the root model's hard-dependency subtree when computing that root's effective inputs and outputs. -- In multiscale graph building, if another model depends on a process that exists only as a nested hard dependency, the code resolves that dependency back to the master soft node that owns that hard subtree. +Use one configuration grammar: -So "hard dependencies do not directly participate in the soft graph" is true for execution structure, but false if interpreted as "their IO is irrelevant to graph compilation." - -### Soft dependencies - -- Soft dependencies are inferred by matching model inputs against outputs. -- Matching is name-based after variable flattening, not based on a richer semantic contract. -- Same-scale soft dependencies are built after hard-dependency trees are known. -- A process cannot also list one of its hard dependencies as a soft dependency. -- `PreviousTimeStep` variables are removed from current-step soft dependency inference. -- Soft dependencies are represented by `SoftDependencyNode`. -- A soft node may have multiple parents. -- A node is considered runnable once all of its parent nodes have already run for the current traversal. -- If no producer output matches an input, no soft edge is added. Soft-edge construction does not itself fail on missing producers. - -### Single-scale graph build - -Single-scale graph construction is: - -1. Build `HardDependencyNode`s for each declared process. -2. Attach explicit hard-dependency children under their parents. -3. Traverse each hard-dependency root and collect its effective inputs and outputs. -4. Build one `SoftDependencyNode` per hard-dependency root. -5. Infer parent and child links by matching inputs to outputs. - -### Multiscale graph build - -Multiscale graph construction is more involved: - -1. Normalize the user mapping into `ModelMapping`. -2. Build per-scale hard-dependency graphs. -3. Resolve multiscale hard dependencies declared across scales. -4. Compute per-scale effective inputs and outputs for each hard-dependency root. -5. Build one `SoftDependencyNode` per root process per scale. -6. Compile mapped variables and reverse mappings. -7. Infer same-scale soft dependencies. -8. Infer cross-scale soft dependencies from mapped variables and reverse mappings. -9. If a dependency points to a nested hard dependency, redirect it to the owning soft node. -10. Check the final graph for cycles. - -### Cycle handling - -- The graph is expected to be acyclic. -- The official way to break a same-step cycle is `PreviousTimeStep`. -- `PreviousTimeStep` breaks cycles by suppressing current-step edge creation, not by adding special scheduler logic. -- In multiscale runs, cycle detection happens after the cross-scale graph is assembled. -- Single-scale `dep(...)` relies mostly on builder-time guards. Multiscale `dep(mapping)` also runs an explicit global cycle check on the final soft graph. - -## Multiscale Mapping Model - -### Mapping modes - -PlantSimEngine distinguishes three mapping modes: - -- `SingleNodeMapping(scale)`: one scalar value is read from one source scale. -- `MultiNodeMapping(scales)`: one input reads a vector of values from many source nodes. -- `SelfNodeMapping()`: a source scale must expose a scalar reference to itself so other scales can share it. - -The runtime carrier is `MappedVar`, which stores: - -- the mapping mode -- the local variable name -- the source variable name -- the resolved default value +```julia +ModelSpec(model; name=:application, on=selector, inputs=(...), calls=(...), every=Dates.Hour(1), environment=Environment(...)) +``` -### Supported mapping forms +- `on` selects where the model runs. +- `inputs` declares value dependencies. +- `calls` declares manually executable hard dependencies. +- `Updates(:x; after=:producer)` orders intentional duplicate writers. +- `output_routing=(x=:stream_only,)` excludes an output from canonical + ownership while retaining its stream. -These are the important user-level forms and what they become internally: +## Selectors -| User form | Meaning | Runtime shape | -| --- | --- | --- | -| `:x => :Plant` | scalar read from one `:Plant` node | shared `Ref` | -| `:x => (:Plant => :y)` | scalar read with renaming | shared `Ref` | -| `:x => [:Leaf]` | vector read from all `:Leaf` nodes | `RefVector` | -| `:x => [:Leaf, :Internode]` | vector read from several scales | `RefVector` | -| `:x => [:Leaf => :a, :Internode => :b]` | vector read with per-scale renaming | `RefVector` | -| `PreviousTimeStep(:x) => ...` | lagged mapping, excluded from same-step dependency build | lagged input | -| `PreviousTimeStep(:x)` | pure cycle-breaking marker | local/default value | -| `:x => (Symbol(\"\") => :y)` | same-scale rename | `RefVariable` alias | +Multiplicity: + +- `One(...)` +- `OptionalOne(...)` +- `Many(...)` + +Scope and topology: -### Mapping compilation pipeline +- `SceneScope()` +- `Self()`: the current object +- `Subtree()`: the current object and its descendants +- `SelfPlant()`: the current plant instance/root +- `Ancestor(...)` +- `Scope(name)` +- `Relation(...)` -`mapped_variables(...)` does not just mirror user syntax. It compiles it. +Use keyword criteria for object labels: `kind=:plant`, `species=:oil_palm`, +`scale=:Leaf`, and `name=:leaf_1`. -The main passes are: +`Self()` never means the model, species, or plant unless the current object is +itself that plant. -1. Start from effective per-scale inputs and outputs collected from hard-dependency roots. -2. Add variables that are outputs of one scale but must appear as inputs at another scale. -3. Convert scalar cross-scale reads into self-mapped outputs on the source scale so one shared `Ref` exists. -4. Resolve default values recursively back to the ultimate producer. -5. Convert mapping descriptors into runtime carriers: - - scalar mappings become shared `Ref`s - - multi-node mappings become empty `RefVector`s - - same-scale renames become `RefVariable` +## Value Coupling -### Reverse mapping and status wiring +The compiler resolves `ModelSpec(...; inputs=...)` to reference carriers: -- Reverse mapping is computed before the reference conversion pass. -- Reverse mapping answers: "when a source node is initialized, which target scale/vector inputs should receive a reference to this source variable?" -- Reverse mapping excludes scalar `SingleNodeMapping` edges when `all=false`, because scalar sharing is already handled by shared `Ref`s. +- one source uses a shared `Ref`; +- many homogeneous sources use `RefVector`; +- heterogeneous sources use `ObjectRefVector`; +- temporal policies read typed output streams. -During `init_node_status!`: +Use `Diagnostics.input_carrier`, `Diagnostics.input_value`, `Diagnostics.explain_bindings`, and +`Diagnostics.has_reference_carrier` instead of inspecting internal fields. -1. A copy of the scale template is made. -2. `:node => Ref(node)` is injected. -3. Remaining uninitialized variables may be filled from MTG attributes. -4. The template becomes a `Status`. -5. The status is pushed into `statuses[scale]`. -6. If this node feeds any downstream `RefVector`, its `Ref`s are pushed into those target vectors. -7. The status is stored on the MTG node under `:plantsimengine_status`. +Same-object input/output matches are inferred when unique. Cross-object +coupling should be explicit with `ModelSpec(...; inputs=...)`. -### Copies vs references +## Hard Calls -- MTG attribute initialization copies plain values into the status. -- If the MTG attribute itself is already a `Ref`, that `Ref` is preserved. -- The runtime cannot create a live reference directly into a dict-backed MTG attribute. -- Cross-scale sharing is reference-based once the status exists. +Hard dependencies are parent-controlled: -## Multi-Rate Runtime - -Multi-rate behavior is layered on top of the multiscale MTG runtime. +1. Declare them with model-level `Call(...)` or scenario-level `ModelSpec(...; calls=...)`. +2. Execute all resolved targets with `run_call!(context, name)`. It always + returns a vector-like `CallTargets` collection. +3. For selective or iterative execution, inspect `call_targets(context, name)` + and execute individual `CallTarget`s with `run_call!`. -### Timing and policies +`run_call!` defaults to `publish=false`, which is appropriate for iterative +trial states. Publish only the accepted state with `publish=true`. -- `timespec(model)` defines the model's default clock. The default is `ClockSpec(1.0, 0.0)`. -- `ModelSpec.timestep` can override runtime clock selection. -- `output_policy(model)` declares per-output temporal policy defaults. - -Supported schedule policies are: - -- `HoldLast()`: use the latest available producer value. -- `Interpolate()`: interpolate or hold/extrapolate producer streams. -- `Integrate()`: reduce values over the consumer window, default reducer is `SumReducer()`. -- `Aggregate()`: reduce values over the consumer window, default reducer is `MeanReducer()`. +Applications used exclusively as call targets are not run by the root +scheduler and do not receive inferred soft bindings. -### ModelSpec configuration surface +## Time -`ModelSpec` is the configuration point for scenario-specific runtime behavior. +- `ModelSpec(...; every=Dates.Period)` configures application cadence. +- `timespec(model)` provides a model default. +- `timestep_hint(model)` validates compatibility when cadence comes from the + environment base step. +- `HoldLast`, `Interpolate`, `Integrate`, and `Aggregate` configure temporal + input policies. +- `PreviousTimeStep(:x)` breaks same-step cycles. -It can define: +Dates periods are converted using meteorology `duration`. Model code should not +know its scenario timestep unless the scientific model explicitly requires it. -- `multiscale`: mapping declaration -- `timestep`: runtime clock -- `input_bindings`: explicit producer selection for consumer inputs -- `meteo_bindings`: per-model weather aggregation -- `meteo_window`: weather window selection strategy -- `output_routing`: `:canonical` or `:stream_only` -- `scope`: `:global`, `:self`, `:plant`, `:scene`, `ScopeId`, or callable +## Environment -### Input binding inference +- `Environment(...)` configures provider selection and source remapping. +- Global meteorology and spatial backends use the same model-facing contract. +- Spatial object-to-environment handles are compiled and cached. +- `move_object!`, `update_geometry!`, or + `mark_environment_binding_dirty!` invalidate affected bindings. +- `run_call!(context, name; environment=trial_state)` samples transient + backend-specific state through each target's compiled handle. +- `environment_outputs_` declares environment variables a controller may commit, and + `commit_environment!` commits only the accepted state. -- If explicit `InputBindings` are absent, the package tries to infer bindings from the dependency graph and mapping. -- Unique same-scale producers win first. -- Unique cross-scale producers are accepted when unambiguous. -- Existing multiscale mapping hints can disambiguate some cross-scale cases. -- Ambiguity is an error and must be resolved explicitly. - -### Runtime sequence in multi-rate MTG mode - -For each dependency node and each status at that node's scale: - -1. Decide whether the model should run at the current time according to its clock. -2. Resolve consumer inputs from temporal state with explicit or inferred bindings. -3. Sample or aggregate meteo for the model. -4. Call the model's `run!`. -5. Publish outputs back into temporal caches and streams. -6. Materialize any requested online exports. - -Important consequences: - -- In non-multirate MTG runs, cross-scale coupling is mostly direct aliasing through shared refs. -- In multirate MTG runs, temporal state can overwrite consumer inputs just before execution. -- Multi-rate MTG runs are currently forced to sequential execution. - -## Configurations Developers Must Keep In Mind - -A variable seen by a model may be in any of these supported configurations: +## Lifecycle -- Plain local status value initialized by the user. -- Plain local status value initialized from MTG node attributes. -- Output computed locally at the same scale. -- Same-scale alias of another local variable through `RefVariable`. -- Scalar value mapped from another scale through a shared `Ref`. -- Vector of references mapped from one or many other scales through `RefVector`. -- Output computed at one scale and written into another scale, which means it is injected as an input on the receiving scale during mapping compilation. -- Value marked as `PreviousTimeStep`, which removes it from same-step dependency inference. -- Input resolved from a hard dependency that is called manually inside another model. -- Input resolved from temporal streams instead of directly from the current status value. -- Input bound explicitly with `InputBindings`. -- Input bound implicitly by inference from producers and mappings. -- Input sampled with `HoldLast`, `Interpolate`, `Integrate`, or `Aggregate`. -- Output published canonically into status state. -- Output published as `:stream_only`, meaning it participates in temporal streams but not canonical output ownership. -- Value partitioned by scope (`:global`, `:self`, `:plant`, `:scene`, or custom scope function). +- `add_organ!` is the high-level operation for MTG-backed growth. It creates + the node, reuses the model's MTG status policy, applies initial values, + attaches the status, and registers the object. +- `register_object!`, `remove_object!`, and `reparent_object!` mutate topology. +- Use `register_object!` directly only when the caller already owns a fully + initialized `Object`. +- Structural changes refresh application targets, value carriers, call + targets, writer checks, and schedules after the application that made the + change; new objects can run applications that remain later in the timestep. +- Geometry changes refresh only affected environment bindings when possible. +- Removed objects keep their historical output samples. + +## Outputs -When changing dependency, mapping, or runtime code, assume all of these modes can exist in the same simulation. - -## Execution Semantics And Important Caveats - -- Soft-dependency order controls model order. MTG topology does not define execution order within a scale. -- Within one scale, execution order follows the order of `statuses[scale]`, which comes from MTG traversal at initialization time. -- `SingleNodeMapping` assumes the source node is unique at runtime. The mapping layer does not enforce uniqueness. -- `RefVector` ordering is traversal order, not a guaranteed biological ordering. -- Hard dependencies are manual calls. If model code stops calling them, the declared hard dependency no longer executes. -- Hard dependencies still influence graph compilation through their effective inputs and outputs. -- Multiscale redirection from nested hard dependencies back to the owning soft node is implemented with upward walking through parent links and a defensive depth guard. Treat that path as fragile. -- MTG topology changes after `init_statuses` leave `statuses`, node attributes, and populated `RefVector`s stale. Reinitialize after topology changes. -- Same-scale renaming does not create a graph-wide shared ref. It creates a per-status alias. -- `parent_vars` is dependency metadata, not a full provenance graph, and in multiscale builds it can be overwritten when a node has both same-scale and cross-scale parents. -- Duplicate canonical publishers for one `(scale, variable)` are invalid in multi-rate mode unless non-canonical producers are marked `:stream_only`. -- User `extra` arguments are not allowed in MTG runs because `GraphSimulation` already occupies that slot. -- String scale names still work in many places but are deprecated. Prefer `Symbol` scales. -- `ModelList` is deprecated as the primary API. Prefer `ModelMapping`. -- `run_node_multiscale!` currently uses `node.simulation_id[1]` as the visitation guard. Treat that code carefully if you touch traversal semantics. -- Some variable collection helpers use set-like flattening, so collection order is not always stable. Do not attach semantics to incidental variable ordering. +- `run!(model; outputs=:none)` starts a fresh timeline and returns + `Simulation`; use `outputs=:all` or output requests to retain streams. +- `continue!(simulation)` and `step!(simulation)` advance the same timeline. +- `final_state(simulation)` returns the latest one-object status snapshot; + pass an object id or selector for multi-object simulations. +- `outputs(sim)` exposes retained typed streams. +- `OutputRequest` selects retained/resampled outputs. +- `collect_outputs(sim)` materializes output rows. +- `Diagnostics.explain_output_retention(sim)` reports why each stream is retained. + +Streams are keyed by application, object, and variable so repeated processes do +not overwrite each other. + +## Performance Rules + +- Keep model parameters and status values generic; do not force `Float64`. +- Preserve concrete model, status, carrier, and stream types. +- Do not copy values when a reference carrier is sufficient. +- Keep dynamic dispatch at compiled batch boundaries, not per object. +- Preserve cached hard-call targets and homogeneous execution batches. +- Test allocations for hot loops that run over many organs. ## High-Signal Files -- `src/PlantSimEngine.jl`: module layout and exports. -- `src/Abstract_model_structs.jl`: `AbstractModel` and `process`. -- `src/processes/process_generation.jl`: `@process`. -- `src/processes/models_inputs_outputs.jl`: model declarations and runtime traits. -- `src/variables_wrappers.jl`: `UninitializedVar`, `PreviousTimeStep`, `RefVariable`. -- `src/component_models/Status.jl`: reference-based status container. -- `src/component_models/RefVector.jl`: vector of references. -- `src/dependencies/*`: hard and soft dependency graph construction and traversal. -- `src/mtg/MultiScaleModel.jl`: mapping syntax normalization. -- `src/mtg/ModelSpec.jl`: runtime configuration wrapper. -- `src/mtg/mapping/*`: mapping compilation, reverse mapping, initialization helpers. -- `src/mtg/initialisation.jl`: status creation and MTG wiring. -- `src/mtg/GraphSimulation.jl`: simulation wrapper. -- `src/time/multirate.jl`: clocks, policies, temporal storage types. -- `src/time/runtime/*`: input resolution, scopes, publishers, meteo sampling, output export. -- `src/run.jl`: single-scale and multiscale execution. - -## Practical Rule For Future Changes - -If you change dependency, mapping, or runtime behavior, re-check all of these questions: - -1. Does it still work for both single-scale and MTG runs? -2. Does it preserve aliasing semantics for `Status` and `RefVector`? -3. Does it preserve the distinction between hard dependencies and soft dependencies? -4. Does it still handle scalar mappings, vector mappings, same-scale aliasing, and cross-scale writes? -5. Does it still behave correctly with `PreviousTimeStep`? -6. Does it still work when input bindings are inferred instead of explicit? -7. Does it still work in multi-rate mode with temporal policies and scoped streams? -8. Does it remain correct if the producer is nested under a hard dependency? +- `src/composite_model_api.jl`: dependency-ordered include boundary for the sole + CompositeModel/Object compiler and runtime. +- `src/composite_model/registry_topology.jl`: objects, registry, templates, + instances, overrides, topology, and lifecycle ownership. +- `src/composite_model/selectors.jl`: selector normalization and resolution. +- `src/composite_model/compilation.jl`: applications, carriers, calls, writer + validation, schedules, and structured compilation explanations. +- `src/composite_model/environment_bindings.jl`: global/spatial environment + bindings and invalidation. +- `src/composite_model/runtime_outputs.jl`: execution, temporal streams, hard-call + publication, retention, and output collection. +- `src/composite_model/scenario_dsl.jl`: small scenario construction helpers. +- `src/ModelSpec.jl`: model application configuration. +- `src/component_models/Status.jl`: reference-based status. +- `src/component_models/RefVector.jl`: homogeneous reference vectors. +- `src/time/multirate.jl`: clocks and temporal policies. +- `src/time/runtime/clocks.jl`: Dates-based timing. +- `src/time/runtime/environment_sampling.jl`: model-facing environment sampling. +- `src/time/runtime/environment_backends.jl`: environment backend contract. +- `test/test-unified-model-object-api.jl`: broad integration coverage. +- `test/test-model-*.jl`: focused CompositeModel/Object behavioral contracts. + +## Change Checklist + +When changing compilation or runtime behavior, verify: + +1. one object and many objects; +2. same-object and cross-object inputs; +3. `One`, `OptionalOne`, and `Many`; +4. hard calls and iterative publication; +5. duplicate writers and `Updates`; +6. multirate policies and `PreviousTimeStep`; +7. global and spatial environments; +8. object creation, removal, reparenting, and movement; +9. templates, instances, and overrides; +10. generic numeric types and allocation-sensitive execution. + +## API evolution policy + +This project is in active development and has no stable public API yet. + +When implementing API changes: + +- Do not preserve backward compatibility unless explicitly requested. +- Do not add deprecated aliases, compatibility wrappers, fallback methods, old keyword support, migration layers, or dual APIs. +- Prefer a clean breaking change over supporting both old and new APIs. +- Update all internal call sites, tests, and documentation to the new API. +- Remove obsolete code instead of keeping it. +- If existing tests fail because they expect the old API, update the tests to match the new API. +- Before adding compatibility code, stop and ask for confirmation. diff --git a/CHANGELOG.md b/CHANGELOG.md index 95527f37f..2bc275bcf 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -1,5 +1,32 @@ # Changelog +## v0.15.0 + +### Breaking changes + +- Environment backends now compile an opaque per-target handle with + `bind_environment`. Accepted state is committed explicitly with + `commit_environment!`, while provider-aware trial state is passed with + `run_call!(context, name; environment=state)`. The former support/scatter, + scoped override, and context-level meteorology APIs were removed. +- Hard dependencies now execute through + `run_call!(context::RunContext, name::Symbol; ...)`, which executes every + selector-resolved target and always returns a vector-like `CallTargets` + collection. +- The singular hard-call accessor and string-name hard-call methods were + removed. Use `only(call_targets(context, :name))` for fine-grained access to + a `One` dependency. +- Direct recursive dependency execution is no longer supported. Model kernels + must run inside a compiled `CompositeModel` and receive a `RunContext`. + +### Added + +- `CallTargets`, a cached `AbstractVector` view over compiled hard-call targets + that is allocation-free to retrieve. +- `run_call!(context, name)` for the common execute-all operation while + retaining `run_call!(target::CallTarget)` for selective, per-target, and + iterative control. + ## v0.14.1 Changes in this section are based on the git history since [`v0.14.0`](https://github.com/VirtualPlantLab/PlantSimEngine.jl/releases/tag/v0.14.0), corresponding to the GitHub compare view for [`v0.14.1`](https://github.com/VirtualPlantLab/PlantSimEngine.jl/compare/v0.14.0...v0.14.1). @@ -27,7 +54,7 @@ working with PlantSimEngine internals. edges, variable dependency edges, scale filters, relationship filters, search, overview/detail modes, and an inspector. - An interactive browser-based graph editor through `edit_graph`, backed by a - local `HTTP.jl` server and WebSocket session. + local `HTTP.jl` server and WebSocket session. - The live graph editor runs as a package extension that depends on `HTTP.jl`; static graph visualization is available without loading `HTTP`. @@ -48,7 +75,7 @@ working with PlantSimEngine internals. - Visualization of required initialization values and graph diagnostics even when a mapping is incomplete or cyclic. - A new documentation page for graph visualization and editing: - [`docs/src/step_by_step/graph_visualization_editor.md`](docs/src/step_by_step/graph_visualization_editor.md). + [`docs/src/guides/graph_visualizer_editor.md`](docs/src/guides/graph_visualizer_editor.md). - Playwright end-to-end tests for the browser editor and new Julia tests for the static graph viewer and editor extension. - A local `plantsimengine` Codex skill describing the package architecture and @@ -80,7 +107,7 @@ and substantially expands the documentation. The main user-facing breaking change in this release is the move toward `Symbol`-based scale names in mappings and multi-scale configuration. Code that still uses string scales such as `"Leaf"` or `"Plant"` should be updated to use -symbols such as `:Leaf` and `:Plant`, especially in `ModelMapping(...)`, +symbols such as `:Leaf` and `:Plant`, especially in `PlantSimEngine.ModelMapping(...)`, `MultiScaleModel(...)`, and explicit multi-rate bindings. `ModelList` is also on the deprecation path in favor of `ModelMapping`, so this release is a good time to migrate mapping code to the newer API. @@ -95,7 +122,7 @@ to migrate mapping code to the newer API. `InputBindings`, `MeteoBindings`, `MeteoWindow`, `OutputRouting`, and `ScopeModel`. - New model traits for multi-rate inference and defaults: - `output_policy`, `timestep_hint`, and `meteo_hint`. + `output_policy`, `timestep_hint`, and `environment_hint`. - New export API for resampled output streams with `OutputRequest(...)` and `collect_outputs(...)`. - New debugging/introspection helpers: @@ -136,12 +163,12 @@ to migrate mapping code to the newer API. ### Deprecated -- `run!(::ModelList, ...)` is deprecated. Use `run!(ModelMapping(...), ...)` +- `run!(::ModelList, ...)` is deprecated. Use `run!(PlantSimEngine.ModelMapping(...), ...)` instead. - `run!` with collections of `ModelList` is deprecated. Use collections of `ModelMapping` instead. - `run!(mtg, mapping::AbstractDict, ...)` is deprecated. Construct a - `ModelMapping(...)` first, or call `run!(mtg, ModelMapping(mapping), ...)`. + `PlantSimEngine.ModelMapping(...)` first, or call `run!(mtg, PlantSimEngine.ModelMapping(mapping), ...)`. - String scale names are deprecated in multi-scale mapping APIs. Use `Symbol` scales such as `:Leaf` instead of `"Leaf"`. - `ModelList` remains available for now but is being phased out in favor of @@ -152,7 +179,7 @@ to migrate mapping code to the newer API. #### 1. Replace ad hoc mappings with `ModelMapping` If you previously used `ModelList(...)` directly for single-scale runs, or a -plain `Dict` for MTG runs, migrate to `ModelMapping(...)`. +plain `Dict` for MTG runs, migrate to `PlantSimEngine.ModelMapping(...)`. Before: @@ -172,13 +199,13 @@ mapping = Dict( After: ```julia -leaf = ModelMapping( +leaf = PlantSimEngine.ModelMapping( process1 = Process1Model(), process2 = Process2Model(), status = (x = 1.0,), ) -mapping = ModelMapping( +mapping = PlantSimEngine.ModelMapping( :Leaf => (ToyAssimModel(),), :Plant => (ToyGrowthModel(),), ) @@ -192,7 +219,7 @@ When a model should run at a cadence different from the meteo, wrap it in Typical pattern: ```julia -mapping = ModelMapping( +mapping = PlantSimEngine.ModelMapping( :Leaf => ( ModelSpec(HourlyLeafModel()) |> TimeStepModel(1.0), ), @@ -239,7 +266,7 @@ If your mappings still use string scales, migrate them to symbols. Before: ```julia -mapping = ModelMapping( +mapping = PlantSimEngine.ModelMapping( "Leaf" => (ToyAssimModel(),), ) @@ -250,7 +277,7 @@ MultiScaleModel([:A => "Leaf"]) After: ```julia -mapping = ModelMapping( +mapping = PlantSimEngine.ModelMapping( :Leaf => (ToyAssimModel(),), ) @@ -289,7 +316,7 @@ For reusable models, it is now often worth defining: - `output_policy(::Type{<:MyModel})` to describe the natural aggregation rule for a produced variable, - `timestep_hint(::Type{<:MyModel})` to declare valid/preferred cadences, -- `meteo_hint(::Type{<:MyModel})` to declare default weather aggregation rules. +- `environment_hint(::Type{<:MyModel})` to declare default environment aggregation rules. This is optional, but it makes inference more useful and error messages more actionable. diff --git a/Project.toml b/Project.toml index 364c8be5d..59f321b62 100644 --- a/Project.toml +++ b/Project.toml @@ -1,22 +1,18 @@ name = "PlantSimEngine" uuid = "9a576370-710b-4269-adf9-4f603a9c6423" -version = "0.14.1" +version = "0.15.0" authors = ["Rémi Vezy and contributors"] [deps] -AbstractTrees = "1520ce14-60c1-5f80-bbc7-55ef81b5835c" CSV = "336ed68f-0bac-5ca0-87d4-7b16caf5d00b" -DataAPI = "9a962f9c-6df0-11e9-0e5d-c546b8b5ee8a" DataFrames = "a93c6f00-e57d-5684-b7b6-d8193f3e46c0" Dates = "ade2ca70-3891-5945-98fb-dc099432e06a" -FLoops = "cc61a311-1640-44b5-9fba-1b764f453329" InteractiveUtils = "b77e0a4c-d291-57a0-90e8-8db25a27a240" JSON = "682c06a0-de6a-54ab-a142-c8b1cf79cde6" Markdown = "d6f4376e-aef5-505a-96c1-9c027394607a" MultiScaleTreeGraph = "dd4a991b-8a45-4075-bede-262ee62d5583" PlantMeteo = "4630fe09-e0fb-4da5-a846-781cb73437b6" Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c" -SHA = "ea8e919c-243c-51af-8825-aaa63cd721ce" Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2" Tables = "bd369af6-aec1-5ad0-b16a-f7cc5008161c" Term = "22787eb5-b846-44ae-b979-8e399b8463ab" @@ -28,20 +24,16 @@ HTTP = "cd3eb016-35fb-5094-929b-558a96fad6f3" PlantSimEngineGraphEditorExt = "HTTP" [compat] -AbstractTrees = "0.4" CSV = "0.10" -DataAPI = "1.15" DataFrames = "1" Dates = "1.10" -FLoops = "0.2" HTTP = "1, 2.0" InteractiveUtils = "1.10" -JSON = "1" +JSON = "1.6.1" Markdown = "1.10" MultiScaleTreeGraph = "0.15.1" PlantMeteo = "0.8.2" Random = "1.10" -SHA = "0.7.0" Statistics = "1.10" Tables = "1" Term = "2" diff --git a/README.md b/README.md index 39ae36e10..288e5c037 100644 --- a/README.md +++ b/README.md @@ -9,369 +9,228 @@ [![DOI](https://zenodo.org/badge/571659510.svg)](https://zenodo.org/badge/latestdoi/571659510) [![JOSS](https://joss.theoj.org/papers/137e3e6c2ddc349bec39e06bb04e4e09/status.svg)](https://joss.theoj.org/papers/137e3e6c2ddc349bec39e06bb04e4e09) -- [PlantSimEngine](#plantsimengine) - - [Overview](#overview) - - [Unique Features](#unique-features) - - [Automatic Model Coupling](#automatic-model-coupling) - - [Flexibility with Precision Control](#flexibility-with-precision-control) - - [Multi-rate Execution](#multi-rate-execution) - - [Batteries included](#batteries-included) - - [Ask Questions](#ask-questions) - - [Installation](#installation) - - [Example usage](#example-usage) - - [Simple example](#simple-example) - - [Model coupling](#model-coupling) - - [Multiscale modelling](#multiscale-modelling) - - [Multi-rate modelling](#multi-rate-modelling) - - [Projects that use PlantSimEngine](#projects-that-use-plantsimengine) - - [Performance](#performance) - - [Make it yours](#make-it-yours) +PlantSimEngine is a Julia framework for composing soil-plant-atmosphere +simulations from reusable process models. -## Overview +A modeler writes generic kernels with: -`PlantSimEngine` is a comprehensive framework for building models of the soil-plant-atmosphere continuum. It includes everything you need to **prototype, evaluate, test, and deploy** plant/crop models at any scale, with a strong emphasis on performance and efficiency, so you can focus on building and refining your models. +- `inputs_` declarations using `Required(T)` or `Default(value)` +- `outputs_` +- optional `dep`, `timespec`, `output_policy`, `environment_inputs_`, and + `environment_outputs_` traits +- `run!(model, status, environment, constants, context)` -**Why choose PlantSimEngine?** +A simulation author assembles those kernels on objects with `CompositeModel`, +`Object`, and one direct application constructor: -- **Simplicity**: Write less code, focus on your model's logic, and let the framework handle the rest. -- **Modularity**: Each model component can be developed, tested, and improved independently. Assemble complex simulations by reusing pre-built, high-quality modules. -- **Standardisation**: Clear, enforceable guidelines ensure that all models adhere to best practices. This built-in consistency means that once you implement a model, it works seamlessly with others in the ecosystem. -- **Optimised Performance**: Don't re-invent the wheel. Delegating low-level tasks to PlantSimEngine guarantees that your model will benefit from every improvement in the framework. Enjoy faster prototyping, robust simulations, and efficient execution using Julia's high-performance capabilities. - -## Unique Features - -### Automatic Model Coupling - -**Seamless Integration:** PlantSimEngine leverages Julia's multiple-dispatch capabilities to automatically compute the dependency graph between models. This allows researchers to effortlessly couple models without writing complex connection code or manually managing dependencies. - -**Intuitive Multi-Scale Support:** The framework naturally handles models operating at different scales—from organelle to ecosystem—connecting them with minimal effort and maintaining consistency across scales. - -### Flexibility with Precision Control - -**Effortless Model Switching:** Researchers can switch between different component models using a simple syntax without rewriting the underlying model code. This enables rapid comparison between different hypotheses and model versions, accelerating the scientific discovery process. - -### Multi-rate Execution - -**Mix model cadences in one simulation:** PlantSimEngine can run models at different timesteps within the same MTG simulation. This makes it possible to combine, for example, hourly leaf processes with daily plant balances and weekly reporting models without writing custom scheduling glue. - -**Explicit bindings between rates:** `TimeStepModel`, `InputBindings`, `MeteoBindings`, `ScopeModel`, and `OutputRequest` let you declare how model inputs, meteorology, and exported outputs should behave when rates differ. - -## Batteries included - -- **Automated Management**: Seamlessly handle inputs, outputs, time-steps, objects, and dependency resolution. -- **Iterative Development**: Fast and interactive prototyping of models with built-in constraints to avoid errors and sensible defaults to streamline the model writing process. -- **Control Your Degrees of Freedom**: Fix variables to constant values or force to observations, use simpler models for specific processes to reduce complexity. -- **Multi-Rate Scheduling**: Combine hourly, daily, and coarser models in the same simulation, with explicit policies for input aggregation and meteorological sampling. -- **High-Speed Computations**: Achieve impressive performance with benchmarks showing operations in the 100th of nanoseconds range for complex models (see this [benchmark script](https://github.com/VirtualPlantLab/PlantSimEngine.jl/blob/main/examples/benchmark.jl)). -- **Parallelize and Distribute Computing**: Out-of-the-box support for sequential, multi-threaded, or distributed computations over objects, time-steps, and independent processes, thanks to [Floops.jl](https://juliafolds.github.io/FLoops.jl/stable/). -- **Scale Effortlessly**: Methods for computing over objects, time-steps, and [Multi-Scale Tree Graphs](https://github.com/VEZY/MultiScaleTreeGraph.jl). -- **Compose Freely**: Use any types as inputs, including [Unitful](https://github.com/PainterQubits/Unitful.jl) for unit propagation and [MonteCarloMeasurements.jl](https://github.com/baggepinnen/MonteCarloMeasurements.jl) for measurement error propagation. - -## Ask Questions +```julia +ModelSpec( + model; + name=:application, + on=Many(scale=:Leaf), + inputs=(...), + calls=(...), + every=Hour(1), + environment=Environment(...), + output_routing=(...), + updates=Updates(...), +) +``` -If you have any questions or feedback, [open an issue](https://github.com/VirtualPlantLab/PlantSimEngine.jl/issues) or ask on [discourse](https://fspm.discourse.group/c/software/virtual-plant-lab). +This is the package API for multiscale, multi-plant, soil, microclimate, and +model-scale simulations. ## Installation -To install the package, enter the Julia package manager mode by pressing `]` in the REPL, and execute the following command: +In Julia package mode: ```julia add PlantSimEngine ``` -To use the package, execute this command from the Julia REPL: +Then: ```julia using PlantSimEngine ``` -## Example usage +## Quickstart -The package is designed to be easy to use, and to help users avoid errors when implementing, coupling and simulating models. +This example runs three existing toy models on one model object: -### Simple example - -Here's a simple example of a model that simulates the growth of a plant, using a simple exponential growth model: +1. `ToyDegreeDaysCumulModel` computes daily thermal time. +2. `ToyLAIModel` consumes cumulative thermal time and computes LAI. +3. `Beer` consumes LAI and meteorology to compute absorbed PAR. ```julia -# ] add PlantSimEngine -using PlantSimEngine - -# Include the model definition from the examples sub-module: +using PlantSimEngine, PlantMeteo, Dates, DataFrames using PlantSimEngine.Examples -# Define the model: -model = ModelMapping( - ToyLAIModel(), - status=(TT_cu=1.0:2000.0,), # Pass the cumulated degree-days as input to the model +meteo_day = read_weather( + joinpath(pkgdir(PlantSimEngine), "examples/meteo_day.csv"); + duration=Dates.Day, ) -run!(model) # run the model - -status(model) # extract the status, i.e. the output of the model -``` - -Which gives: - -``` -TimeStepTable{Status{(:TT_cu, :LAI...}(1300 x 2): -╭─────┬────────────────┬────────────╮ -│ Row │ TT_cu │ LAI │ -│ │ Float64 │ Float64 │ -├─────┼────────────────┼────────────┤ -│ 1 │ 1.0 │ 0.00560052 │ -│ 2 │ 2.0 │ 0.00565163 │ -│ 3 │ 3.0 │ 0.00570321 │ -│ 4 │ 4.0 │ 0.00575526 │ -│ 5 │ 5.0 │ 0.00580778 │ -│ ⋮ │ ⋮ │ ⋮ │ -╰─────┴────────────────┴────────────╯ - 1295 rows omitted -``` - -> **Note** -> The `ToyLAIModel` is available from the [examples folder](https://github.com/VirtualPlantLab/PlantSimEngine.jl/tree/main/examples), and is a simple exponential growth model. It is used here for the sake of simplicity, but you can use any model you want, as long as it follows `PlantSimEngine` interface. - -Of course you can plot the outputs quite easily: - -```julia -# ] add CairoMakie -using CairoMakie - -lines(model[:TT_cu], model[:LAI], color=:green, axis=(ylabel="LAI (m² m⁻²)", xlabel="Cumulated growing degree days since sowing (°C)")) -``` - -![LAI Growth](examples/LAI_growth.png) - -### Model coupling - -Model coupling is done automatically by the package, and is based on the dependency graph between the models. To couple models, we just have to add them to the `ModelMapping`. For example, let's couple the `ToyLAIModel` with a model for light interception based on Beer's law: - -```julia -# ] add PlantSimEngine, PlantMeteo, Dates -using PlantSimEngine, PlantMeteo, Dates - -# Include the model definition from the examples folder: -using PlantSimEngine.Examples - -# Import the example meteorological data: -meteo_day = read_weather(joinpath(pkgdir(PlantSimEngine), "examples/meteo_day.csv"), duration=Dates.Day) - -# Define the list of models for coupling: -model = ModelMapping( +model = CompositeModel( + ToyDegreeDaysCumulModel(), ToyLAIModel(), - Beer(0.6), - status=(TT_cu=cumsum(meteo_day[:, :TT]),), # Pass the cumulated degree-days as input to `ToyLAIModel`, this could also be done using another model + Beer(0.6); + environment=meteo_day, ) -``` - -The `ModelMapping` couples the models by automatically computing the dependency graph of the models. The resulting dependency graph is: -``` -╭──── Dependency graph ──────────────────────────────────────────╮ -│ ╭──── LAI_Dynamic ─────────────────────────────────────────╮ │ -│ │ ╭──── Main model ────────╮ │ │ -│ │ │ Process: LAI_Dynamic │ │ │ -│ │ │ Model: ToyLAIModel │ │ │ -│ │ │ Dep: │ │ │ -│ │ ╰────────────────────────╯ │ │ -│ │ │ ╭──── Soft-coupled model ─────────╮ │ │ -│ │ │ │ Process: light_interception │ │ │ -│ │ └──│ Model: Beer │ │ │ -│ │ │ Dep: (LAI_Dynamic = (:LAI,),) │ │ │ -│ │ ╰─────────────────────────────────╯ │ │ -│ ╰──────────────────────────────────────────────────────────╯ │ -╰────────────────────────────────────────────────────────────────╯ +sim = run!(model; steps=30, outputs=:all) +out = collect_outputs(sim; sink=DataFrame) +first(out, 6) ``` -```julia -# Run the simulation: -run!(model, meteo_day) +The compiler infers the unambiguous same-object bindings from each model's +declared inputs and outputs: `ToyLAIModel` receives `TT_cu` from +`:Degreedays`, and `Beer` receives `LAI` from `:LAI_Dynamic`. -status(model) +```julia +select( + DataFrame(explain_bindings(model)), + :application_id, + :input, + :source_application_ids, + :carrier_kind, + :copy_semantics, +) ``` -Which returns: +## Multi-Object Coupling -``` -TimeStepTable{Status{(:TT_cu, :LAI...}(365 x 3): -╭─────┬────────────────┬────────────┬───────────╮ -│ Row │ TT_cu │ LAI │ aPPFD │ -│ │ Float64 │ Float64 │ Float64 │ -├─────┼────────────────┼────────────┼───────────┤ -│ 1 │ 0.0 │ 0.00554988 │ 0.0476221 │ -│ 2 │ 0.0 │ 0.00554988 │ 0.0260688 │ -│ 3 │ 0.0 │ 0.00554988 │ 0.0377774 │ -│ 4 │ 0.0 │ 0.00554988 │ 0.0468871 │ -│ 5 │ 0.0 │ 0.00554988 │ 0.0545266 │ -│ ⋮ │ ⋮ │ ⋮ │ ⋮ │ -╰─────┴────────────────┴────────────┴───────────╯ - 360 rows omitted -``` +Use the `inputs` keyword when a model needs values from selected objects. This +model-scale LAI application reads live references to the surface of every +plant in the model: ```julia -# Plot the results: -using CairoMakie - -fig = Figure(resolution=(800, 600)) -ax = Axis(fig[1, 1], ylabel="LAI (m² m⁻²)") -lines!(ax, model[:TT_cu], model[:LAI], color=:mediumseagreen) - -ax2 = Axis(fig[2, 1], xlabel="Cumulated growing degree days since sowing (°C)", ylabel="aPPFD (mol m⁻² d⁻¹)") -lines!(ax2, model[:TT_cu], model[:aPPFD], color=:firebrick1) +plant_scene = CompositeModel( + Object(:scene; scale=:Scene, kind=:scene), + Object(:plant_1; scale=:Plant, kind=:plant, parent=:scene, + status=Status(surface=12.0)), + Object(:plant_2; scale=:Plant, kind=:plant, parent=:scene, + status=Status(surface=8.0)); + applications=( + ModelSpec( + ToyLAIfromLeafAreaModel(100.0); + name=:scene_lai, + on=One(scale=:Scene), + inputs=( + :plant_surfaces => Many( + scale=:Plant, + within=SceneScope(), + var=:surface, + ), + ), + ), + ), +) -fig +run!(plant_scene) +scene_status = only(model_objects(plant_scene; scale=:Scene)).status +(total_surface=scene_status.total_surface, LAI=scene_status.LAI) ``` -![LAI Growth and light interception](examples/LAI_growth2.png) +Use `within=Self()` for plant-local aggregations, for example a plant +allocation model summing only the leaves inside the current plant. Use +`within=SceneScope()` for model-wide aggregation. -### Multiscale modelling +## Manual Calls -> See the Multi-scale modeling section of the docs for more details. - -The package is designed to be easily scalable, and can be used to simulate models at different scales. For example, you can simulate a model at the leaf scale, and then couple it with models at any other scale, *e.g.* internode, plant, soil, scene scales. Here's an example of a simple model that simulates plant growth using sub-models operating at different scales: +Use the `calls` keyword when a parent model must directly run selected child models, +for example a model energy-balance solver that iterates leaf temperatures: ```julia -mapping = ModelMapping( - :Scene => ToyDegreeDaysCumulModel(), - :Plant => ( - MultiScaleModel( - model=ToyLAIModel(), - mapped_variables=[ - :TT_cu => :Scene, - ], - ), - Beer(0.6), - MultiScaleModel( - model=ToyAssimModel(), - mapped_variables=[:soil_water_content => :Soil], - ), - MultiScaleModel( - model=ToyCAllocationModel(), - mapped_variables=[ - :carbon_demand => [:Leaf, :Internode], - :carbon_allocation => [:Leaf, :Internode] - ], - ), - MultiScaleModel( - model=ToyPlantRmModel(), - mapped_variables=[:Rm_organs => [:Leaf => :Rm, :Internode => :Rm],], - ), - ), - :Internode => ( - MultiScaleModel( - model=ToyCDemandModel(optimal_biomass=10.0, development_duration=200.0), - mapped_variables=[:TT => :Scene,], - ), - MultiScaleModel( - model=ToyInternodeEmergence(TT_emergence=20.0), - mapped_variables=[:TT_cu => :Scene], +ModelSpec( + SceneEnergyBalance(); + name=:scene_energy, + on=One(scale=:Scene), + calls=( + :leaf_energy => Many( + kind=:plant, + scale=:Leaf, + within=SceneScope(), + application=:energy_balance, ), - ToyMaintenanceRespirationModel(1.5, 0.06, 25.0, 0.6, 0.004), - Status(carbon_biomass=1.0) - ), - :Leaf => ( - MultiScaleModel( - model=ToyCDemandModel(optimal_biomass=10.0, development_duration=200.0), - mapped_variables=[:TT => :Scene,], + :soil => One( + kind=:soil, + scale=:Soil, + within=SceneScope(), + application=:soil_water, ), - ToyMaintenanceRespirationModel(2.1, 0.06, 25.0, 1.0, 0.025), - Status(carbon_biomass=1.0) - ), - :Soil => ( - ToySoilWaterModel(), ), -); -``` - -We can import an example plant from the package: - -```julia -mtg = import_mtg_example() + every=Hour(1), +) ``` -Make a fake meteorological data: - -```julia -meteo = Weather( - [ - Atmosphere(T=20.0, Wind=1.0, Rh=0.65, Ri_PAR_f=300.0), - Atmosphere(T=25.0, Wind=0.5, Rh=0.8, Ri_PAR_f=500.0) -] -); -``` +Scenario-level `inputs` and `calls` should usually name the concrete producer +or callee with `application=...`. Use process identities in model-level +contracts such as `dep(model)`, where the model author cannot know application +names chosen by future scenarios. -And run the simulation: +Inside the parent model, `run_call!(context, :leaf_energy)` executes every target +and returns a vector-like collection. For iterative control, +`call_targets(context, :leaf_energy)` returns the collection without executing +it. `run_call!(target; publish=false)` is the default for trial iterations, and +`run_call!(target; publish=true)` publishes the accepted state. -```julia -out_vars = ModelMapping( - :Scene => (:TT_cu,), - :Plant => (:carbon_allocation, :carbon_assimilation, :soil_water_content, :aPPFD, :TT_cu, :LAI), - :Leaf => (:carbon_demand, :carbon_allocation), - :Internode => (:carbon_demand, :carbon_allocation), - :Soil => (:soil_water_content,), -) +## What PlantSimEngine Handles -out = run!(mtg, mapping, meteo, outputs=out_vars, executor=SequentialEx()); -``` +- object graphs with arbitrary plant architecture; +- several plant species and repeated plant instances through templates; +- same-rate reference wiring and typed many-object carriers; +- multirate scheduling with `Dates.Period` values; +- temporal policies such as `HoldLast`, `Interpolate`, `Integrate`, and + `Aggregate`; +- automatic global or spatial environment binding; +- mutable microclimate outputs through `environment_outputs_`; +- growth, pruning, reparenting, and movement with binding-cache refresh; +- structured explanations for users and agents. -We can then extract the outputs in a `DataFrame` and sort them: +Useful inspection helpers include: ```julia -using DataFrames -df_out = convert_outputs(out, DataFrame) -sort!(df_out, [:timestep, :node]) +explain_objects(model) +explain_scopes(model) +explain_bindings(model) +explain_calls(model) +explain_environment_bindings(model) +explain_schedule(model) +explain_execution_plan(model) ``` -| **timestep**
`Int64` | **organ**
`String` | **node**
`Int64` | **carbon\_allocation**
`U{Nothing, Float64}` | **TT\_cu**
`U{Nothing, Float64}` | **carbon\_assimilation**
`U{Nothing, Float64}` | **aPPFD**
`U{Nothing, Float64}` | **LAI**
`U{Nothing, Float64}` | **soil\_water\_content**
`U{Nothing, Float64}` | **carbon\_demand**
`U{Nothing, Float64}` | -|------------------------:|----------------------:|--------------------:|-----------------------------------------------------------------------------------:|------------------------------------:|--------------------------------------------------:|-----------------------------------:|---------------------------------:|--------------------------------------------------:|--------------------------------------------:| -| 1 | Scene | 1 | | 10.0 | | | | | | -| 1 | Soil | 2 | | | | | | 0.3 | | -| 1 | Plant | 3 | | 10.0 | 0.299422 | 4.99037 | 0.00607765 | 0.3 | | -| 1 | Internode | 4 | 0.0742793 | | | | | | 0.5 | -| 1 | Leaf | 5 | 0.0742793 | | | | | | 0.5 | -| 1 | Internode | 6 | 0.0742793 | | | | | | 0.5 | -| 1 | Leaf | 7 | 0.0742793 | | | | | | 0.5 | -| 2 | Scene | 1 | | 25.0 | | | | | | -| 2 | Soil | 2 | | | | | | 0.2 | | -| 2 | Plant | 3 | | 25.0 | 0.381154 | 9.52884 | 0.00696482 | 0.2 | | -| 2 | Internode | 4 | 0.0627036 | | | | | | 0.75 | -| 2 | Leaf | 5 | 0.0627036 | | | | | | 0.75 | -| 2 | Internode | 6 | 0.0627036 | | | | | | 0.75 | -| 2 | Leaf | 7 | 0.0627036 | | | | | | 0.75 | -| 2 | Internode | 8 | 0.0627036 | | | | | | 0.75 | -| 2 | Leaf | 9 | 0.0627036 | | | | | | 0.75 | - -An example output of a multiscale simulation is shown in the documentation of PlantBiophysics.jl: - -![Plant growth simulation](docs/src/www/image.png) +## Documentation -### Multi-rate modelling +- [Stable documentation](https://VirtualPlantLab.github.io/PlantSimEngine.jl/stable) +- [Development documentation](https://VirtualPlantLab.github.io/PlantSimEngine.jl/dev) +- [CompositeModel/object quickstart](https://VirtualPlantLab.github.io/PlantSimEngine.jl/dev/composite_model/quickstart/) +- [CompositeModel/object migration guide](https://VirtualPlantLab.github.io/PlantSimEngine.jl/dev/migration_composite_model/) +- [Public API reference](https://VirtualPlantLab.github.io/PlantSimEngine.jl/dev/API/API_public/) -PlantSimEngine also supports multi-rate MTG simulations, where different models run at different cadences inside the same execution. A typical use case is to run leaf-scale processes hourly, aggregate them into daily plant-scale balances, and then export weekly summary series from the same simulation. +## Projects That Use PlantSimEngine -The dedicated documentation now has three pages: a short introduction to the -core ideas, a fuller step-by-step tutorial, and an advanced configuration page: - -- [Introduction to multi-rate execution](https://VirtualPlantLab.github.io/PlantSimEngine.jl/stable/multirate/introduction/) -- [Step-by-step hourly, daily, weekly simulation](https://VirtualPlantLab.github.io/PlantSimEngine.jl/stable/multirate/multirate_tutorial/) -- [Advanced multi-rate configuration](https://VirtualPlantLab.github.io/PlantSimEngine.jl/stable/multirate/advanced_configuration/) - -## Projects that use PlantSimEngine - -Take a look at these projects that use PlantSimEngine: - -- [PlantBiophysics.jl](https://github.com/VEZY/PlantBiophysics.jl) - For the simulation of biophysical processes for plants such as photosynthesis, conductance, energy fluxes, and temperature -- [XPalm](https://github.com/PalmStudio/XPalm.jl) - An experimental crop model for oil palm +- [PlantBiophysics.jl](https://github.com/VEZY/PlantBiophysics.jl) for + plant biophysical processes such as photosynthesis, conductance, energy + fluxes, and temperature. +- [XPalm](https://github.com/PalmStudio/XPalm.jl), an experimental crop model + for oil palm. ## Performance -PlantSimEngine delivers impressive performance for plant modeling tasks. On an M1 MacBook Pro, a toy model for leaf area over a year at daily time-scale took only 260 μs to perform (about 688 ns per day), and 275 μs (756 ns per day) when coupled to a light interception model. These benchmarks demonstrate performance on par with compiled languages like Fortran or C, far outpacing typical interpreted language implementations. - -For example, PlantBiophysics.jl, which implements ecophysiological models using PlantSimEngine, has been measured to run up to 38,000 times faster than equivalent implementations in other scientific computing languages. +PlantSimEngine keeps model kernels close to regular Julia functions while the +runtime handles dependency scheduling, object selection, temporal aggregation, +and environment sampling. On an M1 MacBook Pro, toy daily simulations run in +hundreds of microseconds, and PlantBiophysics.jl models using PlantSimEngine +have been measured much faster than equivalent implementations in typical +scientific scripting languages. -## Make it yours +For performance-sensitive composite models, inspect the compiled representation with +`explain_execution_plan(model)` to see homogeneous batches and concrete carrier +types. -The package is developed so anyone can easily implement plant/crop models, use it freely and as you want thanks to its MIT license. +## License And Contributions -If you develop such tools and it is not on the list yet, please make a PR or contact me so we can add it! 😃 Make sure to read the community guidelines before in case you're not familiar with such things. +PlantSimEngine is distributed under the MIT license. Questions and bug reports +are welcome on [GitHub issues](https://github.com/VirtualPlantLab/PlantSimEngine.jl/issues) +or the [FSPM discourse](https://fspm.discourse.group/c/software/virtual-plant-lab). diff --git a/benchmark/Project.toml b/benchmark/Project.toml index 16cbac02d..0d1d915cc 100644 --- a/benchmark/Project.toml +++ b/benchmark/Project.toml @@ -7,6 +7,8 @@ PlantBiophysics = "7ae8fcfa-76ad-4ec6-9ea7-5f8f5e2d6ec9" PlantMeteo = "4630fe09-e0fb-4da5-a846-781cb73437b6" PlantSimEngine = "9a576370-710b-4269-adf9-4f603a9c6423" Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c" +SHA = "ea8e919c-243c-51af-8825-aaa63cd721ce" +Sockets = "6462fe0b-24de-5631-8697-dd941f90decc" Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2" Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40" XPalm = "6b523e1e-d512-416c-8e51-a8fbef0064e7" diff --git a/benchmark/benchmarks.jl b/benchmark/benchmarks.jl index f3bdc06f7..d8a977dea 100644 --- a/benchmark/benchmarks.jl +++ b/benchmark/benchmarks.jl @@ -17,36 +17,220 @@ elseif Sys.islinux() suite_name = suite_name * "linux" end const SUITE = BenchmarkGroup() -SUITE[suite_name] = BenchmarkGroup(["PSE", "PBP", "XPalm"]) +const INCLUDE_DOWNSTREAM_BENCHMARKS = get( + ENV, + "PSE_BENCHMARK_INCLUDE_DOWNSTREAM", + get(ENV, "GITHUB_ACTIONS", "false") == "true" ? "false" : "true", +) == "true" +_supports_composite_object_benchmarks(engine) = + isdefined(engine, :CompositeModel) && + isdefined(engine, :Object) && + isdefined(engine, :RunContext) +const SUPPORTS_COMPOSITE_OBJECT_BENCHMARKS = + get(ENV, "PSE_BENCHMARK_FORCE_LEGACY_BASELINE", "false") != "true" && + _supports_composite_object_benchmarks(PlantSimEngine) +SUITE[suite_name] = BenchmarkGroup( + INCLUDE_DOWNSTREAM_BENCHMARKS && + SUPPORTS_COMPOSITE_OBJECT_BENCHMARKS ? + ["PSE", "PBP", "XPalm"] : ["PSE"], +) +SUITE[suite_name]["PSE_status_read_write"] = @benchmarkable begin + status.value += 1.0 + status.value +end setup = (status = PlantSimEngine.Status(value=0.0)) -# "PSE benchmark" -include("test-PSE-benchmark.jl") -SUITE[suite_name]["PSE"] = @benchmarkable do_benchmark_on_heavier_mtg() +if SUPPORTS_COMPOSITE_OBJECT_BENCHMARKS + # Composite-model benchmarks cannot be constructed while AirspeedVelocity + # evaluates this script against a pre-CompositeModel baseline revision. + include(joinpath(@__DIR__, "test-PSE-benchmark.jl")) + SUITE[suite_name]["PSE"] = @benchmarkable benchmark_heavier_scene( + model, + requests, + nsteps, + ) setup = ((model, requests, nsteps) = setup_heavier_model_benchmark()) -if isdefined(PlantSimEngine, :ModelSpec) # Only in new versions - include("test-multirate-buffer-benchmark.jl") - mtg_mr, mapping_mr, meteo_mr, reqs_mr, tracked_mr, nsteps_mr = setup_multirate_buffer_benchmark() - SUITE[suite_name]["PSE_multirate_status_tracked_run"] = @benchmarkable benchmark_multirate_status_tracked_run($mtg_mr, $mapping_mr, $meteo_mr, $tracked_mr, $nsteps_mr) - SUITE[suite_name]["PSE_multirate_output_request_run"] = @benchmarkable benchmark_multirate_output_request_run($mtg_mr, $mapping_mr, $meteo_mr, $reqs_mr, $tracked_mr, $nsteps_mr) + include(joinpath(@__DIR__, "test-multirate-buffer-benchmark.jl")) + SUITE[suite_name]["PSE_multirate_retain_all_run"] = @benchmarkable benchmark_multirate_retain_all_run( + model, + nsteps, + ) setup = ((model, ignored_requests, nsteps) = setup_multirate_buffer_benchmark()) + SUITE[suite_name]["PSE_multirate_output_request_run"] = @benchmarkable benchmark_multirate_output_request_run( + model, + requests, + nsteps, + ) setup = ((model, requests, nsteps) = setup_multirate_buffer_benchmark()) + SUITE[suite_name]["PSE_multirate_no_output_run"] = @benchmarkable benchmark_multirate_no_output_run( + model, + nsteps, + ) setup = ((model, ignored_requests, nsteps) = setup_multirate_buffer_benchmark()) + + include(joinpath(@__DIR__, "test-hard-call-path-benchmark.jl")) + for usage in (:zero, :sparse, :dense) + SUITE[suite_name]["PSE_hard_calls_$(usage)"] = + @benchmarkable benchmark_hard_call_path( + model, + nsteps, + ) setup = ((model, nsteps) = setup_hard_call_path_benchmark( + usage=$usage, + )) + end + for (kind, repeats, target_count) in ( + (:singular, 1, 1), + (:repeated, 8, 1), + (:nested, 1, 1), + (:many, 1, 1000), + (:heterogeneous, 1, 2), + (:sampled_environment, 1, 1), + (:published, 1, 1), + ) + SUITE[suite_name]["PSE_compiled_hard_call_$(kind)"] = + @benchmarkable benchmark_compiled_hard_call( + model, + nsteps, + ) setup = ((model, nsteps) = + setup_compiled_hard_call_benchmark( + kind=$kind, + repeats=$repeats, + target_count=$target_count, + )) + end + SUITE[suite_name]["PSE_lifecycle_small"] = + @benchmarkable benchmark_lifecycle_event( + simulation, + new_index, + ) setup = ((simulation, new_index) = + setup_lifecycle_hard_call_benchmark( + nobjects=32, + usage=:zero, + )) + SUITE[suite_name]["PSE_lifecycle_large"] = + @benchmarkable benchmark_lifecycle_event( + simulation, + new_index, + ) setup = ((simulation, new_index) = + setup_lifecycle_hard_call_benchmark( + nobjects=5000, + usage=:zero, + )) + SUITE[suite_name]["PSE_lifecycle_immediate_hard_call"] = + @benchmarkable benchmark_lifecycle_event( + simulation, + new_index, + ) setup = ((simulation, new_index) = + setup_lifecycle_hard_call_benchmark( + nobjects=1000, + usage=:dense, + )) end -# "PBP benchmark" -include("test-plantbiophysics.jl") -SUITE[suite_name]["PBP"] = @benchmarkable benchmark_plantbiophysics() -leaf, meteo = setup_benchmark_plantbiophysics_multitimestep() -SUITE[suite_name]["PBP_multiple_timesteps_MT"] = @benchmarkable benchmark_plantbiophysics_multitimestep_MT($leaf, $meteo) -SUITE[suite_name]["PBP_multiple_timesteps_ST"] = @benchmarkable benchmark_plantbiophysics_multitimestep_ST($leaf, $meteo) +if INCLUDE_DOWNSTREAM_BENCHMARKS && + SUPPORTS_COMPOSITE_OBJECT_BENCHMARKS + # "PBP benchmark" + include(joinpath(@__DIR__, "test-plantbiophysics.jl")) + const PLANTBIOPHYSICS_PR_BENCHMARK_STEPS = 100 + SUITE[suite_name]["PBP_multistep_no_outputs"] = + @benchmarkable benchmark_plantbiophysics_multistep( + model, + nsteps; + outputs=:none, + ) setup = ((model, nsteps) = setup_plantbiophysics_multistep( + nsteps=PLANTBIOPHYSICS_PR_BENCHMARK_STEPS, + )) + SUITE[suite_name]["PBP_multistep_all_outputs"] = + @benchmarkable benchmark_plantbiophysics_multistep( + model, + nsteps; + outputs=:all, + ) setup = ((model, nsteps) = setup_plantbiophysics_multistep( + nsteps=PLANTBIOPHYSICS_PR_BENCHMARK_STEPS, + )) + SUITE[suite_name]["PBP_construction"] = + @benchmarkable setup_plantbiophysics_multistep( + nsteps=PLANTBIOPHYSICS_PR_BENCHMARK_STEPS, + ) + SUITE[suite_name]["PBP_one_step_fanout"] = + @benchmarkable benchmark_plantbiophysics_batch( + scenes, + ) setup = (scenes = setup_benchmark_plantbiophysics_batch()) + + # "XPalm benchmark" + include(joinpath(@__DIR__, "test-xpalm.jl")) + include(joinpath(@__DIR__, "performance_regression.jl")) + const XPALM_PR_BENCHMARK_STEPS = 100 + SUITE[suite_name]["XPalm_setup_100"] = + @benchmarkable xpalm_default_param_create( + nsteps=XPALM_PR_BENCHMARK_STEPS, + ) seconds = 30 + + SUITE[suite_name]["XPalm_run_100"] = + @benchmarkable xpalm_default_param_run( + model, + requests, + nsteps, + ) setup = ((model, requests, nsteps) = xpalm_default_param_create(; + nsteps=XPALM_PR_BENCHMARK_STEPS, + )) -# "XPalm benchmark" -include("test-xpalm.jl") -SUITE[suite_name]["XPalm_setup"] = @benchmarkable xpalm_default_param_create() seconds = 120 + SUITE[suite_name]["XPalm_reference_outputs_100"] = + @benchmarkable xpalm_reference_param_run( + model, + requests, + nsteps, + ) setup = ((model, requests, nsteps) = xpalm_reference_param_create(; + nsteps=XPALM_PR_BENCHMARK_STEPS, + )) -palm, models, out_vars, meteo = xpalm_default_param_create() -sim_outputs = xpalm_default_param_run(palm, models, out_vars, meteo) + SUITE[suite_name]["XPalm_no_outputs_100"] = + @benchmarkable xpalm_reference_param_run( + model, + requests, + nsteps; + outputs=:none, + ) setup = ((model, requests, nsteps) = xpalm_reference_param_create(; + nsteps=XPALM_PR_BENCHMARK_STEPS, + )) -SUITE[suite_name]["XPalm_run"] = @benchmarkable xpalm_default_param_run(palm, models, out_vars, meteo) setup = ((palm, models, out_vars, meteo) = xpalm_default_param_create()) -SUITE[suite_name]["XPalm_convert_outputs"] = @benchmarkable xpalm_default_param_convert_outputs($sim_outputs) + SUITE[suite_name]["XPalm_small_outputs_100"] = + @benchmarkable xpalm_reference_param_run( + model, + requests, + nsteps, + ) setup = ((model, requests, nsteps) = xpalm_small_param_create(; + nsteps=XPALM_PR_BENCHMARK_STEPS, + )) -#tune!(SUITE) -#results = run(SUITE, verbose=true) -#BenchmarkTools.save(dirname(@__FILE__) * "/output.json", median(results)) + SUITE[suite_name]["XPalm_all_outputs_100"] = + @benchmarkable xpalm_reference_param_run( + model, + OutputRequest[], + nsteps; + outputs=:all, + ) setup = ((model, nsteps) = xpalm_reference_model_create(; + nsteps=XPALM_PR_BENCHMARK_STEPS, + )) +end + +if abspath(PROGRAM_FILE) == @__FILE__ + tune!(SUITE) + results = run(SUITE; verbose=true) + default_name = + "benchmark-$(Dates.format(Dates.now(), dateformat"yyyymmdd-HHMMSS")).json" + output_path = get( + ENV, + "PSE_BENCHMARK_OUTPUT", + joinpath(@__DIR__, "results", default_name), + ) + mkpath(dirname(output_path)) + BenchmarkTools.save(output_path, median(results)) + if INCLUDE_DOWNSTREAM_BENCHMARKS && + SUPPORTS_COMPOSITE_OBJECT_BENCHMARKS + summary_path = replace(output_path, r"\.[^.]+$" => "-summary.csv") + metadata = _performance_metadata(; + warmup_policy="BenchmarkTools tune plus per-benchmark setup", + ) + write_benchmark_summary(summary_path, results, metadata) + @info "PlantSimEngine benchmark suite complete" output_path summary_path + else + @info "PlantSimEngine benchmark suite complete" output_path + end +end diff --git a/benchmark/performance_regression.jl b/benchmark/performance_regression.jl new file mode 100644 index 000000000..64d0305d3 --- /dev/null +++ b/benchmark/performance_regression.jl @@ -0,0 +1,799 @@ +using BenchmarkTools +using CSV +using DataFrames +using Dates +using PlantSimEngine +using SHA +using Sockets +using Statistics +using XPalm + +isdefined(@__MODULE__, :xpalm_reference_param_create) || + include(joinpath(@__DIR__, "test-xpalm.jl")) + +const PERFORMANCE_SMOKE_STEPS = 2 +const PERFORMANCE_SHORT_STEPS = 100 +const PERFORMANCE_MEDIUM_STEPS = 1000 +const PERFORMANCE_FULL_STEPS = 4160 +const PERFORMANCE_STATISTICAL_SAMPLES = 3 + +function _performance_git_revision(path) + try + return readchomp(`git -C $path rev-parse HEAD`) + catch + return "unknown" + end +end + +function _performance_path_hash(path) + if isfile(path) + return bytes2hex(SHA.sha256(read(path))) + elseif isdir(path) + entries = String[] + for (root, directories, files) in walkdir(path) + sort!(directories) + for file in sort!(files) + file_path = joinpath(root, file) + relative_path = relpath(file_path, path) + push!( + entries, + string( + relative_path, + '\0', + bytes2hex(SHA.sha256(read(file_path))), + ), + ) + end + end + return bytes2hex(SHA.sha256(codeunits(join(entries, '\n')))) + end + return "missing" +end + +function _performance_fixture_hash(xpalm_root) + paths = ( + joinpath(xpalm_root, "0-data", "meteo.csv"), + joinpath( + xpalm_root, + "test", + "references", + "regression", + "v0.6.1", + ), + ) + entries = String[ + string(relpath(path, xpalm_root), '\0', _performance_path_hash(path)) + for path in paths + ] + return bytes2hex(SHA.sha256(codeunits(join(entries, '\n')))) +end + +function _performance_metadata(; warmup_policy) + pse_root = dirname(@__DIR__) + xpalm_root = dirname(dirname(pathof(XPalm))) + plantbiophysics_source = Base.find_package("PlantBiophysics") + plantbiophysics_root = isnothing(plantbiophysics_source) ? + nothing : + dirname(dirname(plantbiophysics_source)) + plantgeom_source = Base.find_package("PlantGeom") + plantgeom_root = isnothing(plantgeom_source) ? + nothing : + dirname(dirname(plantgeom_source)) + manifest_path = joinpath(pse_root, "benchmark", "Manifest.toml") + return ( + recorded_at=Dates.format(Dates.now(), dateformat"yyyy-mm-ddTHH:MM:SS.sss"), + julia_version=string(VERSION), + hostname=Sockets.gethostname(), + machine=Sys.MACHINE, + cpu=Sys.CPU_NAME, + memory_bytes=Sys.total_memory(), + threads=Threads.nthreads(), + plantsimengine_revision=_performance_git_revision(pse_root), + plantbiophysics_revision=isnothing(plantbiophysics_root) ? + "unavailable" : + _performance_git_revision( + plantbiophysics_root, + ), + plantgeom_revision=isnothing(plantgeom_root) ? + "unavailable" : + _performance_git_revision(plantgeom_root), + xpalm_revision=_performance_git_revision(xpalm_root), + manifest_hash=_performance_path_hash(manifest_path), + fixture_hash=_performance_fixture_hash(xpalm_root), + warmup_policy=warmup_policy, + ) +end + +function _benchmark_summary_records( + results, + metadata; + benchmark_path=String[], +) + records = NamedTuple[] + for (name, result) in pairs(results) + path = [benchmark_path; string(name)] + if result isa BenchmarkTools.Trial + median_estimate = BenchmarkTools.median(result) + minimum_estimate = BenchmarkTools.minimum(result) + push!( + records, + merge( + metadata, + ( + benchmark=join(path, "/"), + samples=length(result), + median_time_ns=median_estimate.time, + minimum_time_ns=minimum_estimate.time, + median_memory_bytes=median_estimate.memory, + minimum_memory_bytes=minimum_estimate.memory, + median_allocations=median_estimate.allocs, + minimum_allocations=minimum_estimate.allocs, + ), + ), + ) + else + append!( + records, + _benchmark_summary_records( + result, + metadata; + benchmark_path=path, + ), + ) + end + end + return records +end + +function write_benchmark_summary(path, results, metadata) + records = _benchmark_summary_records(results, metadata) + mkpath(dirname(path)) + CSV.write(path, DataFrame(records)) + return records +end + +function _performance_record!( + records, + metadata, + profile, + stage, + metric, + value, + unit, +) + push!( + records, + merge( + metadata, + ( + profile=String(profile), + stage=String(stage), + metric=String(metric), + value=Float64(value), + unit=String(unit), + ), + ), + ) + return records +end + +function _checkpoint_performance_records(path, records) + isnothing(path) && return records + mkpath(dirname(path)) + CSV.write(path, DataFrame(records)) + return records +end + +function _performance_allocation_count(measurement) + stats = measurement.gcstats + return sum(( + Int(getproperty(stats, name)) + for name in (:malloc, :realloc, :poolalloc, :bigalloc) + if hasproperty(stats, name) + ); init=0) +end + +function _timed_performance_operation(operation) + GC.gc() + return @timed operation() +end + +function _measure_performance_stage!( + operation, + records, + metadata, + profile, + stage, + checkpoint_path=nothing, + ; + samples::Int=1, + sample_factory=nothing, +) + samples >= 1 || error("Performance stage samples must be positive.") + started_at = time_ns() + measurement = try + _timed_performance_operation(operation) + catch + _performance_record!( + records, + metadata, + profile, + stage, + :failed, + 1, + :count, + ) + _performance_record!( + records, + metadata, + profile, + stage, + :wall_time_before_failure, + (time_ns() - started_at) / 1.0e9, + :seconds, + ) + _checkpoint_performance_records(checkpoint_path, records) + rethrow() + end + measurements = Any[measurement] + for _ in 2:samples + sample_operation = isnothing(sample_factory) ? + operation : + sample_factory() + push!( + measurements, + _timed_performance_operation(sample_operation), + ) + end + times = getproperty.(measurements, :time) + memories = getproperty.(measurements, :bytes) + allocations = _performance_allocation_count.(measurements) + _performance_record!( + records, + metadata, + profile, + stage, + :wall_time, + measurement.time, + :seconds, + ) + _performance_record!( + records, + metadata, + profile, + stage, + :median_time, + median(times), + :seconds, + ) + _performance_record!( + records, + metadata, + profile, + stage, + :minimum_time, + minimum(times), + :seconds, + ) + _performance_record!( + records, + metadata, + profile, + stage, + :allocated, + measurement.bytes, + :bytes, + ) + _performance_record!( + records, + metadata, + profile, + stage, + :median_memory, + median(memories), + :bytes, + ) + _performance_record!( + records, + metadata, + profile, + stage, + :minimum_memory, + minimum(memories), + :bytes, + ) + _performance_record!( + records, + metadata, + profile, + stage, + :allocations, + allocations[1], + :count, + ) + _performance_record!( + records, + metadata, + profile, + stage, + :median_allocations, + median(allocations), + :count, + ) + _performance_record!( + records, + metadata, + profile, + stage, + :minimum_allocations, + minimum(allocations), + :count, + ) + _performance_record!( + records, + metadata, + profile, + stage, + :samples, + samples, + :count, + ) + _performance_record!( + records, + metadata, + profile, + stage, + :gc_time, + measurement.gctime, + :seconds, + ) + _checkpoint_performance_records(checkpoint_path, records) + return measurement.value +end + +function _record_runtime_performance!( + records, + metadata, + profile, + stage, + simulation, +) + performance = PlantSimEngine.Advanced.runtime_performance(simulation) + isnothing(performance) && return records + for (metric, value) in sort!(collect(performance.counts); by=first) + _performance_record!( + records, + metadata, + profile, + stage, + metric, + value, + :count, + ) + end + for (metric, value) in sort!( + collect(performance.elapsed_seconds); + by=first, + ) + _performance_record!( + records, + metadata, + profile, + stage, + metric, + value, + :seconds, + ) + end + return records +end + +function _record_xpalm_state!( + records, + metadata, + profile, + stage, + state, +) + for metric in (:current_step, :phytomer_count, :lai, :ftsw) + _performance_record!( + records, + metadata, + profile, + stage, + metric, + getproperty(state, metric), + :value, + ) + end + return records +end + +function _performance_steps(profile) + profile == :smoke && return PERFORMANCE_SMOKE_STEPS + profile == :short && return PERFORMANCE_SHORT_STEPS + profile == :medium && return PERFORMANCE_MEDIUM_STEPS + profile == :full && return PERFORMANCE_FULL_STEPS + error( + "Unsupported performance profile `$(profile)`. Use `:smoke`, `:short`, ", + "`:medium`, or `:full`.", + ) +end + +function _warmup_xpalm_performance!(profile_steps) + lifecycle_steps = min(profile_steps, PERFORMANCE_SHORT_STEPS) + no_output_model, no_output_steps = + xpalm_reference_model_create(; nsteps=lifecycle_steps) + xpalm_reference_param_run( + no_output_model, + OutputRequest[], + no_output_steps; + outputs=:none, + ) + + reference_model, reference_requests, reference_steps = + xpalm_reference_param_create(; nsteps=PERFORMANCE_SMOKE_STEPS) + reference_simulation = xpalm_reference_param_run( + reference_model, + reference_requests, + reference_steps, + ) + xpalm_default_param_collect_outputs(reference_simulation) + return nothing +end + +function run_xpalm_performance_profile(; + profile=:short, + checkpoint_path=nothing, +) + normalized_profile = Symbol(profile) + nsteps = _performance_steps(normalized_profile) + warmup_policy = + "unmeasured outputs=:none prefix ($(min(nsteps, PERFORMANCE_SHORT_STEPS)) steps) " * + "plus requested-output smoke ($(PERFORMANCE_SMOKE_STEPS) steps)" + _warmup_xpalm_performance!(nsteps) + metadata = _performance_metadata(; warmup_policy=warmup_policy) + records = NamedTuple[] + + compile_model, _ = xpalm_reference_model_create(; nsteps=nsteps) + initial_compilation = _measure_performance_stage!( + records, + metadata, + normalized_profile, + :initial_scene_compilation, + checkpoint_path, + samples=PERFORMANCE_STATISTICAL_SAMPLES, + sample_factory=() -> begin + sample_model, _ = + xpalm_reference_model_create(; nsteps=nsteps) + return () -> + PlantSimEngine.Advanced.refresh_bindings!(sample_model) + end, + ) do + PlantSimEngine.Advanced.refresh_bindings!(compile_model) + end + _performance_record!( + records, + metadata, + normalized_profile, + :initial_scene_compilation, + :application_count, + length(initial_compilation.applications), + :count, + ) + + steady_model, _ = xpalm_reference_model_create(; nsteps=2) + steady_simulation = xpalm_reference_param_run( + steady_model, + OutputRequest[], + 1; + outputs=:none, + ) + steady_simulation = _measure_performance_stage!( + records, + metadata, + normalized_profile, + :clean_steady_state_step, + checkpoint_path, + samples=PERFORMANCE_STATISTICAL_SAMPLES, + sample_factory=() -> begin + sample_model, _ = + xpalm_reference_model_create(; nsteps=2) + sample_simulation = xpalm_reference_param_run( + sample_model, + OutputRequest[], + 1; + outputs=:none, + ) + return () -> continue!(sample_simulation) + end, + ) do + continue!(steady_simulation) + end + current_step(steady_simulation) == 2 || error( + "XPalm clean-step benchmark did not advance to step two.", + ) + + no_output_setup = _measure_performance_stage!( + records, + metadata, + normalized_profile, + :scene_construction_no_outputs, + checkpoint_path, + samples=PERFORMANCE_STATISTICAL_SAMPLES, + ) do + xpalm_reference_model_create(; nsteps=nsteps) + end + no_output_model, no_output_steps = no_output_setup + no_output_simulation = _measure_performance_stage!( + records, + metadata, + normalized_profile, + :simulation_no_outputs, + checkpoint_path, + samples=PERFORMANCE_STATISTICAL_SAMPLES, + sample_factory=() -> begin + sample_model, sample_steps = + xpalm_reference_model_create(; nsteps=nsteps) + return () -> xpalm_reference_param_run( + sample_model, + OutputRequest[], + sample_steps; + outputs=:none, + performance=true, + ) + end, + ) do + xpalm_reference_param_run( + no_output_model, + OutputRequest[], + no_output_steps; + outputs=:none, + performance=true, + ) + end + _record_runtime_performance!( + records, + metadata, + normalized_profile, + :simulation_no_outputs, + no_output_simulation, + ) + _checkpoint_performance_records(checkpoint_path, records) + + small_setup = _measure_performance_stage!( + records, + metadata, + normalized_profile, + :scene_and_request_compile_small_outputs, + checkpoint_path, + samples=PERFORMANCE_STATISTICAL_SAMPLES, + ) do + xpalm_small_param_create(; nsteps=nsteps) + end + small_model, small_requests, small_steps = small_setup + small_simulation = _measure_performance_stage!( + records, + metadata, + normalized_profile, + :simulation_small_outputs, + checkpoint_path, + samples=PERFORMANCE_STATISTICAL_SAMPLES, + sample_factory=() -> begin + sample_model, sample_requests, sample_steps = + xpalm_small_param_create(; nsteps=nsteps) + return () -> xpalm_reference_param_run( + sample_model, + sample_requests, + sample_steps; + performance=true, + ) + end, + ) do + xpalm_reference_param_run( + small_model, + small_requests, + small_steps; + performance=true, + ) + end + _record_runtime_performance!( + records, + metadata, + normalized_profile, + :simulation_small_outputs, + small_simulation, + ) + + reference_setup = _measure_performance_stage!( + records, + metadata, + normalized_profile, + :scene_and_request_compile_reference_outputs, + checkpoint_path, + samples=PERFORMANCE_STATISTICAL_SAMPLES, + ) do + xpalm_reference_param_create(; nsteps=nsteps) + end + reference_model, reference_requests, reference_steps = reference_setup + reference_simulation = _measure_performance_stage!( + records, + metadata, + normalized_profile, + :simulation_reference_outputs, + checkpoint_path, + samples=PERFORMANCE_STATISTICAL_SAMPLES, + sample_factory=() -> begin + sample_model, sample_requests, sample_steps = + xpalm_reference_param_create(; nsteps=nsteps) + return () -> xpalm_reference_param_run( + sample_model, + sample_requests, + sample_steps; + performance=true, + ) + end, + ) do + xpalm_reference_param_run( + reference_model, + reference_requests, + reference_steps; + performance=true, + ) + end + reference_outputs = _measure_performance_stage!( + records, + metadata, + normalized_profile, + :collect_reference_outputs, + checkpoint_path, + samples=PERFORMANCE_STATISTICAL_SAMPLES, + ) do + xpalm_default_param_collect_outputs(reference_simulation) + end + _record_runtime_performance!( + records, + metadata, + normalized_profile, + :simulation_reference_outputs, + reference_simulation, + ) + + all_output_setup = _measure_performance_stage!( + records, + metadata, + normalized_profile, + :scene_construction_all_outputs, + checkpoint_path, + samples=PERFORMANCE_STATISTICAL_SAMPLES, + ) do + xpalm_reference_model_create(; nsteps=nsteps) + end + all_output_model, all_output_steps = all_output_setup + all_output_simulation = _measure_performance_stage!( + records, + metadata, + normalized_profile, + :simulation_all_outputs, + checkpoint_path, + samples=PERFORMANCE_STATISTICAL_SAMPLES, + sample_factory=() -> begin + sample_model, sample_steps = + xpalm_reference_model_create(; nsteps=nsteps) + return () -> xpalm_reference_param_run( + sample_model, + OutputRequest[], + sample_steps; + outputs=:all, + performance=true, + ) + end, + ) do + xpalm_reference_param_run( + all_output_model, + OutputRequest[], + all_output_steps; + outputs=:all, + performance=true, + ) + end + _record_runtime_performance!( + records, + metadata, + normalized_profile, + :simulation_all_outputs, + all_output_simulation, + ) + + no_output_state = xpalm_reference_final_state(no_output_simulation) + small_state = xpalm_reference_final_state(small_simulation) + reference_state = xpalm_reference_final_state(reference_simulation) + all_output_state = xpalm_reference_final_state(all_output_simulation) + _record_xpalm_state!( + records, + metadata, + normalized_profile, + :final_state_no_outputs, + no_output_state, + ) + _record_xpalm_state!( + records, + metadata, + normalized_profile, + :final_state_reference_outputs, + reference_state, + ) + _record_xpalm_state!( + records, + metadata, + normalized_profile, + :final_state_small_outputs, + small_state, + ) + _record_xpalm_state!( + records, + metadata, + normalized_profile, + :final_state_all_outputs, + all_output_state, + ) + _checkpoint_performance_records(checkpoint_path, records) + no_output_state == small_state == reference_state == all_output_state || error( + "XPalm performance fixtures diverged across output-retention modes: ", + "none=$(no_output_state), small=$(small_state), ", + "reference=$(reference_state), all=$(all_output_state).", + ) + isempty(reference_outputs) && error( + "XPalm performance reference output collection returned no tables.", + ) + + if normalized_profile == :full + xpalm_reference_state_matches(reference_state) || error( + "XPalm full-cycle performance fixture does not match the committed v0.6.1 final state: ", + "$(reference_state).", + ) + high_level_outputs = _measure_performance_stage!( + records, + metadata, + normalized_profile, + :historical_end_to_end_reference, + checkpoint_path, + samples=PERFORMANCE_STATISTICAL_SAMPLES, + ) do + xpalm_reference_end_to_end(; nsteps=nsteps) + end + xpalm_reference_high_level_state_matches(high_level_outputs) || error( + "XPalm historical end-to-end performance fixture does not match the committed ", + "v0.6.1 final state.", + ) + end + + return ( + records=records, + no_output_state=no_output_state, + small_state=small_state, + reference_state=reference_state, + all_output_state=all_output_state, + ) +end + +function write_xpalm_performance_profile(path; profile=:short) + result = run_xpalm_performance_profile(; + profile=profile, + checkpoint_path=path, + ) + _checkpoint_performance_records(path, result.records) + return result +end + +if abspath(PROGRAM_FILE) == @__FILE__ + profile = Symbol(get(ENV, "PSE_PERFORMANCE_PROFILE", "short")) + default_name = "xpalm-$(profile)-$(Dates.format(Dates.now(), dateformat"yyyymmdd-HHMMSS")).csv" + output_path = get( + ENV, + "PSE_PERFORMANCE_OUTPUT", + joinpath(@__DIR__, "results", default_name), + ) + result = write_xpalm_performance_profile(output_path; profile=profile) + @info "XPalm performance profile complete" profile output_path final_state=result.reference_state +end diff --git a/benchmark/prepare_full_performance_project.jl b/benchmark/prepare_full_performance_project.jl new file mode 100644 index 000000000..3a2eaf9b6 --- /dev/null +++ b/benchmark/prepare_full_performance_project.jl @@ -0,0 +1,20 @@ +using TOML + +function prepare_full_performance_project!(project_path) + project = TOML.parsefile(project_path) + pop!(project, "sources", nothing) + open(project_path, "w") do io + TOML.print(io, project) + end + return project_path +end + +function prepare_plantbiophysics_performance_project!(project_path) + project = TOML.parsefile(project_path) + pop!(project, "sources", nothing) + pop!(project["deps"], "XPalm", nothing) + open(project_path, "w") do io + TOML.print(io, project) + end + return project_path +end diff --git a/benchmark/release_baselines/README.md b/benchmark/release_baselines/README.md new file mode 100644 index 000000000..a955ce4e2 --- /dev/null +++ b/benchmark/release_baselines/README.md @@ -0,0 +1,82 @@ +# Pinned downstream release baselines + +These isolated projects preserve the release stacks used by the performance +acceptance checks. They deliberately do not share the main benchmark manifest. +Instantiate and run each project in a fresh Julia process with one Julia thread: + +```sh +JULIA_NUM_THREADS=1 julia --project=benchmark/release_baselines/plantbiophysics -e 'using Pkg; Pkg.instantiate()' +JULIA_NUM_THREADS=1 julia --project=benchmark/release_baselines/plantbiophysics benchmark/release_baselines/plantbiophysics/run.jl + +JULIA_NUM_THREADS=1 julia --project=benchmark/release_baselines/xpalm -e 'using Pkg; Pkg.instantiate()' +JULIA_NUM_THREADS=1 julia --project=benchmark/release_baselines/xpalm benchmark/release_baselines/xpalm/run.jl +``` + +Both runners warm the relevant API before collecting several one-setup, +many-timestep samples. They write a CSV result when an output path is supplied +as their first argument and otherwise place it beside the runner. Construction +is outside the timed region. Julia startup and package loading are excluded. + +Pinned sources: + +- PlantSimEngine `v0.14.1`, commit + `503af98c3709a0b1207407e3741b7cb09ebfbcf7`; +- PlantBiophysics `v0.17.0`, commit + `9f39af4ffd48bab234e5d80b89cd52c67b9f3f82`; +- XPalm `v0.6.1`, commit + `a0dbf2e8d6fa9e21f8e8ced3220da184b3ee3f4c`. + +Do not commit generated manifests or result CSV files. Preserve the runner, +resolved manifest, raw CSV, machine description, Julia version, and thread +count together when recording a release decision. + +## Accepted local comparison, 2026-08-11 + +The release decision was checked on an Apple M3 Max MacBook Pro with 36 GB RAM, +macOS/Darwin 25.5.0, and Julia 1.12.1. The accepted current stack used +PlantSimEngine runtime commit `d5480c50`, PlantBiophysics commit `dbd04e0`, and +XPalm commit `192e43f7`. The release commits are the pinned sources listed +above. + +PlantBiophysics used one Julia thread and a single constructed leaf scene for +one continuous 8,760-step trajectory. Each row is the median of 10 samples; +construction was outside the timed steady-state rows. + +| Stack and output policy | Median | Minimum | Per step | Allocated bytes | Allocations | Release ratio | +| --- | ---: | ---: | ---: | ---: | ---: | ---: | +| release, normal retained outputs | 85.142 ms | not retained | 9.719 us | 129,536,608 | 1,759,504 | 1.000x | +| current, `outputs=:none` | 18.414 ms | 17.430 ms | 2.102 us | 25,883,792 | 288,137 | 0.216x | +| current, `outputs=:all` | 32.216 ms | 30.238 ms | 3.678 us | 47,792,736 | 868,558 | 0.378x | + +Current PlantBiophysics construction was 16.359 ms median. The separate +100-scene, one-step fan-out diagnostic was 15.205 ms median and is not used as +the acceptance metric. The complete 113,880-row retained-output trajectory was +exactly identical to the pre-optimization current stack, with a maximum +absolute difference of 0.0. + +XPalm used 10 Julia threads, although its model execution remained sequential. +Both sides warmed a 100-step run, prepared meteorology and `Palm` outside each +timed sample, and timed the same high-level `XPalm.xpalm` scope: scene +construction, the 4,160-step lifecycle run, requested outputs, and DataFrame +materialization. Julia startup and package loading were excluded. Five samples +were forced with a 120-second BenchmarkTools budget. + +| Stack | Median | Per step | Allocated bytes | Allocations | Release ratio | +| --- | ---: | ---: | ---: | ---: | ---: | +| XPalm `v0.6.1` / PlantSimEngine `v0.14.1` | 5.416 s | 1.302 ms | 6,898,039,968 | 80,317,174 | 1.000x | +| current XPalm / current PlantSimEngine | 8.035 s | 1.931 ms | 3,378,642,888 | 39,259,563 | **1.483x** | + +Raw full-cycle times, in seconds: + +- release: `5.115200625`, `5.384637000`, `5.416365375`, `5.474346833`, `5.782515542`; +- current: `7.953668959`, `7.961468750`, `8.034666500`, `8.041943916`, `8.071678500`. + +The current full-cycle output matched the committed XPalm `v0.6.1` reference: +step 4,160, 344 phytomers, LAI `5.0587602356164405`, and FTSW +`0.7991179101191216`. A separate staged profile kept construction and retention +costs distinct: 7.779 ms initial compilation, 6.438 ms no-output scene +construction, 83.562 ms for a 100-step no-output run, 79.818 ms for the same +short requested-output simulation, 3.323 ms to materialize its retained output, +and 95.263 ms with all outputs retained. The 100-step no-output profile included +10 lifecycle binding refreshes; the accepted 4,160-step timing includes all +growth-related refresh work. diff --git a/benchmark/release_baselines/plantbiophysics/.gitignore b/benchmark/release_baselines/plantbiophysics/.gitignore new file mode 100644 index 000000000..5e16486bd --- /dev/null +++ b/benchmark/release_baselines/plantbiophysics/.gitignore @@ -0,0 +1,2 @@ +Manifest.toml +latest.csv diff --git a/benchmark/release_baselines/plantbiophysics/Project.toml b/benchmark/release_baselines/plantbiophysics/Project.toml new file mode 100644 index 000000000..9fe9dbaa9 --- /dev/null +++ b/benchmark/release_baselines/plantbiophysics/Project.toml @@ -0,0 +1,18 @@ +[deps] +BenchmarkTools = "6e4b80f9-dd63-53aa-95a3-0cdb28fa8baf" +CSV = "336ed68f-0bac-5ca0-87d4-7b16caf5d00b" +DataFrames = "a93c6f00-e57d-5684-b7b6-d8193f3e46c0" +Dates = "ade2ca70-3891-5945-98fb-dc099432e06a" +PlantBiophysics = "7ae8fcfa-76ad-4ec6-9ea7-5f8f5e2d6ec9" +PlantMeteo = "4630fe09-e0fb-4da5-a846-781cb73437b6" +PlantSimEngine = "9a576370-710b-4269-adf9-4f603a9c6423" +Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c" + +[sources] +PlantBiophysics = {rev = "9f39af4ffd48bab234e5d80b89cd52c67b9f3f82", url = "https://github.com/VEZY/PlantBiophysics.jl"} +PlantSimEngine = {rev = "503af98c3709a0b1207407e3741b7cb09ebfbcf7", url = "https://github.com/VirtualPlantLab/PlantSimEngine.jl"} + +[compat] +PlantBiophysics = "=0.17.0" +PlantSimEngine = "=0.14.1" +julia = "1.12" diff --git a/benchmark/release_baselines/plantbiophysics/run.jl b/benchmark/release_baselines/plantbiophysics/run.jl new file mode 100644 index 000000000..f0227518b --- /dev/null +++ b/benchmark/release_baselines/plantbiophysics/run.jl @@ -0,0 +1,93 @@ +using BenchmarkTools +using CSV +using DataFrames +using Dates +using PlantBiophysics +using PlantMeteo +using PlantSimEngine +using Random + +const NSTEPS = parse(Int, get(ENV, "PSE_RELEASE_BASELINE_STEPS", "8760")) +const SAMPLES = parse(Int, get(ENV, "PSE_RELEASE_BASELINE_SAMPLES", "12")) + +function forcing_set(n::Int) + Random.seed!(1) + ranges = ( + T=range(18, 40; length=10_000), + Wind=range(0.5, 20; length=10_000), + P=range(90, 101; length=10_000), + Rh=range(0.1, 0.98; length=10_000), + Ca=range(360, 900; length=10_000), + JMaxRef=range(200.0, 300.0; length=10_000), + VcMaxRef=range(150.0, 250.0; length=10_000), + RdRef=range(0.3, 2.0; length=10_000), + Ra_SW_f=range(10, 500; length=10_000), + sky_fraction=range(0.0, 1.0; length=10_000), + d=range(0.001, 0.5; length=10_000), + TPURef=range(5.0, 20.0; length=10_000), + g0=range(0.001, 2.0; length=10_000), + g1=range(0.5, 15.0; length=10_000), + ) + return DataFrame((; ( + name => [rand(values) for _ in 1:n] + for (name, values) in pairs(ranges) + )...)) +end + +function atmosphere(row) + return Atmosphere( + T=row.T, + Wind=row.Wind, + P=row.P, + Rh=row.Rh, + Cₐ=row.Ca, + duration=Hour(1), + ) +end + +function setup_workload(nsteps::Int) + forcing = forcing_set(nsteps) + first_row = first(eachrow(forcing)) + weather = Weather([atmosphere(row) for row in eachrow(forcing)]) + leaf = ModelMapping( + energy_balance=Monteith(), + photosynthesis=Fvcb( + VcMaxRef=first_row.VcMaxRef, + JMaxRef=first_row.JMaxRef, + RdRef=first_row.RdRef, + TPURef=first_row.TPURef, + ), + stomatal_conductance=Medlyn(first_row.g0, first_row.g1), + status=( + Ra_SW_f=first_row.Ra_SW_f, + sky_fraction=first_row.sky_fraction, + aPPFD=first_row.Ra_SW_f * 0.48 * 4.57, + d=first_row.d, + ), + ) + return leaf, weather +end + +warm_leaf, warm_weather = setup_workload(min(NSTEPS, 2)) +run!(warm_leaf, warm_weather) + +trial = @benchmark run!(leaf, weather) setup = ( + (leaf, weather) = setup_workload($NSTEPS) +) samples = SAMPLES evals = 1 +estimate = BenchmarkTools.median(trial) +record = DataFrame([((; + stack="PlantBiophysics v0.17.0 / PlantSimEngine v0.14.1", + julia_version=string(VERSION), + threads=Threads.nthreads(), + nsteps=NSTEPS, + samples=length(trial), + output_policy="release default retained outputs", + median_time_ns=estimate.time, + median_time_per_step_ns=estimate.time / NSTEPS, + median_memory_bytes=estimate.memory, + median_allocations=estimate.allocs, +))]) + +output_path = isempty(ARGS) ? joinpath(@__DIR__, "latest.csv") : only(ARGS) +CSV.write(output_path, record) +record diff --git a/benchmark/release_baselines/xpalm/.gitignore b/benchmark/release_baselines/xpalm/.gitignore new file mode 100644 index 000000000..5e16486bd --- /dev/null +++ b/benchmark/release_baselines/xpalm/.gitignore @@ -0,0 +1,2 @@ +Manifest.toml +latest.csv diff --git a/benchmark/release_baselines/xpalm/Project.toml b/benchmark/release_baselines/xpalm/Project.toml new file mode 100644 index 000000000..d9b3aa3ac --- /dev/null +++ b/benchmark/release_baselines/xpalm/Project.toml @@ -0,0 +1,15 @@ +[deps] +BenchmarkTools = "6e4b80f9-dd63-53aa-95a3-0cdb28fa8baf" +CSV = "336ed68f-0bac-5ca0-87d4-7b16caf5d00b" +DataFrames = "a93c6f00-e57d-5684-b7b6-d8193f3e46c0" +PlantSimEngine = "9a576370-710b-4269-adf9-4f603a9c6423" +XPalm = "6b523e1e-d512-416c-8e51-a8fbef0064e7" + +[sources] +PlantSimEngine = {rev = "503af98c3709a0b1207407e3741b7cb09ebfbcf7", url = "https://github.com/VirtualPlantLab/PlantSimEngine.jl"} +XPalm = {rev = "a0dbf2e8d6fa9e21f8e8ced3220da184b3ee3f4c", url = "https://github.com/PalmStudio/XPalm.jl"} + +[compat] +PlantSimEngine = "=0.14.1" +XPalm = "=0.6.1" +julia = "1.12" diff --git a/benchmark/release_baselines/xpalm/run.jl b/benchmark/release_baselines/xpalm/run.jl new file mode 100644 index 000000000..e857c7933 --- /dev/null +++ b/benchmark/release_baselines/xpalm/run.jl @@ -0,0 +1,97 @@ +using BenchmarkTools +using CSV +using DataFrames +using XPalm + +const SAMPLES = parse(Int, get(ENV, "PSE_RELEASE_BASELINE_SAMPLES", "5")) +const TIME_BUDGET_SECONDS = + parse(Float64, get(ENV, "PSE_RELEASE_BASELINE_SECONDS", "120")) +const REFERENCE_VARIABLES = Dict{Symbol,Any}( + :Scene => (:lai, :leaf_area, :aPPFD), + :Plant => ( + :plant_age, + :leaf_area, + :aPPFD, + :Rm, + :carbon_assimilation, + :phytomer_count, + :biomass_bunch_harvested, + :biomass_bunch_harvested_cum, + :n_bunches_harvested, + :n_bunches_harvested_cum, + :biomass_oil_harvested, + :biomass_oil_harvested_cum, + ), + :Soil => (:ftsw, :root_depth), +) + +function setup_workload() + meteo = CSV.read( + joinpath(dirname(dirname(pathof(XPalm))), "0-data", "meteo.csv"), + DataFrame, + ) + palm = XPalm.Palm( + initiation_age=0, + parameters=XPalm.default_parameters(), + ) + return meteo, palm +end + +function run_workload(meteo, palm) + return XPalm.xpalm( + meteo, + DataFrame; + vars=REFERENCE_VARIABLES, + architecture=false, + palm=palm, + ) +end + +warm_meteo, warm_palm = setup_workload() +run_workload(warm_meteo[1:100, :], warm_palm) + +trial = @benchmark run_workload(meteo, palm) setup = ( + (meteo, palm) = setup_workload() +) samples = SAMPLES evals = 1 seconds = TIME_BUDGET_SECONDS +estimate = BenchmarkTools.median(trial) + +check_meteo, check_palm = setup_workload() +outputs = run_workload(check_meteo, check_palm) +final_state = ( + current_step=nrow(outputs[:Plant]), + phytomer_count=last(outputs[:Plant].phytomer_count), + lai=last(outputs[:Scene].lai), + ftsw=last(outputs[:Soil].ftsw), +) +expected = ( + current_step=4160, + phytomer_count=344, + lai=5.0587602356164405, + ftsw=0.7991179101191216, +) +final_state.current_step == expected.current_step || error("XPalm step mismatch") +final_state.phytomer_count == expected.phytomer_count || error("XPalm phytomer mismatch") +isapprox(final_state.lai, expected.lai; atol=1.0e-8, rtol=1.0e-8) || + error("XPalm LAI mismatch") +isapprox(final_state.ftsw, expected.ftsw; atol=1.0e-8, rtol=1.0e-8) || + error("XPalm FTSW mismatch") + +record = DataFrame([((; + stack="XPalm v0.6.1 / PlantSimEngine v0.14.1", + julia_version=string(VERSION), + threads=Threads.nthreads(), + nsteps=final_state.current_step, + samples=length(trial), + output_policy="historical requested outputs and DataFrame materialization", + median_time_ns=estimate.time, + median_time_per_step_ns=estimate.time / final_state.current_step, + median_memory_bytes=estimate.memory, + median_allocations=estimate.allocs, + phytomer_count=final_state.phytomer_count, + lai=final_state.lai, + ftsw=final_state.ftsw, +))]) + +output_path = isempty(ARGS) ? joinpath(@__DIR__, "latest.csv") : only(ARGS) +CSV.write(output_path, record) +record diff --git a/benchmark/test-PSE-benchmark.jl b/benchmark/test-PSE-benchmark.jl index 080f02b1a..056d0877d 100644 --- a/benchmark/test-PSE-benchmark.jl +++ b/benchmark/test-PSE-benchmark.jl @@ -15,10 +15,12 @@ end ToyInternodeCrazyEmergence(; TT_emergence=300.0) = ToyInternodeCrazyEmergence(TT_emergence) -PlantSimEngine.inputs_(m::ToyInternodeCrazyEmergence) = (TT_cu=-Inf,) +PlantSimEngine.inputs_(m::ToyInternodeCrazyEmergence) = (TT_cu=Required(Float64),) PlantSimEngine.outputs_(m::ToyInternodeCrazyEmergence) = (TT_cu_emergence=0.0,) -function PlantSimEngine.run!(m::ToyInternodeCrazyEmergence, models, status, meteo, constants=nothing, sim_object=nothing) +function PlantSimEngine.run!(m::ToyInternodeCrazyEmergence, status, environment, constants=nothing, context=nothing) + + model = runtime_model(context) #root = get_root(status.node) @@ -28,21 +30,21 @@ function PlantSimEngine.run!(m::ToyInternodeCrazyEmergence, models, status, mete if length(MultiScaleTreeGraph.children(status.node)) == 1 && status.TT_cu - status.TT_cu_emergence >= m.TT_emergence - status_new_internode = add_organ!(status.node, sim_object, "<", :Internode, 2, index=1) - add_organ!(status_new_internode.node, sim_object, "+", :Leaf, 2, index=1) + status_new_internode = add_organ!(status.node, model, "<", :Internode, 2; index=1, initial_status=(carbon_biomass=1.0, TT_cu_emergence=0.0)) + add_organ!(status_new_internode.node, model, "+", :Leaf, 2; index=1, initial_status=(carbon_biomass=1.0,)) status_new_internode.TT_cu_emergence = status.TT_cu elseif (length(MultiScaleTreeGraph.children(status.node)) >= 2 && length(MultiScaleTreeGraph.children(status.node)) < 7) && status.TT_cu - status.TT_cu_emergence >= m.TT_emergence - status_new_internode = add_organ!(status.node, sim_object, "<", :Internode, 2, index=1) - add_organ!(status.node, sim_object, "+", :Leaf, 2, index=4) - add_organ!(status.node, sim_object, "+", :Leaf, 2, index=5) + status_new_internode = add_organ!(status.node, model, "<", :Internode, 2; index=1, initial_status=(carbon_biomass=1.0, TT_cu_emergence=0.0)) + add_organ!(status.node, model, "+", :Leaf, 2; index=4, initial_status=(carbon_biomass=1.0,)) + add_organ!(status.node, model, "+", :Leaf, 2; index=5, initial_status=(carbon_biomass=1.0,)) status_new_internode.TT_cu_emergence = status.TT_cu elseif (length(MultiScaleTreeGraph.children(status.node)) >= 7 && length(MultiScaleTreeGraph.children(status.node)) < 30) && status.TT_cu - status.TT_cu_emergence >= m.TT_emergence - add_organ!(status.node, sim_object, "+", :Leaf, 2, index=6) - add_organ!(status.node, sim_object, "+", :Leaf, 2, index=7) - add_organ!(status.node, sim_object, "+", :Leaf, 2, index=8) - add_organ!(status.node, sim_object, "+", :Leaf, 2, index=9) - add_organ!(status.node, sim_object, "+", :Leaf, 2, index=10) - add_organ!(status.node, sim_object, "+", :Leaf, 2, index=11) + add_organ!(status.node, model, "+", :Leaf, 2; index=6, initial_status=(carbon_biomass=1.0,)) + add_organ!(status.node, model, "+", :Leaf, 2; index=7, initial_status=(carbon_biomass=1.0,)) + add_organ!(status.node, model, "+", :Leaf, 2; index=8, initial_status=(carbon_biomass=1.0,)) + add_organ!(status.node, model, "+", :Leaf, 2; index=9, initial_status=(carbon_biomass=1.0,)) + add_organ!(status.node, model, "+", :Leaf, 2; index=10, initial_status=(carbon_biomass=1.0,)) + add_organ!(status.node, model, "+", :Leaf, 2; index=11, initial_status=(carbon_biomass=1.0,)) end @@ -50,73 +52,56 @@ function PlantSimEngine.run!(m::ToyInternodeCrazyEmergence, models, status, mete end -# Wrapped this into a function so that it doesn't plague the benchmark with variables on a global scope -#@check_allocs -function do_benchmark_on_heavier_mtg() +function _benchmark_mtg_status(node) + data = Dict{Symbol,Any}(:node => node) + scale = MultiScaleTreeGraph.symbol(node) + scale in (:Leaf, :Internode) && (data[:carbon_biomass] = 1.0) + scale == :Plant && (data[:carbon_allocation] = zeros(4)) + return Status((; data...)) +end + +function setup_heavier_model_benchmark() mtg = import_mtg_example() - # Example meteo, 365 timesteps : meteo_day = read_weather(joinpath(pkgdir(PlantSimEngine), "examples/meteo_day.csv"), duration=Day) - - #similar to the mtg growth test but with a much lower emergence threshold - mapping = ModelMapping( - :Scene => ToyDegreeDaysCumulModel(), - :Plant => ( - MultiScaleModel( - model=ToyLAIModel(), - mapped_variables=[ - :TT_cu => :Scene, - ], - ), - PlantSimEngine.Examples.Beer(0.6), - MultiScaleModel( - model=ToyCAllocationModel(), - mapped_variables=[ - :carbon_assimilation => [:Leaf], - :carbon_demand => [:Leaf, :Internode], - :carbon_allocation => [:Leaf, :Internode] - ], - ), - MultiScaleModel( - model=ToyPlantRmModel(), - mapped_variables=[:Rm_organs => [:Leaf => :Rm, :Internode => :Rm],], - ), - ), - :Internode => ( - MultiScaleModel( - model=ToyCDemandModel(optimal_biomass=10.0, development_duration=200.0), - mapped_variables=[:TT => :Scene,], - ), - MultiScaleModel( - model=ToyInternodeCrazyEmergence(TT_emergence=1.0), - mapped_variables=[:TT_cu => :Scene], - ), - ToyMaintenanceRespirationModel(1.5, 0.06, 25.0, 0.6, 0.004), - Status(carbon_biomass=1.0) - ), - :Leaf => ( - MultiScaleModel( - model=ToyAssimModel(), - mapped_variables=[:soil_water_content => :Soil, :aPPFD => :Plant], - ), - MultiScaleModel( - model=ToyCDemandModel(optimal_biomass=10.0, development_duration=200.0), - mapped_variables=[:TT => :Scene,], - ), - ToyMaintenanceRespirationModel(2.1, 0.06, 25.0, 1.0, 0.025), - Status(carbon_biomass=1.0) - ), - :Soil => ( - ToySoilWaterModel(), - ), + applications = ( + ModelSpec(ToyDegreeDaysCumulModel(); name=:scene_degree_days, on=One(scale=:Scene)), + ModelSpec(ToyLAIModel(); name=:plant_lai, on=Many(scale=:Plant), inputs=(:TT_cu => One(scale=:Scene, within=SceneScope(), application=:scene_degree_days, var=:TT_cu))), + ModelSpec(PlantSimEngine.Examples.Beer(0.6); name=:plant_light, on=Many(scale=:Plant)), + ModelSpec(ToyPlantRmModel(); name=:plant_rm, on=Many(scale=:Plant), inputs=(:Rm_organs => Many(scale=(:Leaf, :Internode), within=Subtree(), var=:Rm))), + ModelSpec(ToyCAllocationModel(); name=:plant_allocation, on=Many(scale=:Plant), inputs=(:carbon_assimilation => Many(scale=:Leaf, within=Subtree(), application=:leaf_assimilation, var=:carbon_assimilation), + :carbon_demand => Many(scale=(:Leaf, :Internode), within=Subtree(), var=:carbon_demand),)), + ModelSpec(ToyCDemandModel(optimal_biomass=10.0, development_duration=200.0); name=:internode_demand, on=Many(scale=:Internode), inputs=(:TT => One(scale=:Scene, within=SceneScope(), application=:scene_degree_days, var=:TT))), + ModelSpec(ToyInternodeCrazyEmergence(TT_emergence=1.0); name=:internode_emergence, on=Many(scale=:Internode), inputs=(:TT_cu => One(scale=:Scene, within=SceneScope(), application=:scene_degree_days, var=:TT_cu))), + ModelSpec(ToyMaintenanceRespirationModel(1.5, 0.06, 25.0, 0.6, 0.004); name=:internode_respiration, on=Many(scale=:Internode)), + ModelSpec(ToyAssimModel(); name=:leaf_assimilation, on=Many(scale=:Leaf), inputs=(:soil_water_content => One(scale=:Soil, within=SceneScope(), application=:soil_water, var=:soil_water_content), + :aPPFD => One(scale=:Plant, within=Ancestor(scale=:Plant), application=:plant_light, var=:aPPFD),)), + ModelSpec(ToyCDemandModel(optimal_biomass=10.0, development_duration=200.0); name=:leaf_demand, on=Many(scale=:Leaf), inputs=(:TT => One(scale=:Scene, within=SceneScope(), application=:scene_degree_days, var=:TT))), + ModelSpec(ToyMaintenanceRespirationModel(2.1, 0.06, 25.0, 1.0, 0.025); name=:leaf_respiration, on=Many(scale=:Leaf)), + ModelSpec(ToySoilWaterModel(); name=:soil_water, on=One(scale=:Soil)), ) - out_vars = Dict( - :Leaf => (:carbon_assimilation, :carbon_demand, :soil_water_content, :carbon_allocation), - :Internode => (:carbon_allocation, :TT_cu_emergence), - :Plant => (:carbon_allocation,), - :Soil => (:soil_water_content,), + model = CompositeModel( + mtg; + applications=applications, + environment=meteo_day, + status=_benchmark_mtg_status, ) + requests = OutputRequest[ + OutputRequest(:Leaf, :carbon_assimilation; name=:leaf_assimilation, application=:leaf_assimilation), + OutputRequest(:Leaf, :carbon_demand; name=:leaf_demand, application=:leaf_demand), + OutputRequest(:Internode, :TT_cu_emergence; name=:internode_emergence, application=:internode_emergence), + OutputRequest(:Plant, :carbon_offer; name=:plant_carbon_offer, application=:plant_allocation), + OutputRequest(:Soil, :soil_water_content; name=:soil_water, application=:soil_water), + ] + return model, requests, length(meteo_day) +end + +function benchmark_heavier_scene(model, requests, nsteps) + return run!(model; steps=nsteps, outputs=requests) +end - out = run!(mtg, mapping, meteo_day, tracked_outputs=out_vars, executor=SequentialEx()) -end \ No newline at end of file +function do_benchmark_on_heavier_mtg() + model, requests, nsteps = setup_heavier_model_benchmark() + return benchmark_heavier_scene(model, requests, nsteps) +end diff --git a/benchmark/test-hard-call-path-benchmark.jl b/benchmark/test-hard-call-path-benchmark.jl new file mode 100644 index 000000000..50a4c0e4c --- /dev/null +++ b/benchmark/test-hard-call-path-benchmark.jl @@ -0,0 +1,502 @@ +using Dates +using PlantSimEngine + +PlantSimEngine.@process "benchmark_call_source" verbose = false +PlantSimEngine.@process "benchmark_call_controller" verbose = false +PlantSimEngine.@process "benchmark_bulk_call_controller" verbose = false +PlantSimEngine.@process "benchmark_sampled_environment_source" verbose = false +PlantSimEngine.@process "benchmark_sampled_environment_controller" verbose = false +PlantSimEngine.@process "benchmark_unrelated_work" verbose = false + +struct BenchmarkCallSourceModel <: AbstractBenchmark_Call_SourceModel end +struct BenchmarkAlternateCallSourceModel <: AbstractBenchmark_Call_SourceModel end +struct BenchmarkCallControllerModel <: AbstractBenchmark_Call_ControllerModel end +struct BenchmarkBulkCallControllerModel{P,C} <: + AbstractBenchmark_Bulk_Call_ControllerModel + repeats::Int + publish::P + capture_context::C +end +struct BenchmarkSampledEnvironmentSourceModel <: + AbstractBenchmark_Sampled_Environment_SourceModel end +struct BenchmarkSampledEnvironmentControllerModel{E} <: + AbstractBenchmark_Sampled_Environment_ControllerModel + sampled_environment::E +end +struct BenchmarkUnrelatedWorkModel <: AbstractBenchmark_Unrelated_WorkModel end + +const BENCHMARK_BULK_CALL_CONTEXT = Ref{Any}() + +PlantSimEngine.inputs_(::BenchmarkCallSourceModel) = NamedTuple() +PlantSimEngine.outputs_(::BenchmarkCallSourceModel) = (signal=0,) + +function PlantSimEngine.run!( + ::BenchmarkCallSourceModel, + status, + environment, + constants, + context, +) + status.signal += 1 + return nothing +end + +PlantSimEngine.inputs_(::BenchmarkSampledEnvironmentSourceModel) = NamedTuple() +PlantSimEngine.outputs_(::BenchmarkSampledEnvironmentSourceModel) = + (temperature_seen=0.0,) +PlantSimEngine.environment_inputs_(::BenchmarkSampledEnvironmentSourceModel) = + (T=Required(Float64),) + +function PlantSimEngine.run!( + ::BenchmarkSampledEnvironmentSourceModel, + status, + environment, + constants, + context, +) + status.temperature_seen = environment.T + return nothing +end + +PlantSimEngine.inputs_(::BenchmarkSampledEnvironmentControllerModel) = + NamedTuple() +PlantSimEngine.outputs_(::BenchmarkSampledEnvironmentControllerModel) = + (executions=0,) + +function PlantSimEngine.run!( + model::BenchmarkSampledEnvironmentControllerModel, + status, + environment, + constants, + context, +) + run_call!( + context, + :source; + sampled_environment=model.sampled_environment, + publish=false, + ) + BENCHMARK_BULK_CALL_CONTEXT[] = context + status.executions += 1 + return nothing +end + +PlantSimEngine.inputs_(::BenchmarkAlternateCallSourceModel) = NamedTuple() +PlantSimEngine.outputs_(::BenchmarkAlternateCallSourceModel) = (signal=0,) + +function PlantSimEngine.run!( + ::BenchmarkAlternateCallSourceModel, + status, + environment, + constants, + context, +) + status.signal += 2 + return nothing +end + +PlantSimEngine.inputs_(::BenchmarkCallControllerModel) = NamedTuple() +PlantSimEngine.outputs_(::BenchmarkCallControllerModel) = (called_signal=0,) + +function PlantSimEngine.run!( + ::BenchmarkCallControllerModel, + status, + environment, + constants, + context, +) + target = only(run_call!(context, :source; publish=false)) + status.called_signal = target.status.signal + return nothing +end + +PlantSimEngine.inputs_(::BenchmarkBulkCallControllerModel) = NamedTuple() +PlantSimEngine.outputs_(::BenchmarkBulkCallControllerModel) = (executions=0,) + +function PlantSimEngine.run!( + model::BenchmarkBulkCallControllerModel, + status, + environment, + constants, + context, +) + for _ in 1:model.repeats + run_call!(context, :source; publish=model.publish) + end + model.capture_context && (BENCHMARK_BULK_CALL_CONTEXT[] = context) + status.executions += model.repeats + return nothing +end + +PlantSimEngine.inputs_(::BenchmarkUnrelatedWorkModel) = NamedTuple() +PlantSimEngine.outputs_(::BenchmarkUnrelatedWorkModel) = (work=0,) + +function PlantSimEngine.run!( + ::BenchmarkUnrelatedWorkModel, + status, + environment, + constants, + context, +) + status.work += 1 + return nothing +end + +function setup_hard_call_path_benchmark(; + nobjects=1000, + usage=:sparse, + steps=100, +) + usage in (:zero, :sparse, :dense) || error( + "Unsupported hard-call benchmark usage `$(usage)`. Use `:zero`, ", + "`:sparse`, or `:dense`.", + ) + objects = Any[PlantSimEngine.Object(:scene; scale=:Scene)] + append!( + objects, + ( + PlantSimEngine.Object( + Symbol(:leaf_, index); + scale=:Leaf, + name=Symbol(:leaf_, index), + parent=:scene, + ) + for index in 1:nobjects + ), + ) + source = ModelSpec( + BenchmarkCallSourceModel(); + name=:source, + on=Many(scale=:Leaf), + ) + unrelated = ModelSpec( + BenchmarkUnrelatedWorkModel(); + name=:unrelated, + on=Many(scale=:Leaf), + ) + applications = if usage == :zero + (source, unrelated) + else + caller_selector = + usage == :sparse ? + One(name=:leaf_1) : + Many(scale=:Leaf) + caller = ModelSpec( + BenchmarkCallControllerModel(); + name=:controller, + on=caller_selector, + calls=( + :source => + One(within=Self(), application=:source), + ), + ) + (source, caller, unrelated) + end + return CompositeModel(objects...; applications=applications), Int(steps) +end + +function benchmark_hard_call_path(model, steps) + return run!(model; steps=steps, outputs=:none) +end + +function setup_compiled_hard_call_benchmark(; + kind=:singular, + target_count=1000, + repeats=1, + publish=false, + steps=100, +) + kind in ( + :singular, + :repeated, + :nested, + :many, + :heterogeneous, + :sampled_environment, + :published, + ) || + error("Unsupported compiled hard-call benchmark kind `$(kind)`.") + if kind == :heterogeneous + template = CompositeModelTemplate( + ( + ModelSpec( + BenchmarkCallSourceModel(); + name=:source, + on=Many(scale=:Leaf), + ), + ModelSpec( + BenchmarkBulkCallControllerModel(1, false, true); + name=:controller, + on=One(scale=:Plant), + calls=( + :source => Many( + scale=:Leaf, + within=Subtree(), + application=:source, + ), + ), + ), + ); + kind=:plant, + ) + instance = ObjectInstance( + :benchmark_plant, + template; + root=PlantSimEngine.Object( + :plant; + scale=:Plant, + parent=:scene, + ), + objects=( + PlantSimEngine.Object( + :leaf_1; + scale=:Leaf, + parent=:plant, + ), + PlantSimEngine.Object( + :leaf_2; + scale=:Leaf, + parent=:plant, + ), + ), + object_overrides=( + Override( + object=:leaf_2, + application=:source, + model=BenchmarkAlternateCallSourceModel(), + ), + ), + ) + return ( + CompositeModel( + PlantSimEngine.Object(:scene; scale=:Scene), + instance, + ), + Int(steps), + ) + end + if kind == :sampled_environment + model = CompositeModel( + PlantSimEngine.Object(:scene; scale=:Scene, name=:scene), + PlantSimEngine.Object( + :leaf_1; + scale=:Leaf, + name=:leaf_1, + parent=:scene, + ); + applications=( + ModelSpec( + BenchmarkSampledEnvironmentSourceModel(); + name=:source, + on=One(name=:leaf_1), + ), + ModelSpec( + BenchmarkSampledEnvironmentControllerModel((T=30.0,)); + name=:controller, + on=One(name=:scene), + calls=( + :source => One( + name=:leaf_1, + application=:source, + ), + ), + ), + ), + environment=(T=20.0, duration=Hour(1)), + ) + return model, Int(steps) + end + leaf_count = kind == :many ? target_count : 1 + objects = Any[PlantSimEngine.Object(:scene; scale=:Scene, name=:scene)] + if kind == :nested + push!( + objects, + PlantSimEngine.Object( + :middle; + scale=:Plant, + name=:middle, + parent=:scene, + ), + ) + end + append!( + objects, + ( + PlantSimEngine.Object( + Symbol(:leaf_, index); + scale=:Leaf, + name=Symbol(:leaf_, index), + parent=kind == :nested ? :middle : :scene, + ) + for index in 1:leaf_count + ), + ) + + source = ModelSpec( + BenchmarkCallSourceModel(); + name=:source, + on=Many(scale=:Leaf), + ) + if kind == :nested + middle = ModelSpec( + BenchmarkBulkCallControllerModel(1, false, false); + name=:middle, + on=One(name=:middle), + calls=( + :source => One( + name=:leaf_1, + within=Subtree(), + application=:source, + ), + ), + ) + root = ModelSpec( + BenchmarkBulkCallControllerModel(1, false, true); + name=:root, + on=One(name=:scene), + calls=( + :source => One( + name=:middle, + within=Subtree(), + application=:middle, + ), + ), + ) + applications = (source, middle, root) + else + selector = kind == :many ? + Many(scale=:Leaf, application=:source) : + One(name=:leaf_1, application=:source) + effective_repeats = kind == :repeated ? repeats : 1 + effective_publish = kind == :published ? true : publish + controller = ModelSpec( + BenchmarkBulkCallControllerModel( + effective_repeats, + effective_publish, + true, + ); + name=:controller, + on=One(name=:scene), + calls=(:source => selector,), + ) + applications = (source, controller) + end + return ( + CompositeModel(objects...; applications=applications), + Int(steps), + ) +end + +benchmark_compiled_hard_call(model, steps) = + run!(model; steps=steps, outputs=:none) + +function setup_compiled_hard_call_step(; kwargs...) + model, _ = setup_compiled_hard_call_benchmark(; steps=1, kwargs...) + return run!(model; steps=1, outputs=:none) +end + +benchmark_compiled_hard_call_step(simulation) = step!(simulation) + +function benchmark_compiled_hard_call_invocation( + context::T; + repeats=1, + publish=false, +) where {T} + for _ in 1:repeats + run_call!(context, :source; publish=publish) + end + return nothing +end + +function compiled_hard_call_invocation_allocations( + context::T; + repeats=1, + publish=false, +) where {T} + benchmark_compiled_hard_call_invocation( + context; + repeats=repeats, + publish=publish, + ) + return @allocated benchmark_compiled_hard_call_invocation( + context; + repeats=repeats, + publish=publish, + ) +end + +function benchmark_sampled_hard_call_invocation( + context::T, + sampled_environment, +) where {T} + run_call!( + context, + :source; + sampled_environment=sampled_environment, + publish=false, + ) + return nothing +end + +function sampled_hard_call_invocation_allocations( + context::T, + sampled_environment, +) where {T} + benchmark_sampled_hard_call_invocation(context, sampled_environment) + return @allocated benchmark_sampled_hard_call_invocation( + context, + sampled_environment, + ) +end + +function hard_call_path_summary(model) + rows = PlantSimEngine.Diagnostics.explain_execution_plan(model) + return ( + no_call_targets=sum(( + row.batch_size for row in rows + if row.call_capability == :no_calls + ); init=0), + call_capable_targets=sum(( + row.batch_size for row in rows + if row.call_capability == :compiled_calls + ); init=0), + unrelated_no_call_targets=sum(( + row.batch_size for row in rows + if row.application_id == :unrelated && + row.call_capability == :no_calls + ); init=0), + ) +end + +function setup_lifecycle_hard_call_benchmark(; + nobjects=1000, + usage=:zero, +) + model, _ = setup_hard_call_path_benchmark(; + nobjects=nobjects, + usage=usage, + steps=1, + ) + simulation = run!( + model; + steps=1, + outputs=:none, + performance=true, + ) + return simulation, nobjects + 1 +end + +function benchmark_lifecycle_event(simulation, new_index) + new_id = Symbol(:leaf_, new_index) + register_object!( + simulation.model, + PlantSimEngine.Object( + new_id; + scale=:Leaf, + name=new_id, + parent=:scene, + ), + ) + continue!(simulation) + return simulation +end diff --git a/benchmark/test-multirate-buffer-benchmark.jl b/benchmark/test-multirate-buffer-benchmark.jl index 2bc67d5a5..ac35ead70 100644 --- a/benchmark/test-multirate-buffer-benchmark.jl +++ b/benchmark/test-multirate-buffer-benchmark.jl @@ -1,6 +1,4 @@ using PlantSimEngine -using MultiScaleTreeGraph -using PlantMeteo using Dates PlantSimEngine.@process "mrbenchsource" verbose = false @@ -9,90 +7,83 @@ struct MRBenchSourceModel <: AbstractMrbenchsourceModel end PlantSimEngine.inputs_(::MRBenchSourceModel) = NamedTuple() PlantSimEngine.outputs_(::MRBenchSourceModel) = (X=-Inf,) -function PlantSimEngine.run!(m::MRBenchSourceModel, models, status, meteo, constants=nothing, extra=nothing) +function PlantSimEngine.run!(m::MRBenchSourceModel, status, environment, constants=nothing, context=nothing) m.n[] += 1 status.X = float(m.n[]) end PlantSimEngine.@process "mrbenchconsumer4" verbose = false struct MRBenchConsumer4Model <: AbstractMrbenchconsumer4Model end -PlantSimEngine.inputs_(::MRBenchConsumer4Model) = (X=[-Inf],) +PlantSimEngine.inputs_(::MRBenchConsumer4Model) = (X=Required(Vector{Float64}),) PlantSimEngine.outputs_(::MRBenchConsumer4Model) = (Y4=-Inf,) -function PlantSimEngine.run!(::MRBenchConsumer4Model, models, status, meteo, constants=nothing, extra=nothing) +function PlantSimEngine.run!(::MRBenchConsumer4Model, status, environment, constants=nothing, context=nothing) status.Y4 = sum(status.X) end PlantSimEngine.@process "mrbenchconsumer24" verbose = false struct MRBenchConsumer24Model <: AbstractMrbenchconsumer24Model end -PlantSimEngine.inputs_(::MRBenchConsumer24Model) = (X=[-Inf],) +PlantSimEngine.inputs_(::MRBenchConsumer24Model) = (X=Required(Vector{Float64}),) PlantSimEngine.outputs_(::MRBenchConsumer24Model) = (Y24=-Inf,) -function PlantSimEngine.run!(::MRBenchConsumer24Model, models, status, meteo, constants=nothing, extra=nothing) +function PlantSimEngine.run!(::MRBenchConsumer24Model, status, environment, constants=nothing, context=nothing) status.Y24 = sum(status.X) end -function _build_multirate_benchmark_mtg(nleaves::Int) - mtg = Node(MultiScaleTreeGraph.NodeMTG("/", :Scene, 1, 0)) - plant = Node(mtg, MultiScaleTreeGraph.NodeMTG("+", :Plant, 1, 1)) - internode = Node(plant, MultiScaleTreeGraph.NodeMTG("/", :Internode, 1, 2)) - - for i in 1:nleaves - Node(internode, MultiScaleTreeGraph.NodeMTG("+", :Leaf, i, 2)) - end - - return mtg +function _build_multirate_benchmark_objects(nleaves::Int) + objects = PlantSimEngine.Object[ + PlantSimEngine.Object(:plant; scale=:Plant), + ] + append!( + objects, + [ + PlantSimEngine.Object(Symbol(:leaf_, i); scale=:Leaf, parent=:plant) for + i in 1:nleaves + ], + ) + return objects end function setup_multirate_buffer_benchmark(; nleaves=2000, ndays=30) - mtg = _build_multirate_benchmark_mtg(nleaves) - - mapping = ModelMapping( - :Leaf => ( - ModelSpec(MRBenchSourceModel(Ref(0))) |> TimeStepModel(1.0), - ), - :Plant => ( - ModelSpec(MRBenchConsumer4Model()) |> - MultiScaleModel([:X => [:Leaf]]) |> - TimeStepModel(ClockSpec(4.0, 1.0)) |> - InputBindings(; X=(process=:mrbenchsource, var=:X, scale=:Leaf, policy=Integrate())), - ModelSpec(MRBenchConsumer24Model()) |> - MultiScaleModel([:X => [:Leaf]]) |> - TimeStepModel(ClockSpec(24.0, 1.0)) |> - InputBindings(; X=(process=:mrbenchsource, var=:X, scale=:Leaf, policy=Integrate())), - ), + objects = _build_multirate_benchmark_objects(nleaves) + applications = ( + ModelSpec(MRBenchSourceModel(Ref(0)); name=:hourly_source, on=Many(scale=:Leaf), every=Hour(1)), + ModelSpec(MRBenchConsumer4Model(); name=:four_hour_consumer, on=One(scale=:Plant), inputs=(:X => Many( + scale=:Leaf, + within=Subtree(), + application=:hourly_source, + var=:X, + policy=Integrate(), + window=Hour(4), + )), every=Hour(4)), + ModelSpec(MRBenchConsumer24Model(); name=:daily_consumer, on=One(scale=:Plant), inputs=(:X => Many( + scale=:Leaf, + within=Subtree(), + application=:hourly_source, + var=:X, + policy=Integrate(), + window=Day(1), + )), every=Day(1)), ) nsteps = 24 * ndays - meteo = Weather(repeat([Atmosphere(T=20.0, Wind=1.0, Rh=0.65)], nsteps)) + environment = [(T=20.0, Wind=1.0, Rh=0.65, duration=Hour(1)) for _ in 1:nsteps] + model = CompositeModel(objects...; applications=applications, environment=environment) reqs = [ - OutputRequest(:Leaf, :X; name=:x_hourly, process=:mrbenchsource, policy=HoldLast()), - OutputRequest(:Leaf, :X; name=:x_daily_sum, process=:mrbenchsource, policy=Integrate(), clock=ClockSpec(24.0, 1.0)), + OutputRequest(:Plant, :Y4; name=:four_hour_total, application=:four_hour_consumer), + OutputRequest(:Plant, :Y24; name=:daily_total, application=:daily_consumer), + OutputRequest(:Leaf, :X; name=:x_daily_sum, application=:hourly_source, policy=Integrate(), clock=Day(1)), ] + return model, reqs, nsteps +end - tracked = Dict(:Plant => (:Y4, :Y24), :Leaf => (:X,)) - return mtg, mapping, meteo, reqs, tracked, nsteps +function benchmark_multirate_retain_all_run(model, nsteps) + return run!(model; steps=nsteps, outputs=:all) end -function benchmark_multirate_status_tracked_run(mtg, mapping, meteo, tracked, nsteps) - run!( - mtg, - mapping, - meteo, - nsteps=nsteps, - check=true, - executor=SequentialEx(), - tracked_outputs=tracked - ) +function benchmark_multirate_output_request_run(model, reqs, nsteps) + return run!(model; steps=nsteps, outputs=reqs) end -function benchmark_multirate_output_request_run(mtg, mapping, meteo, reqs, tracked, nsteps) - run!( - mtg, - mapping, - meteo, - nsteps=nsteps, - check=true, - executor=SequentialEx(), - tracked_outputs=reqs - ) +function benchmark_multirate_no_output_run(model, nsteps) + return run!(model; steps=nsteps, outputs=:none) end diff --git a/benchmark/test-plantbiophysics.jl b/benchmark/test-plantbiophysics.jl index 83b6f0c21..5e685df3c 100644 --- a/benchmark/test-plantbiophysics.jl +++ b/benchmark/test-plantbiophysics.jl @@ -1,182 +1,254 @@ -# For local testing : -#using Pkg -#Pkg.develop("PlantSimEngine") -#using PlantSimEngine - -using Pkg -#Pkg.add(url="https://github.com/VEZY/PlantBiophysics.jl#dev") -#Pkg.instantiate() -using Statistics -#using DataFrames -#using CSV -using Random +using BenchmarkTools +using CSV +using Dates +using DataFrames using PlantBiophysics -#using BenchmarkTools -#using Test -#using PlantMeteo - -function benchmark_plantbiophysics() - - Random.seed!(1) # Set random seed - microbenchmark_steps = 100 # Number of times the microbenchmark is run - microbenchmark_evals = 1 # N. times each sample is run to be sure of the output - N = 100 # Number of timesteps simulated for each microbenchmark step +using PlantMeteo +using PlantSimEngine +using Random - length_range = 10000 - Ra_SW_f = range(10, 500, length=length_range) - Ta = range(18, 40, length=length_range) - Wind = range(0.5, 20, length=length_range) - P = range(90, 101, length=length_range) - Rh = range(0.1, 0.98, length=length_range) - Ca = range(360, 900, length=length_range) - skyF = range(0.0, 1.0, length=length_range) - d = range(0.001, 0.5, length=length_range) - Jmax = range(200.0, 300.0, length=length_range) - Vmax = range(150.0, 250.0, length=length_range) - Rd = range(0.3, 2.0, length=length_range) - TPU = range(5.0, 20.0, length=length_range) - g0 = range(0.001, 2.0, length=length_range) - g1 = range(0.5, 15.0, length=length_range) - vars = hcat([Ta, Wind, P, Rh, Ca, Jmax, Vmax, Rd, Ra_SW_f, skyF, d, TPU, g0, g1]) +function _plantbiophysics_forcing_set(n::Int) + Random.seed!(1) + length_range = 10_000 + ranges = ( + T=range(18, 40; length=length_range), + Wind=range(0.5, 20; length=length_range), + P=range(90, 101; length=length_range), + Rh=range(0.1, 0.98; length=length_range), + Ca=range(360, 900; length=length_range), + JMaxRef=range(200.0, 300.0; length=length_range), + VcMaxRef=range(150.0, 250.0; length=length_range), + RdRef=range(0.3, 2.0; length=length_range), + Ra_SW_f=range(10, 500; length=length_range), + sky_fraction=range(0.0, 1.0; length=length_range), + d=range(0.001, 0.5; length=length_range), + TPURef=range(5.0, 20.0; length=length_range), + g0=range(0.001, 2.0; length=length_range), + g1=range(0.5, 15.0; length=length_range), + ) + columns = (; ( + name => [rand(values) for _ in 1:n] + for (name, values) in pairs(ranges) + )...) + return DataFrame(columns) +end - set = [rand.(vars) for i = 1:N] - set = reshape(vcat(set...), (length(set[1]), length(set)))' - name = [ - "T", - "Wind", - "P", - "Rh", - "Ca", - "JMaxRef", - "VcMaxRef", - "RdRef", - "Ra_SW_f", - "sky_fraction", - "d", - "TPURef", - "g0", - "g1", - ] - set = DataFrame(set, name) - @. set[!, :vpd] = e_sat(set.T) - vapor_pressure(set.T, set.Rh) - @. set[!, :aPPFD] = set.Ra_SW_f * 0.48 * 4.57 +function _plantbiophysics_atmosphere(row) + return Atmosphere( + T=row.T, + Wind=row.Wind, + P=row.P, + Rh=row.Rh, + Cₐ=row.Ca, + duration=Hour(1), + ) +end - constants = Constants() - #time_PB = Vector{Float64}(undef, N*microbenchmark_steps) - for i = 1:N - leaf = ModelMapping( - energy_balance=Monteith(), - photosynthesis=Fvcb( - VcMaxRef=set.VcMaxRef[i], - JMaxRef=set.JMaxRef[i], - RdRef=set.RdRef[i], - TPURef=set.TPURef[i], - ), - stomatal_conductance=Medlyn(set.g0[i], set.g1[i]), - status=( - Ra_SW_f=set.Ra_SW_f[i], - sky_fraction=set.sky_fraction[i], - aPPFD=set.aPPFD[i], - d=set.d[i], - ), - ) - #deps = PlantSimEngine.dep(leaf) - meteo = Atmosphere(T=set.T[i], Wind=set.Wind[i], P=set.P[i], Rh=set.Rh[i], Cₐ=set.Ca[i]) - #st = PlantMeteo.row_struct(leaf.status[1]) - #b_PB = @benchmark run!($leaf, $meteo, $constants, nothing; executor = ThreadedEx()) evals = microbenchmark_evals samples = microbenchmark_steps - run!(leaf, meteo, constants, nothing; executor=ThreadedEx()) +function _plantbiophysics_leaf_scene( + row; + environment=_plantbiophysics_atmosphere(row), +) + return PlantBiophysics.leaf_scene( + Monteith(), + Fvcb( + VcMaxRef=row.VcMaxRef, + JMaxRef=row.JMaxRef, + RdRef=row.RdRef, + TPURef=row.TPURef, + ), + Medlyn(row.g0, row.g1); + status=Status( + Ra_SW_f=row.Ra_SW_f, + sky_fraction=row.sky_fraction, + aPPFD=row.Ra_SW_f * 0.48 * 4.57, + d=row.d, + ), + environment=environment, + ) +end - # transform in seconds - #=for j in 1:microbenchmark_steps - time_PB[microbenchmark_steps*(i-1) + j] = b_PB.times[j]*1e-9 - end=# - end - #return time_PB +function setup_plantbiophysics_multistep(; nsteps=8760) + forcing = _plantbiophysics_forcing_set(nsteps) + environment = Weather([ + _plantbiophysics_atmosphere(row) + for row in eachrow(forcing) + ]) + return ( + _plantbiophysics_leaf_scene(first(eachrow(forcing)); environment), + nsteps, + ) end -function setup_benchmark_plantbiophysics_multitimestep() +function benchmark_plantbiophysics_multistep(model, nsteps; outputs=:none) + return run!(model; steps=nsteps, outputs=outputs) +end - Random.seed!(1) # Set random seed - N = 100 # Number of timesteps simulated for each microbenchmark step +function setup_benchmark_plantbiophysics_batch(; n=100) + forcing = _plantbiophysics_forcing_set(n) + return [_plantbiophysics_leaf_scene(row) for row in eachrow(forcing)] +end - length_range = 10000 - Ra_SW_f = range(10, 500, length=length_range) - Ta = range(18, 40, length=length_range) - Wind = range(0.5, 20, length=length_range) - P = range(90, 101, length=length_range) - Rh = range(0.1, 0.98, length=length_range) - Ca = range(360, 900, length=length_range) - skyF = range(0.0, 1.0, length=length_range) - d = range(0.001, 0.5, length=length_range) - Jmax = range(200.0, 300.0, length=length_range) - Vmax = range(150.0, 250.0, length=length_range) - Rd = range(0.3, 2.0, length=length_range) - TPU = range(5.0, 20.0, length=length_range) - g0 = range(0.001, 2.0, length=length_range) - g1 = range(0.5, 15.0, length=length_range) - vars = hcat([Ta, Wind, P, Rh, Ca, Jmax, Vmax, Rd, Ra_SW_f, skyF, d, TPU, g0, g1]) +function benchmark_plantbiophysics_batch(scenes) + constants = Constants() + for model in scenes + run!(model; constants=constants, outputs=:none) + end + return nothing +end - set = [rand.(vars) for i = 1:N] - set = reshape(vcat(set...), (length(set[1]), length(set)))' - name = [ - "T", - "Wind", - "P", - "Rh", - "Ca", - "JMaxRef", - "VcMaxRef", - "RdRef", - "Ra_SW_f", - "sky_fraction", - "d", - "TPURef", - "g0", - "g1", - ] - set = DataFrame(set, name) - @. set[!, :vpd] = e_sat(set.T) - vapor_pressure(set.T, set.Rh) - @. set[!, :aPPFD] = set.Ra_SW_f * 0.48 * 4.57 +function benchmark_plantbiophysics_fanout(; n=100) + scenes = setup_benchmark_plantbiophysics_batch(; n=n) + return benchmark_plantbiophysics_batch(scenes) +end - leaf = Vector{ModelMapping}(undef, N) - for i = 1:N - leaf[i] = ModelMapping( - energy_balance=Monteith(), - photosynthesis=Fvcb( - VcMaxRef=set.VcMaxRef[i], - JMaxRef=set.JMaxRef[i], - RdRef=set.RdRef[i], - TPURef=set.TPURef[i], - ), - stomatal_conductance=Medlyn(set.g0[i], set.g1[i]), - status=( - Ra_SW_f=set.Ra_SW_f, - sky_fraction=set.sky_fraction, - aPPFD=set.aPPFD, - d=set.d, - ), - ) +function _plantbiophysics_performance_record( + stage, + trial; + scope, + output_policy, + nscenes, + nsteps_per_scene, +) + median_estimate = BenchmarkTools.median(trial) + minimum_estimate = BenchmarkTools.minimum(trial) + total_model_steps = nscenes * nsteps_per_scene + median_time_per_step_ns = if iszero(total_model_steps) + NaN + else + median_estimate.time / total_model_steps end - - atm = Vector{Atmosphere}(undef, N) - for i in 1:N - atm[i] = Atmosphere(T=set.T[i], Wind=set.Wind[i], P=set.P[i], Rh=set.Rh[i], Cₐ=set.Ca[i]) + minimum_time_per_step_ns = if iszero(total_model_steps) + NaN + else + minimum_estimate.time / total_model_steps end - meteo = Weather(atm) - - return leaf, meteo + return ( + recorded_at=Dates.format( + Dates.now(), + dateformat"yyyy-mm-ddTHH:MM:SS.sss", + ), + stage=String(stage), + julia_version=string(VERSION), + threads=Threads.nthreads(), + plantsimengine_version=string(pkgversion(PlantSimEngine)), + plantbiophysics_version=string(pkgversion(PlantBiophysics)), + scope=String(scope), + output_policy=String(output_policy), + nscenes=nscenes, + nsteps_per_scene=nsteps_per_scene, + total_model_steps=total_model_steps, + samples=length(trial), + median_time_ns=median_estimate.time, + minimum_time_ns=minimum_estimate.time, + median_time_per_step_ns=median_time_per_step_ns, + minimum_time_per_step_ns=minimum_time_per_step_ns, + median_memory_bytes=median_estimate.memory, + minimum_memory_bytes=minimum_estimate.memory, + median_allocations=median_estimate.allocs, + minimum_allocations=minimum_estimate.allocs, + ) end -function benchmark_plantbiophysics_multitimestep_MT(leaf, meteo) - N = length(meteo) - for i in 1:N - run!(leaf[i], meteo, Constants(), nothing; executor=ThreadedEx()) - end +function run_plantbiophysics_performance_profile(; + nsteps=8760, + fanout_scenes=100, + samples=10, +) + nsteps > 0 || error("PlantBiophysics benchmark step count must be positive.") + fanout_scenes > 0 || + error("PlantBiophysics benchmark fan-out count must be positive.") + samples > 0 || + error("PlantBiophysics benchmark sample count must be positive.") + + warm_model, warm_steps = setup_plantbiophysics_multistep(; + nsteps=min(nsteps, 2), + ) + benchmark_plantbiophysics_multistep( + warm_model, + warm_steps; + outputs=:none, + ) + warm_model, warm_steps = setup_plantbiophysics_multistep(; + nsteps=min(nsteps, 2), + ) + benchmark_plantbiophysics_multistep( + warm_model, + warm_steps; + outputs=:all, + ) + benchmark_plantbiophysics_fanout(; n=min(fanout_scenes, 2)) + + no_retention_trial = BenchmarkTools.@benchmark benchmark_plantbiophysics_multistep( + model, + $nsteps; + outputs=:none, + ) setup = ((model, setup_steps) = setup_plantbiophysics_multistep( + nsteps=$nsteps, + )) samples = samples evals = 1 + retain_all_trial = BenchmarkTools.@benchmark benchmark_plantbiophysics_multistep( + model, + $nsteps; + outputs=:all, + ) setup = ((model, setup_steps) = setup_plantbiophysics_multistep( + nsteps=$nsteps, + )) samples = samples evals = 1 + construction_trial = BenchmarkTools.@benchmark setup_plantbiophysics_multistep( + nsteps=$nsteps, + ) samples = samples evals = 1 + fanout_trial = BenchmarkTools.@benchmark benchmark_plantbiophysics_batch( + scenes, + ) setup = (scenes = setup_benchmark_plantbiophysics_batch( + n=$fanout_scenes, + )) samples = samples evals = 1 + + return [ + _plantbiophysics_performance_record( + :steady_state_no_retention, + no_retention_trial; + scope=:one_setup_many_timesteps, + output_policy=:none, + nscenes=1, + nsteps_per_scene=nsteps, + ), + _plantbiophysics_performance_record( + :steady_state_retain_all, + retain_all_trial; + scope=:one_setup_many_timesteps, + output_policy=:all, + nscenes=1, + nsteps_per_scene=nsteps, + ), + _plantbiophysics_performance_record( + :construction_only, + construction_trial; + scope=:setup, + output_policy=:not_applicable, + nscenes=1, + nsteps_per_scene=0, + ), + _plantbiophysics_performance_record( + :one_step_fanout, + fanout_trial; + scope=:many_setups_one_timestep, + output_policy=:none, + nscenes=fanout_scenes, + nsteps_per_scene=1, + ), + ] end -function benchmark_plantbiophysics_multitimestep_ST(leaf, meteo) - N = length(meteo) - for i in 1:N - run!(leaf[i], meteo, Constants(), nothing; executor=SequentialEx()) - end -end \ No newline at end of file +function write_plantbiophysics_performance_profile( + path; + nsteps=8760, + fanout_scenes=100, + samples=10, +) + records = run_plantbiophysics_performance_profile(; + nsteps=nsteps, + fanout_scenes=fanout_scenes, + samples=samples, + ) + mkpath(dirname(path)) + CSV.write(path, DataFrame(records)) + return records +end diff --git a/benchmark/test-xpalm.jl b/benchmark/test-xpalm.jl index e3d9f7c98..e06317c2a 100644 --- a/benchmark/test-xpalm.jl +++ b/benchmark/test-xpalm.jl @@ -1,60 +1,235 @@ -#using Pkg -#Pkg.develop("PlantSimEngine") -#using PlantSimEngine - -using Pkg -#Pkg.add(url="https://github.com/PalmStudio/XPalm.jl#dev") -#Pkg.instantiate() -using Test -using PlantMeteo#, MultiScaleTreeGraph -#using CairoMakie, AlgebraOfGraphics -using DataFrames, CSV, Statistics +using BenchmarkTools +using CSV +using DataFrames using Dates +using PlantSimEngine using XPalm -using BenchmarkTools -function xpalm_default_param_create() - meteo = CSV.read(joinpath(dirname(dirname(pathof(XPalm))), "0-data", "meteo.csv"), DataFrame) - #meteo.duration = [Dates.Day(i[1:1]) for i in meteo.duration] - m = Weather(meteo) +const XPALM_REFERENCE_BENCHMARK_VARIABLES = Dict{Symbol,Any}( + :Scene => (:lai, :leaf_area, :aPPFD), + :Plant => ( + :plant_age, + :leaf_area, + :aPPFD, + :Rm, + :carbon_assimilation, + :phytomer_count, + :biomass_bunch_harvested, + :biomass_bunch_harvested_cum, + :n_bunches_harvested, + :n_bunches_harvested_cum, + :biomass_oil_harvested, + :biomass_oil_harvested_cum, + ), + :Soil => (:ftsw, :root_depth), +) + +const XPALM_SMALL_BENCHMARK_VARIABLES = Dict{Symbol,Any}( + :Scene => (:lai,), +) + +function _xpalm_output_requests(model, vars) + applications = PlantSimEngine.Diagnostics.explain_applications(model) + requests = OutputRequest[] + for (scale, variables) in pairs(vars) + for variable in variables + scale_symbol = Symbol(scale) + variable_symbol = Symbol(variable) + candidates = [ + row.application_id + for row in applications + if ( + scale_symbol in row.target_scales || + PlantSimEngine.Diagnostics.object_address( + row.applies_to, + ).scale == scale_symbol + ) && variable_symbol in row.outputs + ] + isempty(candidates) && error( + "No XPalm benchmark output publisher for `$(scale_symbol).$(variable_symbol)`.", + ) + push!( + requests, + OutputRequest( + scale_symbol, + variable_symbol; + name=Symbol(scale, "__", variable), + application=last(candidates), + ), + ) + end + end + return requests +end + +function _xpalm_benchmark_meteo(; nsteps=nothing) + meteo = CSV.read( + joinpath(dirname(dirname(pathof(XPalm))), "0-data", "meteo.csv"), + DataFrame, + ) + :duration in propertynames(meteo) || + (meteo.duration = fill(Day(1), nrow(meteo))) + isnothing(nsteps) && return meteo + requested_steps = Int(nsteps) + 1 <= requested_steps <= nrow(meteo) || error( + "XPalm benchmark `nsteps` must be between 1 and $(nrow(meteo)), got $(requested_steps).", + ) + return meteo[1:requested_steps, :] +end - out_vars = Dict{Symbol,Any}( +function xpalm_reference_model_create(; nsteps=nothing) + meteo = _xpalm_benchmark_meteo(; nsteps=nsteps) + palm = XPalm.Palm( + initiation_age=0, + parameters=XPalm.default_parameters(), + ) + model = XPalm.xpalm_scene(palm; environment=meteo) + return model, nrow(meteo) +end + +function _xpalm_benchmark_scene(vars; nsteps=nothing) + model, resolved_steps = xpalm_reference_model_create(; nsteps=nsteps) + return model, _xpalm_output_requests(model, vars), resolved_steps +end + +function xpalm_default_param_create(; nsteps=nothing) + vars = Dict{Symbol,Any}( :Scene => (:lai,), - # :Scene => (:LAI, :scene_leaf_area, :aPPFD, :TEff), - # :Plant => (:plant_age, :ftsw, :newPhytomerEmergence, :aPPFD, :plant_leaf_area, :carbon_assimilation, :carbon_offer_after_rm, :Rm, :TT_since_init, :TEff, :phytomer_count, :newPhytomerEmergence), - :Leaf => (:Rm, :potential_area, :TT_since_init, :TEff, :biomass, :carbon_demand, :carbon_allocation,), - # :Leaf => (:Rm, :potential_area), - # :Internode => (:Rm, :carbon_allocation, :carbon_demand), + :Leaf => ( + :Rm, + :potential_area, + :TT_since_init, + :biomass, + :carbon_demand, + ), :Male => (:Rm,), - # :Female => (:biomass,), - # :Soil => (:TEff, :ftsw, :root_depth), ) + return _xpalm_benchmark_scene(vars; nsteps=nsteps) +end - # Example 1: Run the model with the default parameters (but output as a DataFrame): - palm = XPalm.Palm(initiation_age=0, parameters=XPalm.default_parameters()) - models = XPalm.model_mapping(palm) - return palm, models, out_vars, m +function xpalm_small_param_create(; nsteps=nothing) + return _xpalm_benchmark_scene( + XPALM_SMALL_BENCHMARK_VARIABLES; + nsteps=nsteps, + ) end -function xpalm_default_param_run(palm, models, out_vars, meteo) - sim_outputs = PlantSimEngine.run!(palm.mtg, models, meteo, tracked_outputs=out_vars, executor=PlantSimEngine.SequentialEx(), check=false) - return sim_outputs +function xpalm_reference_param_create(; nsteps=nothing) + return _xpalm_benchmark_scene( + XPALM_REFERENCE_BENCHMARK_VARIABLES; + nsteps=nsteps, + ) end -function xpalm_default_param_convert_outputs(sim_outputs) - df = PlantSimEngine.convert_outputs(sim_outputs, DataFrame, no_value=missing) - return df +function xpalm_reference_end_to_end(; nsteps=nothing) + meteo = _xpalm_benchmark_meteo(; nsteps=nsteps) + return XPalm.xpalm( + meteo, + DataFrame; + vars=XPALM_REFERENCE_BENCHMARK_VARIABLES, + architecture=false, + palm=XPalm.Palm( + initiation_age=0, + parameters=XPalm.default_parameters(), + ), + ) end +function xpalm_default_param_run( + model, + requests, + nsteps; + outputs=requests, + performance=false, +) + return PlantSimEngine.run!( + model; + steps=nsteps, + outputs=outputs, + performance=performance, + ) +end + +function xpalm_reference_final_phytomer_count(simulation) + plant = only(PlantSimEngine.model_objects(simulation.model; scale=:Plant)) + return plant.status.phytomer_count +end + +function xpalm_reference_final_state(simulation) + plant = only(PlantSimEngine.model_objects(simulation.model; scale=:Plant)) + scene = only(PlantSimEngine.model_objects(simulation.model; scale=:Scene)) + soil = only(PlantSimEngine.model_objects(simulation.model; scale=:Soil)) + return ( + current_step=PlantSimEngine.current_step(simulation), + phytomer_count=plant.status.phytomer_count, + lai=scene.status.lai, + ftsw=soil.status.ftsw, + ) +end + +function xpalm_reference_param_run( + model, + requests, + nsteps; + outputs=requests, + performance=false, +) + return xpalm_default_param_run( + model, + requests, + nsteps; + outputs=outputs, + performance=performance, + ) +end -println(Pkg.status("XPalm")) +function xpalm_reference_full_cycle_expected_state() + return ( + current_step=4160, + phytomer_count=344, + lai=5.0587602356164405, + ftsw=0.7991179101191216, + ) +end -#=@testset "XPalm simple test" begin - # default number of seconds is 5 - b_XP = @benchmark xpalm_default_param_run() seconds = 120 +function xpalm_reference_state_matches( + state, + expected=xpalm_reference_full_cycle_expected_state(); + atol=1.0e-8, + rtol=1.0e-8, +) + return state.current_step == expected.current_step && + state.phytomer_count == expected.phytomer_count && + isapprox(state.lai, expected.lai; atol=atol, rtol=rtol) && + isapprox(state.ftsw, expected.ftsw; atol=atol, rtol=rtol) +end - #N = length(b_XP.times) +function xpalm_reference_high_level_final_state(outputs) + plant = outputs[:Plant] + scene = outputs[:Scene] + soil = outputs[:Soil] + return ( + current_step=nrow(plant), + phytomer_count=last(plant.phytomer_count), + lai=last(scene.lai), + ftsw=last(soil.ftsw), + ) +end - @test mean(b_XP.times*1e-9) > 10 - @test mean(b_XP.times*1e-9) < 15 -end =# \ No newline at end of file +function xpalm_reference_high_level_state_matches( + outputs; + expected=xpalm_reference_full_cycle_expected_state(), + atol=1.0e-8, + rtol=1.0e-8, +) + return xpalm_reference_state_matches( + xpalm_reference_high_level_final_state(outputs), + expected; + atol=atol, + rtol=rtol, + ) +end + +function xpalm_default_param_collect_outputs(simulation) + return PlantSimEngine.collect_outputs(simulation; sink=DataFrame) +end diff --git a/benchmark/test/runtests.jl b/benchmark/test/runtests.jl new file mode 100644 index 000000000..4eb4100f3 --- /dev/null +++ b/benchmark/test/runtests.jl @@ -0,0 +1,920 @@ +using BenchmarkTools +using CSV +using DataFrames +using Dates +using MultiScaleTreeGraph +using PlantMeteo +using PlantSimEngine +using PlantSimEngine.Examples +using Profile +using Statistics +using Test +using TOML + +const BENCHMARK_TEST_PATTERN = + isempty(ARGS) ? nothing : Regex(only(ARGS), "i") +benchmark_test_enabled(name) = + isnothing(BENCHMARK_TEST_PATTERN) || + occursin(BENCHMARK_TEST_PATTERN, name) + +if benchmark_test_enabled("full-performance project bootstrap smoke") + @testset "full-performance project bootstrap smoke" begin + include( + joinpath( + @__DIR__, + "..", + "prepare_full_performance_project.jl", + ), + ) + mktempdir() do directory + project_path = joinpath(directory, "Project.toml") + cp( + joinpath(@__DIR__, "..", "Project.toml"), + project_path, + ) + prepare_full_performance_project!(project_path) + project = TOML.parsefile(project_path) + @test !haskey(project, "sources") + @test haskey(project["deps"], "PlantSimEngine") + @test haskey(project["deps"], "XPalm") + @test haskey(project["deps"], "PlantBiophysics") + end + mktempdir() do directory + project_path = joinpath(directory, "Project.toml") + cp( + joinpath(@__DIR__, "..", "Project.toml"), + project_path, + ) + prepare_plantbiophysics_performance_project!(project_path) + project = TOML.parsefile(project_path) + @test !haskey(project, "sources") + @test haskey(project["deps"], "PlantSimEngine") + @test haskey(project["deps"], "PlantBiophysics") + @test !haskey(project["deps"], "XPalm") + end + + release_root = joinpath(@__DIR__, "..", "release_baselines") + release_projects = Dict( + :plantbiophysics => TOML.parsefile( + joinpath(release_root, "plantbiophysics", "Project.toml"), + ), + :xpalm => TOML.parsefile( + joinpath(release_root, "xpalm", "Project.toml"), + ), + ) + @test release_projects[:plantbiophysics]["sources"][ + "PlantBiophysics" + ]["rev"] == "9f39af4ffd48bab234e5d80b89cd52c67b9f3f82" + @test release_projects[:plantbiophysics]["sources"][ + "PlantSimEngine" + ]["rev"] == "503af98c3709a0b1207407e3741b7cb09ebfbcf7" + @test release_projects[:xpalm]["sources"]["XPalm"]["rev"] == + "a0dbf2e8d6fa9e21f8e8ced3220da184b3ee3f4c" + @test release_projects[:xpalm]["sources"][ + "PlantSimEngine" + ]["rev"] == "503af98c3709a0b1207407e3741b7cb09ebfbcf7" + for downstream in keys(release_projects) + runner = joinpath(release_root, String(downstream), "run.jl") + @test Meta.parseall(read(runner, String)) isa Expr + end + end +end + +if benchmark_test_enabled("PlantSimEngine benchmark API smoke") + @testset "PlantSimEngine benchmark API smoke" begin + include(joinpath(@__DIR__, "..", "test-PSE-benchmark.jl")) + model, requests, _ = setup_heavier_model_benchmark() + simulation = benchmark_heavier_scene(model, requests, 1) + @test current_step(simulation) == 1 + @test !isempty(collect_outputs(simulation; sink=nothing)) + end +end + +if benchmark_test_enabled("multirate benchmark API smoke") + @testset "multirate benchmark API smoke" begin + include(joinpath(@__DIR__, "..", "test-multirate-buffer-benchmark.jl")) + model, requests, nsteps = + setup_multirate_buffer_benchmark(; ndays=1, nleaves=4) + simulation = + benchmark_multirate_output_request_run(model, requests, nsteps) + @test current_step(simulation) == nsteps + @test !isempty(collect_outputs(simulation; sink=nothing)) + no_output_model, _, no_output_steps = + setup_multirate_buffer_benchmark(; ndays=1, nleaves=4) + no_output_simulation = + benchmark_multirate_no_output_run( + no_output_model, + no_output_steps, + ) + @test current_step(no_output_simulation) == no_output_steps + retention = + PlantSimEngine.Diagnostics.explain_output_retention( + no_output_simulation, + ) + @test all( + row.reasons == (:temporal_dependency,) + for row in retention + ) + @test maximum( + length, + values(outputs(no_output_simulation)), + ) <= 25 + end +end + +if benchmark_test_enabled("lifecycle benchmark API smoke") + @testset "lifecycle benchmark API smoke" begin + isdefined(@__MODULE__, :BenchmarkCallSourceModel) || + include( + joinpath( + @__DIR__, + "..", + "test-hard-call-path-benchmark.jl", + ), + ) + for (nobjects, usage) in ( + (8, :zero), + (64, :zero), + (16, :dense), + ) + simulation, new_index = + setup_lifecycle_hard_call_benchmark(; + nobjects=nobjects, + usage=usage, + ) + benchmark_lifecycle_event(simulation, new_index) + new_id = Symbol(:leaf_, new_index) + new_object = only( + object for object in model_objects( + simulation.model; + scale=:Leaf, + ) + if object.id == ObjectId(new_id) + ) + @test current_step(simulation) == 2 + @test new_object.status.work == 1 + @test new_object.status.signal == 1 + if usage == :dense + @test new_object.status.called_signal == 1 + end + performance = + PlantSimEngine.Advanced.runtime_performance(simulation) + @test performance.counts[ + :execution_target_rebuild_new + ] <= 3 + end + end +end + +if benchmark_test_enabled("hard-call path benchmark API smoke") + @testset "hard-call path benchmark API smoke" begin + include(joinpath(@__DIR__, "..", "test-hard-call-path-benchmark.jl")) + expected_call_targets = Dict( + :zero => 0, + :sparse => 1, + :dense => 16, + ) + for usage in (:zero, :sparse, :dense) + model, steps = setup_hard_call_path_benchmark(; + nobjects=16, + usage=usage, + steps=2, + ) + summary = hard_call_path_summary(model) + @test summary.call_capable_targets == + expected_call_targets[usage] + @test summary.unrelated_no_call_targets == 16 + simulation = benchmark_hard_call_path(model, steps) + @test current_step(simulation) == steps + @test all( + object.status.work == steps + for object in model_objects(model; scale=:Leaf) + ) + end + for (kind, repeats, target_count, expected_signal) in ( + (:singular, 1, 1, 2), + (:repeated, 8, 1, 16), + (:nested, 1, 1, 2), + (:many, 1, 8, 2), + (:published, 1, 1, 2), + ) + model, steps = setup_compiled_hard_call_benchmark(; + kind=kind, + repeats=repeats, + target_count=target_count, + steps=2, + ) + simulation = benchmark_compiled_hard_call(model, steps) + @test current_step(simulation) == steps + leaves = model_objects(model; scale=:Leaf) + @test length(leaves) == target_count + @test all( + leaf.status.signal == expected_signal for leaf in leaves + ) + end + heterogeneous_model, heterogeneous_steps = + setup_compiled_hard_call_benchmark(; + kind=:heterogeneous, + steps=2, + ) + heterogeneous_simulation = benchmark_compiled_hard_call( + heterogeneous_model, + heterogeneous_steps, + ) + heterogeneous_leaves = sort!( + model_objects(heterogeneous_model; scale=:Leaf); + by=object -> string(object.id.value), + ) + @test current_step(heterogeneous_simulation) == 2 + @test getproperty.(getproperty.(heterogeneous_leaves, :status), :signal) == + [2, 4] + sampled_model, sampled_steps = setup_compiled_hard_call_benchmark(; + kind=:sampled_environment, + steps=2, + ) + sampled_simulation = benchmark_compiled_hard_call( + sampled_model, + sampled_steps, + ) + sampled_leaf = only(model_objects(sampled_model; scale=:Leaf)) + @test current_step(sampled_simulation) == 2 + @test sampled_leaf.status.temperature_seen == 30.0 + for (kind, repeats, target_count) in ( + (:singular, 1, 1), + (:repeated, 8, 1), + (:nested, 1, 1), + (:many, 1, 8), + (:heterogeneous, 1, 2), + ) + setup_compiled_hard_call_step(; + kind=kind, + repeats=repeats, + target_count=target_count, + ) + context = BENCHMARK_BULK_CALL_CONTEXT[] + @test compiled_hard_call_invocation_allocations( + context; + repeats=repeats, + publish=false, + ) == 0 + end + setup_compiled_hard_call_step(; kind=:published) + published_context = BENCHMARK_BULK_CALL_CONTEXT[] + @test compiled_hard_call_invocation_allocations( + published_context; + publish=true, + ) <= 256 + setup_compiled_hard_call_step(; kind=:sampled_environment) + sampled_context = BENCHMARK_BULK_CALL_CONTEXT[] + @test sampled_hard_call_invocation_allocations( + sampled_context, + (T=31.0,), + ) == 0 + end +end + +if benchmark_test_enabled("internal-only benchmark suite assembly smoke") + @testset "internal-only benchmark suite assembly smoke" begin + benchmark_module = Module(:InternalOnlyBenchmarkSuite) + Core.eval( + benchmark_module, + :(include(path) = Base.include(@__MODULE__, path)), + ) + Core.eval(benchmark_module, :(const Object = Nothing)) + include_error = try + withenv( + "GITHUB_ACTIONS" => "true", + "PSE_BENCHMARK_INCLUDE_DOWNSTREAM" => nothing, + "PSE_BENCHMARK_FORCE_LEGACY_BASELINE" => nothing, + ) do + Base.include( + benchmark_module, + joinpath(@__DIR__, "..", "benchmarks.jl"), + ) + end + nothing + catch error + sprint(showerror, error, catch_backtrace()) + end + @test isnothing(include_error) + if isnothing(include_error) + suite = getfield( + benchmark_module, + :SUITE, + )[getfield(benchmark_module, :suite_name)] + @test haskey(suite, "PSE_status_read_write") + @test haskey(suite, "PSE") + @test haskey(suite, "PSE_hard_calls_zero") + @test haskey(suite, "PSE_lifecycle_large") + @test !haskey(suite, "PBP") + @test !haskey(suite, "PBP_batch_run") + @test !haskey(suite, "XPalm_run_100") + @test !haskey(suite, "XPalm_all_outputs_100") + end + end +end + +if benchmark_test_enabled("legacy benchmark suite assembly smoke") + @testset "legacy benchmark suite assembly smoke" begin + benchmark_module = Module(:LegacyBenchmarkSuite) + Core.eval( + benchmark_module, + :(include(path) = Base.include(@__MODULE__, path)), + ) + include_error = try + withenv( + "GITHUB_ACTIONS" => "true", + "PSE_BENCHMARK_INCLUDE_DOWNSTREAM" => nothing, + "PSE_BENCHMARK_FORCE_LEGACY_BASELINE" => "true", + ) do + Base.include( + benchmark_module, + joinpath(@__DIR__, "..", "benchmarks.jl"), + ) + end + nothing + catch error + sprint(showerror, error, catch_backtrace()) + end + @test isnothing(include_error) + if isnothing(include_error) + suite = getfield( + benchmark_module, + :SUITE, + )[getfield(benchmark_module, :suite_name)] + @test haskey(suite, "PSE_status_read_write") + @test !haskey(suite, "PSE") + @test !haskey(suite, "PSE_multirate_no_output_run") + @test !haskey(suite, "PSE_hard_calls_zero") + @test !haskey(suite, "PBP") + @test !haskey(suite, "XPalm_run_100") + end + end +end + +if benchmark_test_enabled("PlantBiophysics benchmark API smoke") + @testset "PlantBiophysics benchmark API smoke" begin + include(joinpath(@__DIR__, "..", "test-plantbiophysics.jl")) + scenes = setup_benchmark_plantbiophysics_batch(; n=2) + @test isnothing(benchmark_plantbiophysics_batch(scenes)) + model, nsteps = setup_plantbiophysics_multistep(; nsteps=2) + simulation = benchmark_plantbiophysics_multistep( + model, + nsteps; + outputs=:none, + ) + @test current_step(simulation) == nsteps + records = run_plantbiophysics_performance_profile(; + nsteps=2, + fanout_scenes=2, + samples=2, + ) + @test Set(record.stage for record in records) == + Set([ + "steady_state_no_retention", + "steady_state_retain_all", + "construction_only", + "one_step_fanout", + ]) + steady_records = filter( + record -> record.scope == "one_setup_many_timesteps", + records, + ) + @test length(steady_records) == 2 + @test all(record.nscenes == 1 for record in steady_records) + @test all(record.nsteps_per_scene == 2 for record in steady_records) + @test all(record.total_model_steps == 2 for record in steady_records) + @test all(record.samples == 2 for record in records) + @test all(record.minimum_time_ns > 0 for record in records) + end +end + +if !isnothing(BENCHMARK_TEST_PATTERN) && + benchmark_test_enabled("PlantBiophysics benchmark performance") + @testset "PlantBiophysics benchmark performance" begin + isdefined(@__MODULE__, :run_plantbiophysics_performance_profile) || + include(joinpath(@__DIR__, "..", "test-plantbiophysics.jl")) + output_path = get( + ENV, + "PSE_PLANTBIOPHYSICS_BENCHMARK_OUTPUT", + joinpath( + @__DIR__, + "..", + "results", + "plantbiophysics-full-latest.csv", + ), + ) + samples = parse( + Int, + get(ENV, "PSE_PLANTBIOPHYSICS_BENCHMARK_SAMPLES", "10"), + ) + nsteps = parse( + Int, + get(ENV, "PSE_PLANTBIOPHYSICS_BENCHMARK_STEPS", "8760"), + ) + fanout_scenes = parse( + Int, + get(ENV, "PSE_PLANTBIOPHYSICS_FANOUT_SCENES", "100"), + ) + records = write_plantbiophysics_performance_profile( + output_path; + nsteps=nsteps, + fanout_scenes=fanout_scenes, + samples=samples, + ) + @test isfile(output_path) + @test length(records) == 4 + @test only( + record.nsteps_per_scene for record in records + if record.stage == "steady_state_no_retention" + ) == nsteps + @test only( + record.nscenes for record in records + if record.stage == "one_step_fanout" + ) == fanout_scenes + @test all(record.samples == samples for record in records) + end +end + +if benchmark_test_enabled("XPalm benchmark API smoke") + @testset "XPalm benchmark API smoke" begin + include(joinpath(@__DIR__, "..", "test-xpalm.jl")) + model, requests, _ = xpalm_default_param_create() + simulation = PlantSimEngine.run!(model; steps=1, outputs=requests) + @test current_step(simulation) == 1 + @test !isempty(xpalm_default_param_collect_outputs(simulation)) + end +end + +if benchmark_test_enabled("XPalm staged performance profile smoke") + @testset "XPalm staged performance profile smoke" begin + include(joinpath(@__DIR__, "..", "performance_regression.jl")) + metadata = _performance_metadata(; warmup_policy="metadata smoke") + @test length(metadata.manifest_hash) == 64 + @test length(metadata.fixture_hash) == 64 + @test !isempty(metadata.hostname) + @test !isempty(metadata.plantgeom_revision) + result = run_xpalm_performance_profile(; profile=:smoke) + @test result.no_output_state == result.reference_state + @test result.small_state == result.reference_state + @test result.all_output_state == result.reference_state + @test result.reference_state.current_step == PERFORMANCE_SMOKE_STEPS + @test any( + row -> + row.stage == "simulation_reference_outputs" && + row.metric == "steps_executed" && + row.value == PERFORMANCE_SMOKE_STEPS, + result.records, + ) + @test any( + row -> + row.stage == "initial_scene_compilation" && + row.metric == "median_time", + result.records, + ) + @test any( + row -> + row.stage == "clean_steady_state_step" && + row.metric == "median_time", + result.records, + ) + @test any( + row -> + row.stage == "simulation_small_outputs" && + row.metric == "median_time", + result.records, + ) + @test any( + row -> + row.stage == "simulation_all_outputs" && + row.metric == "median_time", + result.records, + ) + @test any( + row -> + row.stage == "collect_reference_outputs" && + row.metric == "wall_time", + result.records, + ) + @test any( + row -> + row.stage == "simulation_reference_outputs" && + row.metric == "median_time", + result.records, + ) + @test any( + row -> + row.stage == "simulation_reference_outputs" && + row.metric == "minimum_allocations", + result.records, + ) + @test only( + row.value for row in result.records + if row.stage == "simulation_reference_outputs" && + row.metric == "samples" + ) == PERFORMANCE_STATISTICAL_SAMPLES + trial = BenchmarkTools.@benchmark 1 + 1 samples = 2 evals = 1 + group = BenchmarkTools.BenchmarkGroup() + group["tiny"] = trial + summary = _benchmark_summary_records(group, metadata) + @test length(summary) == 1 + @test only(summary).benchmark == "tiny" + @test only(summary).samples == 2 + @test only(summary).minimum_time_ns <= only(summary).median_time_ns + @test only(summary).median_allocations == 0 + end +end + +if !isnothing(BENCHMARK_TEST_PATTERN) && + benchmark_test_enabled("benchmark suite assembly smoke") + @testset "benchmark suite assembly smoke" begin + include(joinpath(@__DIR__, "..", "benchmarks.jl")) + suite = SUITE[suite_name] + @test haskey(suite, "PSE_hard_calls_zero") + @test haskey(suite, "PSE_hard_calls_sparse") + @test haskey(suite, "PSE_hard_calls_dense") + @test haskey(suite, "PSE_compiled_hard_call_singular") + @test haskey(suite, "PSE_compiled_hard_call_repeated") + @test haskey(suite, "PSE_compiled_hard_call_nested") + @test haskey(suite, "PSE_compiled_hard_call_many") + @test haskey(suite, "PSE_compiled_hard_call_heterogeneous") + @test haskey(suite, "PSE_compiled_hard_call_sampled_environment") + @test haskey(suite, "PSE_compiled_hard_call_published") + @test haskey(suite, "PSE_lifecycle_small") + @test haskey(suite, "PSE_lifecycle_large") + @test haskey( + suite, + "PSE_lifecycle_immediate_hard_call", + ) + @test haskey(suite, "PSE_multirate_no_output_run") + @test haskey(suite, "PBP_multistep_no_outputs") + @test haskey(suite, "PBP_multistep_all_outputs") + @test haskey(suite, "PBP_construction") + @test haskey(suite, "PBP_one_step_fanout") + @test haskey(suite, "XPalm_small_outputs_100") + @test haskey(suite, "XPalm_all_outputs_100") + end +end + +if !isnothing(BENCHMARK_TEST_PATTERN) && + benchmark_test_enabled("XPalm staged performance profile short") + @testset "XPalm staged performance profile short" begin + include(joinpath(@__DIR__, "..", "performance_regression.jl")) + output_path = joinpath( + @__DIR__, + "..", + "results", + "xpalm-short-latest.csv", + ) + result = write_xpalm_performance_profile(output_path; profile=:short) + @test result.no_output_state == result.reference_state + @test result.reference_state.current_step == PERFORMANCE_SHORT_STEPS + @test isfile(output_path) + @test any( + row -> + row.stage == "simulation_no_outputs" && + row.metric == "execution_targets_visited", + result.records, + ) + end +end + +if !isnothing(BENCHMARK_TEST_PATTERN) && + benchmark_test_enabled("XPalm staged performance profile medium") + @testset "XPalm staged performance profile medium" begin + include(joinpath(@__DIR__, "..", "performance_regression.jl")) + output_path = joinpath( + @__DIR__, + "..", + "results", + "xpalm-medium-latest.csv", + ) + result = write_xpalm_performance_profile(output_path; profile=:medium) + @test result.no_output_state == result.reference_state + @test result.reference_state.current_step == PERFORMANCE_MEDIUM_STEPS + @test isfile(output_path) + @test any( + row -> + row.stage == "simulation_no_outputs" && + row.metric == "output_retention_reuses", + result.records, + ) + end +end + +if !isnothing(BENCHMARK_TEST_PATTERN) && + benchmark_test_enabled("XPalm staged performance profile full") + @testset "XPalm staged performance profile full" begin + include(joinpath(@__DIR__, "..", "performance_regression.jl")) + output_path = joinpath( + @__DIR__, + "..", + "results", + "xpalm-full-latest.csv", + ) + result = write_xpalm_performance_profile(output_path; profile=:full) + @test result.no_output_state == result.reference_state + @test xpalm_reference_state_matches(result.reference_state) + @test isfile(output_path) + @test any( + row -> + row.stage == "historical_end_to_end_reference" && + row.metric == "wall_time", + result.records, + ) + end +end + +if !isnothing(BENCHMARK_TEST_PATTERN) && + benchmark_test_enabled("XPalm full no-output performance") + @testset "XPalm full no-output performance" begin + include(joinpath(@__DIR__, "..", "performance_regression.jl")) + _warmup_xpalm_performance!(PERFORMANCE_FULL_STEPS) + metadata = _performance_metadata(; + warmup_policy="unmeasured full-profile standard warmup", + ) + records = NamedTuple[] + output_path = joinpath( + @__DIR__, + "..", + "results", + "xpalm-full-no-output-latest.csv", + ) + model, nsteps = _measure_performance_stage!( + records, + metadata, + :full, + :scene_construction_no_outputs, + output_path, + ) do + xpalm_reference_model_create(; nsteps=PERFORMANCE_FULL_STEPS) + end + simulation = _measure_performance_stage!( + records, + metadata, + :full, + :simulation_no_outputs, + output_path, + ) do + xpalm_reference_param_run( + model, + OutputRequest[], + nsteps; + outputs=:none, + ) + end + final_state = xpalm_reference_final_state(simulation) + _record_xpalm_state!( + records, + metadata, + :full, + :final_state_no_outputs, + final_state, + ) + _checkpoint_performance_records(output_path, records) + @test final_state.current_step == PERFORMANCE_FULL_STEPS + @test final_state.phytomer_count == 344 + @test isfile(output_path) + end +end + +if !isnothing(BENCHMARK_TEST_PATTERN) && + benchmark_test_enabled("XPalm full warmed no-output performance") + @testset "XPalm full warmed no-output performance" begin + include(joinpath(@__DIR__, "..", "performance_regression.jl")) + warmup_model, warmup_steps = + xpalm_reference_model_create(; nsteps=PERFORMANCE_FULL_STEPS) + xpalm_reference_param_run( + warmup_model, + OutputRequest[], + warmup_steps; + outputs=:none, + ) + model, nsteps = + xpalm_reference_model_create(; nsteps=PERFORMANCE_FULL_STEPS) + metadata = _performance_metadata(; + warmup_policy="unmeasured complete 4,160-day lifecycle run", + ) + records = NamedTuple[] + output_path = joinpath( + @__DIR__, + "..", + "results", + "xpalm-full-warmed-no-output-latest.csv", + ) + simulation = _measure_performance_stage!( + records, + metadata, + :full, + :simulation_warmed_no_outputs, + output_path, + ) do + xpalm_reference_param_run( + model, + OutputRequest[], + nsteps; + outputs=:none, + ) + end + final_state = xpalm_reference_final_state(simulation) + _record_xpalm_state!( + records, + metadata, + :full, + :final_state_warmed_no_outputs, + final_state, + ) + _checkpoint_performance_records(output_path, records) + wall_time = only( + row.value for row in records + if row.stage == "simulation_warmed_no_outputs" && + row.metric == "wall_time" + ) + @test final_state.current_step == PERFORMANCE_FULL_STEPS + @test final_state.phytomer_count == 344 + @test xpalm_reference_state_matches(final_state) + @test wall_time <= 20.0 + @test isfile(output_path) + end +end + +if !isnothing(BENCHMARK_TEST_PATTERN) && + benchmark_test_enabled("XPalm full steady tail performance") + @testset "XPalm full steady tail performance" begin + include(joinpath(@__DIR__, "..", "performance_regression.jl")) + _warmup_xpalm_performance!(PERFORMANCE_SHORT_STEPS) + model, nsteps = + xpalm_reference_model_create(; nsteps=PERFORMANCE_FULL_STEPS) + tail_steps = 660 + simulation = xpalm_reference_param_run( + model, + OutputRequest[], + nsteps - tail_steps; + outputs=:none, + ) + GC.gc() + measurement = @timed PlantSimEngine.continue!( + simulation; + steps=tail_steps, + ) + output_path = joinpath( + @__DIR__, + "..", + "results", + "xpalm-full-steady-tail-latest.csv", + ) + CSV.write( + output_path, + DataFrame( + metric=["wall_time", "allocated", "gc_time"], + value=[ + measurement.time, + measurement.bytes, + measurement.gctime, + ], + ), + ) + @test current_step(simulation) == PERFORMANCE_FULL_STEPS + @test isfile(output_path) + end +end + +if !isnothing(BENCHMARK_TEST_PATTERN) && + benchmark_test_enabled("XPalm allocation profile short") + @testset "XPalm allocation profile short" begin + include(joinpath(@__DIR__, "..", "performance_regression.jl")) + _warmup_xpalm_performance!(PERFORMANCE_SHORT_STEPS) + model, nsteps = + xpalm_reference_model_create(; nsteps=PERFORMANCE_SHORT_STEPS) + Profile.Allocs.clear() + simulation = Profile.Allocs.@profile sample_rate = 0.01 xpalm_reference_param_run( + model, + OutputRequest[], + nsteps; + outputs=:none, + ) + allocation_results = Profile.Allocs.fetch() + pse_root = dirname(dirname(@__DIR__)) + xpalm_root = dirname(dirname(pathof(XPalm))) + totals = Dict{ + Tuple{String,String,Int,String,String}, + Tuple{Int,Int}, + }() + for allocation in allocation_results.allocs + frame_index = findfirst(allocation.stacktrace) do frame + file = string(frame.file) + occursin(pse_root, file) || occursin(xpalm_root, file) + end + isnothing(frame_index) && continue + frame = allocation.stacktrace[frame_index] + file = string(frame.file) + source = occursin(pse_root, file) ? "PlantSimEngine" : "XPalm" + key = ( + source, + file, + frame.line, + string(frame.func), + string(allocation.type), + ) + count, bytes = get(totals, key, (0, 0)) + totals[key] = (count + 1, bytes + allocation.size) + end + rows = [ + ( + source=first(key), + file=key[2], + line=key[3], + function_name=key[4], + allocation_type=key[5], + sampled_allocations=first(value), + sampled_bytes=last(value), + sample_rate=0.01, + ) + for (key, value) in totals + ] + sort!(rows; by=row -> row.sampled_bytes, rev=true) + output_path = joinpath( + @__DIR__, + "..", + "results", + "xpalm-allocations-short-latest.csv", + ) + CSV.write(output_path, DataFrame(rows)) + @test current_step(simulation) == PERFORMANCE_SHORT_STEPS + @test !isempty(rows) + @test isfile(output_path) + end +end + +if !isnothing(BENCHMARK_TEST_PATTERN) && + benchmark_test_enabled("XPalm CPU profile medium") + @testset "XPalm CPU profile medium" begin + include(joinpath(@__DIR__, "..", "performance_regression.jl")) + _warmup_xpalm_performance!(PERFORMANCE_MEDIUM_STEPS) + model, nsteps = + xpalm_reference_model_create(; nsteps=PERFORMANCE_MEDIUM_STEPS) + Profile.clear() + simulation = Profile.@profile xpalm_reference_param_run( + model, + OutputRequest[], + nsteps; + outputs=:none, + ) + output_path = joinpath( + @__DIR__, + "..", + "results", + "xpalm-cpu-medium-latest.txt", + ) + open(output_path, "w") do io + Profile.print( + io; + format=:flat, + sortedby=:count, + C=false, + combine=true, + ) + end + @test current_step(simulation) == PERFORMANCE_MEDIUM_STEPS + @test isfile(output_path) + end +end + +if !isnothing(BENCHMARK_TEST_PATTERN) && + benchmark_test_enabled("XPalm CPU profile full") + @testset "XPalm CPU profile full" begin + include(joinpath(@__DIR__, "..", "performance_regression.jl")) + _warmup_xpalm_performance!(PERFORMANCE_FULL_STEPS) + model, nsteps = + xpalm_reference_model_create(; nsteps=PERFORMANCE_FULL_STEPS) + profiled_steps = 660 + simulation = xpalm_reference_param_run( + model, + OutputRequest[], + nsteps - profiled_steps; + outputs=:none, + ) + Profile.clear() + Profile.@profile PlantSimEngine.continue!( + simulation; + steps=profiled_steps, + ) + output_path = joinpath( + @__DIR__, + "..", + "results", + "xpalm-cpu-full-latest.txt", + ) + open(output_path, "w") do io + Profile.print( + io; + format=:flat, + sortedby=:count, + C=false, + combine=true, + ) + end + @test current_step(simulation) == PERFORMANCE_FULL_STEPS + @test isfile(output_path) + end +end diff --git a/docs/make.jl b/docs/make.jl index e73b539d3..9d3640e97 100644 --- a/docs/make.jl +++ b/docs/make.jl @@ -1,26 +1,33 @@ #using Pkg #Pkg.develop("PlantSimEngine") using PlantSimEngine -using PlantSimEngine.Examples using PlantMeteo using DataFrames, CSV using Documenter using CairoMakie +using PlantSimEngine.Examples -DocMeta.setdocmeta!(PlantSimEngine, :DocTestSetup, :(using PlantSimEngine, PlantMeteo, DataFrames, CSV, CairoMakie); recursive=true) - -function build_graph_viewer_example() - mapping = ModelMapping( +function build_model_graph_example() + output_dir = joinpath(@__DIR__, "src", "assets") + mkpath(output_dir) + model = PlantSimEngine.CompositeModel( ToyDegreeDaysCumulModel(), ToyLAIModel(), - Beer(0.5), + Beer(0.6); + status=(TT=12.0,), + id=:plant, + scale=:Plant, + kind=:plant, + ) + GraphEditor.write_model_graph_view( + joinpath(output_dir, "model_graph_example.html"), + model, ) - path = joinpath(@__DIR__, "src", "www", "simple_dependency_graph.html") - write_graph_view(path, mapping) - return nothing end -build_graph_viewer_example() +build_model_graph_example() + +DocMeta.setdocmeta!(PlantSimEngine, :DocTestSetup, :(using PlantSimEngine, PlantMeteo, DataFrames, CSV, CairoMakie); recursive=true) makedocs(; modules=[PlantSimEngine], @@ -35,71 +42,93 @@ makedocs(; size_threshold=700000 ), pages=[ "Home" => "index.md", - "Introduction" => [ + "Start here" => [ "Why PlantSimEngine ?" => "./introduction/why_plantsimengine.md", - "Why Julia ?" => "./introduction/why_julia.md", - ], - "Prerequisites" => [ - "Installing and running PlantSimEngine" => "./prerequisites/installing_plantsimengine.md", - "Key Concepts" => "./prerequisites/key_concepts.md", - "Julia language basics" => "./prerequisites/julia_basics.md", + "Mental model" => "./journeys/users/mental_model.md", + "One object over time" => "./journeys/users/one_object.md", + "Several same-scale objects" => "./journeys/users/several_objects.md", ], - "Getting Started" => [ - "First simulation" => "./step_by_step/detailed_first_example.md", - "Model Coupling" => "./step_by_step/simple_model_coupling.md", - "Model Switching" => "./step_by_step/model_switching.md", - "Graph visualization and editing" => "./step_by_step/graph_visualization_editor.md", - "Quick examples" => "./step_by_step/quick_and_dirty_examples.md", - "Implementing a process" => "./step_by_step/implement_a_process.md", - "Implementing a model" => "./step_by_step/implement_a_model.md", - "Parallelization" => "./step_by_step/parallelization.md", - "Advanced coupling and hard dependencies" => "./step_by_step/advanced_coupling.md", - "Implementing a model : additional notes" => "./step_by_step/implement_a_model_additional.md", + "Structure and composition" => [ + "One multiscale plant" => "./journeys/users/one_plant.md", + "Several plants" => "./journeys/users/several_plants.md", + "Value coupling" => "./guides/multiscale/value_coupling.md", + "Importing an MTG" => "./guides/multiscale/import_mtg.md", + "How composite models execute" => "./guides/multiscale/concepts.md", + "Visualizing structure" => "./guides/multiscale/visualizing_structure.md", ], - "Execution" => "model_execution.md", - "Model traits" => "model_traits.md", - "AI agent skill" => "agent_skill.md", - "Working with data" => [ - "Reducing DoF" => "./working_with_data/reducing_dof.md", - "Fitting" => "./working_with_data/fitting.md", - "Input types" => "./working_with_data/inputs.md", - "Visualizing outputs and data" => "./working_with_data/visualising_outputs.md", - "Floating-point considerations" => "./working_with_data/floating_point_accumulation_error.md", + "Environment and time" => [ + "Read an environment" => "./journeys/users/environments.md", + "Different model cadences" => "./journeys/users/cadences.md", + "Hourly, daily, and weekly" => "./guides/time/hourly_daily_weekly.md", + "Advanced configuration" => "./guides/time/advanced_time_environment.md", ], - "Moving to multiscale" => [ - "Multiscale considerations" => "./multiscale/multiscale_considerations.md", - "Converting a simulation to multi-scale" => "./multiscale/single_to_multiscale.md", - "More variable mapping examples" => "./multiscale/multiscale.md", - "Handling cyclic dependencies" => "./multiscale/multiscale_cyclic.md", - "Multiscale coupling considerations" => "./multiscale/multiscale_coupling.md", - "Building a simple plant" => [ - "A rudimentary plant simulation" => "./multiscale/multiscale_example_1.md", - "Expanding the plant simulation" => "./multiscale/multiscale_example_2.md", - "Fixing bugs in the plant simulation" => "./multiscale/multiscale_example_3.md", - ], - "Visualizing our toy plant with PlantGeom" => "./multiscale/multiscale_example_4.md", + "Dynamic and advanced simulations" => [ + "Modify plant structure" => "./journeys/users/structure_changes.md", + "Modify the environment" => "./journeys/users/mutable_environments.md", + "Control advanced execution" => "./journeys/users/advanced_execution.md", + "MAESPA-style synthesis" => "./journeys/users/maespa_synthesis.md", + "Part 2: roots and water" => "./tutorials/growing_plant/part2_roots_water.md", + "Part 3: debugging" => "./tutorials/growing_plant/part3_debugging.md", + "Manual calls" => "./guides/multiscale/manual_calls.md", + "Advanced coupling and hard dependencies" => "./step_by_step/advanced_coupling.md", ], - "Multi-rate tutorials" => [ - "Introduction to multi-rate execution" => "./multirate/introduction.md", - "Step-by-step hourly/daily/weekly simulation" => "./multirate/multirate_tutorial.md", - "Advanced multi-rate configuration" => "./multirate/advanced_configuration.md", + "Implement models" => [ + "Basic contract and reuse" => "./journeys/modelers/basic_model.md", + "Cross-object values" => "./journeys/modelers/cross_object_values.md", + "Environment and cadence traits" => "./journeys/modelers/environment_and_cadence.md", + "Hard dependencies" => "./journeys/modelers/hard_dependencies.md", + "Mutable environment controllers" => "./journeys/modelers/mutable_environment.md", + "Port an existing model" => "./guides/modelers/port_existing_model.md", + "Implement a process" => "./step_by_step/implement_a_process.md", + "Implement a model" => "./step_by_step/implement_a_model.md", + "Composition and switching" => "./step_by_step/model_switching.md", + "Stateful models" => "./guides/modelers/stateful_models.md", + "Additional notes" => "./step_by_step/implement_a_model_additional.md", ], - "Troubleshooting and testing" => [ - "Troubleshooting" => "./troubleshooting_and_testing/plantsimengine_and_julia_troubleshooting.md", - "Automated testing" => "./troubleshooting_and_testing/downstream_tests.md", - "Tips and Workarounds" => "./troubleshooting_and_testing/tips_and_workarounds.md", - "Implicit contracts" => "./troubleshooting_and_testing/implicit_contracts.md", - ], "API" => [ + "Reference" => [ + "Installing PlantSimEngine" => "./prerequisites/installing_plantsimengine.md", + "Julia language basics" => "./prerequisites/julia_basics.md", + "Why Julia ?" => "./introduction/why_julia.md", + "Model execution" => "model_execution.md", + "Model traits" => "model_traits.md", + "Collecting and plotting outputs" => "./guides/data/outputs_plotting.md", + "Forcing observations" => "./guides/data/forcing_observations.md", + "Numerical reliability" => "./guides/data/numerical_reliability.md", + "Parameter fitting" => "./working_with_data/fitting.md", + "Graph editor" => "./guides/graph_visualizer_editor.md", + "Common errors" => "./troubleshooting/common_errors.md", + "Runtime contracts" => "./troubleshooting/runtime_contracts.md", + "Dependency cycles" => "./troubleshooting/dependency_cycles.md", + "Downstream testing" => "./troubleshooting_and_testing/downstream_tests.md", + "Environment backend extensions" => "./guides/extensions/environment_backends.md", + "AI agent skill" => "agent_skill.md", "Public API" => "./API/API_public.md", + "Public symbol inventory" => "./API/public_symbols.md", "Example models" => "./API/API_examples.md", - "Internal API" => "./API/API_private.md",], - "Developer guidelines" => "developers.md", - "Roadmap" => "planned_features.md", + ], + "Migration" => [ + "From the mapping runtime" => "migration_composite_model.md", + ], + "Maintainers" => [ + "Developer guidelines" => "developers.md", + "Internal API" => "./API/API_private.md", + "Public API refinement decisions" => "./dev/public_api_refinement_decisions.md", + "Public API refinement completion audit" => "./dev/public_api_refinement_completion_audit.md", + "Composite model/object design" => "./dev/composite_model_design.md", + "Composite model/object implementation plan" => "./dev/composite_model_implementation_plan.md", + "Composite model/object completion audit" => "./dev/composite_model_completion_audit.md", + "MAESPA-style composite-model example handoff" => "./dev/maespa_model_handoff.md", + "Code cleanup audit" => "./dev/code_cleanup_audit.md", + "Release notes handoff" => "./dev/release_notes_handoff.md", + "Roadmap" => "planned_features.md", + ], ] ) -deploydocs(; - repo="github.com/VirtualPlantLab/PlantSimEngine.jl.git", - devbranch="main", - push_preview=true, # Visit https://VirtualPlantLab.github.io/PlantSimEngine.jl/previews/PR128 to visualize the preview of the PR #128 -) +if get(ENV, "PLANTSIMENGINE_DOCS_BUILD_ONLY", "false") != "true" + deploydocs(; + repo="github.com/VirtualPlantLab/PlantSimEngine.jl.git", + devbranch="main", + push_preview=true, # Visit https://VirtualPlantLab.github.io/PlantSimEngine.jl/previews/PR128 to visualize the preview of the PR #128 + ) +end diff --git a/docs/paper/paper.md b/docs/paper/paper.md index 974dec5a0..29f2b3a82 100644 --- a/docs/paper/paper.md +++ b/docs/paper/paper.md @@ -31,7 +31,8 @@ bibliography: paper.bib - Switch between models without changing any code, with a simple syntax to define the model to use for a given process - Reduce the degrees of freedom by fixing variables, passing measurements, or using a simpler model for a given process - Fast computation, with 100th of nanoseconds for one model, two coupled models (see this [benchmark script](https://github.com/VirtualPlantLab/PlantSimEngine.jl/blob/main/examples/benchmark.jl)), or the full energy balance of a leaf using [PlantBiophysics.jl](https://github.com/VEZY/PlantBiophysics.jl) [@vezy_vezyplantbiophysicsjl_2023], a package that uses PlantSimEngine -- Out of the box sequential, parallel (multi-threaded) or distributed (multi-process) computations over objects, time-steps and independent processes (thanks to [Floops.jl](https://juliafolds.github.io/FLoops.jl/stable/)) +- Sequential scene execution through concrete application/object batches. A + public parallel or distributed executor is not currently part of the API. - Easily scalable, with methods for computing over objects, time-steps and even [Multi-Scale Tree Graphs](https://github.com/VEZY/MultiScaleTreeGraph.jl) [@vezy_multiscaletreegraphjl_2023] - Composable, allowing the use of any types as inputs such as [Unitful](https://github.com/PainterQubits/Unitful.jl) to propagate units, or [MonteCarloMeasurements.jl](https://github.com/baggepinnen/MonteCarloMeasurements.jl) [@carlson_montecarlomeasurementsjl_2020] to propagate measurement error diff --git a/docs/src/API/API_public.md b/docs/src/API/API_public.md index b36380e4c..0aa29605d 100644 --- a/docs/src/API/API_public.md +++ b/docs/src/API/API_public.md @@ -1,165 +1,192 @@ # Public API +## Unified CompositeModel/Object API + +### Scenario and model applications + +- `CompositeModel` stores objects, model applications, instances, and environment. +- `CompositeModel(model, models...; status=..., timestep=...)` is the concise one-object + form and lowers to the same object/application representation. +- `Object` represents one runtime entity with stable identity and status. +- `CompositeModelTemplate` and `ObjectInstance` reuse a model across instances. +- `ModelSpec(model; name=..., on=..., inputs=..., calls=..., every=..., + environment=..., output_routing=..., updates=...)` is the one application + construction form. + +### Coupling + +- `ModelSpec(...; inputs=...)` declares value dependencies. +- `ModelSpec(...; calls=...)` declares manually executable child models. +- `Updates(:variable; after=:application_id)` orders intentional duplicate writers. +- `Input(...)` and `Call(...)` express model defaults through `dep(model)`. +- `run_call!(context, :name; publish=false)` executes every resolved hard-call + target and always returns a vector-like `CallTargets` collection. +- `run_call!(context, :name; sampled_environment=value)` forwards one already + sampled model-facing environment through cached typed execution batches. +- `call_model(context, :name)` returns the concrete model when a call resolves + to exactly one target. +- `call_targets(context, :name)` returns the same non-executing collection for + fine-grained execution with `run_call!(target; ...)`. + +### Model input schema + +- `Required(T)` declares an input that object state or another application must + supply. `T` is an expected type and may be generic. +- `Default(value)` declares a true model fallback that needs no user + initialization. +- `inputs_(model)` uses only these explicit declarations; plain literals are + rejected. +- `outputs_(model)` literals remain initial output-state values. +- `init_variables(model)` returns only genuine input defaults and initial + output values. + +### Selectors + +- Multiplicity: `One(...)`, `OptionalOne(...)`, and `Many(...)`. +- Scope: `SceneScope()`, `Self()`, `Subtree()`, `SelfPlant()`, + `Ancestor(...)`, and `Scope(name)`. +- Label criteria: `kind=...`, `species=...`, `scale=...`, and `name=...`. +- Topology relations: `Relation(...)`. + +`Self()` always means the current object: the object on which the consuming +application runs. It means a plant only when that object is itself the plant. + +Selector fields are checked where the selector is used: + +| Context | Accepted criteria | +|---|---| +| `ModelSpec(...; on=...)` | `kind`, `species`, `scale`, `name`, and a scene or named scope | +| `ModelSpec(...; inputs=...)` | object criteria plus `process`, `application`, `var`, `policy`, `window`, `from_status`, and `after` | +| `ModelSpec(...; calls=...)` | object criteria plus `process` and `application` | +| object queries and `OutputRequest` selectors | object criteria only | + +Unsupported or misspelled fields fail when the selector is constructed. +Object-relative scopes and relations require a current object, so they belong +in inputs, calls, or contextual object/output queries rather than application +targets. + +### Time and environment + +- `ModelSpec(...; every=period)` sets an application cadence. +- `HoldLast`, `Interpolate`, `Integrate`, and `Aggregate` define temporal + input policies. +- `Environment(...)` configures environment providers and source remapping. +- Models declare sampled environment variables with `environment_inputs_`. +- Mutable environment controllers pass trial state with + `run_call!(context, name; environment=trial_state)` and commit accepted state + with `commit_environment!`. +- `OutputRequest(selector, variable; ...)` selects retained and optionally + resampled streams using the same object selector grammar. + +### Lifecycle + +- `objects_from_mtg` and `CompositeModel(mtg; ...)` adapt an MTG into the object + registry. +- `add_organ!` creates and initializes a new organ in an MTG-backed model. +- `runtime_model(context)` gives lifecycle-capable kernels sanctioned access to + the live model from their `RunContext`. +- `register_object!`, `remove_object!`, and `reparent_object!` change + topology. +- `move_object!` and `update_geometry!` change spatial state. +- Supported lifecycle operations automatically invalidate and refresh the + affected structural or spatial bindings before the next timestep. +- `run!(model; steps=..., outputs=:none)` starts a fresh result timeline and + returns a `Simulation`. +- `continue!(simulation; steps=...)` and `step!(simulation)` advance an + existing timeline without resetting temporal state. +- `current_step(simulation)` reports the accepted timeline position. +- `final_state(simulation)` returns a latest-state snapshot without + requiring output retention; pass an object id or selector for multi-object + simulations. +- `collect_outputs(sim)` materializes retained output streams. + +### Explanations + +Use the `Diagnostics` namespace instead of inspecting internals: + +- `Diagnostics.explain_objects` +- `Diagnostics.explain_instances` +- `Diagnostics.explain_scopes` +- `Diagnostics.explain_applications` +- `Diagnostics.explain_bindings` +- `Diagnostics.explain_calls` +- `Diagnostics.explain_environment_bindings` +- `Diagnostics.explain_schedule` +- `Diagnostics.explain_writers` +- `Diagnostics.explain_execution_plan` +- `Diagnostics.explain_output_retention` +- `Diagnostics.explain_outputs` +- `Diagnostics.explain_initialization` +- `Diagnostics.input_carrier`, `Diagnostics.input_value`, and + `Diagnostics.has_reference_carrier` +- `Diagnostics.object_address` + +See [Migrating To The CompositeModel/Object API](../migration_composite_model.md) for +translations from removed APIs. + +### CompositeModel graph visualization and editing + +- `GraphEditor.compile_model_report(model; strict=false)` preserves partial graph state and + structured diagnostics for incomplete or cyclic composite models. +- `GraphEditor.model_graph_view(model; level=:applications)` returns the typed graph view. +- `GraphEditor.model_graph_view_json(model)` serializes the same DTO used by the browser. +- `GraphEditor.write_model_graph_view(path, model)` writes a self-contained static viewer. +- `GraphEditor.edit_graph(model; templates=..., environments=...)` starts the optional HTTP editor after `using HTTP` and keeps catalog values authoritative in Julia. +- `GraphEditor.current_model(session)`, `GraphEditor.undo!(session)`, + `GraphEditor.redo!(session)`, and `close(session)` control an interactive + session from Julia. + +See [Visualize And Edit A CompositeModel](../guides/graph_visualizer_editor.md) for the +runnable workflow, model discovery, selector previews, cycle breaking, and +Documenter embedding. + +### Environment backend extensions + +Backend packages extend the protocol under `EnvironmentAPI`, including +`EnvironmentAPI.AbstractEnvironmentBackend`, +`EnvironmentAPI.bind_environment`, `EnvironmentAPI.sample`, +`EnvironmentAPI.commit_environment!`, and `EnvironmentAPI.update_index!`. +The root-level `commit_environment!` remains part of the ordinary model-kernel +workflow for committing an accepted controller state. + +### Fitting and evaluation + +Generic fitting and metrics live under `Evaluation`: `Evaluation.fit`, +`Evaluation.RMSE`, `Evaluation.NRMSE`, `Evaluation.EF`, and `Evaluation.dr`. +PlantMeteo reducers are accessed from `PlantMeteo` directly rather than being +re-exported by PlantSimEngine. + +## Advanced compiler API + +```@docs +PlantSimEngine.Advanced +``` + +Compiler representations, cache refresh operations, and low-level binding +compilers live under `PlantSimEngine.Advanced`. They are intended for package +integration, diagnostics development, and compiler work rather than ordinary +scenario composition. Prefer `Diagnostics.explain_*`, which accepts a +`CompositeModel` directly, over manually compiling and inspecting fields. + +Examples include `Advanced.compile_composite_model`, `Advanced.refresh_bindings!`, and +the `Advanced.CompiledCompositeModel` family. These qualified APIs may evolve more +quickly than the default modeling interface. + ## Index ```@index Pages = ["API_public.md"] ``` -## API documentation +## API Documentation ```@autodocs -Modules = [PlantSimEngine] +Modules = [ + PlantSimEngine, + PlantSimEngine.Diagnostics, + PlantSimEngine.GraphEditor, + PlantSimEngine.EnvironmentAPI, + PlantSimEngine.Evaluation, +] Private = false ``` - -## Multi-rate policy examples - -For mapping-level multi-rate configuration, combine: - -- `ModelSpec(...)` -- `TimeStepModel(...)` -- `InputBindings(...)` -- `MeteoBindings(...)` -- `MeteoWindow(...)` -- `OutputRouting(...)` -- `ScopeModel(...)` -- `timespec(::Type{<:AbstractModel})` (optional trait) -- `output_policy(::Type{<:AbstractModel})` (optional trait) -- `timestep_hint(::Type{<:AbstractModel})` (optional trait) -- `meteo_hint(::Type{<:AbstractModel})` (optional trait) -- `resolved_model_specs(mapping)` (utility) -- `explain_model_specs(mapping_or_sim)` (utility) -- `OutputRequest(...)` in `tracked_outputs` for resampled exports - -`TimeStepModel(...)` accepts: -- `Real` step counts -- `ClockSpec` -- fixed `Dates` periods (`Dates.Second`, `Dates.Minute`, `Dates.Hour`, `Dates.Day`, ...) - -Period conversion detail: -- Period-based timesteps are converted using the meteo base step `duration`. -- Example: `TimeStepModel(Dates.Day(1))` with hourly meteo (`Dates.Hour(1)`) maps to `ClockSpec(24.0, 1.0)`, - so execution times are `t = 1, 25, 49, ...`. - -Trait-based inference detail: -- If `TimeStepModel(...)` is omitted, runtime resolves timestep from: -: `timespec(model)` when non-default, otherwise meteo `duration`. -- `timestep_hint(::Type{<:Model})` is then interpreted as: -: `required` = hard compatibility constraint, `preferred` = informational only. -- If `InputBindings(...)` is omitted, same-name sources are inferred automatically from -: unique producers (same scale first, then cross-scale). Ambiguous cases require explicit bindings. -- For inferred bindings, policy defaults to producer `output_policy` when defined, otherwise `HoldLast()`. -- Explicit `InputBindings(..., policy=...)` always overrides trait defaults. -- `output_policy` is hint-only: it is applied only when an output is actually consumed/exported. -- If `MeteoBindings(...)` / `MeteoWindow(...)` are omitted, `meteo_hint(::Type{<:Model})` -: may provide `(; bindings=..., window=...)`. -- Explicit mapping-level configuration always overrides hints. - -Compatibility checks: -- Meteo `duration` is mandatory when meteo is provided. -- For models with meteo-derived timestep, runtime enforces `timestep_hint.required`. -- `timestep_hint.preferred` never sets runtime timestep by itself. - -Scope selection detail: -- `ScopeModel(:global)` is the default and shares streams across the whole simulation. -- `ScopeModel(:plant)` isolates streams within each plant subtree. -- `ScopeModel(:scene)` isolates by scene ancestor. -- `ScopeModel(:self)` isolates by node id. - -### Exporting variables at requested rates - -```julia -req_hold = OutputRequest(:Leaf, :A; name=:A_hourly, process=:assim, policy=HoldLast()) -req_day = OutputRequest(:Leaf, :A; name=:A_daily_sum, process=:assim, policy=Integrate(), clock=ClockSpec(24.0, 1.0)) -run!(sim, meteo; tracked_outputs=[req_hold, req_day], executor=SequentialEx()) -out = collect_outputs(sim; sink=DataFrame) - -# or directly: -out_status, out = run!( - sim, - meteo; - tracked_outputs=[req_hold, req_day], - return_requested_outputs=true, -) -``` - -- `process` is optional when the source is canonical and unique. -- `policy` defines how source streams are resampled at export time. -- `clock` defines the export schedule; omit it to export every simulation step. - -### Default hold-last - -```julia -ModelSpec(ConsumerModel()) |> -TimeStepModel(ClockSpec(2.0, 1.0)) |> -InputBindings(; x=(process=:producer, var=:x)) -``` - -### Meteo aggregation bindings - -```julia -ModelSpec(DailyModel()) |> -TimeStepModel(ClockSpec(24.0, 1.0)) |> -MeteoWindow(CalendarWindow(:day; anchor=:current_period, week_start=1, completeness=:strict)) |> -MeteoBindings( - T=MeanWeighted(), # default source is :T - Ri_SW_f=RadiationEnergy(), # integrate W m-2 to MJ m-2 over the model window - custom_peak=(source=:custom_var, reducer=MaxReducer()), -) -``` - -`MeteoWindow(...)` options: -- `RollingWindow()` (default): trailing rolling window driven by `dt`. -- `CalendarWindow(period; anchor, week_start, completeness)` with: -: `period` in `:day`, `:week`, `:month` -: `anchor` in `:current_period`, `:previous_complete_period` -: `week_start` in `1:7` (1 = Monday) -: `completeness` in `:allow_partial`, `:strict` - -### Parameterized window reducers - -`Integrate()` defaults to `SumReducer()`; `Aggregate()` defaults to `MeanReducer()`. -With the same reducer, they are runtime-equivalent. -Use `Integrate` for accumulation semantics and `Aggregate` for summary-statistics semantics. - -```julia -ModelSpec(DailyModel()) |> -TimeStepModel(ClockSpec(24.0, 1.0)) |> -InputBindings(; a=(process=:hourly_assim, var=:A, scale=:Leaf, policy=Integrate(SumReducer()))) - -ModelSpec(DailyModel()) |> -TimeStepModel(ClockSpec(24.0, 1.0)) |> -InputBindings(; a=(process=:hourly_assim, var=:A, scale=:Leaf, policy=Aggregate(MaxReducer()))) - -ModelSpec(DailyModel()) |> -TimeStepModel(ClockSpec(24.0, 1.0)) |> -InputBindings(; a=(process=:hourly_assim, var=:A, scale=:Leaf, policy=Integrate(vals -> maximum(vals) - minimum(vals)))) - -ModelSpec(DailyModel()) |> -TimeStepModel(ClockSpec(24.0, 1.0)) |> -InputBindings(; a=(process=:hourly_assim, var=:A, scale=:Leaf, policy=Integrate((vals, durations) -> sum(vals .* durations)))) - -ModelSpec(DailyModel()) |> -TimeStepModel(ClockSpec(24.0, 1.0)) |> -InputBindings(; a=(process=:hourly_assim, var=:A, scale=:Leaf, policy=Integrate(PlantMeteo.DurationSumReducer()))) -``` - -Built-in reducer types are: -`SumReducer()`, `MeanReducer()`, `MaxReducer()`, `MinReducer()`, `FirstReducer()`, `LastReducer()`. -The same reducer objects are also used by `MeteoBindings(...)`. -Custom reducers/callables can accept either `(values)` or `(values, durations_seconds)`. - -### Parameterized interpolation mode - -`Interpolate()` defaults to `mode=:linear, extrapolation=:linear`. - -```julia -ModelSpec(FastModel()) |> -TimeStepModel(1.0) |> -InputBindings(; x=(process=:slow_source, var=:x, policy=Interpolate())) - -ModelSpec(FastModel()) |> -TimeStepModel(1.0) |> -InputBindings(; x=(process=:slow_source, var=:x, policy=Interpolate(; mode=:hold, extrapolation=:hold))) -``` diff --git a/docs/src/API/public_symbols.md b/docs/src/API/public_symbols.md new file mode 100644 index 000000000..b66a721cc --- /dev/null +++ b/docs/src/API/public_symbols.md @@ -0,0 +1,138 @@ +# Public Symbol Inventory + +This page records the supported default namespace and the four focused public +submodules. Compiler representations and cache controls are intentionally +listed separately under [`PlantSimEngine.Advanced`](#advanced-namespace). + +`using PlantSimEngine` imports the ordinary model-author and simulation-user +workflow plus the `Diagnostics`, `GraphEditor`, `EnvironmentAPI`, and +`Evaluation` module names. Their members remain qualified unless a user +explicitly imports one of those submodules. + +## Scenario composition + +- CompositeModel structure: `CompositeModel`, `Object`, `ObjectId`, `CompositeModelTemplate`, + `ObjectInstance`, `Override`. +- Applications: `ModelSpec`, `Environment`, and `Updates`. +- Application inspection: `application_name`, `applies_to`, `value_inputs`, + `model_calls`, `environment_config`, `output_routing`, `updates`. +- Dependency defaults: `Input`, `Call`, `PreviousTimeStep`. + +## Object selectors and queries + +- Multiplicity: `One`, `OptionalOne`, `Many`. +- Scope and topology: `SceneScope`, `Self`, `Subtree`, `SelfPlant`, `Ancestor`, + `Scope`, `Relation`. +- Label criteria are selector keywords: `kind`, `species`, `scale`, and + `name`. +- Queries: `object_ids`, `model_objects`, `resolve_object_ids`, + `resolve_objects`. +- Object data: `geometry`, `position`, `bounds`. + +## Execution, lifecycle, and outputs + +- Execution: `run!`, `continue!`, `step!`, `Simulation`, `current_step`, + `runtime_model`, `final_state`. +- Output selection and collection: `OutputRequest`, `outputs`, + `collect_outputs`. +- Lifecycle: `register_object!`, `add_organ!`, `remove_object!`, + `reparent_object!`, `move_object!`, `update_geometry!`, + `mark_environment_binding_dirty!`, `objects_from_mtg`. +- Hard calls: `RunContext`, `CallTarget`, `CallTargets`, `call_model`, + `call_targets`, `run_call!`. + +## Diagnostics namespace + +`PlantSimEngine.Diagnostics` owns structured explanations and supported +inspection: + +- Structure: `Diagnostics.explain_objects`, `Diagnostics.explain_instances`, `Diagnostics.explain_scopes`. +- Compilation: `Diagnostics.explain_applications`, `Diagnostics.explain_bindings`, + `Diagnostics.explain_calls`, `Diagnostics.explain_writers`, + `Diagnostics.explain_schedule`, `Diagnostics.explain_execution_plan`. +- Initialization, environment, and outputs: `Diagnostics.explain_initialization`, + `Diagnostics.explain_environment`, `Diagnostics.explain_environment_bindings`, + `Diagnostics.explain_output_retention`, `Diagnostics.explain_outputs`. +- Supported carrier inspection: `Diagnostics.input_carrier`, `Diagnostics.input_value`, + `Diagnostics.has_reference_carrier`. +- Normalized selector addresses: `Diagnostics.ObjectAddress`, + `Diagnostics.object_address`. + +## Model-author contract + +- Model identity: `AbstractModel`, `@process`, `process`. +- State schema and initialization: `Status`, `Required`, `Default`, + `init_variables`, `dep`. +- Model IO inspection: `inputs`, `outputs`, `variables`, + `environment_inputs`, `environment_outputs`, + `validate_environment_inputs`. +- Timing and routing traits: `timespec`, `output_policy`, `timestep_hint`, + `environment_hint`, `environment_bindings`, `environment_window`. + +The underscore declarations `inputs_`, `outputs_`, `environment_inputs_`, and +`environment_outputs_` are intentionally unexported extension functions. +Model authors implement them with qualified definitions such as +`PlantSimEngine.inputs_(model) = ...`. `inputs_` must return explicit +`Required(T)` or `Default(value)` declarations; `outputs_` returns initial +output-state values. + +## Time and reducers + +- Scheduling: `ClockSpec`, `SchedulePolicy`, `HoldLast`, `Interpolate`, + `Integrate`, `Aggregate`. +- Meteorology reducers are not re-exported. Use qualified PlantMeteo names, + for example `PlantMeteo.MeanReducer` or `PlantMeteo.RadiationEnergy`. + +## EnvironmentAPI namespace + +- Backend contract: `EnvironmentAPI.AbstractEnvironmentBackend`, `EnvironmentAPI.EnvironmentContext`, + `EnvironmentAPI.GlobalConstant`, `EnvironmentAPI.environment_backend`, `EnvironmentAPI.environment_variables`, + `EnvironmentAPI.base_step_seconds`, `EnvironmentAPI.get_nsteps`, and + `EnvironmentAPI.bind_environment`. +- Sampling and mutation: `EnvironmentAPI.sample`, + `EnvironmentAPI.sample_environment`, `EnvironmentAPI.commit_environment!`, + and `EnvironmentAPI.update_index!`. +- PlantMeteo conveniences: `Atmosphere`, `Constants`, `Weather`. + +## GraphEditor namespace + +- Discovery and DTOs: `GraphEditor.available_models`, + `GraphEditor.model_descriptor`, `GraphEditor.compile_model_report`, + `GraphEditor.ModelGraphView`, and `GraphEditor.model_graph_view`. +- Serialization and static views: `GraphEditor.model_graph_view_json`, + `GraphEditor.model_graph_view_html`, and + `GraphEditor.write_model_graph_view`. +- Semantic edits and sessions live under the same namespace, including + `GraphEditor.AddModelApplication`, `GraphEditor.apply_model_graph_edit`, + `GraphEditor.edit_graph`, `GraphEditor.current_model`, + `GraphEditor.undo!`, and `GraphEditor.redo!`. + +## Evaluation namespace + +- Fitting and metrics: `Evaluation.fit`, `Evaluation.RMSE`, + `Evaluation.NRMSE`, `Evaluation.EF`, and `Evaluation.dr`. + +## Advanced namespace + +`PlantSimEngine.Advanced` contains the qualified compiler and cache API: + +- registries and compiled representations: `ObjectRegistry`, `CompiledCompositeModel`, + `CompiledModelApplication`, `CompiledModelInputBinding`, + `CompiledModelCallBinding`, `CompiledEnvironmentBinding`, + `CompiledEnvironmentBindings`; +- carrier and adapter implementation types: `ObjectRefVector`, + `TimeStepTable`; +- compiler and cache operations: `compile_composite_model`, `refresh_bindings!`, + `refresh_environment_bindings!`, `compile_environment_bindings`; +- cache diagnostics: `bindings_dirty`, `environment_bindings_dirty`, + `model_revision`, `environment_revision`, `compiled_bindings`, + `compiled_environment_bindings`. + +These names require explicit qualification or `using PlantSimEngine.Advanced`. +They are not part of the concise user namespace and may evolve with compiler +implementation requirements. + +The namespace-boundary test in `test/test-model-api-stabilization.jl` compares +the complete default public-name set with an explicit inventory and separately +checks every focused submodule. Adding or removing an export therefore requires +an intentional inventory update. diff --git a/docs/src/FAQ/translate_a_model.md b/docs/src/FAQ/translate_a_model.md deleted file mode 100644 index 89b2b6a4c..000000000 --- a/docs/src/FAQ/translate_a_model.md +++ /dev/null @@ -1,157 +0,0 @@ -# I want to use PlantSimEngine for my model - -```@setup mymodel -using PlantSimEngine -using CairoMakie -# Import the example models defined in the `Examples` sub-module: -using PlantSimEngine.Examples -using PlantMeteo, Dates - -function lai_toymodel(TT_cu; max_lai=8.0, dd_incslope=500, inc_slope=70, dd_decslope=1000, dec_slope=20) - LAI = max_lai * (1 / (1 + exp((dd_incslope - TT_cu) / inc_slope)) - 1 / (1 + exp((dd_decslope - TT_cu) / dec_slope))) - if LAI < 0 - LAI = 0 - end - return LAI -end - -meteo_day = read_weather(joinpath(pkgdir(PlantSimEngine), "examples/meteo_day.csv"), duration=Dates.Day) -``` - -If you already have a model, you can easily use `PlantSimEngine` to couple it with other models with minor adjustments. - -## Toy LAI Model - -### Model description - -Let's take an example with a simple LAI model that we define below: - -```julia -""" -Simulate leaf area index (LAI, m² m⁻²) for a crop based on the amount of degree-days since sowing with a simple double-logistic function. - -# Arguments - -- `TT_cu`: degree-days since sowing -- `max_lai=8`: Maximum value for LAI -- `dd_incslope=500`: degree-days at which we get the maximal increase in LAI -- `inc_slope=5`: slope of the increasing part of the LAI curve -- `dd_decslope=1000`: degree-days at which we get the maximal decrease in LAI -- `dec_slope=2`: slope of the decreasing part of the LAI curve -""" -function lai_toymodel(TT_cu; max_lai=8.0, dd_incslope=500, inc_slope=70, dd_decslope=1000, dec_slope=20) - LAI = max_lai * (1 / (1 + exp((dd_incslope - TT_cu) / inc_slope)) - 1 / (1 + exp((dd_decslope - TT_cu) / dec_slope))) - if LAI < 0 - LAI = 0 - end - return LAI -end -``` - -This model takes the number of days since sowing as input and returns the simulated LAI. We can plot the simulated LAI for a year: - -```@example mymodel -using CairoMakie - -lines(1:1300, lai_toymodel.(1:1300), color=:green, axis=(ylabel="LAI (m² m⁻²)", xlabel="Days since sowing")) -``` - -### Changes for PlantSimEngine - -The model can be implemented using `PlantSimEngine` as follows: - -#### Define a process - -If the process of LAI dynamic is not implemented yet, we can define it like so: - -```julia -@process LAI_Dynamic -``` - -#### Define the model - -We have to define a structure for our model that will contain the parameters of the model: - -```julia -struct ToyLAIModel <: AbstractLai_DynamicModel - max_lai::Float64 - dd_incslope::Int - inc_slope::Float64 - dd_decslope::Int - dec_slope::Float64 -end -``` - -We can also define default values for the parameters by defining a method with keyword arguments: - -```julia -ToyLAIModel(; max_lai=8.0, dd_incslope=500, inc_slope=70, dd_decslope=1000, dec_slope=20) = ToyLAIModel(max_lai, dd_incslope, inc_slope, dd_decslope, dec_slope) -``` - -This way users can create a model with default parameters just by calling `ToyLAIModel()`, or they can specify only the parameters they want to change, *e.g.* `ToyLAIModel(inc_slope=80.0)` - -#### Define inputs / outputs - -Then we can define the inputs and outputs of the model, and the default value at initialization: - -```julia -PlantSimEngine.inputs_(::ToyLAIModel) = (TT_cu=-Inf,) -PlantSimEngine.outputs_(::ToyLAIModel) = (LAI=-Inf,) -``` - -!!! note - Note that we use `-Inf` for the default value, it is the recommended value for `Float64` (-999 for `Int`), as it is a valid value for this type, and is easy to catch in the outputs if not properly set because it propagates nicely. You can also use `NaN` instead. - -#### Define the model function - -Finally, we can define the model function that will be called at each time step: - -```julia -function PlantSimEngine.run!(::ToyLAIModel, models, status, meteo, constants=nothing, extra=nothing) - status.LAI = models.LAI_Dynamic.max_lai * (1 / (1 + exp((models.LAI_Dynamic.dd_incslope - status.TT_cu) / model.LAI_Dynamic.inc_slope)) - 1 / (1 + exp((models.LAI_Dynamic.dd_decslope - status.TT_cu) / models.LAI_Dynamic.dec_slope))) - - if status.LAI < 0 - status.LAI = 0 - end -end -``` - -!!! note - Note that we don't return the value of the LAI in the definition of the function. This is because we rather update its value in the status directly. The status is a structure that efficiently stores the state of the model at each time step, and it contains all variables either declared as inputs or outputs of the model. This way, we can access the value of the LAI at any time step by calling `status.LAI`. - -!!! note - The function is defined for **one time step** only, and is called at each time step automatically by PlantSimEngine. This means that we don't have to loop over the time steps in the function. - -#### [Running a simulation](@id defining_the_meteo) - -Now that we have everything set up, we can run a simulation. The first step here is to define the weather: - -```julia -# Import the packages we need: -using PlantMeteo, Dates - -# Define the period of the simulation: -period = [Dates.Date("2021-01-01"), Dates.Date("2021-12-31")] - -# Get the weather data for CIRAD's site in Montpellier, France: -meteo = get_weather(43.649777, 3.869889, period, sink = DataFrame) - -# Compute the degree-days with a base temperature of 10°C: -meteo.TT = max.(meteo.T .- 10.0, 0.0) - -# Aggregate the weather data to daily values: -meteo_day = to_daily(meteo, :TT => (x -> sum(x) / 24) => :TT) -``` - -Then we can define our list of models, passing the values for `TT_cu` in the status at initialization: - -```@example mymodel -m = ModelMapping( - ToyLAIModel(), - status = (TT_cu = cumsum(meteo_day.TT),), -) - -outputs_sim = run!(m) - -lines(outputs_sim[:TT_cu], outputs_sim[:LAI], color=:green, axis=(ylabel="LAI (m² m⁻²)", xlabel="Days since sowing")) -``` diff --git a/docs/src/agent_skill.md b/docs/src/agent_skill.md index e432ba383..0af63b06e 100644 --- a/docs/src/agent_skill.md +++ b/docs/src/agent_skill.md @@ -8,12 +8,31 @@ The skill file is stored in the repository at: skills/plantsimengine/SKILL.md ``` -Users can download the `skills/plantsimengine` folder and tell their agent to use the `plantsimengine` skill when working with PlantSimEngine.jl. The skill gives agents the package-specific conventions they need for: +Users can download the `skills/plantsimengine` folder and tell their agent to +use the `plantsimengine` skill when working with PlantSimEngine.jl. The skill +gives agents the package-specific conventions they need for: -- composing existing models with `ModelMapping`; -- declaring spatial multiscale mappings with scale symbols and `MultiScaleModel`; -- configuring multirate simulations with `ModelSpec`, `TimeStepModel`, `InputBindings`, and temporal policies; -- implementing or wrapping models with `@process`, `inputs_`, `outputs_`, `run!`, hard dependencies, and model traits. +- building object graphs with `CompositeModel`, `Object`, `CompositeModelTemplate`, and + `ObjectInstance`; +- applying models with `ModelSpec` and `on`; +- coupling values and manual model calls with `inputs` and `calls`; +- using cached hard-call plans through bulk `run_call!`, singular `call_model`, + and lifecycle-maintained object target buffers; +- configuring multirate simulations with `every`, `Dates.Period` values, + and temporal policies; +- binding global or spatial microclimate through `Environment`; +- reasoning about model-clock weather aggregation, `environment_hint` reducers, and + scenario source overrides; +- inspecting compiled scenarios with structured explanation helpers; +- reporting supplied, generated, bound, and unresolved variables with + `Diagnostics.explain_initialization`; +- accessing the live model from lifecycle-capable kernels with + `runtime_model(context)`; +- inspecting homogeneous runtime batches with `Diagnostics.explain_execution_plan`; +- collecting raw or requested model outputs with `outputs`, + `OutputRequest`, `collect_outputs`, and `Diagnostics.explain_output_retention`; +- implementing or wrapping models with `@process`, `inputs_`, `outputs_`, + `run!`, hard dependencies, and model traits. The canonical source is [`skills/plantsimengine/SKILL.md`](https://github.com/VirtualPlantLab/PlantSimEngine.jl/blob/main/skills/plantsimengine/SKILL.md). diff --git a/docs/src/assets/.gitignore b/docs/src/assets/.gitignore new file mode 100644 index 000000000..e02769089 --- /dev/null +++ b/docs/src/assets/.gitignore @@ -0,0 +1 @@ +/model_graph_example.html diff --git a/docs/src/composite_model/quickstart.md b/docs/src/composite_model/quickstart.md new file mode 100644 index 000000000..988ae41cc --- /dev/null +++ b/docs/src/composite_model/quickstart.md @@ -0,0 +1,261 @@ +# CompositeModel/Object Quickstart + +This page is the shortest path to a native composite-model/object simulation. + +Use this API for new multiscale, multi-plant, soil, microclimate, and +model-scale simulations. Applications use one direct constructor: + +```julia +ModelSpec( + model; + name=:application, + on=Many(scale=:Leaf), + inputs=(...), + calls=(...), + every=Dates.Hour(1), + environment=Environment(...), + output_routing=(...), + updates=Updates(...), +) +``` + +Scenarios are defined with `CompositeModel` and model applications. A model is a +reusable process implementation; an application is one configured use of that +model, including its name, target objects, inputs, cadence, and environment. +One application may run on many objects, and the same model may appear in +several applications with different parameters or targets. + +```@setup model_object_quickstart +using PlantSimEngine, PlantMeteo, Dates, DataFrames +using PlantSimEngine.Examples +``` + +## One Object, Several Models + +For models that all run on one object, the concise constructor lowers directly +to the ordinary CompositeModel/Object representation: + +```julia +model = CompositeModel(ModelA(), ModelB(); status=(initial_value=1.0,)) +``` + +Use the explicit form later in this guide when applications need names, +selectors, or other scenario policies. + +The first model has one object, `:scene`, and three model applications: + +- `ToyDegreeDaysCumulModel` computes daily thermal time; +- `ToyLAIModel` consumes cumulative thermal time and computes LAI; +- `Beer` consumes LAI and meteorology to compute absorbed PAR. + +The model implementations are ordinary PlantSimEngine kernels. The model +application layer decides where they run. With no explicit `every`, these +applications use the environment cadence. + +```@example model_object_quickstart +meteo_day = read_weather( + joinpath(pkgdir(PlantSimEngine), "examples/meteo_day.csv"); + duration=Dates.Day, +) + +model = CompositeModel( + ToyDegreeDaysCumulModel(), + ToyLAIModel(), + Beer(0.6); + environment=meteo_day, +) + +sim = run!(model; steps=30, outputs=:all) +out = collect_outputs(sim; sink=DataFrame) +first(out, 6) +``` + +The `Simulation` provides a snapshot of the latest status values: + +```@example model_object_quickstart +scene_status = final_state(sim) +(TT_cu=scene_status.TT_cu, LAI=scene_status.LAI, aPPFD=scene_status.aPPFD) +``` + +## Inspect The Compiled Bindings + +Before running, `Diagnostics.explain_initialization(model)` classifies each variable as +`:required`, `:defaulted`, `:supplied`, `:producer_bound`, `:generated`, or +`:environment_bound`. The report remains available when required values are +missing, so it can be used to finish configuring a model. + +The compiler infers unambiguous same-object dependencies from declared model +inputs and outputs: + +- `:LAI_Dynamic` reads `TT_cu` from `:Degreedays`; +- `:light_interception` reads `LAI` from `:LAI_Dynamic`. + +```@example model_object_quickstart +select( + DataFrame(Diagnostics.explain_bindings(model)), + :application_id, + :input, + :source_application_ids, + :carrier_kind, + :copy_semantics, +) +``` + +`carrier_kind = :ref` and `copy_semantics = :live_references` mean the +consumer sees a shared reference rather than a copied value. + +For runtime performance diagnostics, inspect the execution plan: + +```@example model_object_quickstart +select( + DataFrame(Diagnostics.explain_execution_plan(model)), + :application_id, + :object_ids, + :batch_size, + :inner_loop_dispatch, +) +``` + +## Request Outputs + +By default, model runs retain no user output streams. Pass `outputs=:all` to +retain every publisher, or pass `OutputRequest` values to retain and +materialize selected streams plus those required by temporal inputs. + +```@example model_object_quickstart +request = OutputRequest( + Many(scale=:Scene), + :LAI; + name=:lai_every_two_days, + application=:LAI_Dynamic, + policy=HoldLast(), + clock=Day(2), +) + +requested_sim = run!( + model; + steps=30, + outputs=request, +) + +collect_outputs(requested_sim, :lai_every_two_days; sink=nothing)[1:4] +``` + +The retention explanation reports why a stream was kept: + +```@example model_object_quickstart +Diagnostics.explain_output_retention(requested_sim) +``` + +## Many Objects As Inputs + +Use `ModelSpec(...; inputs=...)` when a model needs values from selected objects. This +model-scale LAI model reads live references to the surface of every plant: + +```@example model_object_quickstart +plant_scene = CompositeModel( + Object(:scene; scale=:Scene, kind=:scene), + Object( + :plant_1; + scale=:Plant, + kind=:plant, + parent=:scene, + status=Status(surface=12.0), + ), + Object( + :plant_2; + scale=:Plant, + kind=:plant, + parent=:scene, + status=Status(surface=8.0), + ); + applications=( + ModelSpec(ToyLAIfromLeafAreaModel(100.0); name=:scene_lai, on=One(scale=:Scene), inputs=(:plant_surfaces => Many( + scale=:Plant, + within=SceneScope(), + var=:surface, + ),)), + ), +) + +plant_sim = run!(plant_scene) +plant_model_status = final_state(plant_sim, One(scale=:Scene)) +(total_surface=plant_model_status.total_surface, LAI=plant_model_status.LAI) +``` + +The compiled binding shows a `RefVector` carrier: + +```@example model_object_quickstart +select( + DataFrame(Diagnostics.explain_bindings(plant_scene)), + :application_id, + :input, + :source_ids, + :carrier_kind, + :copy_semantics, +) +``` + +If the consumer model runs on each plant, use `within=Subtree()` to read only +objects inside the current plant. Use `within=SceneScope()` when a model model +must aggregate all matching objects. + +## Manual Calls + +Use `ModelSpec(...; calls=...)` when a parent model must directly run selected child models. +This is the mechanism for iterative solvers such as model energy balance: + +```julia +ModelSpec(SceneEnergyBalance(); name=:scene_energy, on=One(scale=:Scene), calls=(:leaf_energy => Many( + kind=:plant, + scale=:Leaf, + within=SceneScope(), + application=:energy_balance, + ), + :soil => One( + kind=:soil, + scale=:Soil, + within=SceneScope(), + application=:soil_water, + ),), every=Hour(1)) +``` + +For a one-shot call, execute all targets directly: + +```julia +targets = run_call!(context, :leaf_energy; publish=true) +``` + +`targets` is always vector-like regardless of whether the declaration uses +`One`, `OptionalOne`, or `Many`. For iterative control, retrieve the same +compiled targets without executing them: + +```julia +function PlantSimEngine.run!(model::SceneEnergyBalance, status, environment, + constants, context) + trial = trial_environment(model, status) + run_call!(context, :leaf_energy; environment=trial, publish=false) + + accepted = accepted_environment(model, status) + commit_environment!(context, accepted) + run_call!(context, :leaf_energy; publish=true) + + return nothing +end +``` + +`run_call!` defaults to `publish=false`, so trial calls mutate target statuses +without publishing temporal streams or committing mutable environment updates. +Pass non-committing trial state with `environment=trial_state`, then call +`commit_environment!` before publishing the accepted state. + +## Next Steps + +- [Migrating To The CompositeModel/Object API](../migration_composite_model.md) translates + scenarios written with removed APIs. +- [Public API](../API/API_public.md) lists constructors, selectors, lifecycle + helpers, environment helpers, and explanation helpers. +- [Model traits](../model_traits.md) documents `inputs_`, `outputs_`, `dep`, + `timespec`, `output_policy`, and `environment_inputs_`. +- [MAESPA-style model example handoff](../dev/maespa_model_handoff.md) + records the current multi-plant model energy-balance acceptance example. diff --git a/docs/src/dev/code_cleanup_audit.md b/docs/src/dev/code_cleanup_audit.md new file mode 100644 index 000000000..1e75bafb0 --- /dev/null +++ b/docs/src/dev/code_cleanup_audit.md @@ -0,0 +1,97 @@ +# Code Cleanup Audit + +## Status + +The compatibility cleanup is implemented on the `multi-plants` branch. + +The package now has one scenario compiler and runtime: the composite-model/object API. +The following superseded implementations were removed rather than deprecated: + +- `ModelList` and `SingleScaleModelSet`; +- `ModelMapping` and `MultiScaleModel`; +- `DependencyGraph`, `HardDependencyNode`, and `SoftDependencyNode`; +- `GraphSimulation` and the MTG mapping runner; +- mapping-specific multirate input resolution and output export; +- the unreleased domain prototype that preceded the composite-model/object API, + including `Domain`, `SimulationMapping`, `Route`, `AllDomains`, + `HardDomains`, and its separate scheduler, runtime, environment bridge, and + output publisher; +- mapping-only initialization, dataframe, dimension, and topology helpers; +- unused parallel-executor traits after removal of the executor runtime; +- dead `UninitializedVar`, `RefVariable`, `TreeAlike`, and `StatusView` types; +- the unreleased `CompositeModelTemplate(...; mapping=...)` alias and legacy + selector-to-mapping conversion helpers; +- compatibility tests, tutorials, and executable examples. + +Migration details are retained in +[`migration_composite_model.md`](../migration_composite_model.md) and +[`release_notes_handoff.md`](release_notes_handoff.md). + +## Current Ownership + +| Concern | Owner | +| --- | --- | +| Object registry, selectors, compilation, execution, lifecycle | `src/composite_model_api.jl` | +| Model application configuration | `src/ModelSpec.jl` | +| Status and reference vectors | `src/component_models/Status.jl`, `src/component_models/RefVector.jl` | +| Dates-based clocks and policies | `src/time/multirate.jl`, `src/time/runtime/clocks.jl` | +| Environment sampling | `src/time/runtime/environment_sampling.jl` | +| Environment backends | `src/time/runtime/environment_backends.jl` | +| Output request definition | `src/time/runtime/output_export.jl` | + +## Remaining Review Rules + +Future cleanup should reject: + +- a second scenario/runtime abstraction parallel to `CompositeModel`; +- compatibility wrappers for unreleased APIs; +- package-specific behavior in PlantSimEngine; +- model kernels that know their scenario object, timestep, or coupling unless + the scientific algorithm requires a hard call; +- dynamic per-object dispatch or copying in hot loops when compiled typed + batches and reference carriers are available; +- undocumented public names or agent instructions that describe removed APIs. + +## Verification + +Current cleanup evidence: + +- the `src` tree contains only the composite-model/object runtime and supporting status, + time, environment, fitting, trait, and example files; +- empty directories left by removed subsystems were deleted; +- `git diff --check` passes; +- PlantSimEngine precompiles and loads from a clean Kaimon session; +- `test/test-unified-model-object-api.jl` passes 576 tests; +- the complete package environment passes 885 tests, including Aqua and + doctests; +- `test/test-fitting.jl` passes; +- the documentation build passes, including executable examples and + cross-reference checks; +- repository search finds no superseded scenario-runtime definitions or + references in source, tests, examples, README, public docs, or the packaged + agent skill; +- remaining `ModelMapping` and `MultiScaleModel` references outside + development notes are migration text that explicitly points historical code + to the composite-model/object API. +- repository search finds no `Domain`, `SimulationMapping`, `Route`, + `AllDomains`, or `HardDomains` implementations, exports, tests, examples, or + public documentation. The only remaining references are development/release + notes that record their removal from this unreleased branch; +- ignored `.DS_Store` files were removed from the working tree outside `.git`. +- `ModelSpec` pipe-helper boilerplate was consolidated behind shared internal + helpers while keeping the public `on`, `inputs`, `calls`, `every`, + `Environment`, `Updates`, and `output_routing` grammar unchanged. +- the duplicate `Advanced.TimeStepTable` export was removed from the PlantMeteo + re-export block; `Advanced.TimeStepTable` remains exported once from the core status + export list. +- stale `PlantSimEngine.Examples` exports for the deleted + `ToyInternodeEmergence` example were removed. + +Downstream verification: + +- PlantBiophysics passes 117/117 tests against this working tree. +- XPalm's uncommitted CompositeModel/Object migration executes 74/75 assertions. The + remaining assertion retains the removed runtime's first-step LAI value, + while the explicit current dependency order produces zero from the initial + zero-biomass leaf before plant/model aggregation. PlantSimEngine intentionally + contains no package-specific compatibility workaround for that stale fixture. diff --git a/docs/src/dev/composite_model_completion_audit.md b/docs/src/dev/composite_model_completion_audit.md new file mode 100644 index 000000000..828ea4573 --- /dev/null +++ b/docs/src/dev/composite_model_completion_audit.md @@ -0,0 +1,96 @@ +# Unified CompositeModel/Object Completion Audit + +This audit records the evidence used to assess the breaking composite-model/object +redesign against `composite_model_design.md` and +`composite_model_implementation_plan.md`. + +Audit date: June 12, 2026. + +## Result + +The unified composite-model/object redesign is implemented as the primary public +configuration API. + +The superseded mapping implementation and the unreleased intermediate +prototype were removed after the composite-model/object runtime replaced them. + +## Public Contract + +The exported scenario vocabulary centers on: + +```julia +CompositeModel +Object +ModelSpec +Updates +Environment +``` + +Legacy scenario constructors such as `ModelMapping` and `MultiScaleModel` were +removed. + +Evidence: + +- `src/PlantSimEngine.jl` +- `docs/src/API/API_public.md` +- `docs/src/migration_composite_model.md` +- `README.md` + +## Requirement Evidence + +| Requirement | Evidence | +| --- | --- | +| One model object registry without prescribing plant topology | `CompositeModel`, `Object`, selectors, relations, scopes, and `objects_from_mtg` in `src/composite_model_api.jl`; selector and MTG adapter tests in `test/test-unified-model-object-api.jl` | +| Reusable species models and repeated plant instances | `CompositeModelTemplate`, `ObjectInstance`, `Override`, shared model ownership, and homogeneous/heterogeneous batches; four-instance and override tests | +| Soft/value dependencies | Compiled `ModelSpec(...; inputs=...)` bindings, same-object inference, scalar references, `RefVector`, `Advanced.ObjectRefVector`, temporal carriers, renaming, and optional inputs | +| Manual hard dependencies | Compiled `ModelSpec(...; calls=...)`, vector-like `CallTargets`, `run_call!(context, name)`, and fine-grained `run_call!(target)`; trial calls default to `publish=false` and accepted calls publish explicitly | +| Model-author dependency defaults | `Input(...)` and `Call(...)` entries from `dep(model)`, with `ModelSpec` overrides and binding provenance in explanations | +| Multirate execution | `every=Dates.Period`, model `timespec`, input policies, explicit windows, `PreviousTimeStep`, and stable compiled scheduling | +| Generic value types | Reference and temporal tests using `ModelObjectDualLike{BigFloat}` and `BigFloat` interpolation/integration without `Float64` conversion | +| Reference semantics and low-copy execution | Shared scalar references, typed many-object carriers, preinstalled status bindings, zero-allocation materialization tests, and a zero-allocation warmed 128-object execution batch | +| Duplicate writers | Canonical writer validation and `Updates(:variable; after=...)`, including pruning-after-allocation tests | +| Growth, pruning, reparenting, and movement | Central lifecycle APIs, structural/environment cache invalidation, dynamic target/carrier rebuilding, removed-object output history, and object-scoped geometry refresh tests | +| Automatic meteorology and microclimate | `environment_inputs_`, global and spatial backends, ancestor geometry fallback, source remapping, model hints, tabular aggregation, cached opaque handles, `run_call!(...; environment=trial_state)` trial sampling, and `commit_environment!` accepted mutable commits | +| Structured agent explanations | Object, instance, scope, application, binding, call, model-bundle, environment, schedule, writer, execution-plan, output, and retention explanations returning structured rows | +| Initialization workflow | `Required(T)` and `Default(value)` make the input contract explicit; `Diagnostics.explain_initialization` classifies required, defaulted, supplied, generated, producer-bound, and environment-bound variables before strict compilation | +| Runtime model access | `runtime_model` is the public accessor used by lifecycle-capable kernels and accepts `CompositeModel`, `RunContext`, and `Simulation` | +| One-object ergonomics | `CompositeModel(model, models...; status=...)` lowers to the same object/application compiler and runtime as explicit construction | +| Output ownership and retention | Application-qualified streams, `output_routing`, `OutputRequest(application=...)`, dynamic-object exports, and bounded policy-specific dependency histories | +| MAESPA acceptance case | `build_maespa_scene` and `run_maespa_example` use `CompositeModelTemplate`, `ObjectInstance`, `on`, `inputs`, `calls`, and `every`; verified by `test/test-maespa-model-example.jl` | +| Documentation and migration | CompositeModel/object-first README, home page, quickstart, execution guide, public API, migration guide, and explicitly labeled legacy reference sections | + +## Verification + +The following gates passed from a clean, controllable Kaimon Julia session: + +```text +test/test-unified-model-object-api.jl 576 passed +test/runtests.jl 885 passed +docs/make.jl passed +PlantBiophysics/test/runtests.jl 117 passed +git diff --check passed +``` + +The complete package suite includes Aqua, all focused restoration files, the +broad unified runtime regression, examples, fitting, and doctests. The +documentation build completed its executable examples, doctests, +cross-references, document checks, and HTML rendering successfully. + +The current uncommitted XPalm CompositeModel/Object migration loads this PlantSimEngine +worktree and executes 74 of 75 downstream assertions. Its remaining assertion +expects the removed runtime's first-step LAI (`0.000272`); the current compiled +dependency order correctly runs leaf area before plant and model aggregation, +so the initial zero-biomass leaf produces `0.0`. This is a downstream fixture +expectation in a dirty migration worktree, not a package-specific behavior to +restore in PlantSimEngine. No XPalm workaround was added here. + +## Compatibility Boundary + +Historical mapping source and tests were removed. Migration guidance remains +in the documentation for downstream packages moving to the composite-model/object API. +The branch-only intermediate prototype was also removed because it was never +released and has no compatibility boundary. + +Requested output histories are still materialized after a run. Dependency-only +temporal histories are bounded, but a fully online output sink would be an +additional optimization rather than a missing requirement of this redesign. diff --git a/docs/src/dev/composite_model_design.md b/docs/src/dev/composite_model_design.md new file mode 100644 index 000000000..f0fd4b22a --- /dev/null +++ b/docs/src/dev/composite_model_design.md @@ -0,0 +1,719 @@ +# Unified CompositeModel/Object Design + +This page records the target breaking design for one composite-model/object +configuration and runtime API. + +The central idea is: + +> Structural groupings and scales are selections over objects in one model. + +The engine should expose one way to say "this model input comes from these +objects" and one way to say "this model must manually call these models". The +compiler can then choose whether the runtime carrier is a `Ref`, `RefVector`, +temporal stream, materialized value, or callable model handle. + +The public API should be simple enough to remember as: + +```julia +ModelSpec( + model; + name=:application, + on=Many(scale=:Leaf), + inputs=(...), + calls=(...), + every=Dates.Hour(1), + environment=Environment(...), + output_routing=(...), + updates=Updates(...), +) +``` + +Everything else should either be a selector, a trait declared by the model +author, or an internal compiled carrier. + +## Core Concepts + +### CompositeModel + +A `CompositeModel` is the whole simulation universe. It contains: + +- simulated objects; +- model applications; +- environment providers; +- time/runtime state; +- caches for object selections and environment bindings. + +Plants, soil, atmosphere, microclimate grids, organs, sensors, and artificial +objects all live in the same model-level object graph. + +### Object + +An object is any simulated entity with identity. It may have: + +- a unique object id; +- one or more labels, such as `scale=:Leaf`, `kind=:plant`, + `species=:oil_palm`; +- parent/child links; +- geometry or position; +- status variables; +- model applications. + +The engine must not prescribe a plant architecture. A plant can be described as +`Plant -> Internode -> Leaf`, `Plant -> Axis -> Segment -> Leaf`, +`Plant -> Metamer -> Organ`, or another topology. The engine only needs object +identity, labels, and relations. + +Existing `MultiScaleTreeGraph.Node` topologies enter the same registry through +`objects_from_mtg(root; ...)` or `CompositeModel(root; ...)`. The adapter traverses once +and accepts accessors for ids, labels, status, and geometry; the timestep +runtime does not query the MTG topology. + +### Scale + +A scale is a label on objects, not a separate runtime layer. Examples: + +```julia +:Scene +:Plant +:Axis +:Internode +:Leaf +:Soil +:SoilLayer +:Voxel +``` + +### Scope + +A scope is a named or inferred subset of objects. Examples: + +```julia +SceneScope() +Self() +SelfPlant() +Ancestor(scale=:Plant) +Scope(:oil_palm) +Many(kind=:plant) +Many(species=:oil_palm) +``` + +`Self()` means only the current object: the object on which the consuming +application runs. It never means the model, species, or plant unless that +object is itself the plant. `Subtree()` means that object and its descendants. +Neither spelling changes meaning with scale. + +`SelfPlant()` is the nearest containing plant scope. The more generic form is +`Ancestor(scale=:Plant)`. Use these when a model running below the plant scale +must access siblings or state inside the containing plant. + +Reusable plant models should use scope-relative queries. If an allocation +model is applied to each `:Plant`, `Many(scale=:Leaf, within=Subtree())` means +"the leaves inside this plant", not all leaves in the model. The same query +applied to an axis-scale model means "the leaves inside this axis". + +CompositeModel-level models widen the scope explicitly with `within=SceneScope()`. + +Topology-relative selections use `Relation(...)`: + +```julia +One(Relation(:parent)) +Many(Relation(:children)) +Many(Relation(:ancestors); scale=:Plant) +Many(Relation(:descendants); scale=:Leaf) +Many(Relation(:siblings)) +``` + +Supported relations are `:self`, `:parent`, `:children`, `:ancestors`, +`:descendants`, and `:siblings`. They resolve relative to the current model +application object. An explicit `within=...` scope intersects the relation +result; inferred default scopes do not hide parents or siblings. Relation +results are normalized to stable object-id order before bindings are compiled. + +### Object Template And Instance + +An object template is a reusable model/parameter bundle, for example one oil +palm species model. An object instance is one concrete object in the model. + +The same template can be mounted several times: + +```julia +oil_palm = CompositeModelTemplate( + kind=:plant, + species=:oil_palm, + applications=oil_palm_applications, + parameters=oil_palm_parameters, +) + +model = CompositeModel( + ObjectInstance(:palm_1, oil_palm; root=node1), + ObjectInstance(:palm_2, oil_palm; root=node2), + ObjectInstance(:palm_3, oil_palm; root=node3), + ObjectInstance(:palm_4, oil_palm; root=node4), +) +``` + +Models and parameters can be overridden at instance or object level: + +```julia +ObjectInstance(:palm_2, oil_palm; overrides=( + stomatal_conductance = Tuzet(; g1=3.2), +)) + +Override( + object=:leaf_12, + application=:photosynthesis, + model=Fvcb(; VcMaxRef=90.0), +) +``` + +Ownership is reference-based and explicit: + +- a template retains the supplied model and parameter objects without copying; +- unchanged instances share those exact objects; +- an instance override replaces one complete model application with another + user-owned model object; +- an object override replaces that application only for the selected object; +- PlantSimEngine does not mutate model fields or implicitly merge parameter + dictionaries. + +Overrides must preserve the model contract: process identity and declared +status/environment variable names cannot change. Parameter-only overrides of +the same concrete model type retain concrete runtime dispatch. Heterogeneous +alternative implementations are supported but may require dynamic dispatch for +the exceptional application. + +### Model Kernel And Model Application + +A model kernel is the reusable model implementation written by a modeler. It +defines a process, parameters, `inputs_`, `outputs_`, optional `dep` defaults, +optional environment traits, and `run!`. + +A model application is the scenario-specific use of that kernel on selected +objects, at a selected rate, with selected value inputs, model calls, update +rules, output routing, and environment binding behavior. + +The model kernel should not need to know: + +- the species it will be used with; +- the model it will be embedded in; +- the timestep chosen by the user; +- whether its inputs come from local state, another scale, another object, a + temporal stream, units, automatic differentiation values, or uncertainty + wrappers. + +The scenario owns those decisions through `ModelSpec`. + +Target shape: + +```julia +ModelSpec(LeafEnergyBalance(); name=:leaf_energy, on=Many(kind=:plant, scale=:Leaf), inputs=(...), calls=(...), every=Hour(1)) +``` + +Application names are optional when a process occurs only once. Scenario +declarations identify singular producers and call targets with +`application=:sunlit_photosynthesis`; `process=...` is reserved for explicit +discovery queries such as `Many(process=:photosynthesis)`. + +## Unified Model Configuration + +`ModelSpec` is the single scenario wrapper. Released mapping-era configuration +is replaced by explicit value inputs and callable model calls. + +### Applies To + +Use `ModelSpec(...; on=...)` to declare the object set where a model application runs. +This should be first-class, not inferred from a container or mapping key. + +```julia +ModelSpec(LeafState(); on=Many(kind=:plant, scale=:Leaf)) + +ModelSpec(AllocationModel(); on=Many(kind=:plant, scale=:Plant)) + +ModelSpec(SceneEB(); on=One(scale=:Scene)) +``` + +The same model kernel can be applied several times with different selectors, +parameters, timesteps, or input bindings. The compiler should normalize each +application to a stable application id. + +### Dependency Defaults From Traits + +Model authors should still declare `inputs_`, `outputs_`, and `dep`. In the +final design, `dep(model)` is the model-level place for default dependency +intent. Historical `ModelMapping` declarations are migration inputs to the +CompositeModel/Object runtime, not a second supported path. + +The rule is: + +- `inputs_(model)` declares the variables the model needs; +- `outputs_(model)` declares the variables the model computes; +- `dep(model)` declares default value sources or manual model calls when the + model author knows a sensible coupling pattern; +- `ModelSpec(...; inputs=(...))` and `ModelSpec(...; calls=(...))` override + or specialize those defaults for a specific simulation. + +For example, a plant allocation model can provide a plant-local default: + +```julia +dep(::PlantAllocationModel) = ( + leaf_carbon = Input(Many(scale=:Leaf, within=Subtree(), var=:leaf_carbon)), +) +``` + +An energy-balance model can declare that it usually calls a stomatal +conductance model manually: + +```julia +dep(::LeafEnergyBalanceModel) = ( + stomatal_conductance = Call(process=:stomatal_conductance), +) +``` + +These trait defaults are not absolute wiring. They are model-author defaults +that make common cases work without repeating configuration, while scenario +authors keep final authority through `ModelSpec`. + +Compiler order: + +1. read `inputs_`, `outputs_`, and `dep`; +2. infer simple same-object value dependencies when unambiguous; +3. apply `dep(model)` defaults for value inputs and model calls; +4. apply `ModelSpec` overrides last. + +This order is part of the public contract. It keeps modeler defaults useful +without making them final wiring. Missing or ambiguous inputs after this pass +are errors, not incidental fallback behavior. + +### Value Inputs + +Use `ModelSpec(...; inputs=...)` when a model needs values before its `run!` method executes: + +```julia +ModelSpec(LAIModel(ground_area); inputs=(:leaf_areas => Many(scale=:Leaf, within=SceneScope(), var=:leaf_area))) +``` + +Reusable plant allocation: + +```julia +ModelSpec(AllocationModel(); on=Many(scale=:Plant), inputs=(:leaf_carbon => Many(scale=:Leaf, within=Subtree(), var=:leaf_carbon))) +``` + +The same declaration must compile to: + +- direct `Ref`/`RefVector` wiring when producer and consumer live in the same + object graph and rate; +- temporal stream reads when producer and consumer run at different rates; +- materialization when target status must be assigned before a + model runs; +- source-status lookup for graph-backed object selections. + +The important user rule is: + +- `ModelSpec(...; inputs=...)` means "give this model values"; the runtime schedules or + samples producers; +- the receiving model never manually calls the producer because of an + `ModelSpec(...; inputs=...)` declaration. + +### Carrier And Copy Semantics + +The compiler chooses the carrier, but the semantics must be documented and +explainable: + +| Situation | Preferred carrier | Copy behavior | +| --- | --- | --- | +| same-rate scalar input | shared `Ref` or local alias | no copy when possible | +| same-rate `Many(...)` input | `RefVector` or equivalent typed reference collection | no copy for live values | +| cross-rate input | temporal stream sample | value materialized for the consumer timestep | +| `Integrate` or `Aggregate` input | temporal window reduction | reduced value materialized | +| materialized target status input | compiler-generated assignment | assigned before consumer run | +| environment input | cached `EnvironmentBinding` sample | backend-defined value sample | + +This table is a required part of the design because performance, units, +automatic differentiation, and error propagation depend on preserving user +value types and avoiding hidden copies. + +PlantSimEngine should not force `Float64` internally. Status values, +parameters, environment values, and outputs must be allowed to use units, dual +numbers, uncertainty wrappers, tracked arrays, or other numeric-like types. +Compiled carriers should be parametric and type stable whenever the object set +and value type are known at initialization. + +### Multirate Inputs + +Multirate must be supported by the same `ModelSpec(...; inputs=...)` declaration, not a +separate mapping language. The public time language should remain `Dates` +periods. + +Example: + +```julia +ModelSpec(PlantAllocation(); on=Many(kind=:plant, scale=:Plant), inputs=(:leaf_assimilation => Many( + scale=:Leaf, + within=Subtree(), + var=:assimilation, + policy=Integrate(), + window=Day(1), + )), every=Day(1)) +``` + +Policy precedence should stay explicit: + +1. input-level policy in `ModelSpec(...; inputs=...)`; +2. producer `output_policy(model)`; +3. default `HoldLast()`. + +Cross-rate links must go through temporal state even when they point to objects +that could otherwise be reference-wired. + +Same-timestep feedback cycles are broken explicitly on the receiving input: + +```julia +ModelSpec(CarbonState(); inputs=(PreviousTimeStep(:carbon_biomass) => One( + scale=:Plant, + application=:carbon_allocation, + var=:carbon_biomass, + ),)) +``` + +`PreviousTimeStep(:x)` removes the producer-to-consumer edge from the current +timestep graph and reads the latest source sample at or before the previous +model timestep. Before a source sample exists, the initialized consumer status +value for `x` is used. This makes initialization part of the scenario contract +instead of silently inventing a zero value. + +### Model Calls + +Use `ModelSpec(...; calls=...)` when a model must manually run selected models, typically +inside an iterative solver. This is the required public API name and must be +implemented as part of the unified composite-model/object redesign, not left as a later +rename. + +```julia +ModelSpec(SceneEB(); calls=(:leaf_energy => Many( + kind=:plant, + scale=:Leaf, + process=:energy_balance, + )), calls=(:soil => One(kind=:soil, application=:soil_water))) +``` + +Inside `run!`, the model model receives call handles and calls +`run_call!(call)` during trial iterations, then +`run_call!(call; publish=true)` for the accepted final solution. The default is +deliberately `publish=false`: trial calls mutate target status for convergence +checks but do not append temporal samples or write environment outputs. + +The important user rule is: + +- `ModelSpec(...; calls=...)` means "give this model callable model handles"; +- the parent model owns the call stack and can iterate, reject, or accept trial + calls; +- call outputs are published only according to the call publication contract. + +`Diagnostics.explain_calls(compiled)` exposes this as +`publication_policy=:explicit_accept`, with `default_publish=false` and +`accepted_publish=true`. + +Binding and call explanations also report where each dependency declaration +came from: + +- `origin=:inferred_same_object` for compiler-inferred value dependencies; +- `origin=:model_default` for `Input(...)` or `Call(...)` declarations coming + from `dep(model)`; +- `origin=:model_spec` for scenario-level `ModelSpec(...; inputs=...)` or `ModelSpec(...; calls=...)`, + including declarations that override a model default. + +### Multiplicity + +Selection multiplicity is explicit: + +```julia +One(...) +Many(...) +OptionalOne(...) +``` + +`OptionalOne(...)` resolves to zero or one dependency. With zero matches, an +input keeps its `inputs_` default and a call returns an empty +`call_targets(...)` collection. Explanations retain these unresolved +optional bindings instead of hiding them. + +The compiler validates that `One(...)` resolves to exactly one producer per +consumer scope. `Many(...)` returns a vector-like value or target collection. + +### Address Normalization + +All source and target declarations normalize to an internal address: + +```julia +Diagnostics.ObjectAddress( + scope, + kind, + species, + scale, + name, + process, + application, + var, + relation, + policy, + window, + from_status, + after, + multiplicity, +) +``` + +Only the compiler works with this normalized address. Users should not need to +construct it manually. [`Diagnostics.object_address`](@ref) is the structured diagnostic +view and preserves every normalized selector field, including temporal and +status-routing fields. + +## Object Lifecycle And Spatial Contracts + +Growth, pruning, organ creation, reparenting, and moving organs must all update +the same compiled caches: + +- object selections used by `on`, `inputs`, and `calls`; +- `RefVector` or equivalent many-object carriers; +- temporal stream ownership; +- writer validation; +- environment bindings. + +The public mutation API should make cache invalidation explicit and centralized: + +```julia +register_object!(model, object; parent) +remove_object!(model, object) +reparent_object!(model, object, new_parent) +move_object!(model, object, geometry_or_position) +Advanced.refresh_bindings!(model) +``` + +Spatial environment backends should depend on a small geometry contract, not on +a particular plant representation: + +```julia +position(object_or_status) +geometry(object_or_status) +bounds(object_or_status) +``` + +Packages can provide richer geometry, octrees, voxel grids, or layers, but +PlantSimEngine should only require enough information to bind an object to an +environment provider. + +## Duplicate Writers And Updates + +Most variables should have one canonical writer per object and timestep. When a +variable is intentionally updated by several models, the scenario should say so +where the model applications are assembled: + +```julia +ModelSpec(PruningModel(); on=Many(scale=:Leaf), updates=Updates(:leaf_biomass; after=:carbon_allocation)) +``` + +`Updates(...)` should be rare and explicit. It is a scenario-level ordering +rule, because a model author cannot predict every model that will later update +the same variable. + +## Environment And Microclimate + +Meteorology should remain automatic unless a model or scenario needs special +behavior. Models declare environment variables: + +```julia +environment_inputs_(::LeafEnergyModel) = ( + T=0.0, + Rh=0.0, + Wind=0.0, + Ri_PAR_f=0.0, + CO2=0.0, +) +``` + +The runtime resolves those variables through the model environment service. + +Default resolution: + +1. A global/table environment backend gives every object the current sampled row. +2. A voxel, octree, layered, or grid backend samples the cell bound to the + object. +3. If the object has no position, use the parent position. +4. If no spatial binding can be made, fall back to the global environment or error when + the environment variable is required. + +Users can override the binding contract: + +```julia +EnvironmentResolver( + bind=(model, object) -> containing_cell(model.microclimate, position(object)), +) +``` + +PlantSimEngine should define the protocol and caching hooks, not the voxel or +octree implementation. Specialized packages should provide concrete spatial +backends. + +The environment backend protocol should be small and backend-oriented: + +```julia +handle = EnvironmentAPI.bind_environment(backend, object, context, config) +EnvironmentAPI.sample(backend, handle, variable, time) +EnvironmentAPI.sample(backend, handle, trial_state, variable, time) +commit_environment!(backend, handle, accepted_state, time) +EnvironmentAPI.update_index!(backend, changed_entities, removed_object_ids) +``` + +`environment_inputs_(model)` declares what a model reads from the active environment +provider, while `environment_outputs_(model)` declares what it may commit. Controllers +commit accepted mutable microclimate state with +`commit_environment!(context, accepted_state)` and run trial descendants with +`run_call!(context, name; environment=trial_state)`. Simple global meteorology +remains the default provider. + +Scenario-level environment source remapping belongs on `Environment(...)`, for +example: + +```julia +ModelSpec(LeafGasExchange(); name=:gas_exchange, on=Many(scale=:Leaf), environment=Environment(provider=:global, sources=(CO2=:Ca,))) +``` + +Here the model reads `environment.CO2` because that is its declared generic +contract, while the active environment backend samples the source variable +`:Ca`. Environment binding refresh validates source availability when the +backend can enumerate variables, and explanations report both +`required_inputs` and `source_inputs`. + +Global tabular meteorology follows the model application's compiled +`ModelSpec(...; every=...)`. PlantMeteo samples the table with the reducer and window from +`environment_hint(...)` when the model runs more slowly than the weather base step. +An `Environment(; sources=...)` override replaces only the source variable; it +does not discard the model-author reducer. The prepared weather sampler is +compiled once, and one sampled row is reused by every object targeted by the +same application at that timestep. + +Spatial or mutable backends retain control of their own temporal semantics. +PlantSimEngine supplies the compiled object/cell binding and current simulation +time; a specialized microclimate backend decides whether its local state is +instantaneous, interpolated, or internally integrated. + +### Cached Environment Bindings + +Spatial lookup must not happen for every model call. At initialization and when +objects are created, the runtime builds an environment binding cache: + +```julia +EnvironmentBinding( + object_id, + provider=:microclimate_grid, + cell_id, + variables=(:T, :Rh, :Wind, :Ri_PAR_f), +) +``` + +Runtime sampling is: + +```text +object -> cached binding -> environment cell -> current values +``` + +Invalidation events: + +- object created; +- object removed; +- object moved; +- geometry changed; +- environment grid rebuilt or refined; +- model environment requirements changed. + +Geometry APIs should provide ergonomic invalidation: + +```julia +mark_environment_binding_dirty!(model, object) +update_geometry!(object, geometry; invalidate_environment=true) +``` + +Before each timestep, dirty bindings are refreshed in batch. + +## Compilation Strategy + +The compiler should build one global dependency graph over object addresses. +The graph includes: + +- value dependencies from `ModelSpec(...; inputs=...)`; +- callable dependencies from `ModelSpec(...; calls=...)`; +- model update edges from `Updates(...)`; +- temporal policy edges; +- environment reads and writes; +- object-scope selection caches. + +The runtime representation is an implementation detail: + +- same-rate local links can stay as aliases; +- cross-rate links use temporal state; +- many-object links use `RefVector` or node-value streams; +- call links use `ModelCall` or an equivalent callable runtime handle; +- environment links use cached `EnvironmentBinding`s. + +The final execution plan should group contiguous targets with the same concrete +model, status, model-bundle, input-binding, and environment-binding types. +Dynamic dispatch may occur once at the application/batch boundary, but not for +every leaf in a homogeneous target set. Exceptional model overrides form +separate concrete batches while preserving stable object order. Lifecycle or +environment refreshes rebuild these batches before the next timestep. + +The public explanation API must describe the normalized graph, not the internal +carrier choice. + +## Agent-Facing Requirements + +The final design must be understandable by agents through structured +explanation helpers: + +```julia +Diagnostics.explain_objects(model) +Diagnostics.explain_instances(model) +Diagnostics.explain_scopes(model) +Diagnostics.explain_bindings(sim) +Diagnostics.explain_calls(sim) +Diagnostics.explain_environment_bindings(sim) +Diagnostics.explain_schedule(sim) +Diagnostics.explain_writers(sim) +Diagnostics.explain_execution_plan(sim) +Diagnostics.explain_output_retention(sim) +``` + +These helpers should return stable structured data, not only pretty text. A +binding row should include at least: + +- consumer application id; +- consumer object id; +- consumer variable; +- source selector; +- resolved producer application id or environment provider id; +- resolved producer object ids; +- process/name filters; +- temporal policy and window; +- carrier kind; +- copy/reference semantics; +- reason the binding was chosen; +- whether it came from inference, `dep(model)`, or `ModelSpec`. + +Execution-plan rows should additionally expose the selected object ids, +concrete model/status/carrier types, batch size, and whether the inner loop is +homogeneous and specialized. + +Output-retention rows should expose the retained application id, variable, +retention reasons, compiled retention horizon, and current target count so +agents can distinguish default retain-all behavior, requested output streams, +and bounded temporal-dependency streams. + +Errors should report concrete object labels, scope selectors, process names, +variables, and suggested fixes. + +## API Position + +This is a breaking design. Model kernels use +`run!(model, status, environment, constants, context)` while the scenario +configuration surface uses `CompositeModel`, `Object`, `ModelSpec`, selectors, +`ModelSpec(...; inputs=...)`, `ModelSpec(...; calls=...)`, `ModelSpec(...; every=...)`, and `Environment(...)`. diff --git a/docs/src/dev/composite_model_implementation_plan.md b/docs/src/dev/composite_model_implementation_plan.md new file mode 100644 index 000000000..85fb9c279 --- /dev/null +++ b/docs/src/dev/composite_model_implementation_plan.md @@ -0,0 +1,1035 @@ +# Unified CompositeModel/Object Implementation Plan + +This plan is the persistent handoff for replacing the historical +multiscale-mapping system with one composite-model/object address system. + +The implementation can be incremental internally, but the target API is +breaking. Do not preserve experimental intermediate APIs as user-facing +concepts in the final design. + +The target public surface should be centered on a small set of concepts: + +```julia +ModelSpec( + model; + name=:application, + on=Many(scale=:Leaf), + inputs=(...), + calls=(...), + every=Dates.Hour(1), + environment=Environment(...), + output_routing=(...), + updates=Updates(...), +) +``` + +This is the API memory target for users, modelers, and agents. Additional +types should be selectors, model traits, or internal compiled carriers. + +## Implementation Progress + +- Started Phase 0 by adding typed application metadata, now constructed + directly with `ModelSpec` keywords. +- Added `ModelSpec(model; name=...)` application names and getters: + `application_name`, `applies_to`, `value_inputs`, `model_calls`, and + `environment_config`. +- Added selector and address types: `SceneScope`, `Self`, `Subtree`, + `SelfPlant`, `Ancestor`, `Scope`, `Relation`, `One`, `OptionalOne`, `Many`, + and `Diagnostics.ObjectAddress`. +- Added initial `CompositeModel`/`Object` registry types and lifecycle hooks: + `register_object!`, `remove_object!`, `reparent_object!`, `move_object!`, + and `Advanced.refresh_bindings!`. +- Added registry-backed selector resolution with `resolve_object_ids` and + `resolve_objects` for `SceneScope()`, `Self()`, `SelfPlant()`, + `Ancestor(...)`, `Scope(...)`, label keywords such as `kind=:plant` and + `scale=:Leaf`, and `One`/`OptionalOne`/`Many` cardinality checks. +- Added `Diagnostics.explain_scopes(model)` for agent-readable scope diagnostics. It + reports the global model scope, each object subtree, each named + `Scope(...)`, and label groups by scale, kind, and species with concrete + resolved object ids. +- Selector cardinality and named-scope failures now report the consumer + context, matched object ids, requested criteria, available scales, kinds, + species, and names inside the resolved scope, plus bounded edit-distance + suggestions. +- `Relation(...)` selectors now resolve `:self`, `:parent`, `:children`, + `:ancestors`, `:descendants`, and `:siblings` relative to the consuming + object. Explicit scopes constrain relation results, default dependency scopes + do not erase parent/sibling queries, and compiled `ModelSpec(...; inputs=...)` can use these + relations without runtime selector resolution. +- `Diagnostics.ObjectAddress(selector)` normalizes scope, relation, label, routing, + temporal-policy, and status-ordering fields into one structured diagnostic + record. +- Started the object-address compiler with `Advanced.compile_composite_model(model, specs)` and + compiled model application/binding carriers. The compiler now resolves + `ModelSpec(...; on=...)` target object ids, object-relative `ModelSpec(...; inputs=...)` source + object ids, and object-relative `ModelSpec(...; calls=...)` callee object/application ids + before runtime. +- Added `Diagnostics.explain_applications`, `Diagnostics.explain_bindings`, and `Diagnostics.explain_calls` + for the compiled model view. These explanations expose application ids, + processes, target ids, input source ids, call callee ids, temporal policy, + window, and carrier hints. +- Added status-backed compiled input carriers. When source objects already + hold `Status` values, `ModelSpec(...; inputs=...)` bindings now precompile a scalar shared + `Ref`, a homogeneous `RefVector`, or an `Advanced.ObjectRefVector` fallback for + heterogeneous reference-preserving vectors. `Diagnostics.input_carrier`, `Diagnostics.input_value`, + and `Diagnostics.has_reference_carrier` expose these carriers, and `Diagnostics.explain_bindings` + reports carrier kind, copy/reference semantics, carrier type, and reference + availability. +- Added conservative same-object input inference in the model compiler. When a + model declares an `inputs_` variable that is not covered by explicit/default + `ModelSpec(...; inputs=...)`, and exactly one other application on the same object outputs + the same variable, `Advanced.compile_composite_model` creates an inferred reference binding. + `Diagnostics.explain_bindings` now reports binding `origin` values such as + `:model_default`, `:model_spec`, and `:inferred_same_object`. +- Compiled input bindings now carry producer metadata. When an `ModelSpec(...; inputs=...)` + selector uses `process=` or `application=`, `Advanced.compile_composite_model` validates that a + matching source application exists for the selected source objects. + `Diagnostics.explain_bindings` reports `source_application_ids`, `process`, and + `application` for agent-readable dependency diagnostics. +- Dependency selectors in `ModelSpec(...; inputs=...)` and `ModelSpec(...; calls=...)` now infer a default + scope from the consumer object when no explicit `within=...` is provided: + model objects default to `SceneScope()`, while non-model objects default to + `Self()`. Shared model/soil dependencies from organs should therefore use + `within=SceneScope()` explicitly. +- `Advanced.compile_composite_model` now validates `Required(T)` status inputs + from `inputs_(model)`. Each required input must either have a compiled + binding or already exist on the target object `Status`; otherwise + compilation errors with the concrete application id, object id, and input + variable. +- CompositeModel compilation creates an empty `Status` for model-targeted + objects when status is omitted, inserts missing `outputs_` fields and + `Default(value)` inputs from their initial values, and installs explicitly or + implicitly bound input carriers. Unbound `Required(T)` inputs remain + compilation errors. +- `Advanced.compile_composite_model` now rejects `ModelSpec(...; inputs=...)` declarations whose left-hand + variable is not declared by the target model's `inputs_`. This catches + misspelled or stale scenario bindings before they create silent unused + metadata. +- `Advanced.compile_composite_model` now validates source availability for status-backed + non-temporal `ModelSpec(...; inputs=...)` bindings. When selected source objects already + have `Status` values, the requested source variable must resolve to + references instead of silently compiling to an unused/no-op binding. +- Carrier compilation preserves source `Status` references and arbitrary value + types; tests cover scalar refs, heterogeneous many-object vectors, and a + homogeneous dual-like `BigFloat` value through `RefVector`, model arithmetic, + source mutation, and typed output publication. +- Same-object renaming is supported directly by `ModelSpec(...; inputs=...)`, for example + `inputs=(:renamed_signal => One(within=Self(), var=:signal),)`. The compiler + aliases the source `Ref`, records the renamed source variable in + `Diagnostics.explain_bindings`, and schedules the producer before the consumer. +- Same-rate input carriers are installed directly into consumer `Status` + reference cells during model compilation. Scalar bindings share the source + `Ref`; many-object bindings store the compiled `RefVector` or + `Advanced.ObjectRefVector` once. The timestep runtime performs no assignment for + these bindings, and a focused `Many(...)` materialization gate verifies zero + allocations after compilation. +- Reference wiring adds a missing bound input field to the consumer `Status` + schema when needed, instead of requiring users to duplicate compiler-owned + input placeholders. +- Added call ambiguity validation in the compiled model view: a call can select + by process when unique, and must use `application=:name` when several model + applications with the same process match the same object. +- Added a model binding cache with `Advanced.refresh_bindings!`, `Advanced.bindings_dirty`, + `Advanced.compiled_bindings`, and `Advanced.model_revision`. Object creation, removal, + and reparenting now invalidate the compiled binding cache and bump a model + revision before the next refresh. +- Added an environment binding cache with `Advanced.refresh_environment_bindings!`, + `Advanced.compile_environment_bindings`, `Advanced.CompiledEnvironmentBinding`, + `Advanced.CompiledEnvironmentBindings`, `Advanced.environment_bindings_dirty`, + `Advanced.compiled_environment_bindings`, `Advanced.environment_revision`, and + `Diagnostics.explain_environment_bindings`. The compiler resolves each + application/object environment provider, backend, required + `environment_inputs_`, support descriptor, and backend cell before runtime. +- Added the minimal model geometry contract: `geometry(object_or_status)`, + `position(object_or_status)`, and `bounds(object_or_status)`. Environment + binding refreshes now call `EnvironmentAPI.update_index!(backend, changed_entities, removed_object_ids)` once per + distinct backend before `Advanced.EnvironmentAPI.bind_environment`, giving spatial backends a current + model-wide object/entity list for precomputed microclimate lookup. +- Automatic spatial binding now uses the nearest ancestor geometry when a + target object has no geometry of its own. Existing backends still receive an + `Object` carrying the target id/status, while its binding-time geometry comes + from the ancestor. Explanations report `geometry_source=:self`, `:ancestor`, + or `:global` and the source object id. +- Moving an object invalidates environment bindings for descendants that + inherit its geometry, stopping at descendants with their own geometry. This + preserves unaffected cached bindings. +- Environment refresh now reconciles model environment contracts against + cached spatial bindings. If only `environment_inputs_` changes while application + id, object, process, provider, backend, status, and geometry provenance remain + unchanged, required metadata is updated while the cached cell is reused + without `EnvironmentAPI.update_index!` or `Advanced.EnvironmentAPI.bind_environment`. +- `validate_environment_inputs(model)` and + `validate_environment_inputs(compiled_scene, environment_or_backend)` now validate + composite-model/object model application `environment_inputs_` against the active + environment or an explicit replacement. Errors report model application ids, + so duplicate process applications remain diagnosable. +- `Environment(; sources=(target=:source,))` now remaps model-facing + environment variables to backend source variables. Environment binding + refresh validates missing source variables when the backend can enumerate its + variables, and `Diagnostics.explain_environment_bindings` reports both `required_inputs` + and `source_inputs`. +- CompositeModel applications now infer model-author default environment source remaps + from `environment_hint(...).bindings` when the scenario does not provide explicit + environment bindings. Scenario `Environment(; sources=...)` keeps precedence over + the trait. +- Global tabular meteorology is now sampled at each model application's + compiled clock. `environment_hint(...).bindings` reducers and windows are applied + through PlantMeteo, while `Environment(; sources=...)` replaces only the + source variable and preserves the selected reducer. Prepared weather + samplers are shared by applications using the same weather table, and each + application/timestep sample is cached once per run so all target objects + reuse it. +- Object creation, removal, and reparenting invalidate both structural and + environment bindings. Object movement invalidates only environment bindings, + so moving a leaf or changing its geometry can refresh microclimate lookup + without rebuilding object/model binding carriers. +- Added public geometry invalidation helpers: + `update_geometry!(model, object, geometry; invalidate_environment=true)` + and object-scoped `mark_environment_binding_dirty!(model, object)`. + Geometry-only changes record the affected object ids and refresh only their + compiled environment bindings; descendants inheriting moved ancestor + geometry are invalidated as part of the same object-scoped refresh. +- Started composite-model/object execution with `run!(model; steps=...)`. + The runtime refreshes compiled object bindings and environment bindings, + materializes precompiled `ModelSpec(...; inputs=...)` carriers into consumer `Status` + fields, samples the bound environment backend, and calls generic model + kernels through the existing `run!` contract. +- CompositeModel/object execution now publishes model outputs to model-local temporal + streams. Compiled `ModelSpec(...; inputs=...)` bindings marked as `:temporal_stream` can + materialize `HoldLast`, `Interpolate`, `Integrate`, and `Aggregate` values + before the consumer runs, using selector source ids, source variables, + windows, and the model base timestep. +- CompositeModel temporal `ModelSpec(...; inputs=...)` now honor producer `output_policy(...)` traits + when the selector omits `policy=...` and resolves to a unique source + application. Explicit selector policies remain scenario-level overrides. +- CompositeModel `Interpolate(...)` matches the established multirate runtime: + bracketed samples use linear interpolation, online consumers use linear + extrapolation from the last two samples when requested, and insufficient or + non-interpolable values fall back to hold-last. `mode=:hold` and + `extrapolation=:hold` are supported, invalid modes fail during model + compilation, and interpolation arithmetic preserves generic numeric value + types without converting model values to `Float64`. +- Unified `ModelSpec(...; inputs=...)` now supports explicit lagged dependencies with + `PreviousTimeStep(:input) => selector`. Lagged bindings use temporal streams, + read source samples at or before `t - 1`, preserve the initialized consumer + status value until history exists, and do not add a same-timestep scheduling + edge. This allows feedback cycles to compile without changing generic model + kernels. +- CompositeModel/object execution now exposes explicit mutable environment + commits through `commit_environment!(context, accepted_state)` and + non-committing trial sampling through + `run_call!(context, name; environment=trial_state)`. + Meteorological state stays in the environment backend instead of being staged + through same-named status values. +- Added root application scheduling from `ModelSpec(...; every=...)` using `Dates.Period` + values and the model environment base step. `Diagnostics.explain_schedule` on a + `Advanced.CompiledCompositeModel` now reports each application clock, phase, timestep in base + steps, timestep duration in seconds, and whether the application is scheduled + as a root application or is manual-call-only. +- CompositeModel application scheduling now also honors a model's `timespec(...)` trait + when `ModelSpec(...; every=...)` is omitted. Scenario-level `ModelSpec(...; every=...)` keeps + precedence over the model trait, matching the established multirate runtime. +- CompositeModel application scheduling now validates `timestep_hint(...)` required + bounds for base-step-derived clocks. Hints remain compatibility constraints; + they do not override explicit `ModelSpec(...; every=...)` or non-default `timespec(...)`. +- `Advanced.compile_composite_model` now computes a stable topological application order from + resolved `ModelSpec(...; inputs=...)` producer edges and `Updates(...)` writer-order edges. + Inputs produced by manual-call-only applications are redirected to the parent + application that owns the `ModelSpec(...; calls=...)` call stack. `run!(model)` uses this + precompiled order instead of user declaration order, cycles fail at compile + time, and `Diagnostics.explain_schedule` reports `execution_index`. +- `Advanced.CompiledCompositeModel` now pre-indexes input and call bindings by + `(application_id, object_id)`. Per-object input materialization and + `call_targets` lookup uses these indexes instead of scanning every + binding in the model at each model call. +- `Advanced.CompiledCompositeModel` now also pre-indexes applications by application id. + Hard-call target resolution and stable ordered-application materialization + use this index instead of scanning or rebuilding lookup dictionaries. +- `Advanced.CompiledEnvironmentBindings` now pre-indexes environment bindings by + `(application_id, object_id)`. Environment sampling and mutable environment + output scattering use direct lookup instead of scanning all environment + bindings for every model invocation. +- Added `RunContext` and `CallTarget`. Models can retrieve manual + `ModelSpec(...; calls=...)` targets with `call_targets(context, :name)` and execute + them with `run_call!`, preserving explicit call-stack control in the + composite-model/object runtime. Manual calls execute immediately under the parent call + stack; applications selected by `ModelSpec(...; calls=...)` are skipped by the root + `run!(model)` loop and only execute through `run_call!`. +- Added composite-model/object duplicate-writer validation. During `Advanced.compile_composite_model`, each + `(object, output variable)` now has one canonical writer unless later + writers declare `Updates(:var; after=...)`. The `after` token can match a + previous application id/name or process, so scenario authors can express + cases such as pruning after carbon allocation without changing either model + implementation. +- Added `Diagnostics.explain_writers(compiled)`. It reports each object/variable writer + group, duplicate-writer status, writer application ids/processes, and the + `Updates(...)` declarations used to validate ordered updates. +- Extended `explain_model_specs` rows with application name, target selector, + value inputs, manual calls, and environment metadata. +- Started Phase 3 by compiling simple `ModelSpec(...; inputs=...)` declarations to typed + scale/variable carriers, for example + `inputs=(:x => Many(scale=:Leaf, var=:y),)`. +- Added model-level `Input(...)` defaults from `dep(model)` into + `ModelSpec` value inputs. Scenario-level `ModelSpec(...; inputs=(...))` + overrides those defaults before the native binding is compiled. +- Removed the intermediate scenario bridge after the composite-model/object compiler + gained native `ModelSpec(...; inputs=...)` support. Manual value-transfer carriers are not + retained as user-authored API. +- Removed the intermediate dependency resolver after `ModelSpec(...; calls=...)` became + native composite-model/object metadata. Manual model execution now goes through + `CallTargets`, `call_targets`, and `run_call!`. +- Added model-level `Call(...)` defaults from `dep(model)` into + `ModelSpec` manual-call metadata. Scenario-level + `ModelSpec(...; calls=(...))` overrides those defaults, and + `dep(::ModelSpec)` excludes raw `Call(...)` trait entries so default calls + are normalized through the same bridge as explicit calls. +- Migrated the MAESPA example's model energy-balance hard calls to + scenario-level `ModelSpec(scene_model; calls=(...))`. +- Migrated the MAESPA example's model LAI leaf-area transfer to consumer-side + `ModelSpec(LAIModel(...); inputs=(...))`. +- Started Phase 5 with `CompositeModelTemplate` and `ObjectInstance`. A template stores + reusable composite-model/object `ModelSpec`s plus default object labels, and an + instance mounts those specs inside one named object subtree. +- `CompositeModel(...)` accepts `ObjectInstance` values directly or through its + `instances` keyword. An instance root can be an owned `Object` or the id of + an object supplied separately to the model. +- Mounted template applications receive stable instance-prefixed application + names and an implicit `Scope(instance_name)` on unqualified + `ModelSpec(...; on=...)` selectors. Their `ModelSpec(...; inputs=...)`, `ModelSpec(...; calls=...)`, scheduling, + writer validation, and execution use the normal compiled composite-model/object path. +- Instance overrides can replace one template application by application name + or process. Overrides must be unambiguous and preserve process identity. + Instances without overrides retain the exact shared model object from the + template. +- Template labels fill missing `kind` and `species` metadata throughout the + mounted subtree, while the root receives the instance name used by + `Scope(...)`. Tests cover four instances, plant-local aggregation, shared + model storage, and one process-level model override. +- Added explicit exceptional-organ overrides with + `Override(object=..., application=..., model=...)` through + `ObjectInstance(...; object_overrides=...)`. The override must resolve to one + template application, belong to the instance subtree, and preserve process, + input, output, and environment-variable declarations. +- Object overrides remain one logical model application: the compiler stores + the selected replacement model by target object id. Dependency bindings, + writer ownership, application names, and manual calls therefore remain + unchanged, and no selector resolution occurs in the runtime loop. +- Parameter/model ownership is explicit. Templates retain user-supplied model + and `parameters` objects by reference; unchanged instances share them. + Instance and object overrides retain their user-supplied replacement model + by reference. PlantSimEngine does not copy models or mutate model fields to + merge parameter overrides. +- Same-concrete-type object overrides use a concretely typed object-to-model + table. Structured application explanations report shared/per-object storage, + concrete versus heterogeneous dispatch, overridden object ids, and model + types. +- `CompositeModel` retains mounted instance metadata and `Diagnostics.explain_instances(model)` + reports each instance root, current subtree object ids, mounted application + ids, instance/object overrides, template labels, and parameter ownership. + `Diagnostics.explain_objects(model)` also reports instance membership. +- New objects registered below an instance automatically inherit missing + template `kind` and `species` labels. Instance explanations derive membership + from the current topology, so growth, pruning, and reparenting do not leave a + separate stale membership list. +- CompositeModel hard calls can run under temporary local meteorology with + `run_call!(context, name; environment=local_state)`. Descendants sample the + temporary state through normal environment bindings, while `publish=false` + suppresses output publication and environment commits. This supports + iterative microclimate solvers such as the MAESPA model energy-balance loop. +- Model kernels read their own parameters from the `model` argument. Generic + hard-dependency kernels such as `Monteith` and `Fvcb` discover declared call + targets through `call_targets` and execute them through `run_call!`. +- CompositeModel duplicate-writer validation now ignores manual-call-only applications + when validating canonical root writers. This keeps hard-dependency children + from being treated as independent root writers when they intentionally update + the same object status inside their parent call stack. +- Added a unified composite-model/object MAESPA example path: + `build_maespa_scene(...)` and `run_maespa_example(...)`. + It uses `CompositeModelTemplate`, `ObjectInstance`, `on`, `inputs`, `calls`, + and `every=Dates.Period` with two plant species, one shared soil object, + model LAI, and model energy balance. +- `test/test-maespa-model-example.jl` verifies the unified composite-model/object + MAESPA path. +- `run!(model)` now returns a `Simulation` wrapper with the mutated + `CompositeModel`, compiled model bindings, compiled environment bindings, and the + model-local temporal output streams. This keeps existing status mutation + behavior but makes model outputs inspectable after a run. +- Added `outputs(sim::Simulation)`, `collect_outputs(sim)`, and + `Diagnostics.explain_outputs(sim)` for composite-model/object runs. The explanation reports object + ids, variables, publishing application ids, sample counts, time bounds, and + value types. +- `run!(model; tracked_outputs=...)` now accepts `OutputRequest` and returns + requested model outputs through `collect_outputs(sim)` or + `collect_outputs(sim, :request_name)`. CompositeModel requests are materialized from + retained typed temporal streams after the run. They support `HoldLast`, + `Interpolate`, `Integrate`, and `Aggregate`, `Dates.Period` export clocks, + canonical-publisher inference when unique, explicit `process=...` + selection, and dynamic objects over each object's own published sample + interval. +- CompositeModel output requests now compile a publisher-level retention plan. With + `tracked_outputs=nothing`, the model runtime retains all output streams for + historical inspection. With explicit `tracked_outputs`, including an empty + request vector, it retains only requested publisher streams plus streams + required by temporal `ModelSpec(...; inputs=...)`. Dependency-only streams are pruned after + publication to the compiled policy horizon: latest-only for `HoldLast`, the + input window for `Integrate`/`Aggregate`, and enough source history for + `Interpolate`/`PreviousTimeStep`. Explicitly requested streams retain their + complete histories for post-run export. Export is therefore not yet fully + online, but unrequested temporal dependencies no longer grow for the full + simulation. +- Added `Diagnostics.explain_output_retention(sim)` to report which application/variable + streams are retained and whether the reason is default retention, an output + request, or a temporal dependency. Dependency-only rows also report their + compiled `retention_steps`; unbounded requested/default rows report + `nothing`. +- CompositeModel temporal streams are now keyed by application id, object id, and + variable. Multiple applications can publish the same variable on the same + object without overwriting each other's stream samples. +- CompositeModel output-export tests now cover requested-output `DataFrame` + materialization, canonical publisher inference when `process=` is omitted, + rejection when only stream-only publishers exist, and ambiguity when an + explicit process matches both a stream-only and a canonical publisher. +- CompositeModel `OutputRequest(...)` now accepts `application=...` to select an + explicit application id/name when the same process is mounted more than + once. Explicit application selection can retain and export a + `:stream_only` publisher. +- Each model temporal stream owns a concrete `Vector{Tuple{Float64,T}}` + selected from its first published value rather than boxing all values as + `Any`. Output type changes fail explicitly, and `Interpolate`/`Integrate` + tests verify `BigFloat` histories and reduced values remain `BigFloat`. +- CompositeModel `output_routing=(var=:stream_only,)` now matches the unified graph + semantics: stream-only outputs are excluded from canonical writer validation + and same-object input inference, while remaining available in output streams + and explicit `inputs=(... One(application=:name), ...)` selections. +- `run!(model; steps=...)` now refreshes dirty structural bindings at timestep + boundaries. Objects created, removed, or reparented by a model during one + timestep update `ModelSpec(...; on=...)` target sets, input carriers, call targets, + writer validation, and scheduling before the next timestep. +- Geometry-only mutations refresh environment bindings at the next timestep + without recompiling structural bindings. The returned `Simulation` + always contains final compiled structural and environment bindings, including + mutations performed on the last step. +- Environment dirty tracking is now object-scoped for geometry-only changes. + `move_object!`, `update_geometry!`, and + `mark_environment_binding_dirty!(model, object)` retain unaffected compiled + bindings and re-run `Advanced.EnvironmentAPI.bind_environment` only for applications targeting the + changed object. Structural changes and provider-wide invalidation still + rebuild the complete environment cache. +- Runtime lifecycle tests cover a model-created leaf joining a leaf + application and plant-local `RefVector`, a pruned leaf leaving both before + the next step, and a moved leaf switching mock microclimate cells. +- Root model execution now compiles contiguous homogeneous target batches. + Each target prebinds its concrete model, `Status`, input-binding tuple, and + environment binding. Runtime dispatch occurs once + at the batch function barrier; the inner object loop is specialized on a + concrete target type. +- Exceptional object overrides with another concrete model implementation + become separate batches without changing stable object execution order. + Structural or environment binding refresh recompiles the execution plan + before the next timestep. +- Added `Diagnostics.explain_execution_plan(scene_or_simulation)`. It reports batch object + ids, concrete model/status/carrier types, batch sizes, and inner-loop dispatch + semantics. A focused 128-leaf gate verifies zero allocations inside a warmed + homogeneous no-output batch. +- Added `objects_from_mtg(root; ...)` and `CompositeModel(root::MultiScaleTreeGraph.Node; + ...)`. Existing MTG topology is traversed once into the unified registry, + preserving stable node-derived ids, parent relations, labels, geometry, and + existing `:plantsimengine_status` objects through configurable accessors. + +The composite-model/object compiler is executable: selectors normalize to object +addresses, resolve before runtime, and compile into reference, temporal, call, +writer, and environment carriers. The historical mapping compiler has been +removed. + +## Phase 0: Public Contract Freeze + +Goal: decide the small public vocabulary before implementing internals. + +Define: + +- `ModelSpec(model; name=nothing)` as the model-application wrapper. +- `ModelSpec(...; on=selector)` as the target object-set declaration. +- `ModelSpec(...; inputs=...)` for value dependencies. +- `ModelSpec(...; calls=...)` for manual call-stack dependencies. +- `Updates(...)` for rare ordered duplicate writers. +- `every=period::Dates.Period` and related multirate policies. +- `Environment(...)` for optional environment resolver/backend overrides. + +Rules: + +- a model kernel remains generic and declares `inputs_`, `outputs_`, optional + `dep`, optional `environment_inputs_`, and `run!`; +- a model application decides where the kernel runs, at what rate, and how its + inputs, calls, updates, outputs, and environment are bound; +- application ids are stable and can be generated from explicit `name`, + process, object selector, and occurrence index; +- if several applications provide the same process on the same object set, + selectors must disambiguate by application name or another explicit filter. + +Acceptance tests: + +- a model can be applied twice to the same leaf objects with different names; +- a dependency selector can choose by process when unique and by name when not; +- structured explanations expose model kernel type, process, application name, + and target object ids. + +## Phase 1: CompositeModel Object Registry + +Goal: introduce the internal object model without changing public behavior yet. + +Implement: + +- `ObjectId` as the stable identity key for every runtime object. +- `ModelObject` metadata with labels: + `scale`, `kind`, `species`, optional `name`, parent id, child ids, and + optional geometry/position handle. +- `Advanced.ObjectRegistry` storing objects, parent/child relations, and indexes by + label. +- adapters from existing MTG state into the registry: + each selected root and each MTG node gets an object id; + single-status simulations get one object with `scale=:Default`. +- object lifecycle hooks for add/remove/reparent that mirror the existing MTG + runtime reindexing. + +Acceptance tests: + +- the MAESPA example registers five leaf objects, two plant objects, one soil + object, and one model object; +- `status(sim, :plant_A, :Leaf)` and `status(sim, :Leaf)` can be expressed as + registry queries; +- add/remove/reparent updates object registry relations and status views. + +## Phase 2: Selector And Scope Language + +Goal: make "which objects?" explicit and reusable. + +Implement selector types: + +```julia +SceneScope() +Self() +Subtree() +SelfPlant() +Ancestor(scale=:Plant) +Scope(name) +Relation(...) +``` + +Object labels use keyword criteria such as `kind=:plant`, +`species=:oil_palm`, `scale=:Leaf`, and `name=:leaf_1`. + +Implement multiplicity wrappers: + +```julia +One(selector...) +OptionalOne(selector...) +Many(selector...) +``` + +Selectors must normalize to `Diagnostics.ObjectAddress` objects with enough context to be +resolved relative to a consuming object. + +Implement `ModelSpec(...; on=...)` using the same selector system. The target object +set of a model application must never be hidden inside a mapping key or +implicit scale table. + +Definitions: + +- `Self()` means only the current object: the object on which the consuming + model application runs. It is a plant only when that object is the plant. +- `Subtree()` means the current object and its descendants. +- `SelfPlant()` means the nearest containing plant scope. +- `Ancestor(scale=:Plant)` is the generic selector form for `SelfPlant()`. +- `SceneScope()` means the whole model. +- `Scope(name)` means a named scope or object collection. + +Rules: + +- unqualified selectors inside a reusable plant application bundle default to + `within=Self()`; +- model-level selectors default to `within=SceneScope()`; +- `One(...)` errors unless exactly one object resolves per consumer; +- `Many(...)` preserves stable object-id order; +- object-id order replaces incidental traversal order as the semantic default. +- selectors are resolved during compilation or binding refresh, not inside the + inner model loop. + +Acceptance tests: + +- plant allocation on four oil palms reads only leaves under each plant; +- model LAI reads leaves across all plant objects; +- a species-specific model model can read only `species=:oil_palm` leaves; +- a model application target set declared with `ModelSpec(...; on=...)` produces stable + application/object pairs; +- selector errors report available labels and near matches. + +## Phase 3: Unified Value Inputs + +Goal: use `ModelSpec(...; inputs=...)` as the only user-facing value-dependency declaration. +Historical `MultiScaleModel(...)` mappings are migration sources only. + +Target API: + +```julia +ModelSpec(AllocationModel(); on=Many(kind=:plant, scale=:Plant), inputs=(:leaf_carbon => Many(scale=:Leaf, within=Subtree(), var=:leaf_carbon))) + +ModelSpec(LAIModel(area); on=One(scale=:Scene), inputs=(:leaf_areas => Many(kind=:plant, scale=:Leaf, within=SceneScope(), var=:leaf_area))) +``` + +Implement: + +- `ModelSpec(...; inputs=...)` as `ModelSpec` configuration. +- `Input(...)` or an equivalent internal wrapper that lets `dep(model)` + provide default value-input bindings. +- normalized input bindings from target variable to `Diagnostics.ObjectAddress`. +- compiler pass that decides carrier: + direct reference, `RefVector`, temporal stream, or materialization. +- status-default insertion for materialized target variables using the + consumer model's `inputs_` default. +- temporal policies on value inputs: + `HoldLast`, `Interpolate`, `Integrate`, `Aggregate`. +- `Dates.Period` windows on value inputs, for example `window=Day(1)`. +- copy/reference semantics reporting for every compiled input binding. + +Rules: + +- model authors still declare `inputs_`; scenario authors decide where those + inputs come from; +- `dep(model)` may provide defaults for common value-input bindings in + composite-model/object composition; +- scenario-level `ModelSpec(...; inputs=(...))` always wins over `dep(model)` + defaults; +- same-rate local links should keep reference semantics where possible; +- cross-rate links always go through temporal state; +- duplicate source candidates are errors unless the selector disambiguates; +- materialization carriers, when needed, are internal compiler details + and are not user-authored structs; +- same-rate scalar and many-object links should avoid copies when they can use + aliases, shared refs, `RefVector`, or an equivalent typed carrier; +- PlantSimEngine must preserve arbitrary value types, including units, + automatic differentiation numbers, uncertainty wrappers, and other + numeric-like values. + +Carrier expectations: + +| Binding kind | Runtime carrier | +| --- | --- | +| same-rate scalar | shared `Ref` or local alias | +| same-rate many-object | `RefVector` or equivalent typed reference collection | +| cross-rate | temporal stream sample | +| integrate/aggregate | temporal window reduction | +| materialized cross-object input | generated pre-run status assignment | +| environment | cached environment binding sample | + +Acceptance tests: + +- the MAESPA model LAI cross-object input is declared with `ModelSpec(...; inputs=...)` and + produces the same `lai` and `leaf_area`; +- historical plant allocation `MultiScaleModel([:leaf_carbon => [:Leaf => :leaf_carbon]])` + becomes `ModelSpec(...; inputs=...)` and remains plant-local; +- a same-scale rename currently expressed with `SameScale()` works through + `ModelSpec(...; inputs=...)`; +- multi-rate value inputs integrate object streams by object id. +- same-rate many-object bindings do not allocate per timestep in a benchmarked + hot loop beyond unavoidable model work. +- unitful or dual-number status values survive `ModelSpec(...; inputs=...)` without forced + conversion to `Float64`. + +## Phase 4: Unified Model Calls + +Goal: use `ModelSpec(...; calls=...)` as the only user-facing manual model-call declaration. +The same mechanism must also be usable from `dep(model)` so hard-dependency +traits become default call declarations. + +Target API: + +```julia +ModelSpec( + SceneEB(); + on=One(scale=:Scene), + calls=( + :leaf_energy => + Many(kind=:plant, scale=:Leaf, process=:energy_balance), + :soil => One(kind=:soil, application=:soil_water), + ), +) +``` + +Implement: + +- `ModelSpec(...; calls=...)` as `ModelSpec` configuration. +- `Call(...)` or an equivalent internal wrapper that lets `dep(model)` provide + default manual-call dependencies. +- call resolution from `Diagnostics.ObjectAddress` to concrete `ModelCall` handles, or an + equivalent callable runtime object if the final internal type name differs. +- same-status hard dependency calls using the same public API. +- publication semantics: + trial `run_call!(call)` mutates status only; + final `run_call!(call; publish=true)` appends outputs and temporal + streams. +- structured call explanations with parent application id, selected callee + application ids, selected object ids, selector, and publication behavior. + +Rules: + +- calls are manual call-stack dependencies and are not independently + scheduled under the parent; +- `dep(model)` call defaults are model-author defaults, not final wiring; +- scenario-level `ModelSpec(...; calls=(...))` overrides `dep(model)` defaults; +- hard target outputs still participate in dependency graph compilation through + the owning parent when needed; +- call selection must be visible through explanation helpers. + +Acceptance tests: + +- MAESPA model energy balance uses `ModelSpec(...; calls=...)` and still controls iterative + leaf energy calls; +- missing call selectors report `kind`, `scale`, `process`, and available + matches; +- final accepted calls publish exactly once per timestep. +- an iterative model model can run selected leaf and soil calls several times + with `publish=false` and publish only the accepted state. + +Implemented: + +- `run_call!(::CallTarget)` defaults to `publish=false`, matching the + iterative manual-call contract. +- One-shot accepted calls use `publish=true` explicitly. +- An iterative hard-call regression executes two default non-publishing trials + followed by one accepted call and verifies exactly one environment write and + one temporal output sample for the accepted state. +- `Diagnostics.explain_calls(compiled)` reports + `publication_policy=:explicit_accept`, `default_publish=false`, and + `accepted_publish=true` for every compiled call edge. +- `ModelSpec` now retains per-binding provenance for value inputs and manual + calls. Bindings from `dep(model)` are reported as `:model_default`, + scenario-level `ModelSpec(...; inputs=...)` and `ModelSpec(...; calls=...)` are reported as `:model_spec`, + and compiler-created same-object value links are reported as + `:inferred_same_object`. `Diagnostics.explain_bindings`, `Diagnostics.explain_calls`, and + `explain_model_specs` expose these origins for agent-readable diagnostics. +- Zero-match `OptionalOne(...)` dependencies remain compiled and visible. + Optional inputs retain the consumer `inputs_` default with + `carrier_kind=:optional_default`; optional calls expose an empty target set + and `resolved=false` instead of failing compilation. + +## Phase 5: Object Templates, Instances, And Overrides + +Goal: support several plants of the same species with shared default models and +selective per-instance differences. + +Target API: + +```julia +oil_palm = CompositeModelTemplate( + kind=:plant, + species=:oil_palm, + mapping=oil_palm_mapping, +) + +model = CompositeModel( + ObjectInstance(:palm_1, oil_palm; root=node1), + ObjectInstance(:palm_2, oil_palm; root=node2, overrides=( + stomatal_conductance = Tuzet(; g1=3.2), + )), +) +``` + +Implement: + +- template-level model specs and parameters; +- instance-level model/parameter overrides by process; +- object-level overrides for exceptional organs; +- conflict validation when two overrides target the same process/object. +- shared parameter/model storage when template instances do not override + anything, with explicit copy/ownership behavior when they do. + +Rules: + +- templates do not prescribe topology; they attach mappings to whatever object + tree the instance provides; +- default `Self()` selectors resolve inside the current instance; +- model-wide models must opt into wider scope. + +Acceptance tests: + +- four oil palm instances share model objects/parameters when not overridden; +- one palm instance can override one process parameter; +- allocation remains per plant while model LAI sees all leaves. + +MAESPA status: + +- the unified composite-model/object MAESPA path uses `CompositeModelTemplate` and + `ObjectInstance` for species A and B. + +## Phase 5B: Object Lifecycle And Cache Invalidation + +Goal: make growth, pruning, and moving organs update every compiled binding +through one mutation path. + +Implement public lifecycle hooks: + +```julia +register_object!(model, object; parent) +remove_object!(model, object) +reparent_object!(model, object, new_parent) +move_object!(model, object, geometry_or_position) +Advanced.refresh_bindings!(model) +``` + +Implement invalidation for: + +- object selector caches; +- model application target sets; +- `RefVector` or equivalent many-object carriers; +- temporal stream ownership; +- writer validation; +- environment bindings. + +Rules: + +- topology and geometry changes do not silently leave stale carriers; +- object creation should bind the new object to model applications selected by + `ModelSpec(...; on=...)` before the next timestep; +- moving an object should refresh environment bindings without rebuilding + unrelated model bindings unless the move changes object relations or labels. + +Acceptance tests: + +- creating a new leaf adds it to plant-local allocation and model LAI before + the next timestep; +- pruning/removing a leaf removes it from many-object carriers and temporal + stream ownership; +- changing a leaf insertion angle can refresh only the affected environment + binding when topology is unchanged. + +## Phase 6: Environment Binding Cache + +Goal: make environment and microclimate sampling automatic and fast. + +Implement: + +- `EnvironmentBinding` cache: + object id, backend/provider id, cell/layer id, required variables. +- default environment resolver: + global environment data for non-spatial backends; + object position for spatial backends; + parent position fallback; + global fallback or validation error. +- dirty flags and batched refresh: + `mark_environment_binding_dirty!`; + `update_geometry!(...; invalidate_environment=true)`; + automatic dirty marking on object creation, removal, reparenting, and + environment grid rebuild. +- explanation helper: + `Diagnostics.explain_environment_bindings(sim)`. +- minimal geometry accessors or traits: + `position`, `geometry`, and `bounds`. +- backend protocol: + `Advanced.EnvironmentAPI.bind_environment`, opaque handles, committed/transient `sample`, + `commit_environment!`, and `EnvironmentAPI.update_index!`. +- `Environment(...)` overrides for scenario-specific resolver/backend choices. +- `Environment(; sources=(CO2=:Ca,))` for scenario-specific environment source + remapping without changing model kernels. + +Runtime rule: + +```text +object -> cached binding -> backend cell/layer -> current environment values +``` + +Spatial lookup must happen only during binding refresh, not inside every model +call. + +Acceptance tests: + +- global environment data gives the same values to all objects; +- missing global environment variables fail during environment binding refresh when + the backend can enumerate variables; +- `Environment(; sources=...)` remaps backend variables to model-facing + `environment_inputs_` names and is visible in explanations; +- a model running every two hours over hourly global meteorology receives a + windowed weather sample rather than only the current raw row; +- model `environment_hint` reducers/windows are honored, and an + `Environment(; sources=...)` override changes the source without discarding + the reducer; +- all objects targeted by one application reuse one global weather sample per + application/timestep; +- mock grid backend binds leaves to cells once at initialization; +- moving one leaf marks only that leaf binding dirty and refreshes it before + the next timestep; +- model `environment_inputs_` changes update required variables without recomputing + spatial links unless necessary. +- `commit_environment!(context, accepted_state)` commits mutable microclimate + state back to the active backend. + +## Phase 7: Compiler, Scheduler, And Explanation Cleanup + +Goal: make the unified graph the source of truth. + +Implement: + +- one compiler that builds a global dependency graph over object addresses; +- materialization and multiscale reference wiring as internal carriers; +- object/scope dependency scheduling; +- writer validation through the same graph, including `Updates(...)`; +- model application scheduling from `ModelSpec(...; on=...)` target sets; +- multirate scheduling based on `Dates.Period` values in `ModelSpec(...; every=...)` and + input windows; +- typed compiled bindings that avoid selector resolution in timestep hot loops; +- typed homogeneous execution batches that move dynamic dispatch outside the + per-object inner loop while preserving ordered heterogeneous overrides; +- arbitrary value type preservation through status, input carriers, temporal + storage, and environment samples; +- structured explanation: + `Diagnostics.explain_objects`, `Diagnostics.explain_scopes`, `Diagnostics.explain_bindings`, + `Diagnostics.explain_calls`, `Diagnostics.explain_environment_bindings`, `Diagnostics.explain_schedule`, + `Diagnostics.explain_writers`. + +Acceptance tests: + +- old `MultiScaleModel` examples rewritten with `ModelSpec(...; inputs=...)` produce matching + outputs; +- historical cross-object examples rewritten with `ModelSpec(...; inputs=...)` produce + matching outputs; +- MAESPA hard-call example rewritten with `ModelSpec(...; calls=...)` produces matching + outputs; +- explanation helpers include enough concrete object ids, scales, processes, + and variables for an AI agent to repair bad mappings. +- `Diagnostics.explain_bindings(sim)` reports whether each dependency came from inference, + `dep(model)`, or `ModelSpec`, and reports carrier/copy semantics. +- no selector resolution occurs inside the per-object, per-model timestep loop + for static composite models. +- a warmed homogeneous execution batch performs no allocations beyond model, + output-stream, or backend work requested by the application itself; +- multirate simulations use the same object-address graph as same-rate + simulations. + +## Phase 8: Breaking API Removal And Migration Docs + +Goal: remove the old configuration surface once parity is proven. + +Removed: + +- `MultiScaleModel(...)` as public scenario configuration; +- superseded scenario containers and value-transfer authoring; +- superseded manual-dependency selectors. + +Write migration notes: + +- `MultiScaleModel([:x => [:Leaf => :y]])` -> `inputs=(:x => Many(scale=:Leaf, var=:y),)`; +- cross-object value declarations -> consumer `ModelSpec(...; inputs=...)`; +- manual dependency declarations -> `ModelSpec(...; calls=...)`; +- repeated species assemblies -> `CompositeModelTemplate` plus `ObjectInstance`; +- explicit environment wiring -> environment resolver/binding backend. +- `InputBindings(...)` -> source and temporal policy information inside + `ModelSpec(...; inputs=...)`; +- `MeteoBindings(...)` and `MeteoWindow(...)` -> `Environment(...)` and + environment sampling/window policy; +- `ModelSpec(...; output_routing=...)` -> model-application output policy; +- `PreviousTimeStep(...)` -> temporal policy/cycle-breaking marker in the + unified graph; +- `ScopeModel(...)` -> `ModelSpec(...; on=...)` plus selector scope. + +Regression tests must cover all migrated examples before removal. + +Migration documentation progress: + +- Added `docs/src/migration_composite_model.md` with direct translations for + `MultiScaleModel`, repeated object assemblies, + `TimeStepModel`, `InputBindings`, `MeteoBindings`, `ScopeModel`, and + `SameScale`. +- Documentation navigation and the home page now identify the composite-model/object API + as the target for new multiscale and multi-plant work. +- The documentation home page now uses executable composite-model/object examples as the + primary quickstart. It shows `CompositeModel`, `Object`, `ModelSpec`, `on`, + `inputs`, `every`, automatic same-object binding inference, multi-object + `Many(...)` inputs, and manual `ModelSpec(...; calls=...)` syntax. +- The repository README now mirrors the composite-model/object entry point instead of + teaching `ModelMapping` first. It includes smoke-tested `CompositeModel`/`Object` + quickstart code, `ModelSpec(...; inputs=...)` multi-object coupling, conceptual + `ModelSpec(...; calls=...)` syntax, and links to the migration guide. +- Added `docs/src/composite_model/quickstart.md` as the first native + composite-model/object tutorial page and promoted it in the documentation navigation. + The page contains docs-tested examples for one-object model chaining, + inferred same-object bindings, `OutputRequest` retention, multi-object + `ModelSpec(...; inputs=...)`, `RefVector` carrier explanations, and manual `ModelSpec(...; calls=...)` + syntax. +- The repository agent skill teaches the unified public vocabulary. +- The public API page now starts with curated composite-model/object groups for scenario + construction, selectors, coupling, lifecycle, environment, runtime, and + structured explanations. + +Current removal audit: + +- The unreleased intermediate scenario and runtime subsystem has been deleted, + including its carriers, dependency selectors, target helpers, tests, + examples, and documentation. +- Public manual-call control now uses vector-like `CallTargets`, + `run_call!(context, name)`, `call_targets`, and `run_call!(target)`. +- `RunContext` defines Symbol-named `run_call!` and `call_targets` directly. +- The legacy mapping transforms are removed: + `MultiScaleModel`, `SameScale`, `TimeStepModel`, `InputBindings`, + `MeteoBindings`, `MeteoWindow`, and `ScopeModel` are not retained as + compatibility constructors. +- `ModelMapping` is removed. Retained documentation mentions it only as + historical migration context. +- Historical MTG mapping and mapping-level multirate pages were removed from + the active documentation navigation. A future documentation cleanup can + replace + these historical pages with equivalent composite-model/object tutorials rather than + retaining them as migration reference. +- The model execution page has been rewritten as a composite-model/object-first guide. + It now documents compilation, same-rate reference carriers, temporal + `ModelSpec(...; inputs=...)`, manual `ModelSpec(...; calls=...)`, `Updates(...)`, `ModelSpec(...; every=...)`, + environment binding, output retention, lifecycle cache invalidation, and + compatibility translations from the historical mapping runtime. +- The detailed first simulation tutorial now starts from the composite-model/object API + instead of `ModelMapping`. It introduces model kernels, object status, + compiled applications, inferred same-object bindings, model outputs, and a + short compatibility note for historical mapping examples. +- The quick examples page now uses copy-pasteable composite-model/object examples for + Beer light interception, degree-days/LAI/light coupling, biomass growth, and + retained `OutputRequest` exports. `ModelMapping` appears only in the + compatibility note. +- The standard model coupling, model switching, and coupling more complex + models step-by-step tutorials now teach `CompositeModel`, `Object`, `ModelSpec`, + `on`, `every`, inferred soft `ModelSpec(...; inputs=...)`, and manual + `ModelSpec(...; calls=...)` first. Historical `PlantSimEngine.ModelMapping(...)` appears + only in compatibility notes on those pages. +- The home page has been replaced by native composite-model/object examples. The + repository README has also been replaced by native composite-model/object examples, + and a dedicated composite-model/object quickstart is now available in the main + documentation navigation. +- CompositeModel/object tests cover scheduling, temporal policies, binding inference + and overrides, environment contracts and aggregation, output routing and + application-qualified export, and structured explanations. Legacy mapping + regression tests were removed with the old runtime. +- CompositeModel/object tests now include public environment-contract validation parity for + missing environment variables, explicit `Environment(; sources=...)` + remapping, model-author `environment_hint` source defaults, and validation against + an explicit replacement environment object/backend. +- Test code uses the canonical `ModelSpec(...; every=...)` spelling and composite-model/object + modifiers. Legacy transform tests were removed with the old compatibility + constructors. +- The unified MAESPA path is implemented and tested through `on`, + `inputs`, `calls`, `call_targets`, and `run_call!`. + +## Resolved API Decisions + +- `SceneScope`, `Self`, `Subtree`, `SelfPlant`, `Ancestor`, `Scope`, and + `Relation` are the public topology selector names. Object labels use + `kind=`, `species=`, `scale=`, and `name=` keyword criteria. +- `ModelSpec(...; inputs=...)` is the only scenario-level value-binding + construction form. +- `ModelSpec(...; every=...)` is the canonical timestep configuration. +- `Environment(...)` owns provider/resolver/source configuration. Temporal + value windows belong to the consuming `ModelSpec(...; inputs=...)` selector. +- Object templates own reusable model applications and parameters, not plant + topology construction. They consume explicit object trees or MTGs adapted + through `objects_from_mtg`. +- The old multiscale and mapping-transform implementations have been removed. + +## Completion Evidence + +The requirement-by-requirement evidence and final verification commands are +recorded in `composite_model_completion_audit.md`. diff --git a/docs/src/dev/maespa_model_handoff.md b/docs/src/dev/maespa_model_handoff.md new file mode 100644 index 000000000..b04d9edf1 --- /dev/null +++ b/docs/src/dev/maespa_model_handoff.md @@ -0,0 +1,161 @@ +# MAESPA-Style CompositeModel Example Handoff + +The executable acceptance example is `examples/maespa_model_example.jl`, with +focused coverage in `test/test-maespa-model-example.jl`. + +## CompositeModel Shape + +- One `:Scene` object owns canopy microclimate and model-scale fluxes. +- One shared `:Soil` object owns soil water state. +- Species A and B are reusable `CompositeModelTemplate`s mounted as independent + `ObjectInstance`s. +- Each plant instance contains one plant object, one internode object, and its + own leaf objects. +- Species parameters differ while the model application structure is shared. + +Leaf applications use the copied PlantBiophysics subsample models: + +- `Monteith` for `:energy_balance`; +- `Fvcb` for `:photosynthesis`; +- `Tuzet` for `:stomatal_conductance`. + +## Coupling + +The model energy-balance application controls iterative canopy-air, leaf, and +soil calls. `ModelSpec(...; calls=...)` expresses execution ownership only: the scene model +decides when subprocesses run. + +```julia +ModelSpec(scene_model; name=:scene_eb, on=One(scale=:Scene), inputs=(:psi_soil => + One(kind=:soil, scale=:Soil, application=:soil_water, var=:psi_soil),), calls=(:energy_balance => + Many(kind=:plant, scale=:Leaf, process=:energy_balance), + :soil => + One(kind=:soil, scale=:Soil, application=:soil_water),), environment=Environment(provider=:forcing, sink=:canopy), every=Dates.Hour(1)) +``` + +The scene receives above-canopy forcing from the `:forcing` provider and has +`:canopy` as its explicit commit sink. Trial leaf calls use +`run_call!(context, :energy_balance; environment=trial_environment)`, so all hard-called +leaves sample the trial canopy atmosphere through their compiled handles without +committing it. After convergence, the scene commits the accepted canopy +atmosphere with `commit_environment!(context, accepted_environment)` and publishes one +accepted leaf call against that committed environment. + +Scene/soil values are wired declaratively with `ModelSpec(...; inputs=...)`, not by manually +writing another object's status. The soil model receives accepted scene fluxes +through live references: + +```julia +ModelSpec(SoilWater(...); name=:soil_water, on=One(kind=:soil, scale=:Soil), inputs=(:transpiration => + One( + scale=:Scene, + within=SceneScope(), + application=:scene_eb, + var=:scene_transpiration, + ), + :infiltration => + One( + scale=:Scene, + within=SceneScope(), + application=:scene_eb, + var=:scene_infiltration, + ),), every=Dates.Hour(1)) +``` + +This creates a parent-controlled feedback loop: the scene reads mapped +`psi_soil` when it starts its energy-balance solve, computes accepted scene +water fluxes, writes `scene_transpiration` and `scene_infiltration`, then calls +the soil model. The soil call sees those scene values through input carriers +and publishes the updated soil state. If the intended science is an explicit +lag rather than same-step parent control, use `PreviousTimeStep(:psi_soil)` on +the scene input. + +CompositeModel LAI receives live references to every leaf area: + +```julia +ModelSpec(LAIModel(ground_area); name=:lai_dynamic, on=One(scale=:Scene), inputs=(:leaf_areas => Many( + kind=:plant, + scale=:Leaf, + within=SceneScope(), + process=:leaf_state, + var=:leaf_area, + ),), every=Dates.Day(1)) +``` + +The scene energy-balance model uses the same mapping mechanism for leaf-scale +values needed during the hard-call solve. It maps leaf area, leaf carbon, trial +leaf inputs (`Ra_SW_f`, `aPPFD`, `Ψₗ`), and accepted leaf fluxes (`Rn`, `λE`, +`H`, `A`) into scene-level vector inputs. The scene model then writes or reads +those vectors, while the referenced leaf statuses remain the single source of +truth. + +```julia +ModelSpec(scene_model; name=:scene_eb, on=One(scale=:Scene), inputs=(:leaf_areas => Many(kind=:plant, scale=:Leaf, within=SceneScope(), var=:leaf_area), + :leaf_carbon => Many(kind=:plant, scale=:Leaf, within=SceneScope(), var=:leaf_carbon), + :leaf_Ra_SW_f => Many(kind=:plant, scale=:Leaf, within=SceneScope(), var=:Ra_SW_f), + :leaf_aPPFD => Many(kind=:plant, scale=:Leaf, within=SceneScope(), var=:aPPFD), + :Ψₗ => Many(kind=:plant, scale=:Leaf, within=SceneScope(), var=:Ψₗ), + :leaf_rn => Many(kind=:plant, scale=:Leaf, within=SceneScope(), policy=HoldLast(), var=:Rn), + :leaf_lambda_e => Many(kind=:plant, scale=:Leaf, within=SceneScope(), policy=HoldLast(), var=:λE), + :leaf_h => Many(kind=:plant, scale=:Leaf, within=SceneScope(), policy=HoldLast(), var=:H), + :leaf_a => Many(kind=:plant, scale=:Leaf, within=SceneScope(), policy=HoldLast(), var=:A),)) +``` + +`HoldLast()` is intentional for the leaf flux vectors: it asks the compiler for +live references to the current held status values, so the parent scene solve can +iterate hard-call trial states without materializing temporal streams. + +Allocation is plant-local because its leaf selector uses `within=Subtree()`: + +```julia +ModelSpec(allocation; name=:allocation, on=One(scale=:Plant), inputs=(:leaf_carbon => Many(scale=:Leaf, within=Subtree(), var=:leaf_carbon)), every=Dates.Day(1)) +``` + +## Meteorology + +Input meteorology is above-canopy forcing wrapped in a +`MaespaSingleLayerEnvironment`. The backend stores two meteorological states: + +- `forcing`: the above-canopy `Weather`/time series sampled by the scene; +- `canopy`: the mutable canopy `Atmosphere` sampled by every leaf. + +The scene application uses `Environment(provider=:forcing, sink=:canopy)`. +Leaf energy-balance applications use `Environment(provider=:canopy)`. The +one-layer backend does not look at process names, geometry, or cells; all leaves +intentionally sample the same current canopy atmosphere. + +`canopy_air_update(...)` is a plain helper, not a model application. It reads +canopy-scale leaf fluxes aggregated in the scene, computes the MAESPA-style +canopy air update, and returns a new `Atmosphere`. The accepted solution is +committed directly with: + +```julia +commit_environment!(context, accepted_environment) +``` + +CompositeModel status also stores diagnostics for the resulting below-canopy +microclimate: + +- `canopy_tair`; +- `canopy_vpd`; +- `canopy_rh`; +- `canopy_htot`; +- `canopy_gcanop`. + +Trial iterations pass the candidate atmosphere through `run_call!`, preserving +the leaf applications' compiled provider handles. The accepted state is the +only state committed to the mutable environment backend. + +## Acceptance Checks + +The focused test verifies: + +- five leaves across two species and one shared soil object; +- instance membership and mounted application ids; +- model calls to all leaf energy-balance applications and the soil model; +- nested `Monteith -> Fvcb -> Tuzet` call bundles; +- live-reference LAI and plant-local allocation bindings; +- hourly energy balance and daily LAI/allocation schedules; +- exactly one accepted publication per manually called target and timestep; +- finite canopy microclimate, leaf energy, photosynthesis, soil feedback, and + species-specific allocation after a 25-hour run. diff --git a/docs/src/dev/public_api_refinement_completion_audit.md b/docs/src/dev/public_api_refinement_completion_audit.md new file mode 100644 index 000000000..023b63fb8 --- /dev/null +++ b/docs/src/dev/public_api_refinement_completion_audit.md @@ -0,0 +1,43 @@ +# Public API Refinement Completion Audit + +This audit records the supported contract and the evidence used to stabilize it. +It complements the [decision record](public_api_refinement_decisions.md) and the +[public symbol inventory](../API/public_symbols.md). + +## Contract evidence + +| Requirement | Supported contract | Evidence | +|:--|:--|:--| +| Public boundary | Composition, model-author, diagnostic, and extension symbols are exported by default; compiler/cache representations live under `PlantSimEngine.Advanced`. | `test-model-api-stabilization.jl` checks the namespace boundary; Documenter's missing-doc check covers exported docstrings. | +| Application identity | Repeated process applications require explicit names. Inputs, calls, outputs, overrides, and `Updates(...; after=...)` use canonical application IDs. Singular process references are rejected; `Many(process=...)` remains an explicit discovery query. | Stabilization, binding-inference, hard-call, output, override, and update tests cover repeated applications and actionable errors. | +| Selector grammar | `Self()` is one object, `Subtree()` is that object plus descendants, `SelfPlant()` is the containing plant, and `SceneScope()` is the model. `One`, `OptionalOne`, and `Many` share the same criteria across targeting, coupling, lookup, and outputs. | Multi-plant selector tests, instance/template tests, lifecycle tests, and XPalm downstream tests. | +| Outputs | `outputs=:none` is the safe default; `:all` and selector-based `OutputRequest`s are explicit. Request names are unique, application identity is preserved, and removed-object history remains collectable. | Output-boundary, runtime-matrix, multirate, lifecycle-history, and allocation tests. | +| Execution ownership | `run!` starts a fresh simulation; `continue!` and `step!` advance its live handle without resetting time, streams, schedules, or environment position. | Split-run equivalence, multirate-boundary, environment-resume, and lifecycle-continuation tests. | +| Construction and initialization | `CompositeModel(models...; status=...)` lowers to ordinary objects and `ModelSpec`s. `Diagnostics.explain_initialization` reports application, object, origin, defaults, expected/provided types, and remedies without running kernels. | Concise/explicit lowering equivalence and initialization report tests. | +| Diagnostics | Supported explanation functions accept `CompositeModel` directly and compiled views where useful; simulation overloads avoid field inspection. Results are structured vectors that can be filtered with ordinary Julia predicates. | Structured explanation assertions throughout the model test matrix and documentation examples. | +| Lifecycle | Registration, MTG growth, removal, reparenting, movement, and geometry updates are the supported mutation paths. Cycle/self-parent failures are atomic; structural and geometry invalidation remain targeted. | Stabilization, unified integration, environment, and lifecycle-output tests. | +| Model-author API | The kernel is `run!(model, status, environment, constants, context)`. Model parameters come from `model`; `runtime_model`, call-target accessors, traits, and lifecycle helpers are the supported context surface. | `test-model-contract.jl`, hard-call tests, growing-plant tutorial, and downstream model suites. | +| Compatibility | `tracked_outputs`, singular scenario `process=` references, output-request `process=`, and process-only overrides are removed. Mapping runtimes are not restored. | Migration guide plus rejection tests. | + +## Validation matrix + +The release gate is: + +1. complete PlantSimEngine package tests, including allocation gates and doctests; +2. a full Documenter build with missing-doc and executable-example checks; +3. full PlantBiophysics and XPalm downstream suites against this checkout; +4. benchmark smoke tests for native, multirate, PlantBiophysics, and XPalm paths; +5. `git diff --check` and searches for transitional spellings outside explicit + migration/history documentation. + +This matrix covers one/many objects, all selector multiplicities, soft inputs, +hard calls, duplicate writers, temporal policies, global/spatial environments, +templates, instances, overrides, lifecycle mutation, generic values, output +retention modes, fresh/continued execution, and homogeneous hot-loop allocation. + +## Deliberate compatibility boundary + +Compiled structs and cache controls are qualified advanced APIs and may evolve. +Direct mutation of `Object` or `CompositeModel` fields is unsupported. Historical +`ModelMapping`, executor, and status-vector runtimes are outside the compatibility +surface and must not be reintroduced. diff --git a/docs/src/dev/public_api_refinement_decisions.md b/docs/src/dev/public_api_refinement_decisions.md new file mode 100644 index 000000000..fbc768925 --- /dev/null +++ b/docs/src/dev/public_api_refinement_decisions.md @@ -0,0 +1,105 @@ +# Public API refinement decisions + +This decision record defines the target public contract for the CompositeModel/Object +API. The CompositeModel/Object compiler and runtime remain the only supported scenario +runtime. + +## Terminology and identity + +- An **object** is one runtime entity with a stable `ObjectId`. +- A **model** is one scientific implementation of a process. +- A **process** is model metadata and may have several applications. +- An **application** is one named, configured occurrence of a model in a model. +- User declarations that identify a producer, writer, update predecessor, call + target, or output stream use application identity. +- Process queries are discovery filters. They are not substitutes for an + application identifier when more than one application matches. +- Every application receives a deterministic identifier. An explicit + `ModelSpec(...; name=...)` is used verbatim. An unnamed application uses its + process name only when that identifier is unique; repeated unnamed + applications are rejected with instructions to name them. +- Mounted template applications are qualified as + `instance_name__application_name`. + +## Object selectors and scope + +The same `One`, `OptionalOne`, and `Many` selector values are accepted by +application targeting, inputs, calls, object queries, and output requests. + +Scope names have one meaning: + +- `Self()` selects only the current object. +- `Subtree()` selects the current object and all of its descendants. +- `SelfPlant()` selects the current object's plant root and its descendants. +- `Ancestor(...)` selects the matching ancestor's subtree. +- `SceneScope()` searches the whole model. +- `Scope(name)` searches the named object's subtree. +- `Relation(...)` selects objects with the requested topological relationship. + +Selectors that require a current object fail when used without a context. +Cross-object coupling is always visible in the declaration through `Subtree`, +`SelfPlant`, `Ancestor`, `Scope`, `SceneScope`, or `Relation`. + +## Outputs + +`run!` uses an explicit `outputs` keyword: + +```julia +run!(model; outputs=:none) +run!(model; outputs=:all) +run!(model; outputs=request) +run!(model; outputs=requests) +``` + +The default is `outputs=:none`. Temporal dependency streams required by the +runtime are still retained with bounded histories; they are not user-retained +outputs. + +The former `tracked_outputs` keyword has been removed. Use `outputs` directly; +there is no dual spelling. + +An `OutputRequest` contains an object selector, a variable, an optional +application identifier, a unique result name, and optional temporal resampling +policy. `OutputRequest(:Leaf, :x)` remains a convenience spelling that lowers +to `OutputRequest(Many(scale=:Leaf), :x)` during migration. + +## Execution and continuation + +`run!(model; steps=n, ...)` starts a fresh result timeline at step one while +mutating model status. It returns a live `Simulation` execution handle. + +`continue!(simulation; steps=n)` advances that simulation from its current +step, preserving retained streams, temporal dependency history, environment +position, and multirate clock phase. It returns the same simulation. + +`step!(simulation)` is equivalent to `continue!(simulation; steps=1)`. + +Calling `run!` on an already-mutated model intentionally creates a new result +timeline. Users who intend temporal continuation use `continue!`; the distinct +operation prevents an accidental step-index reset. + +Lifecycle mutations between calls to `continue!` are compiled before the next +timestep using the existing targeted invalidation contract. + +## Public namespaces + +The default namespace is organized around: + +- model composition and execution; +- model-author declarations and kernel helpers; +- supported structured explanations; +- documented environment extension interfaces. + +Compiled representation types, cache dirty flags, raw compiler stages, and +low-level invalidation helpers are qualified advanced/internal APIs unless a +documented external extension requires them. Removing an export does not make a +symbol inaccessible through `PlantSimEngine.Symbol`; it removes the accidental +promise that ordinary users should depend on it. + +## Compatibility policy + +- Removed legacy mapping/executor APIs are not restored. +- Superseded CompositeModel/Object spellings are removed rather than retained + as aliases or fallback methods. +- Benchmarks, examples, documentation, PlantBiophysics, and XPalm target the + canonical API. diff --git a/docs/src/dev/release_notes_handoff.md b/docs/src/dev/release_notes_handoff.md new file mode 100644 index 000000000..43eca1ac5 --- /dev/null +++ b/docs/src/dev/release_notes_handoff.md @@ -0,0 +1,513 @@ +# Release Notes Handoff + +This page is the persistent release-note source for the composite-model/object redesign +and cleanup branch. Keep it factual: mark what is implemented, what is removed, +and what is only planned. + +## Implemented Breaking Cleanup + +Source details live in `code_cleanup_audit.md`. + +- Removed `ModelList`, `ModelMapping`, `GraphSimulation`, `MultiScaleModel`, + and the separate mapping dependency/runtime stack. Use `CompositeModel`, `Object`, + and model applications. +- Removed direct and batch mapping `run!` methods. +- Removed string scale names. Use symbols, for example `:Leaf`. +- Removed mapping-specific type-promotion configuration. +- Removed `ModelMapping` completely; it is not retained as a qualified + compatibility API. +- Removed old multiscale output indexing helpers. Convert outputs explicitly + before indexing. +- Replaced mapping-specific same-scale rename sentinels with + `inputs=(:local => One(within=Self(), var=:source),)`. +- Removed unused parallel-executor traits after deleting the executor runtime. +- Removed dead mapping-era wrappers and traits: `UninitializedVar`, + `RefVariable`, `TreeAlike`, and `StatusView`. +- Removed the unreleased `CompositeModelTemplate(...; mapping=...)` alias and dead + selector-to-mapping conversion helpers. +- Removed stale `PlantSimEngine.Examples` exports for the deleted + `ToyInternodeEmergence` example. +- Replaced many source-side validation `@assert`s with explicit errors. +- Added `Updates(:var; after=:application)` for ordered duplicate writers. +- Added `runtime_model(runtime)` as the sanctioned live-model accessor for + `RunContext` and `Simulation`; kernels no longer need to inspect + `context.compiled.model`. +- Added `Diagnostics.explain_initialization(model)` with structured `:required`, + `:defaulted`, `:supplied`, `:generated`, `:producer_bound`, and + `:environment_bound` dispositions. +- Added `CompositeModel(model, models...; status=...)` as a thin one-object constructor + that lowers to the normal object and `ModelSpec` representation. +- Calendar-aligned windows remain unsupported. Temporal windows use + duration-based `Dates.Period` semantics. + +## Removed Unreleased Scenario Prototype + +An experimental scenario runtime was developed and replaced on this branch +before release. Its source, tests, examples, and documentation were removed +rather than retained as compatibility code. + +The removed API included `Domain`, `SimulationMapping`, `Route`, +`AllDomains`, and `HardDomains`, together with the domain scheduler, run loops, +route materialization, environment bridge, graph runner, and output publisher. +Because this API was never released, there is no compatibility layer or user +migration path for it. + +The reusable behavior now lives in the composite-model/object runtime: object selectors, +compiled `ModelSpec(...; inputs=...)`, manual `ModelSpec(...; calls=...)`, `Dates`-based scheduling, +environment backends, dynamic object lifecycle handling, and structured +explanations. + +Dynamic MTG growth now has one public high-level operation: `add_organ!`. +An MTG-backed `CompositeModel` retains the accessors and status initializer used during +initial adaptation. `add_organ!` reuses that policy for new nodes, merges +explicit initial values, attaches the resulting `Status`, registers the model +object, and invalidates runtime bindings. `register_object!` remains available +as the low-level registry operation. XPalm and PlantGeom were migrated away +from package-local wrappers that duplicated this lifecycle sequence. + +## Implemented MAESPA-Style Example Changes + +The current `examples/maespa_model_example.jl` is the main executable example +for multi-plant model coupling. + +- Uses copied PlantBiophysics subsample models: + `Monteith`, `Fvcb`, and `Tuzet`. +- Uses two plant instances with different parameters and shared scale names + such as `:Plant` and `:Leaf`. +- Uses a shared soil model. +- Uses `SceneEB` with `ModelSpec(...; calls=(...))` to manually run leaf + `:energy_balance` and soil `:soil_water` targets. +- Ports MAESPA-style canopy air temperature and VPD update through the + `canopy_air_update(...)` helper and `gbcanms`. +- Treats input meteorology as above-canopy forcing, runs trial leaves with + `run_call!(...; environment=trial_state)`, commits accepted canopy + meteorology with `commit_environment!`, and writes + below-canopy microclimate diagnostics to model status fields: + `canopy_tair`, `canopy_vpd`, `canopy_rh`, `canopy_htot`, and + `canopy_gcanop`. +- Adds `LAIModel` and declares plant leaf-area materialization with + `ModelSpec(...; inputs=(...))`. +- Computes plant allocation daily from plant-local `leaf_carbon` vectors. +- Adds `run_call!` for manually executing compiled model call targets. +- Adds model-level `Input(...)` and `Call(...)` dependency defaults through + `dep(model)`, with scenario-level `ModelSpec(...; inputs=...)` and `ModelSpec(...; calls=...)` overriding + those defaults in `ModelSpec`. +- Adds initial registry-backed model selector resolution with + `resolve_object_ids` and `resolve_objects` for global, self-relative, + plant-relative, ancestor-relative, and named-scope object selections. +- Adds `Diagnostics.explain_scopes(model)` for structured scope diagnostics. It reports + the model scope, object subtree scopes, named `Scope(...)` entries, and + scale/kind/species label groups with concrete object ids. +- Selector failures now include context, matched object ids, requested + criteria, available labels, and near-match suggestions. Misspelled labels + such as `scale=:Leef` therefore suggest `:Leaf` instead of returning only a + cardinality count. +- `Relation(...)` now supports `:self`, `:parent`, `:children`, `:ancestors`, + `:descendants`, and `:siblings` in object-relative input, call, and query + selectors. Relation results are compiled to concrete object ids and may be + constrained by an explicit scope. Application targets reject relations + because they have no current object context. +- Selector labels now have one spelling (`scale=:Leaf`, `kind=:plant`, + `species=:oil_palm`, and `name=:leaf_1`); the duplicate `Scale`, `Kind`, and + `Species` wrappers were removed. `Diagnostics.ObjectAddress` preserves all normalized + object, routing, temporal, and status-ordering fields, while positional + topology selectors such as `Relation(:parent)` remain supported. +- Adds the first compiled composite-model/object view with `Advanced.compile_composite_model`, + `Advanced.CompiledCompositeModel`, `Advanced.CompiledModelApplication`, `Advanced.CompiledModelInputBinding`, + `Advanced.CompiledModelCallBinding`, `Diagnostics.explain_applications`, + `Diagnostics.explain_bindings`, and `Diagnostics.explain_calls`. +- The compiled model view resolves `ModelSpec(...; on=...)`, `ModelSpec(...; inputs=...)`, and + `ModelSpec(...; calls=...)` to object ids ahead of runtime, and reports temporal policy, + window, carrier hints, and callee application ids for agent-readable + diagnostics. +- Unscoped composite-model/object dependency selectors now infer scope from the consumer: + model consumers default to `SceneScope()`, while non-model consumers default + to `Self()`. Cross-scope shared dependencies, such as leaf models reading + soil state, should use `within=SceneScope()` explicitly. +- Adds status-backed compiled input carriers for the composite-model/object view: + scalar shared refs, homogeneous `RefVector`s, and `Advanced.ObjectRefVector` fallback + carriers. `Diagnostics.input_carrier`, `Diagnostics.input_value`, and `Diagnostics.has_reference_carrier` expose + them for tests, diagnostics, and future runtime execution. +- Same-rate model inputs are now wired into consumer `Status` references once + during compilation. Scalar and `Many(...)` inputs remain live references, + missing bound input fields are compiler-generated without inventing + canonical values for `Required(T)`, and repeated non-temporal input + materialization is allocation-free. +- Same-rate `ModelSpec(...; inputs=...)` carriers preserve arbitrary concrete value types. + Regression coverage passes a dual-like `BigFloat` wrapper through a typed + `RefVector`, model arithmetic, source mutation, and output publication + without conversion to `Float64`. +- Same-object variable renaming now uses normal `ModelSpec(...; inputs=...)` syntax instead of + `SameScale()`. Renamed inputs share the producer reference and contribute the + expected producer-to-consumer scheduling edge. +- `Diagnostics.explain_bindings` now reports stable carrier kind and copy/reference + semantics, making reference-wired inputs and materialized temporal values + explicit for users and agents. +- Adds model binding cache helpers: + `Advanced.refresh_bindings!`, `Advanced.bindings_dirty`, `Advanced.compiled_bindings`, and + `Advanced.model_revision`. Object registration, removal, and reparenting invalidate + cached compiled bindings before the next refresh. +- Adds composite-model/object environment binding cache helpers: + `Advanced.refresh_environment_bindings!`, `Advanced.compile_environment_bindings`, + `Advanced.CompiledEnvironmentBinding`, `Advanced.CompiledEnvironmentBindings`, + `Advanced.environment_bindings_dirty`, `Advanced.compiled_environment_bindings`, + `Advanced.environment_revision`, and `Diagnostics.explain_environment_bindings`. +- Adds `geometry`, `position`, and `bounds` accessors for model objects/statuses. + Environment binding refreshes call `EnvironmentAPI.update_index!(backend, changed_entities, removed_object_ids)` before + binding objects to backend cells/layers, so spatial backends can precompute + model-wide lookup structures. +- Spatial environment binding now falls back to the nearest ancestor geometry + for objects without their own geometry. Binding explanations expose the + geometry provenance, and moving an ancestor refreshes only descendants that + inherit its geometry. +- Environment binding refresh can now update changed `environment_inputs_` metadata + without repeating spatial indexing or cell lookup when the + application/object/provider/geometry contract is otherwise unchanged. +- `Environment(; sources=(CO2=:Ca,))` now remaps model-facing environment + variables to backend source variables. CompositeModel environment binding refresh + validates missing source variables for enumerable backends such as + `EnvironmentAPI.GlobalConstant`, and explanations expose both `required_inputs` and + `source_inputs`. +- `validate_environment_inputs(model)` and + `validate_environment_inputs(compiled_scene, environment_or_backend)` now validate + composite-model/object environment contracts directly. Missing-variable diagnostics use + model application ids, and validation honors both scenario + `Environment(; sources=...)` remaps and model-author `environment_hint` defaults. +- Object movement now invalidates environment bindings without rebuilding the + structural object/model binding cache. +- Adds public geometry lifecycle helpers: + `update_geometry!(model, object, geometry; invalidate_environment=true)` and + object-scoped `mark_environment_binding_dirty!(model, object)`. They + currently invalidate the model environment binding cache and leave room for + finer-grained dirty tracking later. +- Adds the first composite-model/object runtime with `run!(model; steps=...)`. + It materializes compiled `ModelSpec(...; inputs=...)` carriers, samples bound environment + inputs, and executes generic model kernels on object `Status` values. +- CompositeModel/object compiler now infers simple same-object value bindings from + `inputs_`/`outputs_` when one producer is unambiguous. `Diagnostics.explain_bindings` + reports each binding origin, including `:model_default`, `:model_spec`, and + `:inferred_same_object`. +- Compiled input bindings now validate `ModelSpec(...; inputs=...)` `process=`/`application=` + filters when they are provided, and `Diagnostics.explain_bindings` reports + `source_application_ids`, `process`, and `application`. +- `Advanced.compile_composite_model` now errors for required `inputs_(model)` variables that are + neither bound through `ModelSpec(...; inputs=...)`/inference nor present on the target object + `Status`. +- `Advanced.compile_composite_model` now prepares model-owned status schemas automatically: + model-targeted objects may omit `Status`, declared outputs and `Default` + inputs are inserted from their initial values, and bound `Required` inputs + are installed through their compiled carriers. External unbound `Required` + inputs still need explicit initialization. +- `Advanced.compile_composite_model` now rejects `ModelSpec(...; inputs=...)` entries whose receiving variable is + not declared by the model's `inputs_`, making binding typos explicit at + compile time. +- `Advanced.compile_composite_model` now validates status-backed non-temporal `ModelSpec(...; inputs=...)` + source availability, so bindings that select existing source objects but no + source `Status` reference fail at compile time instead of becoming no-ops. +- CompositeModel/object runtime now publishes model outputs to model-local temporal + streams and resolves temporal `ModelSpec(...; inputs=...)` with `HoldLast`, `Integrate`, + and `Aggregate` policies before consumer execution. +- CompositeModel temporal `ModelSpec(...; inputs=...)` now use producer `output_policy(...)` traits as + the default when the selector omits `policy=...` and resolves to a unique + source application. Explicit selector policies override the trait. +- CompositeModel applications now infer model-author default environment source remaps + from `environment_hint(...).bindings` when the scenario does not provide explicit + environment bindings. Scenario `Environment(; sources=...)` remains the override. +- CompositeModel/object runtime exposes `run_call!(...; environment=trial_state)` + for non-committing trial meteorology and `commit_environment!` for accepted + mutable environment + commits from model kernels. +- CompositeModel/object root applications now honor `ModelSpec(...; every=...)` values backed by + `Dates.Period` scheduling. `Diagnostics.explain_schedule` reports normalized clocks and + whether an application is root-scheduled or manual-call-only. +- CompositeModel/object root applications now also honor `timespec(...)` model traits + when no explicit `ModelSpec(...; every=...)` is provided. Scenario-level `ModelSpec(...; every=...)` + remains the override. +- CompositeModel/object root applications now validate `timestep_hint(...)` required + bounds for clocks derived from the model base step. Hints remain + compatibility constraints, not scheduling overrides. +- CompositeModel/object execution now uses a stable topological application order + compiled from `ModelSpec(...; inputs=...)` producer edges and `Updates(...)` ordering. + Dependencies on manual-call-only applications are redirected to their parent + caller, same-timestep cycles fail during compilation, and + `Diagnostics.explain_schedule` reports `execution_index`. +- `Advanced.CompiledCompositeModel` now pre-indexes input and call bindings by application and + object id. Runtime input materialization and hard-call lookup no longer scan + all model bindings for every object/model invocation. +- `Advanced.CompiledCompositeModel` now pre-indexes applications by application id, removing + application scans from hard-call target resolution and dictionary rebuilding + from ordered execution setup. +- `Advanced.CompiledEnvironmentBindings` now pre-indexes environment bindings by + application and object id, removing the model-wide binding scan from + environment sampling and output scattering. +- Adds `RunContext` and `CallTarget`; composite-model/object models can use + `run_call!(context, :name)` plus `call_targets(context, :name)` for fine-grained manual `ModelSpec(...; calls=...)` + execution. +- Applications selected by `ModelSpec(...; calls=...)` are skipped by the root + `run!(model)` loop and execute only through explicit `run_call!`, preserving + parent-controlled hard-call execution. +- Adds composite-model/object duplicate-writer validation in `Advanced.compile_composite_model`. A variable + may have only one canonical writer per object unless later writers declare + `Updates(:var; after=...)`, where `after` can match a previous application + id/name or process. +- Adds `Diagnostics.explain_writers(compiled)` to report object-variable writer groups, + duplicate writers, and the `Updates(...)` declarations that validate ordered + updates. +- Adds the first reusable object-template path with `CompositeModelTemplate` and + `ObjectInstance`. Templates bundle reusable `ModelSpec`s and default + `kind`/`species` labels; instances mount them inside a named object subtree. +- `CompositeModel(...)` accepts mounted instances whose roots are either owned objects + or references to separately supplied model objects. +- Template applications are scoped to their instance and receive stable + instance-prefixed application ids. Unmodified instances share the template's + model objects, while instance overrides can replace one application by name + or process when the replacement implements the same process. +- Adds `Override(...)` and `ObjectInstance(...; object_overrides=...)` for + exceptional organs. Overrides are resolved during compilation to concrete + object ids without splitting the logical application or changing its + dependency bindings. +- Template models, template parameter metadata, and replacement models are + retained by reference. The runtime does not copy models or mutate fields to + apply parameter overrides. +- Override validation requires the same process and declared status/environment + variable names. Application explanations report model storage, dispatch + mode, overridden object ids, and replacement model types. +- Adds `Diagnostics.explain_instances(model)` and instance membership in + `Diagnostics.explain_objects(model)`. Instance rows expose roots, current object + membership, mounted applications, overrides, template labels, and + reference-based parameter ownership. +- Objects created below a mounted instance inherit missing template `kind` and + `species` labels. Membership explanations use the current topology rather + than a copied instance object list. +- CompositeModel hard calls now support trial microclimate through + `run_call!(context, name; environment=local_state)`, so hard-called + descendants resample the temporary environment through their normal + environment bindings. +- CompositeModel hard calls now default to `publish=false`. Trial calls mutate target + status without publishing temporal samples or environment writes; accepted + states must use `run_call!(target; publish=true)`. Iterative-call tests verify + that several trials followed by one accepted call publish exactly once. +- `Diagnostics.explain_calls(compiled)` now exposes the manual-call publication contract + through `publication_policy`, `default_publish`, and `accepted_publish` + fields. +- `ModelSpec` now keeps provenance for `ModelSpec(...; inputs=...)` and `ModelSpec(...; calls=...)`. + Declarations coming from `dep(model)` are `:model_default`, scenario-level + declarations and overrides are `:model_spec`, and structured explanations + expose these origins for release-note and migration diagnostics. +- Compiled `OptionalOne(...)` inputs and calls now accept zero matches. + Optional inputs keep their declared model default, optional calls return an + empty target collection, and both remain visible in structured explanations. +- Model kernels read their own parameters from the `model` argument. Hard-call + models and targets are available through focused context APIs such as + `call_targets`, `run_call!`, and `runtime_model`. +- CompositeModel duplicate-writer validation now ignores manual-call-only applications + when validating canonical root writers, so hard-dependency children are not + treated as independent root writers for variables they update inside a parent + call stack. +- Adds `build_maespa_scene(...)` and `run_maespa_example(...)`. + This unified composite-model/object MAESPA path uses `CompositeModelTemplate`, + `ObjectInstance`, `on`, `inputs`, `calls`, and + `every=Dates.Period` with two plant species, one shared soil object, + model LAI, and model energy balance. +- `test/test-maespa-model-example.jl` verifies the unified composite-model/object + MAESPA path. +- `run!(model)` now returns a `Simulation` wrapper containing the mutated + model, compiled object bindings, compiled environment bindings, and + model-local temporal output streams. +- Adds model output inspection helpers: + `outputs(sim::Simulation)`, `collect_outputs(sim)`, and + `Diagnostics.explain_outputs(sim)`. These expose object ids, variables, publishing + application ids, sample counts, time bounds, and value types. +- `run!(model; tracked_outputs=...)` now accepts `OutputRequest` for + composite-model/object runs. Requested outputs are collected from retained typed model + streams after the run, can be read with `collect_outputs(sim)` or + `collect_outputs(sim, :request_name)`, support the standard temporal + policies and `Dates.Period` export clocks, and respect dynamic object + lifetimes by exporting each object only across its own sample interval. This + now prunes retained streams at publisher level: `tracked_outputs=nothing` + keeps all streams, explicit requests keep requested application/variable + streams plus streams required by temporal `ModelSpec(...; inputs=...)`, and + `tracked_outputs=OutputRequest[]` keeps no streams unless temporal + dependencies require them. Dependency-only streams now have bounded + policy-specific histories: latest-only for `HoldLast`, the required window + for `Integrate`/`Aggregate`, and sufficient recent source samples for + `Interpolate`/`PreviousTimeStep`. Requested and default retain-all streams + still preserve complete histories, and export remains post-run rather than + fully online. +- Adds `Diagnostics.explain_output_retention(sim)` for structured diagnostics of retained + model output streams, their reasons, and the compiled retention horizon for + dependency-only streams. +- CompositeModel temporal streams are now keyed by application id, object id, and + variable, so two applications can publish the same variable on the same + object without overwriting each other's stream samples. +- CompositeModel output-export tests now cover requested-output `DataFrame` + materialization, canonical publisher inference without `process=...`, + rejection when only stream-only publishers exist, and ambiguity when an + explicit process matches both a stream-only and a canonical publisher. +- `OutputRequest(...)` now accepts `application=...` for composite-model/object runs. + This disambiguates repeated applications of the same process and permits + explicit export of a named `:stream_only` publisher. +- CompositeModel temporal streams now retain a concrete value type per + application/object/output stream. Type changes fail explicitly, while + generic values such as `BigFloat` remain typed through publication, + interpolation, and integration. +- CompositeModel temporal `ModelSpec(...; inputs=...)` now implement the complete `Interpolate(...)` + policy used by the existing multirate runtime: linear interpolation when + samples bracket the requested time, online linear extrapolation from the + last two samples, and configurable hold behavior. Interpolation modes are + validated during model compilation, and arithmetic preserves generic value + types such as `BigFloat` instead of coercing model values to `Float64`. +- CompositeModel `ModelSpec(...; inputs=...)` accepts + `PreviousTimeStep(:input) => One(...)` or `Many(...)` for explicit lagged + dependencies. These bindings read the previous model timestep, use the + consumer status initialization before history exists, and are excluded from + same-timestep dependency edges so feedback loops can be compiled. +- CompositeModel `output_routing=(var=:stream_only,)` is honored by canonical writer + validation and same-object input inference. Stream-only outputs are excluded + from canonical ownership, but remain available in output streams and explicit + `inputs=(... One(application=:name), ...)` bindings. +- CompositeModel execution now refreshes dirty structural bindings between timesteps. + Objects created, removed, or reparented by a model update application target + sets, input carriers, call targets, writer validation, and scheduling before + the next timestep. +- Geometry-only changes refresh environment bindings at the next timestep + without rebuilding structural bindings. `Simulation` returns the final + compiled structural and environment state, including changes made during the + last timestep. +- Geometry-only environment invalidation is now object-scoped. Moving or + explicitly marking one organ dirty preserves unaffected compiled environment + bindings and rebinds only model applications targeting that object; + structural model changes still trigger a full rebuild. +- Added runtime lifecycle coverage for organ creation, pruning, plant-local + `RefVector` refresh, historical output retention for removed objects, and + movement between mock microclimate cells. +- CompositeModel root execution now uses compiled homogeneous target batches. Models, + statuses, input bindings, and environment bindings are + prebound, so dynamic dispatch happens once per batch instead of once per + object. Heterogeneous object overrides split into ordered concrete batches. +- Adds `Diagnostics.explain_execution_plan(scene_or_simulation)` and a zero-allocation + warmed 128-leaf inner-loop regression gate. +- Manual `ModelSpec(...; calls=...)` handles now use the public + vector-like `run_call!(context, name)` execute-all API, with + `call_targets(context, name)` followed by `run_call!(target)` for fine-grained control. +- Removed the unreleased intermediate authoring and runtime subsystem after + composite-model/object feature parity was established. +- Adds `objects_from_mtg(root; ...)` and `CompositeModel(mtg; ...)` so existing MTG + topology can be adapted once into the unified registry while preserving + node-derived identity, parent relations, labels, geometry, and existing + status objects. +- CompositeModel applications now sample global tabular meteorology at their compiled + `Dates.Period` clock. PlantMeteo reducers and windows from `environment_hint` are + honored; `Environment(; sources=...)` overrides the source while preserving + the reducer. Prepared samplers are shared, and one sampled row is cached per + application/timestep for all selected objects. + +## Downstream and Performance Validation + +The first complete remote XPalm performance artifact passed on 31 July 2026 in +[GitHub Actions run 30617676544](https://github.com/VirtualPlantLab/PlantSimEngine.jl/actions/runs/30617676544). +The Ubuntu 24.04 / Julia 1.12.1 single-threaded job resolved the four +path-developed repositories, then passed all four correctness assertions in +the complete 4,160-step profile. The correctness matrix took 12 minutes +10 seconds; the full job, including resolution and precompilation, took +16 minutes 55 seconds. + +The retained artifact is +`xpalm-full-performance-30617676544-1` (artifact id `8788421206`, 90-day +retention). It contains the resolved `Manifest.toml` and 363 CSV measurement +rows covering all 16 stages. Every output-retention mode reached the same +committed final state: step 4,160, 344 phytomers, LAI +`5.0587602356164405`, and FTSW `0.7991179101191218`. + +The CSV records these exact source revisions: + +- PlantSimEngine: `a715e2bf4407870f7dcae5fedaca7eab00f2a826` +- XPalm: `460d3b5161732a195517d5be9a4bdbb4cfc41846` +- PlantBiophysics: `b733e05032cde9b60e527cc2b33a472281c995fb` +- PlantGeom: `f53e5633da1a56d546c4a4433e6d1cd3a898ecf9` + +On that runner, the minimum complete-cycle measurements were 20.255 seconds +with no retained outputs, 22.492 seconds with the small request, 23.246 seconds +with the reference request, 61.324 seconds with all outputs, and 15.650 seconds +for the historical end-to-end helper. These runner-specific measurements are a +persisted comparison baseline, not a replacement for the faster local +acceptance-machine targets. + +## Compatibility Boundary + +The composite-model/object runtime and its MAESPA acceptance path are implemented. +Historical mapping APIs and the unreleased intermediate prototype were +removed. The design, implementation history, and completion evidence are +documented in: + +- `composite_model_design.md` +- `composite_model_implementation_plan.md` +- `composite_model_completion_audit.md` + +The completed public migration is: + +- replace historical tutorials with native composite-model/object tutorials where + long-term coverage is still valuable; +- model mappings should be described as model applications: + `ModelSpec(model; name=..., on=..., inputs=(...), calls=(...))`; +- `MultiScaleModel(...)` -> `ModelSpec(...; inputs=...)`. +- `dep(model)` remains the model-level trait for default dependency intent: + defaults can become `Input(...)` value bindings or `Call(...)` manual model + calls, and scenario-level `ModelSpec` configuration overrides them. +- model target scales -> `ModelSpec(...; on=...)` object selectors. +- `InputBindings(...)` -> source, policy, and window information on + `ModelSpec(...; inputs=...)`. +- `MeteoBindings(...)` and `MeteoWindow(...)` -> automatic environment + binding plus `Environment(...)` provider/source overrides. +- `ModelSpec(...; output_routing=...)` -> model-application output policy. +- `ScopeModel(...)` -> `ModelSpec(...; on=...)` plus selector scopes. +- `PreviousTimeStep(...)` remains supported as a temporal/cycle-breaking + marker in the unified object-address graph. +- explicit per-model environment wiring -> automatic environment resolver plus + cached environment bindings. + +Historical mapping examples, tests, and runtime files were removed after the +composite-model/object acceptance path reached feature parity. Migration information is +kept in this release-note handoff and the user-facing migration guide. + +## Migration Documentation Added + +- Added `docs/src/migration_composite_model.md` as the user-facing migration guide + from historical mappings to the composite-model/object API. +- Updated documentation navigation, home-page guidance, multiscale warnings, + and the canonical repository agent skill to direct new + scenarios toward `CompositeModel`, `Object`, `on`, `inputs`, `calls`, + `Updates`, `every`, and `Environment`. +- Replaced the documentation home-page quickstart with executable + composite-model/object examples. The page now introduces `CompositeModel`, `Object`, + `ModelSpec`, `on`, `inputs`, `every`, inferred same-object + bindings, multi-object `Many(...)` inputs, and manual `ModelSpec(...; calls=...)` syntax + before linking to the migration guide. +- Replaced the repository README examples with composite-model/object-first examples. + The README now introduces `CompositeModel`, `Object`, model applications, + multi-object `ModelSpec(...; inputs=...)`, and `ModelSpec(...; calls=...)`. +- Added a native composite-model/object quickstart page to the main documentation + navigation. It provides docs-tested examples for one-object model chaining, + inferred bindings, requested output retention, multi-object `ModelSpec(...; inputs=...)`, + reference carrier explanations, and manual `ModelSpec(...; calls=...)` syntax. +- Rewrote the model execution page as the current composite-model/object execution + guide. It now covers compilation, reference carriers, temporal `ModelSpec(...; inputs=...)`, + manual `ModelSpec(...; calls=...)`, `Updates(...)`, `ModelSpec(...; every=...)`, environment binding, + retained outputs, lifecycle invalidation, and migration translations for + historical mapping constructs. +- Rewrote the detailed first simulation tutorial to use the composite-model/object API. + It now introduces `CompositeModel`, `Object`, `ModelSpec`, `on`, `every`, + compiled applications, inferred same-object bindings, model outputs, and a + migration note for historical examples. +- Rewrote the quick examples page to use native composite-model/object snippets for + Beer light interception, degree-days/LAI/light coupling, biomass growth, and + retained `OutputRequest` exports. Historical mapping usage is confined to + migration records. +- Rewrote the standard model coupling, model switching, and coupling more + complex models tutorials around the composite-model/object API. These pages now show + inferred same-object value bindings, switching one `ModelSpec` application, + execution-plan explanations, and `ModelSpec(...; calls=...)` manual-call wiring. +- Removed legacy mapping transforms and their runtime implementations: + `MultiScaleModel`, `SameScale`, `TimeStepModel`, `InputBindings`, + `MeteoBindings`, `MeteoWindow`, and `ScopeModel`. +- Added a curated unified composite-model/object map to the public API page. diff --git a/docs/src/developers.md b/docs/src/developers.md index acaebb76e..d5eec475e 100644 --- a/docs/src/developers.md +++ b/docs/src/developers.md @@ -26,10 +26,6 @@ PlantSimEngine currently has three main local environments: - `docs/` for the Documenter build; - `benchmark/` for benchmark scripts used to compare performance locally. -The graph viewer/editor also has a small frontend workspace in `frontend/`. It -is a Vite/React application that is compiled into `frontend/dist/` and then -embedded by the Julia static viewer and graph editor extension. - ## Running checks locally ### Main test suite @@ -40,8 +36,9 @@ Run the standard test suite from the repository root: julia --project=test test/runtests.jl ``` -Some tests exercise threaded execution, so it is worth running them with more -than one Julia thread when validating parallel behavior. +The current public runtime is sequential. Running with multiple Julia threads +does not enable a parallel Composite model executor; parallel execution remains roadmap +work and requires dedicated correctness tests before it becomes public. ### Documentation @@ -55,85 +52,77 @@ The docs environment includes the extra packages needed for examples and API documentation, such as `Documenter`, `CairoMakie`, `PlantMeteo`, and `MultiScaleTreeGraph`. -### Graph viewer frontend +### Benchmarks -The graph viewer and editor UI lives in `frontend/`. Use Node 22 or newer, then -install the JavaScript dependencies from the repository root with: +Benchmark scripts live in `benchmark/`. They are useful when a change may alter +runtime characteristics, but they are not a substitute for the main test suite +or downstream integration checks. -```bash -cd frontend -npm ci -``` +## CI workflows -For local development, run the Vite server: +The repository currently relies on these GitHub Actions workflows: -```bash -npm run dev -``` +- `CI.yml` for the main test matrix, docs build, and coverage; +- `Integration.yml` for downstream checks against packages that depend on + PlantSimEngine; +- `Benchmarks.yml` for pull-request benchmark runs; +- `register.yml` and `TagBot.yml` for release automation. -This is useful for frontend-only iteration. The Julia package, however, serves -the compiled assets from `frontend/dist/`, so rebuild the bundle before testing -the Julia viewer/editor or before committing frontend changes: +If a change affects public APIs or execution behavior, check both `CI` and +`Integration` before merging. Benchmark results are useful for regressions, but +should be interpreted alongside the test results. -```bash -npm run build -``` +## Graph Viewer Frontend -`frontend/dist/` is intentionally committed because registered Julia packages -need the browser assets without requiring users to run a Node build step. +The static viewer and HTTP editor share the React application under +`frontend/`. PlantSimEngine releases include the production bundle in +`frontend/dist`, because Julia package installations do not run Node or Vite. +The content hash in asset filenames is intentional: it prevents browsers and +documentation hosts from reusing stale JavaScript after a release. -Run the lightweight frontend checks with: +Install the frontend development dependencies from the repository root: -```bash -npm run typecheck -npm test +```sh +cd frontend +npm ci ``` -The end-to-end tests use Playwright and start a real Julia graph editor session. -Install the Chromium browser once, then run the suite: +Run the fast checks while developing: -```bash -npx playwright install --with-deps chromium -npm run test:e2e +```sh +npm run typecheck +npm test ``` -The E2E helper starts Julia with `julia --project=test --startup-file=no`, loads -`PlantSimEngine`, `PlantSimEngine.Examples`, and `HTTP`, then drives the browser -against the local editor URL. If you already have an editor session running and -want Playwright to use it, set `PSE_GRAPH_EDITOR_URL` to the full session URL, -including the `token` query parameter. +Build the production assets after changing TypeScript, CSS, or frontend +dependencies: -After changing the viewer UI, rebuild the docs to verify the static embedded -viewer too: - -```bash -cd .. -julia --project=docs docs/make.jl +```sh +npm run build ``` -The docs build writes `docs/src/www/simple_dependency_graph.html` as an -intermediate generated asset and copies it into `docs/build/`; that source-side -HTML file is ignored by git. +Commit the resulting `frontend/dist` changes together with the source changes. +Do not commit `frontend/node_modules`, Playwright reports, screenshots, videos, +or local test output. -### Benchmarks +The end-to-end suite starts a real Julia `GraphEditor.edit_graph` session and controls it +with Chromium: -Benchmark scripts live in `benchmark/`. They are useful when a change may alter -runtime characteristics, but they are not a substitute for the main test suite -or downstream integration checks. - -## CI workflows - -The repository currently relies on these GitHub Actions workflows: +```sh +npx playwright install chromium +npm run test:e2e +``` -- `CI.yml` for the main test matrix, docs build, and coverage; -- `Integration.yml` for downstream checks against packages that depend on - PlantSimEngine; -- `Benchmarks.yml` for pull-request benchmark runs; -- `register.yml` and `TagBot.yml` for release automation. +Use `npm run test:e2e:ui` for a headed local debugging session. The tests use +stable `data-testid` attributes for commands and confirm mutations through the +Julia `/state` endpoint. Avoid assertions against generated CSS classes or +implementing PlantSimEngine selector semantics in TypeScript. -If a change affects public APIs or execution behavior, check both `CI` and -`Integration` before merging. Benchmark results are useful for regressions, but -should be interpreted alongside the test results. +Core graph DTO and edit tests live in `test/test-model-graph-view.jl`. +HTTP-extension tests live in `test/test-model-graph-editor-extension.jl`. +When changing the graph schema, update those Julia tests, frontend types, unit +tests, Playwright scenarios, and the committed production bundle in the same +change. ## Documentation impact @@ -159,16 +148,6 @@ were editing. ## Implementation notes -### Generated models from status vectors - -Some multiscale helpers turn status vectors into internal runtime models so that -they can be used in mapping-based simulations. The implementation is kept -deliberately data-driven to avoid top-level `eval()` and world-age issues. - -The relevant code lives in `src/mtg/mapping/model_generation_from_status_vectors.jl`. -If you touch that area, preserve the ability to generate the mapping and build a -`GraphSimulation` within the same function scope. - ### Coverage gaps to keep in mind Not every combination of weather structure, status shape, mapping layout, and diff --git a/docs/src/guides/coupling.md b/docs/src/guides/coupling.md new file mode 100644 index 000000000..545121304 --- /dev/null +++ b/docs/src/guides/coupling.md @@ -0,0 +1,90 @@ +# Coupling Models + +Use `inputs` when a model reads a value produced by another application. A +unique same-object producer is inferred; cross-object sources should use an +explicit `One`, `OptionalOne`, or `Many` selector. Inspect the resolved +references with `Diagnostics.explain_bindings`. + +Use `calls` only when a parent algorithm owns child execution or iteration. +Use `run_call!(context, :name)` to execute every resolved target. Pass +`sampled_environment=value` to this bulk path when the caller already has one +model-facing environment for all targets. Use `call_model(context, :name)` to +inspect a singular dependency model without materializing a public target. For +selection, target status access, custom ordering, or distinct environments, +retrieve the vector-like collection with `call_targets(context, :name)` and +execute individual targets. Trial calls use `publish=false`; accepted state is +published once. +Nested calls inherit publication suppression, so a descendant cannot publish +inside an unpublished ancestor trial. `Diagnostics.explain_calls` and `Diagnostics.explain_schedule` +show call-only targets and ordering. + +`Diagnostics.explain_initialization(model)` classifies values as supplied, generated, +producer-bound, defaulted, required, or environment-bound before execution. + +## Value coupling + +A consumer on the same object needs no scenario syntax when exactly one +canonical producer exists. Make cross-object intent explicit: + +```julia +ModelSpec(PlantBalance(); name=:balance, on=Many(scale=:Plant), inputs=(:assimilation => Many( + scale=:Leaf, + within=Subtree(), + application=:photosynthesis, + var=:carbon, + ), + :soil_water => One( + scale=:Soil, + within=SceneScope(), + application=:soil, + var=:water, + ),)) +``` + +`One` is a contract: zero or multiple matches are errors. Use `OptionalOne` +only when absence has a scientific meaning, and `Many` when aggregation is +part of the consumer model. `within=Subtree()` searches descendants of the +current target; `within=SelfPlant()` anchors repeated plant instances; and +`SceneScope()` is deliberately global. + +By default, an input selector also identifies applications that produce the +selected variable, and those producers are scheduled before the consumer. Use +`from_status=true` only when the input deliberately reads the objects' current +`Status` references independently of any producer: + +```julia +ModelSpec( + ReserveConsumer(); + inputs=( + :organ_reserves => Many( + scale=(:Leaf, :Internode), + within=Subtree(), + var=:reserve, + from_status=true, + after=:plant_allocation, + ), + ), +) +``` + +This is a same-step live-reference binding. It cannot be combined with +`process`, `application`, `policy`, or `window`. It does not infer a producer +edge; use `after=:application_id` when the state must be read or mutated after +a particular application. Otherwise, the scenario's application order is +preserved. + +## Manual calls + +```julia +ModelSpec(Optimizer(); name=:optimizer, on=Many(scale=:Plant), calls=(:leaf_energy => Many(scale=:Leaf, within=Subtree()))) +``` + +Inside `Optimizer`, iterate over `call_targets(context, :leaf_energy)`. Run +candidate states with `run_call!(target; publish=false)` and the accepted state +with `publish=true`. A call-only target is excluded from root scheduling, and +an unpublished outer call suppresses publication by every nested descendant. + +After compilation, inspect `Diagnostics.explain_bindings(compiled)` for source identity +and carrier type, `Diagnostics.explain_calls(compiled)` for call-only targets, and +`Diagnostics.explain_schedule(compiled)` for root execution order. These rows are the +supported diagnostic surface; compiled fields are internal. diff --git a/docs/src/guides/data/environment_inputs.md b/docs/src/guides/data/environment_inputs.md new file mode 100644 index 000000000..abd2c9907 --- /dev/null +++ b/docs/src/guides/data/environment_inputs.md @@ -0,0 +1,10 @@ +# Weather And Environment Inputs + +An environment may be a constant named tuple, one tabular row, or regular +multi-row weather. Every row in a timed sequence needs a positive fixed +`duration`; inconsistent base durations and application substeps are rejected. + +Use `Environment(sources=...)` to map model-facing environment names to +provider columns. Values retain compatible user numeric types. Spatial +providers implement the same model-facing contract and refresh bindings after +object movement or geometry changes. diff --git a/docs/src/guides/data/forcing_observations.md b/docs/src/guides/data/forcing_observations.md new file mode 100644 index 000000000..0b1448d5b --- /dev/null +++ b/docs/src/guides/data/forcing_observations.md @@ -0,0 +1,10 @@ +# Forcing Observed Variables + +Supply a constant observed value in object status when it does not vary. For a +time-varying observation, use a small environment-driven source model that +publishes the canonical variable; downstream applications remain unchanged. + +Replace a process for an entire template instance through instance overrides, +or use `Override` for one exceptional object. The replacement must implement +the same process and input/output contract. + diff --git a/docs/src/guides/data/numerical_reliability.md b/docs/src/guides/data/numerical_reliability.md new file mode 100644 index 000000000..6d5a6aec6 --- /dev/null +++ b/docs/src/guides/data/numerical_reliability.md @@ -0,0 +1,11 @@ +# Numerical Reliability + +Use exact assertions for deliberately exact integer/rational scenarios and +`isapprox` for floating-point scientific results. Splitting a computation +across objects may change reduction order without changing the model. + +PlantSimEngine preserves compatible numeric types through parameters, status, +carriers, meteorology, and streams. Avoid forced `Float64` conversion. For long +or ill-conditioned sums, use pairwise or compensated accumulation inside the +scientific model and test its error tolerance explicitly. + diff --git a/docs/src/guides/data/outputs_plotting.md b/docs/src/guides/data/outputs_plotting.md new file mode 100644 index 000000000..309b802a6 --- /dev/null +++ b/docs/src/guides/data/outputs_plotting.md @@ -0,0 +1,58 @@ +# Collecting And Plotting Outputs + +Run a model with `outputs=:all` or an explicit `OutputRequest`, then call +`collect_outputs(sim)` for ordinary analysis. Rows identify application, +object, variable, timestep/time, and value, so repeated processes cannot +overwrite one another. Convert the rows to a `DataFrame`, filter by +application/object/variable, group, and plot. Use `final_state(sim)` when only +the latest values are needed. + +Runs default to `outputs=:none`. Use `outputs=:all` only when complete stream +history is intentional; selected requests are the memory-safe choice for large +composite models. Raw rows have the stable columns `timestep`, `time`, `application_id`, +`object_id`, `variable`, and `value`. Requested/resampled rows additionally +identify `scale` and `process`. A temporal request emits `missing` when its +policy cannot produce a value for a scheduled output time. +`time` is expressed in model base-step coordinates; application clock metadata +is reported by `Diagnostics.explain_schedule(simulation)`. Values retain their concrete +types, so unit-bearing model outputs remain unit-bearing in collected rows. + +`OutputRequest` controls requested retention or resampling. Dependency streams +may also be retained for runtime correctness. Use +`Diagnostics.explain_output_retention(sim)` to see why each stream exists. Removed objects +retain accepted historical rows. + +```@example collect-output +using Dates +using DataFrames +using PlantSimEngine + +PlantSimEngine.@process "docs_output_counter" verbose = false +struct DocsOutputCounter <: AbstractDocs_Output_CounterModel end +PlantSimEngine.inputs_(::DocsOutputCounter) = NamedTuple() +PlantSimEngine.outputs_(::DocsOutputCounter) = (value=0,) +PlantSimEngine.run!(::DocsOutputCounter, status, environment, constants, context) = + (status.value += 1) + +model = CompositeModel(DocsOutputCounter(); environment=(duration=Hour(1),)) +simulation = run!( + model; + steps=3, + outputs=OutputRequest( + One(scale=:Scene), + :value; + name=:counter, + application=:docs_output_counter, + ), +) +rows = collect_outputs(simulation, :counter; sink=nothing) +table = DataFrame(rows) +@assert table.value == [1, 2, 3] +table +``` + +For plotting, filter the table first and map `time` to the horizontal axis and +`value` to the vertical axis. Group by `application_id` and `object_id` before +drawing lines; grouping by variable alone can accidentally connect different +objects. CairoMakie and other plotting packages consume the resulting columns +without any PlantSimEngine-specific adapter. diff --git a/docs/src/guides/extensions/environment_backends.md b/docs/src/guides/extensions/environment_backends.md new file mode 100644 index 000000000..4c157dc09 --- /dev/null +++ b/docs/src/guides/extensions/environment_backends.md @@ -0,0 +1,94 @@ +# Environment Backend Extensions + +This page is for package authors who connect a meteorology, canopy-layer, +voxel, grid, or other spatial provider to PlantSimEngine. Simulation users +normally configure an existing backend with `Environment(...)` and do not need +this protocol. + +## The boundary + +An extension backend subtypes +`PlantSimEngine.EnvironmentAPI.AbstractEnvironmentBackend` and extends +functions in `PlantSimEngine.EnvironmentAPI`. Keep the concrete backend and +handle types in the extension package. They do not belong in PlantSimEngine's +root namespace. + +The required methods are: + +- `base_step_seconds(backend)`: duration of one base step; +- `get_nsteps(backend)`: available number of steps; +- `bind_environment(backend, object, context, config)`: compile one opaque + handle for an application/object pair; +- `sample(backend, handle, variable, time)`: read committed state. + +Implement `environment_variables(backend)` when the variable names can be +enumerated cheaply. PlantSimEngine then validates model environment inputs +while compiling. + +Mutable or structurally indexed backends add only the capabilities they need: + +- `sample(backend, handle, trial_state, variable, time)` for transient trial + states supplied to `run_call!`; +- `commit_environment!(backend, handle, accepted_state, time)` for accepted + state; +- `update_index!(backend, changed_entities, removed_object_ids)` when topology + or geometry changes require a spatial-index refresh. Initial compilation + supplies all entities; later refreshes supply only the structural delta. + +[`ToySpatialEnvironment`](@ref) is the small, tested implementation used by +the user journeys. + +## Compile routing into the handle + +`bind_environment` receives the target `Object`, an +`EnvironmentAPI.EnvironmentContext`, and the payload configured with +`Environment(...)`. Resolve geometry, layer, voxel, provider, and commit sink +there. Return a concrete handle containing everything later sampling and +committing need. + +PlantSimEngine caches that handle. The hot `sample` methods receive it directly, +so they should not search the object registry or repeat spatial routing. +`EnvironmentContext` contains application id, object id, scale, and process; +runtime status is deliberately absent. + +A controller that reads one provider and writes another can encode both routes +in its handle. For example, the scenario may configure +`Environment(provider=:forcing, sink=:canopy)`, while the backend decides what +those names mean. + +## Trial and commit semantics + +Transient sampling and committing are separate backend operations: + +1. a controller passes its typed trial state to + `run_call!(context, name; environment=trial_state, publish=false)`; +2. PlantSimEngine invokes the transient `sample` overload through each target's + already-compiled handle; +3. the controller accepts a state and calls + `commit_environment!(context, accepted_state)`; +4. PlantSimEngine validates the caller's `environment_outputs_` declaration, + then invokes the backend commit through the caller's handle; +5. the controller publishes accepted called-model outputs explicitly with + `publish=true`. + +The model-facing `commit_environment!(context, state)` is root API. The +backend-facing method belongs to `PlantSimEngine.EnvironmentAPI`; extension +packages should qualify it when adding methods. + +## Refresh and diagnostics + +PlantSimEngine calls `update_index!` once per distinct spatial backend before +binding or rebinding affected targets. Geometry changes invalidate the affected +handles; structural changes can also change the set of bound targets. + +Use these public checks instead of reading compiler fields: + +- `validate_environment_inputs(model)` checks declared variables; +- `Diagnostics.explain_environment_bindings(model)` reports each + application/object handle and geometry source; +- `Diagnostics.explain_environment(simulation)` reports the active backend, + variables, step count, and base-step duration. + +Backend tests should cover at least two objects with distinct handles, +committed and transient sampling, rejected undeclared commits, and handle +refresh after movement or geometry changes. diff --git a/docs/src/guides/graph_visualizer_editor.md b/docs/src/guides/graph_visualizer_editor.md new file mode 100644 index 000000000..b3b620da4 --- /dev/null +++ b/docs/src/guides/graph_visualizer_editor.md @@ -0,0 +1,294 @@ +```@meta +CurrentModule = PlantSimEngine +``` + +# Visualize And Edit A CompositeModel + +The CompositeModel graph shows how model applications, objects, and compiled value +bindings fit together before a simulation runs. Use the static visualizer when +you want an inspectable HTML artifact, and the interactive editor when you want +browser actions to update a Julia [`CompositeModel`](@ref). + +## A Small CompositeModel + +This example applies three toy models to one plant object. The compiler infers +the same-object `TT_cu` and `LAI` bindings from the declared input and output +names. + +```@example graph_viewer +using PlantSimEngine +using PlantSimEngine.Examples + +model = CompositeModel( + ToyDegreeDaysCumulModel(), + ToyLAIModel(), + Beer(0.6); + status=(TT=12.0,), + id=:plant, + scale=:Plant, + kind=:plant, +) + +view = GraphEditor.model_graph_view(model) +view.metadata +``` + +The documentation build writes that graph as a self-contained HTML page and +embeds it below. + +```@raw html + + +``` + +The default **Applications** projection groups all concrete executions of one +application into one card. Use **Objects** to inspect topology and **Executions** +to inspect concrete `(application, object)` pairs. Search, diagnostics, +initialization, selectors, parameters, and resolved edge details remain +available in the static viewer. The topology projection includes model, +template, and instance containers; selecting an instance or object subtree scopes the +application and execution projections until the filter is cleared. + +## Write A Static Viewer + +The static visualizer is part of PlantSimEngine core and does not load a web +server: + +```julia +path = GraphEditor.write_model_graph_view("model-graph.html", model) +``` + +The output bundles the graph payload, JavaScript, and CSS in one HTML file. It +can be opened locally or embedded in Documenter documentation. A downstream +package can generate the file from `docs/make.jl` and place it under +`docs/src/assets`: + +```julia +mkpath(joinpath(@__DIR__, "src", "assets")) +GraphEditor.write_model_graph_view( + joinpath(@__DIR__, "src", "assets", "default_scene.html"), + default_scene(), +) +``` + +Then embed it from a Markdown page with an HTML `iframe`. The graph is +read-only, but its projection controls, search, inspector, and diagnostics are +interactive in the browser. + +## Start The Editor + +The mutable editor is an optional package extension activated by HTTP.jl. Add +HTTP once to the environment that will launch the editor: + +```julia +using Pkg +Pkg.add("HTTP") +``` + +Then start a session: + +```julia +using PlantSimEngine +using HTTP + +session = GraphEditor.edit_graph(model) +``` + +The default browser opens automatically. The returned session also prints its +URL and shutdown command. Julia remains authoritative: browser edits are sent +as semantic commands, applied transactionally to a candidate CompositeModel, compiled, +and returned as a fresh graph state. + +Inspect the current result or stop the server with: + +```julia +edited_scene = GraphEditor.current_model(session) +close(session) +``` + +Call `GraphEditor.edit_graph()` without a CompositeModel to start from an empty scenario. Use +`open_browser=false` on remote machines or when a test controls the browser. + +## Templates And Several Plants + +A template is a reusable set of already coupled applications. Mounting the same +template twice creates two instance-local application sets. Unqualified selectors +remain inside their own plant, so a model in `plant_a` does not accidentally read +values from `plant_b`. + +```julia +using Dates + +plant_template = CompositeModelTemplate(( + ModelSpec( + ToyDegreeDaysCumulModel(); + name=:degree_days, + on=Many(scale=:Plant), + every=Hour(1), + ), + ModelSpec( + ToyLAIModel(); + name=:leaf_area, + on=Many(scale=:Plant), + ), +); kind=:plant, species=:oil_palm) + +plant_a = ObjectInstance( + :plant_a, + plant_template; + root=Object(:plant_a; name=:plant_a, scale=:Plant), +) +plant_b = ObjectInstance( + :plant_b, + plant_template; + root=Object(:plant_b; name=:plant_b, scale=:Plant), +) + +model = CompositeModel(plant_a, plant_b) +session = GraphEditor.edit_graph( + model; + templates=(oil_palm=plant_template,), +) +``` + +The **Add instance** wizard can mount a catalog template on an existing unclaimed +root and its descendants, or create a minimal root and mount the template in one +transaction. Preview the claimed subtree and resolved application targets before +committing. Unmounting removes the applications but keeps the object subtree. + +Catalog templates are presets. The first edit to a mounted preset creates a +model-local replacement shared by all instances that currently use it. The original +preset remains available when adding another instance. Template application names +are fixed because they are part of the template contract. + +## Overrides + +Use an override when one plant or organ needs a different parameterization without +changing the shared template: + +```julia +plant_b = ObjectInstance( + :plant_b, + plant_template; + root=Object(:plant_b; name=:plant_b, scale=:Plant), + overrides=( + degree_days=ToyDegreeDaysCumulModel(T_base=12.0), + ), +) +``` + +The editor offers the same operation at instance or object scope. Julia checks that +the replacement implements the same process and variable contract. + +## Environment Catalogs And Routing + +Environment values remain in Julia. Give the editor a named catalog rather than +serializing backends to the browser: + +```julia +session = GraphEditor.edit_graph( + model; + templates=(oil_palm=plant_template,), + environments=( + weather=weather, + canopy=canopy_backend, + ), +) +``` + +The scene environment can be replaced from this catalog. Each application can use +the scene backend or a catalog backend and can configure `provider`, model-facing +input-to-source mappings, `sink`, and backend-specific typed options. The editor +shows `environment_hint(model)` and the effective compiled bindings read-only, then +asks Julia to validate the candidate routing before it is committed. + +Application cadence and temporal windows use `Dates.Second`, `Dates.Minute`, +`Dates.Hour`, or `Dates.Day`. Whole-scene targeting is also explicit: +`SceneScope()` must be selected deliberately. Omitting the scope keeps a template +application local to each mounted instance. + +## What Can Be Edited + +The editor supports: + +- model objects, metadata, status initialization, and parent topology; +- model applications, constructor parameters, target selectors, and cadence; +- explicit value bindings, hard calls, output routing, and update ordering; +- template catalogs, transactional instance mounting, shared template edits, and overrides; +- named scene and application environment backends, providers, sources, and sinks; +- dependency cycles through an explicit `PreviousTimeStep` break action; +- undo, redo, temporary recovery autosaves, and readable Julia CompositeModel scripts. + +Application target and binding dialogs can ask Julia to preview the concrete +objects selected by a declaration. This is important for `Many`, relative +scopes such as `SelfPlant`, and composite models containing several plant instances. + +## Models From Other Packages + +The model browser reflects concrete `AbstractModel` subtypes currently loaded +in Julia. There is no separate registration API. Loading a model package before +starting the editor makes its models available automatically: + +```julia +using PlantSimEngine +using PlantBiophysics +using HTTP + +session = GraphEditor.edit_graph(model) +``` + +The `+` buttons next to ports use exact declared variable names only. For an +input named `LAI`, the editor lists loaded models whose `outputs_` contains +`LAI`. For an output named `LAI`, it lists models whose `inputs_` contains +`LAI`, as well as compatible applications already present in the CompositeModel. This is +a composition aid, not a scientific compatibility inference. + +When the CompositeModel is saved as Julia code, required package imports are emitted for +the model types used by the CompositeModel. + +## Invalid And Cyclic Composite Models + +Simulation compilation remains strict, but graph compilation preserves as much +structure as possible and attaches diagnostics. This lets the editor display +incomplete selectors, missing initialization, ambiguous writers, and cycles. + +Cycle edges are shown in red. The break workflow asks which consumer input +should read its previous accepted timestep value and asks for initial values +when the affected target objects do not already provide one. The action changes +the application input policy for every target selected by that application. + +!!! warning + `PreviousTimeStep` changes model semantics. It disconnects the selected + input from current-step producers during one run step. Use it only when that + lag and its initialization value are scientifically intentional. + +## Saving And Recovery + +The **Save** action writes readable Julia code whose final binding is +`model = CompositeModel(...)`. Once a path is selected, every successful edit rewrites +that file. The editor also keeps a temporary recovery file and lists recent +CompositeModel scripts in **Open**. + +Generated code is best effort for arbitrary Julia values and external runtime +resources. Templates and instances are written inline. Named environment values are +referenced through an `editor_environments` named tuple, and the generated header +lists the keys that must be supplied when reopening the file: + +```julia +session = GraphEditor.edit_graph( + ; + recover_path="model.jl", + environments=(weather=weather, canopy=canopy_backend), +) +``` + +Missing environment keys fail while the file is opened. Review the generated code +and keep important scenario scripts under Git. diff --git a/docs/src/guides/modelers/port_existing_model.md b/docs/src/guides/modelers/port_existing_model.md new file mode 100644 index 000000000..4c6912fa8 --- /dev/null +++ b/docs/src/guides/modelers/port_existing_model.md @@ -0,0 +1,44 @@ +# Port An Existing Model + +Start with a one-step scientific function and separate four concerns: immutable +parameters, object state, environment forcing, and produced values. Keep the +arithmetic generic; a model should not convert compatible values to `Float64`. + +```@example port-existing-model +using Dates +using PlantSimEngine + +PlantSimEngine.@process "docs_lai_growth" verbose = false + +struct DocsLAIGrowth{T} <: AbstractDocs_Lai_GrowthModel + rate::T +end +PlantSimEngine.inputs_(::DocsLAIGrowth) = (lai=Required(Float64),) +PlantSimEngine.outputs_(::DocsLAIGrowth) = (lai_next=0.0,) +PlantSimEngine.environment_inputs_(::DocsLAIGrowth) = (T=0.0,) +function PlantSimEngine.run!(m::DocsLAIGrowth, status, environment, constants, context) + status.lai_next = status.lai + m.rate * environment.T +end + +model = CompositeModel( + DocsLAIGrowth(0.02); + status=(lai=1.0,), + environment=(T=10.0, duration=Day(1)), +) +simulation = run!(model) +@assert final_state(simulation).lai_next == 1.2 +``` + +Test the scientific function first, then the kernel directly with a `Status`, +and finally the same model through a model. These three levels separate a +scientific error from a model-contract error and a scenario-binding error. +`Diagnostics.explain_initialization(model)` should show `lai` as supplied, `T` as +environment-bound, and `lai_next` as generated. + +Use `Default(value)` only when the scientific model really defines a fallback. +Do not translate an old sentinel such as `-Inf` into a default: use +`Required(T)` when the value must come from the scenario. + +The concise constructor lowers to the ordinary CompositeModel compiler; it is not a +separate runtime. Move to explicit `Object` and `ModelSpec` construction only +when the scenario needs multiple objects, selectors, or named applications. diff --git a/docs/src/guides/modelers/stateful_models.md b/docs/src/guides/modelers/stateful_models.md new file mode 100644 index 000000000..cc6b59ffb --- /dev/null +++ b/docs/src/guides/modelers/stateful_models.md @@ -0,0 +1,11 @@ +# State, History, And Repeated Updates + +Object `Status` is current state, not timestep storage. Use +`PreviousTimeStep(:x)` for a one-step lag, or keep a model-owned ring buffer +when the algorithm requires deeper history. Accepted output streams provide +simulation history. + +Several writers to one canonical variable are rejected unless the application +declares `Updates`. Iterative trial execution belongs to `calls`; use +`publish=false` until a state is accepted. + diff --git a/docs/src/guides/multiscale/concepts.md b/docs/src/guides/multiscale/concepts.md new file mode 100644 index 000000000..9d201c6e4 --- /dev/null +++ b/docs/src/guides/multiscale/concepts.md @@ -0,0 +1,32 @@ +# How Multiscale Composite Models Execute + +One application executes once for every object selected by its +`ModelSpec(...; on=...)` selector. State belongs to the object, while topology +and labels belong to the scenario. +`Self()` is the current object, `SelfPlant()` is its plant-instance root, and +`SceneScope()` is model-wide. Cardinality wrappers decide whether zero, one, +or many matches are valid. + +More objects mean more qualified streams. Removing an object stops future +execution but preserves its accepted historical samples. + +Canonical selector patterns are: + +| Relationship | Pattern | +| --- | --- | +| application targets every leaf | `ModelSpec(model; on=Many(scale=:Leaf))` | +| input from this same object | omit `inputs` when the producer is unique | +| input from one ancestor | `One(Ancestor(scale=:Plant))` | +| input from this plant's leaves | `Many(scale=:Leaf, within=SelfPlant())` | +| input from shared soil | `One(scale=:Soil, within=SceneScope())` | +| optional named organ | `OptionalOne(name=:fruit, within=SelfPlant())` | + +`Self()` always means the current target object. It never implicitly means the +model, process, species, or plant. Prefer object IDs and labels for identity, +and use `Scope(name)` only when the model explicitly defines that scope. + +One application produces a separate stream for every selected object and +output variable. Stream keys also include application identity, so repeated +applications of the same process cannot overwrite each other. Use +`Diagnostics.explain_applications`, `Diagnostics.explain_objects`, and `Diagnostics.explain_bindings` to +verify target and source multiplicities before a long run. diff --git a/docs/src/guides/multiscale/from_one_object.md b/docs/src/guides/multiscale/from_one_object.md new file mode 100644 index 000000000..3ebfa4ca1 --- /dev/null +++ b/docs/src/guides/multiscale/from_one_object.md @@ -0,0 +1,10 @@ +# From One Object To A Multiscale CompositeModel + +First run all models on one object with the concise `CompositeModel(models...; +status=...)` constructor. Then move organ-specific applications to leaf +objects and aggregate their outputs on a plant with `Many(..., +within=SelfPlant())` or an instance-local selector. + +Compare collected, application-qualified outputs with `isapprox`. Exact bitwise +identity is not generally a valid requirement after changing reduction order. + diff --git a/docs/src/guides/multiscale/import_mtg.md b/docs/src/guides/multiscale/import_mtg.md new file mode 100644 index 000000000..a5c01cb57 --- /dev/null +++ b/docs/src/guides/multiscale/import_mtg.md @@ -0,0 +1,10 @@ +# Importing An MTG + +`objects_from_mtg(root)` converts MTG topology and labels into ordinary model +objects. `CompositeModel(root; applications=...)` performs the same adaptation and then +uses the normal CompositeModel compiler. The MTG is an input representation, not a +second runtime. + +For growth, prefer `add_organ!`: it creates the MTG node, applies the model's +status policy, attaches status, and registers the corresponding object. + diff --git a/docs/src/guides/multiscale/manual_calls.md b/docs/src/guides/multiscale/manual_calls.md new file mode 100644 index 000000000..341ee54e3 --- /dev/null +++ b/docs/src/guides/multiscale/manual_calls.md @@ -0,0 +1,43 @@ +# Manual Calls Across Objects + +Declare parent-owned execution with +`ModelSpec(model; calls=(:name => One(...),))` or a `Many(...)` selector. In +the kernel, execute every resolved target with `run_call!(context, :name)`. +The returned `CallTargets` collection is always vector-like, including for +`One` and `OptionalOne`. + +Use the narrowest execution path that matches the algorithm: + +- `run_call!(context, :name; sampled_environment=environment)` executes all + targets directly through cached typed batches. Prefer it when the caller has + already sampled one model-facing environment for every target. +- `call_model(context, :name)` returns the concrete model for a call that + resolves to exactly one target. It is useful when dispatch or model + parameters must be inspected before the bulk call. +- `call_targets(context, :name)` followed by `run_call!(target)` supports + object selection, custom ordering, target status inspection, or a different + sampled environment per target. + +`environment=trial_state` has different semantics from +`sampled_environment=value`. The former is a transient backend state that each +target samples through its compiled environment handle. The latter is already +in the model-facing form and is forwarded without sampling. + +A target used only by calls is absent from root scheduling. Trial calls default +to `publish=false`; publish only an accepted execution. + +## Compiled plans and changing objects + +The call declaration is compiled once with the scenario. Its call name, +applications, selector, multiplicity, ordering, and execution batches remain +fixed during the simulation. Ordinary calls therefore do not resolve selectors +or rebuild public target wrappers in their execution loop. + +Objects may still be created, removed, or reparented during growth. At the +structural refresh barrier, PlantSimEngine updates only the affected resolved +target buffers. Later applications in the same timestep see the new targets; +applications that already ran are not repeated. The following ordinary +timestep returns to the cached execution path. + +Explicit target cadence must match the caller. A target without an explicit +cadence inherits the caller's invocation timing. diff --git a/docs/src/guides/multiscale/value_coupling.md b/docs/src/guides/multiscale/value_coupling.md new file mode 100644 index 000000000..9fe7675a7 --- /dev/null +++ b/docs/src/guides/multiscale/value_coupling.md @@ -0,0 +1,10 @@ +# Coupling Values Across Objects + +- `One(...)` requires exactly one source. +- `OptionalOne(...)` accepts zero or one. +- `Many(...)` supplies a stable object-ID ordered carrier. + +Use `var=` to rename a source and `application=` to distinguish repeated +processes. Homogeneous many-source values use a `RefVector`; heterogeneous +values use an object-aware reference carrier. Inspect both through +`Diagnostics.input_carrier`, `Diagnostics.input_value`, and `Diagnostics.explain_bindings`, not internal fields. diff --git a/docs/src/guides/multiscale/visualizing_structure.md b/docs/src/guides/multiscale/visualizing_structure.md new file mode 100644 index 000000000..abb2acf14 --- /dev/null +++ b/docs/src/guides/multiscale/visualizing_structure.md @@ -0,0 +1,6 @@ +# Visualizing Composite model Structure + +Use `Diagnostics.explain_objects`, `Diagnostics.explain_scopes`, and `Diagnostics.explain_instances` to +obtain stable rows for plotting. Draw nodes by object ID and edges from parent +to child; color by scale, species, or instance. Keep simulation visualization +outside model kernels so model code remains independent of topology packages. diff --git a/docs/src/guides/time/advanced_time_environment.md b/docs/src/guides/time/advanced_time_environment.md new file mode 100644 index 000000000..9fd6a2054 --- /dev/null +++ b/docs/src/guides/time/advanced_time_environment.md @@ -0,0 +1,12 @@ +# Advanced Time And Environment Configuration + +Disambiguate a producer with an explicit selector containing `application`, +`var`, and `within`. Put temporal `policy` and `window` on that input. Configure +environment source renaming and reducers with `Environment`; scenario values +override model-level `environment_hint` entries. + +Use `Diagnostics.explain_bindings`, `Diagnostics.explain_environment_bindings`, and +`Diagnostics.explain_schedule` to inspect the final source, reducer, window, cadence, and +clock origin. All periods that require seconds must be fixed `Dates` periods; +`Month(1)` is intentionally rejected. + diff --git a/docs/src/guides/time/hourly_daily_weekly.md b/docs/src/guides/time/hourly_daily_weekly.md new file mode 100644 index 000000000..759377e8d --- /dev/null +++ b/docs/src/guides/time/hourly_daily_weekly.md @@ -0,0 +1,63 @@ +# Hourly, Daily, And Weekly Models + +Use one hourly leaf application, a daily plant application with +`Many(scale=:Leaf, within=Subtree(), policy=Integrate(), window=Day(1))`, and a +weekly application consuming the daily stream. Each application remains a +normal `ModelSpec`; only its `every` value and input policy differ. + +Runtime dependency streams are retained because consumers need them. Output +resampling is independent: create named `OutputRequest`s for hourly, daily, +and weekly analysis, then compare `Diagnostics.explain_schedule` sample counts with rows +from `collect_outputs`. + +The following reduced example checks the important physical contract: two +leaf rates are integrated independently for 24 hourly samples and then summed +on their plant. + +```@example hourly-daily +using Dates +using PlantSimEngine + +PlantSimEngine.@process "docs_hourly_flux" verbose = false +PlantSimEngine.@process "docs_daily_total" verbose = false +struct DocsHourlyFlux <: AbstractDocs_Hourly_FluxModel end +struct DocsDailyTotal <: AbstractDocs_Daily_TotalModel end +PlantSimEngine.inputs_(::DocsHourlyFlux) = (rate=Required(Float64),) +PlantSimEngine.outputs_(::DocsHourlyFlux) = (flux=0.0,) +PlantSimEngine.run!(::DocsHourlyFlux, status, environment, constants, context) = + (status.flux = status.rate) +PlantSimEngine.inputs_(::DocsDailyTotal) = (fluxes=Required(Vector{Float64}),) +PlantSimEngine.outputs_(::DocsDailyTotal) = (total=0.0,) +PlantSimEngine.run!(::DocsDailyTotal, status, environment, constants, context) = + (status.total = sum(status.fluxes)) + +model = CompositeModel( + Object(:plant; scale=:Plant), + Object(:leaf_1; scale=:Leaf, parent=:plant, status=Status(rate=1.0)), + Object(:leaf_2; scale=:Leaf, parent=:plant, status=Status(rate=2.0)); + applications=( + ModelSpec(DocsHourlyFlux(); name=:hourly, on=Many(scale=:Leaf), every=Hour(1)), + ModelSpec( + DocsDailyTotal(); + name=:daily, + on=One(scale=:Plant), + inputs=( + :fluxes => Many( + scale=:Leaf, within=Subtree(), application=:hourly, var=:flux, + policy=Integrate(), window=Day(1), + ), + ), + every=Day(1), + ), + ), + environment=[(duration=Hour(1),) for _ in 1:25], +) +simulation = run!(model; steps=25) +@assert only(object.status.total for object in model_objects(model) + if object.id == ObjectId(:plant)) == 72.0 +``` + +A weekly consumer uses the same pattern with `every=Week(1)` and a +seven-day window over the daily application. Keep `Integrate` for rates; +choose `Aggregate(reducer)` for states or observations whose physical meaning +is a mean, minimum, maximum, or custom statistic. diff --git a/docs/src/guides/time/multirate_concepts.md b/docs/src/guides/time/multirate_concepts.md new file mode 100644 index 000000000..77f0b5807 --- /dev/null +++ b/docs/src/guides/time/multirate_concepts.md @@ -0,0 +1,12 @@ +# Understanding Model Cadence + +`ModelSpec(...; every=Dates.Period)` sets application cadence. Without +`every`, an application uses `timespec(model)` when non-default and otherwise +the environment base step. `timestep_hint` validates a scientifically +acceptable range; it does not silently change cadence. + +Temporal input policies have different physical meanings: `HoldLast` samples +the latest state, `Aggregate` reduces observations, and `Integrate` multiplies +rates by sample durations. `PreviousTimeStep` deliberately breaks a same-step +cycle. Windows are rolling fixed-duration windows. Civil-day or +previous-complete-calendar-period alignment is not a supported public feature. diff --git a/docs/src/index.md b/docs/src/index.md index d276ef42f..9537e521f 100644 --- a/docs/src/index.md +++ b/docs/src/index.md @@ -2,33 +2,6 @@ CurrentModule = PlantSimEngine ``` -```@setup readme -using PlantSimEngine, PlantMeteo, Dates - -# Import the examples defined in the `Examples` sub-module: -using PlantSimEngine.Examples - -# Import the example meteorological data: -meteo_day = read_weather(joinpath(pkgdir(PlantSimEngine), "examples/meteo_day.csv"), duration=Dates.Day) - -# Define the model mapping: -model = ModelMapping( - ToyLAIModel(); - status=(TT_cu=1.0:2000.0,), # Pass the cumulated degree-days as input to the model -) - -out = run!(model) - -# Define the mapping for coupled models: -model2 = ModelMapping( - ToyLAIModel(), - Beer(0.6); - status=(TT_cu=cumsum(meteo_day[:, :TT]),), # Pass the cumulated degree-days as input to `ToyLAIModel`, this could also be done using another model -) -out2 = run!(model2, meteo_day) - -``` - # PlantSimEngine [![Build Status](https://github.com/VirtualPlantLab/PlantSimEngine.jl/actions/workflows/CI.yml/badge.svg?branch=main)](https://github.com/VirtualPlantLab/PlantSimEngine.jl/actions/workflows/CI.yml?query=branch%3Amain) @@ -40,334 +13,280 @@ out2 = run!(model2, meteo_day) ```@contents Pages = ["index.md"] -Depth = 5 +Depth = 4 ``` ## Overview -`PlantSimEngine` is a comprehensive framework for building models of the soil-plant-atmosphere continuum. It includes everything you need to **prototype, evaluate, test, and deploy** plant/crop models at any scale, with a strong emphasis on performance and efficiency, so you can focus on building and refining your models. - -**Why choose PlantSimEngine?** - -- **Simplicity**: Write less code, focus on your model's logic, and let the framework handle the rest. -- **Modularity**: Each model component can be developed, tested, and improved independently. Assemble complex simulations by reusing pre-built, high-quality modules. -- **Standardisation**: Clear, enforceable guidelines ensure that all models adhere to best practices. This built-in consistency means that once you implement a model, it works seamlessly with others in the ecosystem. -- **Optimised Performance**: Don't re-invent the wheel. Delegating low-level tasks to PlantSimEngine guarantees that your model will benefit from every improvement in the framework. Enjoy faster prototyping, robust simulations, and efficient execution using Julia's high-performance capabilities. - -## Unique Features - -### Automatic Model Coupling - -**Seamless Integration:** PlantSimEngine leverages Julia's multiple-dispatch capabilities to automatically compute the dependency graph between models. This allows researchers to effortlessly couple models without writing complex connection code or manually managing dependencies. +`PlantSimEngine` is a Julia framework for building soil-plant-atmosphere +simulations from small process models. A modeler writes reusable kernels with +`inputs_`, `outputs_`, optional dependency traits, and `run!`. A simulation +author then assembles those kernels on objects in a `CompositeModel`. -**Intuitive Multi-Scale Support:** The framework naturally handles models operating at different scales—from organelle to ecosystem—connecting them with minimal effort and maintaining consistency across scales. +The public scenario API has one application-construction form: -Model coupling can be done in Julia scripts or interactively in the graph view (or both): - -```@raw html - +```julia +ModelSpec( + model; + name=:application, + on=Many(scale=:Leaf), + inputs=(...), + calls=(...), + every=Dates.Hour(1), + environment=Environment(...), + output_routing=(...), + updates=Updates(...), +) ``` -### Flexibility with Precision Control - -**Effortless Model Switching:** Researchers can switch between different component models using a simple syntax without rewriting the underlying model code. This enables rapid comparison between different hypotheses and model versions, accelerating the scientific discovery process. - -### Multi-rate Execution - -**Mix model cadences in one simulation:** PlantSimEngine can run models at different timesteps within the same MTG simulation. This makes it possible to combine, for example, hourly leaf processes with daily plant balances and weekly reporting models without writing custom scheduling glue. - -**Explicit bindings between rates:** `TimeStepModel`, `InputBindings`, `MeteoBindings`, `ScopeModel`, and `OutputRequest` let you declare how model inputs, meteorology, and exported outputs should behave when rates differ. - -## Batteries included - -- **Interactive graph editor**: Compose your model by interactively adding sub-models in a graph editor, and let the framework handle the coupling and execution. -- **Automated Management**: Seamlessly handle inputs, outputs, time-steps, objects, and dependency resolution. -- **Iterative Development**: Fast and interactive prototyping of models with built-in constraints to avoid errors and sensible defaults to streamline the model writing process. -- **Control Your Degrees of Freedom**: Fix variables to constant values or force to observations, use simpler models for specific processes to reduce complexity. -- **Multi-Rate Scheduling**: Combine hourly, daily, and coarser models in the same simulation, with explicit policies for input aggregation and meteorological sampling. -- **High-Speed Computations**: Achieve impressive performance with benchmarks showing operations in the 100th of nanoseconds range for complex models (see this [benchmark script](https://github.com/VirtualPlantLab/PlantSimEngine.jl/blob/main/examples/benchmark.jl)). -- **Parallelize and Distribute Computing**: Out-of-the-box support for sequential, multi-threaded, or distributed computations over objects, time-steps, and independent processes, thanks to [Floops.jl](https://juliafolds.github.io/FLoops.jl/stable/). -- **Scale Effortlessly**: Methods for computing over objects, time-steps, and [Multi-Scale Tree Graphs](https://github.com/VEZY/MultiScaleTreeGraph.jl). -- **Compose Freely**: Use any types as inputs, including [Unitful](https://github.com/PainterQubits/Unitful.jl) for unit propagation and [MonteCarloMeasurements.jl](https://github.com/baggepinnen/MonteCarloMeasurements.jl) for measurement error propagation. - -## Performance - -PlantSimEngine delivers impressive performance for plant modeling tasks. On an M1 MacBook Pro: - -- A toy model for leaf area over a year at daily time-scale took only 260 μs (about 688 ns per day) -- The same model coupled to a light interception model took 275 μs (756 ns per day) - -These benchmarks demonstrate performance on par with compiled languages like Fortran or C, far outpacing typical interpreted language implementations. For example, PlantBiophysics.jl, which implements ecophysiological models using PlantSimEngine, has been measured to run up to 38,000 times faster than equivalent implementations in other scientific computing languages. - -## Ask Questions - -If you have any questions or feedback, [open an issue](https://github.com/VirtualPlantLab/PlantSimEngine.jl/issues) or ask on [discourse](https://fspm.discourse.group/c/software/virtual-plant-lab). +### Models And Applications + +A model is a reusable implementation of a process. A model application is one +configured use of that model in a model: it gives the use a name, selects its +target objects, and configures its inputs, calls, timestep, and environment. + +| Concept | Meaning | +|:--|:--| +| Process | The biological or physical operation, such as light interception | +| Model | An implementation of that process, such as `Beer` | +| Application | One configured use of a model in a `CompositeModel` | +| Target | An object on which that application executes | + +One application can target many objects. The same model can also be used in +several named applications with different parameters, selectors, or cadence. +During compilation, PlantSimEngine resolves each application into its concrete +`(application, object)` executions. + +This means the same model can be reused on one object, many leaves, several +plant species, a shared soil object, or a model-scale energy-balance solver +without changing the model implementation. + +## Why PlantSimEngine? + +- **Modular models**: each process model can be developed, tested, calibrated, + and replaced independently. +- **Explicit coupling**: `ModelSpec(...; inputs=...)` declares value + dependencies, while `calls=...` gives iterative parent solvers manual + control over hard model calls. +- **Object-based multiscale composite models**: scales are labels on objects, so a plant + can be described as plants, axes, internodes, leaves, roots, voxels, or any + topology the model requires. +- **Multirate execution**: use `every=Dates.Hour(1)` or + `every=Dates.Day(1)`, with temporal policies such as `Integrate()` or + `HoldLast()` in the same model. +- **Automatic environment binding**: global weather and spatial microclimate + backends are bound through `Environment(...)`, model `environment_inputs_`, and + explicit accepted-state commits with `commit_environment!`. +- **Performance-oriented internals**: selectors and bindings are compiled + before the timestep loop, same-rate inputs use references when possible, and + homogeneous object batches are specialized. +- **Generic values**: status, model parameters, meteorology, and outputs can + carry units, automatic-differentiation values, uncertainty wrappers, or other + compatible Julia types. ## Installation -To install the package, enter the Julia package manager mode by pressing `]` in the REPL, and execute the following command: +To install the package, enter Julia package mode by pressing `]` in the REPL, +then run: ```julia add PlantSimEngine ``` -To use the package, execute this command from the Julia REPL: +Use it from Julia with: ```julia using PlantSimEngine ``` -## Example usage +## Quickstart: One CompositeModel Object -The package is designed to be easy to use, and to help users avoid errors when implementing, coupling and simulating models. +This example runs three existing toy models on one model object: -### Simple example +1. `ToyDegreeDaysCumulModel` computes daily thermal time. +2. `ToyLAIModel` consumes cumulative thermal time and computes LAI. +3. `Beer` consumes LAI and meteorology to compute absorbed PAR. -Here's a simple example of a model that simulates the growth of a plant, using a simple exponential growth model: +The model kernels are unchanged; the model application layer says where they +run. Since no `every` is specified, these applications use the daily +cadence of `meteo_day`. ```@example readme -# ] add PlantSimEngine -using PlantSimEngine - -# Import the examples defined in the `Examples` sub-module +using PlantSimEngine, PlantMeteo, Dates, DataFrames using PlantSimEngine.Examples -# Define the model mapping: -model = ModelMapping( - ToyLAIModel(); - status=(TT_cu=1.0:2000.0,), # Pass the cumulated degree-days as input to the model +meteo_day = read_weather( + joinpath(pkgdir(PlantSimEngine), "examples/meteo_day.csv"); + duration=Dates.Day, ) -out = run!(model) # run the model and extract its outputs - -out[1:3,:] -``` - -> **Note** -> The `ToyLAIModel` is available from the [examples folder](https://github.com/VirtualPlantLab/PlantSimEngine.jl/tree/main/examples), and is a simple exponential growth model. It is used here for the sake of simplicity, but you can use any model you want, as long as it follows `PlantSimEngine` interface. - -Of course you can plot the outputs quite easily: - -```@example readme -# ] add CairoMakie -using CairoMakie - -lines(out[:TT_cu], out[:LAI], color=:green, axis=(ylabel="LAI (m² m⁻²)", xlabel="Cumulated growing degree days since sowing (°C)")) -``` - -### Model coupling - -Model coupling is done automatically by the package, and is based on the dependency graph between the models. To couple models, we just have to add them to the `ModelMapping`. For example, let's couple the `ToyLAIModel` with a model for light interception based on Beer's law: - -```@example readme -# ] add PlantSimEngine, PlantMeteo -using PlantSimEngine, PlantMeteo, Dates - -# Import the examples defined in the `Examples` sub-module -using PlantSimEngine.Examples - -# Import the example meteorological data: -meteo_day = read_weather(joinpath(pkgdir(PlantSimEngine), "examples/meteo_day.csv"), duration=Dates.Day) - -# Define the mapping for coupled models: -model2 = ModelMapping( +model = CompositeModel( + ToyDegreeDaysCumulModel(), ToyLAIModel(), Beer(0.6); - status=(TT_cu=cumsum(meteo_day[:, :TT]),), # Pass the cumulated degree-days as input to `ToyLAIModel`, this could also be done using another model + environment=meteo_day, ) -# Run the simulation: -out2 = run!(model2, meteo_day) -out2[1:3,:] +sim = run!(model; steps=30, outputs=:all) +out = collect_outputs(sim; sink=DataFrame) +first(out, 6) ``` -The `ModelMapping` couples the models by automatically computing the dependency graph of the models. The resulting dependency graph is: +`ToyLAIModel` does not know where `TT_cu` comes from, and `Beer` does not know +where `LAI` comes from. The compiler infers the unambiguous same-object +bindings from each model's declared inputs and outputs: -``` -╭──── Dependency graph ──────────────────────────────────────────╮ -│ ╭──── LAI_Dynamic ─────────────────────────────────────────╮ │ -│ │ ╭──── Main model ────────╮ │ │ -│ │ │ Process: LAI_Dynamic │ │ │ -│ │ │ Model: ToyLAIModel │ │ │ -│ │ │ Dep: nothing │ │ │ -│ │ ╰────────────────────────╯ │ │ -│ │ │ ╭──── Soft-coupled model ─────────╮ │ │ -│ │ │ │ Process: light_interception │ │ │ -│ │ └──│ Model: Beer │ │ │ -│ │ │ Dep: (LAI_Dynamic = (:LAI,),) │ │ │ -│ │ ╰─────────────────────────────────╯ │ │ -│ ╰──────────────────────────────────────────────────────────╯ │ -╰────────────────────────────────────────────────────────────────╯ +```@example readme +select( + DataFrame(Diagnostics.explain_bindings(model)), + :application_id, + :input, + :source_application_ids, + :carrier_kind, + :copy_semantics, +) ``` -We can plot the results by indexing the outputs with the variable name (e.g. `out2[:LAI]`): +The outputs can be plotted like any other tabular result: ```@example readme using CairoMakie +lai = out[out.variable .== :LAI, :value] +appfd = out[out.variable .== :aPPFD, :value] +tt_cu = out[out.variable .== :TT_cu, :value] + fig = Figure(resolution=(800, 600)) ax = Axis(fig[1, 1], ylabel="LAI (m² m⁻²)") -lines!(ax, out2[:TT_cu], out2[:LAI], color=:mediumseagreen) +lines!(ax, tt_cu, lai, color=:mediumseagreen) ax2 = Axis(fig[2, 1], xlabel="Cumulated growing degree days since sowing (°C)", ylabel="aPPFD (mol m⁻² d⁻¹)") -lines!(ax2, out2[:TT_cu], out2[:aPPFD], color=:firebrick1) - +lines!(ax2, tt_cu, appfd, color=:firebrick1) fig ``` -### Multi-scale modeling - -> See the [Multi-scale modeling](#multi-scale-modeling) section for more details. +## Multi-Object Inputs -The package is designed to be easily scalable, and can be used to simulate models at different scales. For example, you can simulate a model at the leaf scale, and then couple it with models at any other scale, *e.g.* internode, plant, soil, scene scales. Here's an example of a simple model that simulates plant growth using sub-models operating at different scales: +Use `ModelSpec(...; inputs=...)` when a model needs values from selected objects. Here the +model-scale LAI model reads live references to all plant surfaces in the model: ```@example readme -mapping = ModelMapping( - :Scene => ToyDegreeDaysCumulModel(), - :Plant => ( - MultiScaleModel( - model=ToyLAIModel(), - mapped_variables=[ - :TT_cu => :Scene, - ], - ), - Beer(0.6), - MultiScaleModel( - model=ToyAssimModel(), - mapped_variables=[:soil_water_content => :Soil], - ), - MultiScaleModel( - model=ToyCAllocationModel(), - mapped_variables=[ - :carbon_demand => [:Leaf, :Internode], - :carbon_allocation => [:Leaf, :Internode] - ], - ), - MultiScaleModel( - model=ToyPlantRmModel(), - mapped_variables=[:Rm_organs => [:Leaf => :Rm, :Internode => :Rm],], - ), - ), - :Internode => ( - MultiScaleModel( - model=ToyCDemandModel(optimal_biomass=10.0, development_duration=200.0), - mapped_variables=[:TT => :Scene,], - ), - MultiScaleModel( - model=ToyInternodeEmergence(TT_emergence=20.0), - mapped_variables=[:TT_cu => :Scene], - ), - ToyMaintenanceRespirationModel(1.5, 0.06, 25.0, 0.6, 0.004), - Status(carbon_biomass=1.0) - ), - :Leaf => ( - MultiScaleModel( - model=ToyCDemandModel(optimal_biomass=10.0, development_duration=200.0), - mapped_variables=[:TT => :Scene,], - ), - ToyMaintenanceRespirationModel(2.1, 0.06, 25.0, 1.0, 0.025), - Status(carbon_biomass=1.0) +plant_scene = CompositeModel( + Object(:scene; scale=:Scene, kind=:scene), + Object(:plant_1; scale=:Plant, kind=:plant, parent=:scene, + status=Status(surface=12.0)), + Object(:plant_2; scale=:Plant, kind=:plant, parent=:scene, + status=Status(surface=8.0)); + applications=( + ModelSpec(ToyLAIfromLeafAreaModel(100.0); name=:scene_lai, on=One(scale=:Scene), inputs=(:plant_surfaces => Many( + scale=:Plant, + within=SceneScope(), + var=:surface, + ),)), ), - :Soil => ( - ToySoilWaterModel(), - ), -); -nothing # hide -``` - -We can import an example plant from the package: - -```@example readme -mtg = import_mtg_example() -``` - -Make a fake meteorological data: - -```@example readme -meteo = Weather( - [ - Atmosphere(T=20.0, Wind=1.0, Rh=0.65, Ri_PAR_f=300.0), - Atmosphere(T=25.0, Wind=0.5, Rh=0.8, Ri_PAR_f=500.0) -] -); -nothing # hide -``` - -And run the simulation: - -```@example readme -out_vars = Dict( - :Scene => (:TT_cu,), - :Plant => (:carbon_allocation, :carbon_assimilation, :soil_water_content, :aPPFD, :TT_cu, :LAI), - :Leaf => (:carbon_demand, :carbon_allocation), - :Internode => (:carbon_demand, :carbon_allocation), - :Soil => (:soil_water_content,), ) -out = run!(mtg, mapping, meteo, tracked_outputs=out_vars, executor=SequentialEx()); -nothing # hide -``` - -We can then extract the outputs and convert them to a `DataFrame` for each scale and sort them: - -```@example readme -using DataFrames -df_outputs = convert_outputs(out, DataFrame) -leaf_df = df_outputs isa AbstractDict ? df_outputs[:Leaf] : df_outputs -sort!(leaf_df, [:timestep, :node]) +plant_sim = run!(plant_scene) +scene_status = final_state(plant_sim, One(scale=:Scene)) +scene_status ``` -An example output of a multiscale simulation is shown in the documentation of PlantBiophysics.jl: - -![Plant growth simulation](www/image.png) +The same `Many(...)` selector would be plant-local if the consumer ran on a +plant and used `within=Subtree()`. This is the same mechanism used for plant +allocation models that sum their own leaves, model models that aggregate all +plants, and microclimate solvers that select objects inside one environment +cell. -### Multi-rate modeling +When a selector reads a value produced by another model application, prefer +`application=...` to identify the concrete producer. A process name describes +the reusable scientific contract; an application name identifies the mounted +producer in this scenario. This matters as soon as several applications +implement the same process or publish the same variable on different objects. -PlantSimEngine also supports multi-rate MTG simulations, where different models run at different cadences inside the same execution. A typical use case is to run leaf-scale processes hourly, aggregate them into daily plant-scale balances, and then export weekly summary series from the same simulation. +## Manual Calls For Iterative Solvers -The dedicated documentation now has three pages: a short introduction to the -core ideas, a fuller step-by-step tutorial, and an advanced configuration page: +Use `ModelSpec(...; calls=...)` when a parent model must directly run another model, for +example a model energy-balance solver that iterates leaf temperatures until +convergence: -- [Introduction to multi-rate execution](./multirate/introduction.md) -- [Step-by-step hourly, daily, weekly simulation](./multirate/multirate_tutorial.md) -- [Advanced multi-rate configuration](./multirate/advanced_configuration.md) - -## State of the field +```julia +ModelSpec(SceneEnergyBalance(); name=:scene_energy, on=One(scale=:Scene), calls=(:leaf_energy => Many( + kind=:plant, + scale=:Leaf, + within=SceneScope(), + application=:energy_balance, + ), + :soil => One( + kind=:soil, + scale=:Soil, + within=SceneScope(), + application=:soil_water, + ),), every=Hour(1)) +``` -PlantSimEngine is a state-of-the-art plant simulation software that offers significant advantages over existing tools such as OpenAlea, STICS, APSIM, or DSSAT. +The same rule applies to manual calls: scenario wiring should select the +concrete callee application with `application=...`. Model authors use process +requirements in `dep(model)` when they declare generic dependencies, because +they cannot know the application names that a user will choose later. + +Inside `run!`, use `run_call!(context, :leaf_energy)` to execute every target and +receive a vector-like collection. Pass `sampled_environment=value` to the same +bulk call when the parent has already sampled one environment for all targets. +Use `call_model(context, :leaf_energy)` when a singular call's concrete model +must guide an iterative algorithm. Reserve `call_targets` and +`run_call!(target; publish=false)` for selection, custom ordering, target status +inspection, or different per-target environments. Publish the accepted state +once, so temporal outputs and mutable environment writes are recorded exactly +once. + +## Where To Go Next + +- [A mental model](journeys/users/mental_model.md) introduces the seven ideas + used throughout the framework without configuration details. +- [Couple models on one object](journeys/users/one_object.md) is the first + executable journey and runs a coupled simulation over many timesteps. +- [Run the coupling on several objects](journeys/users/several_objects.md) + introduces stable object identity and `Many`. +- [Public API](API/API_public.md) lists the composite-model/object constructors, + selectors, lifecycle hooks, and explanation helpers. +- [Model traits](model_traits.md) explains `inputs_`, `outputs_`, `dep`, + `timespec`, `output_policy`, and `environment_inputs_`. +- [Migration guide](migration_composite_model.md) covers upgrades from earlier + PlantSimEngine releases. -The use of Julia programming language in PlantSimEngine allows for: +## Performance -- Quick and easy prototyping compared to compiled languages -- Significantly better performance than typical interpreted languages -- No need for translation into another compiled language +PlantSimEngine keeps model kernels close to regular Julia functions while the +runtime handles dependency scheduling, object selection, temporal aggregation, +and environment sampling. On an M1 MacBook Pro, toy daily simulations run in +hundreds of microseconds, and PlantBiophysics.jl models using PlantSimEngine +have been measured much faster than equivalent implementations in typical +scientific scripting languages. -Julia's features enable PlantSimEngine to provide: +For performance-sensitive composite models, inspect the supported structured +explanations: -- Multiple-dispatch for automatic computation of model dependency graphs -- Type stability for optimized performance -- Seamless compatibility with powerful tools like MultiScaleTreeGraph.jl for multi-scale computations +```julia +Diagnostics.explain_bindings(model) +Diagnostics.explain_schedule(model) +Diagnostics.explain_execution_plan(model) +``` -PlantSimEngine's approach streamlines the process of model development by automatically managing: +These helpers expose resolved objects, carriers, copy/reference semantics, +application clocks, and homogeneous execution batches. -- Model coupling with automated dependency graph computation -- Time-steps and parallelization -- Input and output variables -- Various types of objects used for simulations (vectors, dictionaries, multi-scale tree graphs) +## Ask Questions -## Projects that use PlantSimEngine +If you have questions or feedback, [open an issue](https://github.com/VirtualPlantLab/PlantSimEngine.jl/issues) +or ask on [discourse](https://fspm.discourse.group/c/software/virtual-plant-lab). -Take a look at these projects that use PlantSimEngine: +## Projects That Use PlantSimEngine - [PlantBiophysics.jl](https://github.com/VEZY/PlantBiophysics.jl) - [XPalm](https://github.com/PalmStudio/XPalm.jl) -## Make it yours - -The package is developed so anyone can easily implement plant/crop models, use it freely and as you want thanks to its MIT license. +## Make It Yours -If you develop such tools and it is not on the list yet, please make a PR or contact me so we can add it! 😃 +PlantSimEngine is distributed under the MIT license. If you develop a package +or model suite that uses it and want it listed here, please open a pull request +or contact the maintainers. diff --git a/docs/src/introduction/why_plantsimengine.md b/docs/src/introduction/why_plantsimengine.md index ed8759658..6813f1051 100644 --- a/docs/src/introduction/why_plantsimengine.md +++ b/docs/src/introduction/why_plantsimengine.md @@ -82,7 +82,10 @@ PlantSimEngine's approach to plant modeling represents a paradigm shift in how s - **Automatic Dependency Resolution:** The system automatically determines the relationships between different models and processes, eliminating the need for manual coupling. -- **Seamless Parallelization:** Out-of-the-box support for parallel and distributed computation allows researchers to focus on the science rather than implementation details. +- **Concrete Batched Execution:** The model compiler groups compatible object + targets into concrete execution batches. A public parallel or distributed + executor is not currently provided; parallel execution remains planned work + that requires explicit correctness and independence guarantees. - **Flexible Model Integration:** The ability to easily combine models from different sources and at different scales facilitates more comprehensive and realistic simulations. diff --git a/docs/src/journeys/modelers/basic_model.md b/docs/src/journeys/modelers/basic_model.md new file mode 100644 index 000000000..4e7cce2e7 --- /dev/null +++ b/docs/src/journeys/modelers/basic_model.md @@ -0,0 +1,156 @@ +# Implement A Basic Model + +**New concept:** the complete one-step model contract. This page then proves +that the same kernel composes automatically on one object and runs unchanged +over several objects. + +For the simulation-user view of these scenarios, see +[Couple Models On One Object](@ref) and +[Run The Coupling On Several Objects](@ref). + +## Model 1: declare the complete contract + +`ToyDevelopmentModel` has one generic parameter, one required input, one true +default, one output initial value, and the final five-argument kernel. This is +the complete tested implementation from `examples/ToyModelDeveloper.jl`: + +```julia +struct ToyDevelopmentModel{T} <: AbstractToy_DevelopmentModel + efficiency::T +end + +PlantSimEngine.inputs_(::ToyDevelopmentModel) = ( + TT=Required(Real), + stress=Default(1.0), +) +PlantSimEngine.outputs_(model::ToyDevelopmentModel) = ( + growth=zero(model.efficiency), +) + +function PlantSimEngine.run!( + model::ToyDevelopmentModel, + status, + environment, + constants, + context, +) + status.growth = model.efficiency * status.TT * status.stress + return nothing +end +``` + +`Required(Real)` is a contract, not an initialization value. `Default(1.0)` +means the scientific model genuinely defines unstressed growth as its +fallback. Output values initialize model state and should match the parameter's +numeric type where practical. + +Test the kernel directly before involving a scenario: + +```@example modeler_basic +using Dates, PlantMeteo, PlantSimEngine, DataFrames +using PlantSimEngine.Examples + +development = ToyDevelopmentModel(0.5) +status = Status(TT=8.0, stress=0.75, growth=0.0) +PlantSimEngine.run!( + development, + status, + nothing, + nothing, + nothing, +) +status.growth +``` + +## Model 2: let one object couple it automatically + +`ToyDegreeDaysCumulModel` publishes `TT`; `ToyDevelopmentModel` requires `TT`. +Because both applications target the same object and the producer is unique, +the scenario needs no explicit `inputs` wiring: + +```@example modeler_basic +one_object = CompositeModel( + Object(:leaf; scale=:Leaf); + applications=( + ModelSpec( + ToyDegreeDaysCumulModel(T_base=10.0); + name=:thermal_time, + on=One(scale=:Leaf), + ), + ModelSpec( + development; + name=:development, + on=One(scale=:Leaf), + ), + ), + environment=Atmosphere( + T=18.0, + Wind=1.0, + Rh=0.7, + duration=Day(1), + ), +) + +select( + DataFrame(Diagnostics.explain_bindings(one_object)), + :application_id, + :input, + :origin, + :source_application_ids, + :carrier_kind, +) +``` + +```@example modeler_basic +one_simulation = run!(one_object) +final_state(one_simulation) +``` + +PlantSimEngine creates `stress=1.0` from the model default and connects `TT` +through a shared `Ref`. The development kernel knows neither fact. + +## Model 3: reuse the kernel over several objects + +Change only application multiplicity from `One` to `Many`: + +```@example modeler_basic +several_objects = CompositeModel( + Object(:leaf_1; scale=:Leaf), + Object(:leaf_2; scale=:Leaf); + applications=( + ModelSpec( + ToyDegreeDaysCumulModel(T_base=10.0); + name=:thermal_time, + on=Many(scale=:Leaf), + ), + ModelSpec( + development; + name=:development, + on=Many(scale=:Leaf), + ), + ), + environment=Atmosphere( + T=18.0, + Wind=1.0, + Rh=0.7, + duration=Day(1), + ), +) + +final_state(run!(several_objects), Many(scale=:Leaf)) +``` + +Do not loop over objects inside `ToyDevelopmentModel.run!`. PlantSimEngine +compiles homogeneous execution targets and invokes the one-target kernel for +each selected object. + +## Model-author recap + +- **You implemented:** parameters, `Required`/`Default` inputs, output initial + state, and one-target arithmetic. +- **PlantSimEngine inferred:** default initialization, same-object coupling, + execution order, and repeated targets. +- **The scenario author keeps explicit:** objects, application names, + multiplicity, and environment data. +- **New API names:** `AbstractModel`, `inputs_`, `outputs_`, `Required`, + `Default`, and `run!`. diff --git a/docs/src/journeys/modelers/cross_object_values.md b/docs/src/journeys/modelers/cross_object_values.md new file mode 100644 index 000000000..4c3c764ff --- /dev/null +++ b/docs/src/journeys/modelers/cross_object_values.md @@ -0,0 +1,158 @@ +# Implement Cross-Object Values + +**New concept:** scalar and vector-like inputs use the same one-step kernel +contract. Object selection and topology remain scenario concerns. + +See [Build One Multiscale Plant](@ref) for the simulation-user construction +journey. + +The plain Julia block below is an excerpt from a shipped example whose +declarations and compositions are tested in `test/test-toy_models.jl`. + +## Model 4: consume one scalar from another object + +`ToyDevelopmentModel` already declares `stress=Default(1.0)`. A scenario may +replace that fallback with one live scalar from a soil object: + +```@example modeler_cross_object +using Dates, PlantMeteo, PlantSimEngine, DataFrames +using PlantSimEngine.Examples + +cross_object = CompositeModel( + Object(:soil; scale=:Soil, status=Status(stress=0.4)), + Object(:leaf; scale=:Leaf, status=Status(TT=10.0)); + applications=( + ModelSpec( + ToyDevelopmentModel(0.5); + name=:development, + on=One(scale=:Leaf), + inputs=( + :stress => One( + scale=:Soil, + within=SceneScope(), + var=:stress, + from_status=true, + ), + ), + ), + ), +) + +cross_simulation = run!(cross_object) +( + leaf=final_state(cross_simulation, :leaf), + binding=only(Diagnostics.explain_bindings(cross_object)), +) +``` + +The model kernel still reads only `status.stress`. It does not search for soil, +know object ids, or copy the scalar each step. The scenario's `One` selector +resolves a shared `Ref`. + +## Model 5: consume a vector-like multiscale value + +`ToyMaintenanceRespirationModel` runs once per leaf and publishes `Rm`. +`ToyPlantRmModel` declares one vector-like input and reduces it: + +```julia +PlantSimEngine.inputs_(::ToyPlantRmModel) = ( + Rm_organs=Required(AbstractVector{<:Real}), +) +PlantSimEngine.outputs_(::ToyPlantRmModel) = (Rm=-Inf,) + +function PlantSimEngine.run!( + model::ToyPlantRmModel, + status, + environment, + constants, + context, +) + status.Rm = sum(status.Rm_organs) + return nothing +end +``` + +The scenario decides that `Rm_organs` means all descendant leaf outputs: + +```@example modeler_cross_object +respiration = ToyMaintenanceRespirationModel( + 2.0, + 0.06, + 25.0, + 0.5, + 0.02, +) + +multiscale = CompositeModel( + Object(:plant; scale=:Plant), + Object( + :leaf_1; + scale=:Leaf, + parent=:plant, + status=Status(carbon_biomass=10.0), + ), + Object( + :leaf_2; + scale=:Leaf, + parent=:plant, + status=Status(carbon_biomass=20.0), + ); + applications=( + ModelSpec( + respiration; + name=:maintenance, + on=Many(scale=:Leaf), + ), + ModelSpec( + ToyPlantRmModel(); + name=:plant_maintenance, + on=One(scale=:Plant), + inputs=( + :Rm_organs => Many( + scale=:Leaf, + within=Subtree(), + application=:maintenance, + var=:Rm, + ), + ), + ), + ), + environment=Atmosphere( + T=25.0, + Wind=1.0, + Rh=0.7, + duration=Hour(1), + ), +) + +multiscale_simulation = run!(multiscale) +( + plant=final_state(multiscale_simulation, :plant), + leaves=final_state(multiscale_simulation, Many(scale=:Leaf)), +) +``` + +```@example modeler_cross_object +select( + DataFrame(Diagnostics.explain_bindings(multiscale)), + :application_id, + :input, + :source_ids, + :carrier_kind, + :copy_semantics, +) +``` + +The `Many` carrier is a live `RefVector`; the aggregation kernel operates on an +`AbstractVector` and stays independent of object count and identity. + +## Model-author recap + +- **You implemented:** scalar or vector-compatible input schemas and ordinary + one-step arithmetic. +- **PlantSimEngine inferred:** shared `Ref` and `RefVector` carriers plus + producer-before-consumer order. +- **The scenario author keeps explicit:** cross-object scope, multiplicity, + source application, and variable remapping. +- **New API names:** `One`, `Many`, `SceneScope`, `Subtree`, `from_status`, + `RefVector`, and `input_carrier`. diff --git a/docs/src/journeys/modelers/environment_and_cadence.md b/docs/src/journeys/modelers/environment_and_cadence.md new file mode 100644 index 000000000..043fdbe88 --- /dev/null +++ b/docs/src/journeys/modelers/environment_and_cadence.md @@ -0,0 +1,152 @@ +# Implement Environment And Cadence Traits + +**New concept:** model-authored runtime traits. Environment declarations name +the fields a kernel samples, while cadence and output-policy traits state when +the same kernel runs and how its values cross clocks. + +Simulation users configure providers in [Understand Environments](@ref) and +application clocks in [Give Models Different Cadences](@ref). + +## Model 6: declare sampled environment inputs + +`ToyMaintenanceRespirationModel` reads object state and sampled temperature. +The tested contract names that environment field explicitly: + +```julia +PlantSimEngine.inputs_(::ToyMaintenanceRespirationModel) = ( + carbon_biomass=Required(Real), +) +PlantSimEngine.environment_inputs_( + model::ToyMaintenanceRespirationModel, +) = (T=zero(model.T_ref),) +PlantSimEngine.outputs_(model::ToyMaintenanceRespirationModel) = ( + Rm=oftype(model.Rm_base, -Inf), +) +``` + +The kernel reads model parameters from `model`, object state from `status`, and +forcing from `environment`: + +```julia +function PlantSimEngine.run!( + model::ToyMaintenanceRespirationModel, + status, + environment, + constants, + context, +) + status.Rm = + status.carbon_biomass * + model.P_alive * + model.nitrogen_content * + model.Rm_base * + model.Q10^((environment.T - model.T_ref) / 10) + return nothing +end +``` + +```@example modeler_environment_time +using Dates, PlantMeteo, PlantSimEngine, DataFrames +using PlantSimEngine.Examples + +respiration = ToyMaintenanceRespirationModel( + 2.0, + 0.06, + 25.0, + 0.5, + 0.02, +) +model = CompositeModel( + Object( + :leaf; + scale=:Leaf, + status=Status(carbon_biomass=10.0), + ); + applications=( + ModelSpec( + respiration; + name=:maintenance, + on=One(scale=:Leaf), + ), + ), + environment=Atmosphere( + T=25.0, + Wind=1.0, + Rh=0.7, + duration=Hour(1), + ), +) + +( + declared=PlantSimEngine.environment_inputs_(respiration), + final=final_state(run!(model)), +) +``` + +The model does not name a provider or inspect raw weather storage. +`Environment(...)` remains scenario configuration. + +## Model 7: declare cadence and output semantics + +`ToyDailyDevelopmentModel` accumulates one increment whenever it runs. Its +model-level traits say “every 24 simulation steps, starting at step 1” and +“consumers may hold the last daily value between publications”: + +```julia +PlantSimEngine.timespec(::Type{<:ToyDailyDevelopmentModel}) = + ClockSpec(24.0, 1.0) +PlantSimEngine.output_policy( + ::Type{<:ToyDailyDevelopmentModel}, +) = (daily_growth=HoldLast(),) +``` + +`ClockSpec` is expressed in simulation steps. Use +`ModelSpec(...; every=Day(1))` when a scenario should express a +duration-relative cadence or override the model default. + +```@example modeler_environment_time +daily = ToyDailyDevelopmentModel(2.0) +daily_model = CompositeModel( + Object(:plant; scale=:Plant); + applications=( + ModelSpec( + daily; + name=:daily_development, + on=One(scale=:Plant), + ), + ), + environment=[ + (duration=Hour(1),) + for _ in 1:25 + ], +) + +daily_simulation = + run!(daily_model; steps=25, outputs=:all) +( + traits=( + clock=PlantSimEngine.timespec(daily), + outputs=PlantSimEngine.output_policy(daily), + ), + schedule=DataFrame(Diagnostics.explain_schedule(daily_model)), + final=final_state(daily_simulation), + retained=DataFrame( + Diagnostics.explain_outputs(daily_simulation), + ), +) +``` + +The model runs at steps 1 and 25. A downstream application can override +`HoldLast` with an explicit selector policy when its scientific interpretation +requires `Integrate`, `Aggregate`, or `Interpolate`. + +## Model-author recap + +- **You implemented:** declared environment reads, a model default clock, and + per-output temporal meaning. +- **PlantSimEngine inferred:** environment validation/sampling, execution + steps, and the default cross-clock policy. +- **The scenario author keeps explicit:** concrete environment provider, + simulation base step, cadence overrides, and input-policy overrides. +- **New API names:** `environment_inputs_`, `timespec`, `ClockSpec`, + `output_policy`, and `HoldLast`. diff --git a/docs/src/journeys/modelers/hard_dependencies.md b/docs/src/journeys/modelers/hard_dependencies.md new file mode 100644 index 000000000..203d11126 --- /dev/null +++ b/docs/src/journeys/modelers/hard_dependencies.md @@ -0,0 +1,167 @@ +# Implement A Hard Dependency + +**New concept:** a process-level hard dependency, used only when the parent +kernel must control another model's execution. Value dependencies should stay +in `inputs_`. + +Simulation users wire and inspect advanced calls in +[Control Advanced Execution](@ref). + +The plain Julia blocks below are excerpts from the shipped, tested +`ToySelectiveCallControllerModel`. + +## Model 8: declare and execute the call + +`ToySelectiveCallControllerModel` declares a reusable default by process, +scale, and relative scope. It cannot know future application names: + +```julia +PlantSimEngine.dep(::ToySelectiveCallControllerModel) = ( + readers=Call(Many( + scale=:Leaf, + process=:toy_environment_reader, + within=Subtree(), + )), +) +``` + +Inside `run!`, the controller inspects the vector-like collection, restricts +the declared call by object id, runs trials without publication, and publishes +one accepted execution: + +```julia +targets = call_targets(context, :readers) +selected = only(call_targets( + context, + :readers; + objects=(ObjectId(model.selected_object),), +)) + +for temperature in model.trial_temperatures + run_call!( + selected; + sampled_environment=(T=temperature,), + publish=false, + ) +end +run_call!( + selected; + sampled_environment=(T=model.accepted_temperature,), + publish=true, +) +``` + +The source excerpt is exercised by the example-model contract suite. Build a +scenario without a `calls` keyword to use that model default: + +```@example modeler_hard_dependency +using PlantSimEngine, DataFrames +using PlantSimEngine.Examples + +environment = ToySpatialEnvironment( + Dict( + :sun => (T=26.0,), + :shade => (T=18.0,), + ); + step_seconds=3600.0, +) +model = CompositeModel( + Object(:plant; scale=:Plant), + Object( + :sun_leaf; + scale=:Leaf, + parent=:plant, + geometry=(cell=:sun,), + ), + Object( + :shade_leaf; + scale=:Leaf, + parent=:plant, + geometry=(cell=:shade,), + ); + applications=( + ModelSpec( + ToyEnvironmentReaderModel(); + name=:reader, + on=Many(scale=:Leaf), + environment=Environment(backend=environment), + ), + ModelSpec( + ToySelectiveCallControllerModel( + (28.0, 31.0), + 22.0; + selected_object=:sun_leaf, + ); + name=:controller, + on=One(scale=:Plant), + ), + ), +) + +DataFrame(Diagnostics.explain_calls(model)) +``` + +```@example modeler_hard_dependency +simulation = run!(model; outputs=:all) +( + controller=final_state(simulation, :plant), + leaves=final_state(simulation, Many(scale=:Leaf)), + publications=filter( + row -> row.application_id == :reader, + DataFrame(Diagnostics.explain_outputs(simulation)), + ), +) +``` + +`origin=:model_default` identifies the `dep(model)` contract. A concrete +scenario can replace it with `ModelSpec(...; calls=...)` when application +identity or target selection differs. + +## Keep the common path bulk and concrete + +The selective example above intentionally materializes one public target +because it chooses an object and gives each trial its own sampled value. If the +algorithm executes every resolved target with the same already-sampled +environment, use the bulk path instead: + +```julia +run_call!( + context, + :readers; + sampled_environment=environment, + publish=false, +) +``` + +This executes the compiler's cached typed batches directly. It avoids creating +or indexing `CallTarget` wrappers inside a timestep loop. + +Some iterative algorithms must inspect a singular dependency model before +executing it. Keep that dispatch concrete with `call_model`, then execute the +same declared call in bulk: + +```julia +reader_model = call_model(context, :reader) +trial = prepare_trial(reader_model, status, environment) +run_call!(context, :reader; sampled_environment=trial, publish=false) +``` + +`call_model` requires exactly one resolved target. Use `call_targets` when the +algorithm also needs target status, object selection, a custom order, or +several distinct sampled environments. + +The dependency definition is immutable after compilation, while its selected +objects are not. Growth, removal, and reparenting refresh the affected target +buffers once at the lifecycle barrier; normal timesteps continue through the +same compiled plan. + +## Model-author recap + +- **You implemented:** a process-level `Call` requirement and explicit + execution inside the parent kernel. +- **PlantSimEngine inferred:** call-only scheduling, resolved targets, nested + context, and publication boundaries. +- **The scenario author keeps explicit:** application overrides and any + architecture-specific target choice. +- **New API names:** `dep`, `Call`, `call_model`, `call_targets`, + `CallTargets`, `run_call!`, `sampled_environment`, and `publish`. diff --git a/docs/src/journeys/modelers/mutable_environment.md b/docs/src/journeys/modelers/mutable_environment.md new file mode 100644 index 000000000..1034f3c19 --- /dev/null +++ b/docs/src/journeys/modelers/mutable_environment.md @@ -0,0 +1,125 @@ +# Implement A Mutable Environment Controller + +**New concept:** accepted mutable environment state. A controller declares +which variables it may commit, evaluates typed trial states, and commits one +accepted state explicitly. + +Simulation users first encounter this workflow in +[Modify The Environment](@ref). Backend packages implement the separate +[Environment Backend Extensions](@ref) contract. + +The plain Julia blocks below are excerpts from the shipped, tested +`ToyEnvironmentControllerModel`. + +## Model 9: declare commit permission + +`ToyEnvironmentControllerModel` declares its reader hard dependency and the +environment variable it may commit: + +```julia +PlantSimEngine.dep(::ToyEnvironmentControllerModel) = ( + reader=Call(One(process=:toy_environment_reader)), +) +PlantSimEngine.environment_outputs_( + model::ToyEnvironmentControllerModel, +) = (T=zero(model.accepted_temperature),) +``` + +Its tested kernel keeps trial, commit, and accepted publication separate: + +```julia +trial_environment = (T=model.trial_temperature,) +trial_target = only(run_call!( + context, + :reader; + environment=trial_environment, + publish=false, +)) + +accepted_environment = (T=model.accepted_temperature,) +commit_environment!(context, accepted_environment) +accepted_target = only(run_call!( + context, + :reader; + environment=accepted_environment, + publish=true, +)) +``` + +`environment_outputs_` is commit permission, not object-status output. +PlantSimEngine validates that the accepted state provides every declared +variable before invoking the backend through the controller's compiled handle. + +## Compose the controller + +The reader needs only a provider. The controller additionally receives +`sink=:cells`; the backend defines what that sink means: + +```@example modeler_mutable_environment +using PlantSimEngine, DataFrames +using PlantSimEngine.Examples + +environment = ToySpatialEnvironment( + Dict(:canopy => (T=20.0,)); + step_seconds=3600.0, +) +model = CompositeModel( + Object( + :leaf; + scale=:Leaf, + geometry=(cell=:canopy,), + ); + applications=( + ModelSpec( + ToyEnvironmentReaderModel(); + name=:reader, + on=One(scale=:Leaf), + environment=Environment(backend=environment), + ), + ModelSpec( + ToyEnvironmentControllerModel(30.0, 22.0); + name=:controller, + on=One(scale=:Leaf), + environment=Environment( + backend=environment, + sink=:cells, + ), + ), + ), +) + +( + call=DataFrame(Diagnostics.explain_calls(model)), + environment=DataFrame( + Diagnostics.explain_environment_bindings(model), + ), +) +``` + +```@example modeler_mutable_environment +simulation = run!(model; outputs=:all) +( + final=final_state(simulation), + committed=environment.cells[:canopy], + publications=filter( + row -> row.application_id == :reader, + DataFrame(Diagnostics.explain_outputs(simulation)), + ), +) +``` + +The rejected `T=30` trial mutates only the reader's trial status. The accepted +`T=22` state is committed once and produces the reader's only retained sample. +If the controller itself runs as an unpublished ancestor call, PlantSimEngine +also suppresses its descendant publications and environment writes. + +## Model-author recap + +- **You implemented:** declared commit variables, typed trial construction, + acceptance logic, explicit commit, and one accepted publication. +- **PlantSimEngine inferred:** permission validation, backend/handle routing, + nested trial suppression, and retained output history. +- **The scenario author keeps explicit:** provider, commit sink, concrete + backend, and any hard-call override. +- **New API names:** `environment_outputs_`, `commit_environment!`, + `Environment`, `environment`, and `publish`. diff --git a/docs/src/journeys/users/advanced_execution.md b/docs/src/journeys/users/advanced_execution.md new file mode 100644 index 000000000..b7db5eea3 --- /dev/null +++ b/docs/src/journeys/users/advanced_execution.md @@ -0,0 +1,219 @@ +# Control Advanced Execution + +## New concept: parent-controlled execution and explicit publication + +Most coupling should remain a value dependency through `inputs`. Use a hard +call only when a parent algorithm must decide whether, when, or how often +another model runs—for example, while iterating toward an accepted leaf +temperature. + +## Declare parent-controlled targets + +Start with one plant and two leaves. The reader application is selected by the +controller's `calls` declaration, so it is call-only rather than independently +scheduled: + +```@example journey_advanced_execution +using PlantSimEngine, DataFrames +using PlantSimEngine.Examples + +environment = ToySpatialEnvironment( + Dict( + :sun => (T=26.0,), + :shade => (T=18.0,), + ); + step_seconds=3600.0, +) + +model = CompositeModel( + Object(:plant; scale=:Plant, kind=:plant), + Object( + :sun_leaf; + scale=:Leaf, + kind=:leaf, + parent=:plant, + geometry=(cell=:sun,), + ), + Object( + :shade_leaf; + scale=:Leaf, + kind=:leaf, + parent=:plant, + geometry=(cell=:shade,), + ); + applications=( + ModelSpec( + ToyEnvironmentReaderModel(); + name=:reader, + on=Many(scale=:Leaf), + environment=Environment(backend=environment), + ), + ModelSpec( + ToySelectiveCallControllerModel( + (28.0, 31.0), + 22.0; + selected_object=:sun_leaf, + ); + name=:controller, + on=One(scale=:Plant), + calls=( + :readers => Many( + scale=:Leaf, + within=Subtree(), + application=:reader, + ), + ), + ), + ), +) + +select( + DataFrame(Diagnostics.explain_calls(model)), + :application_id, + :call, + :callee_application_ids, + :callee_object_ids, + :publication_policy, +) +``` + +`run_call!(context, :readers)` executes every resolved target and returns a +vector-like `CallTargets` collection. `One` still returns a collection of one; +`OptionalOne` returns zero or one; `Many` returns zero or more. + +## Inspect, select, iterate, then publish once + +`ToySelectiveCallControllerModel` needs different treatment per target, so its +kernel first calls `call_targets(context, :readers)` without executing +anything. It records the total, restricts the same declared call to +`:sun_leaf`, runs two temperature trials, and accepts one result: + +```@example journey_advanced_execution +function run_selected_trials!( + target, + trial_temperatures, + accepted_temperature, +) + for temperature in trial_temperatures + run_call!( + target; + sampled_environment=(T=temperature,), + publish=false, + ) + end + run_call!( + target; + sampled_environment=(T=accepted_temperature,), + publish=true, + ) +end +``` + +`publish=false` is the default. Trials may update the called model's current +status for convergence checks, but they neither append output samples nor +commit mutable environment state. Publish exactly the accepted execution. + +```@example journey_advanced_execution +simulation = run!(model; outputs=:all) +( + controller=final_state(simulation, :plant), + leaves=final_state(simulation, Many(scale=:Leaf)), +) +``` + +The controller resolved two targets but selected only `:sun_leaf`. Object +selection uses `call_targets(context, name; objects=(ObjectId(:sun_leaf),))`; +it does not depend on iteration order. Two trials +left no history; its accepted call published once, while `:shade_leaf` was +never executed: + +```@example journey_advanced_execution +filter( + row -> row.application_id == :reader, + DataFrame(Diagnostics.explain_outputs(simulation)), +) +``` + +Use `run_call!(context, name; environment=trial_state)` when every target +should sample the same provider-aware trial state through its own compiled +handle. If the caller has already sampled the model-facing environment, use +`run_call!(context, name; sampled_environment=value)` to execute all targets +through cached typed batches. Use `call_targets` and +`run_call!(target; sampled_environment=...)` only for selection, custom order, +status inspection, or distinct already-sampled environments. For one target, +`call_model(context, name)` provides allocation-free access to its concrete +model when an algorithm must dispatch on model type or read its parameters. + +## Order intentional duplicate writers + +One canonical variable normally has one writer. Two applications that both +claim `stock` therefore fail compilation unless their relationship is +intentional and ordered. `Updates` makes that ownership explicit: + +```@example journey_advanced_execution +writer_model = CompositeModel( + Object(:reserve; scale=:Organ); + applications=( + ModelSpec( + ToyStockWriterModel(4); + name=:initial_stock, + on=One(scale=:Organ), + ), + ModelSpec( + ToyStockWriterModel(8); + name=:adjusted_stock, + on=One(scale=:Organ), + updates=Updates(:stock; after=:initial_stock), + ), + ModelSpec( + ToyStockWriterModel(99); + name=:alternative_stock, + on=One(scale=:Organ), + output_routing=(stock=:stream_only,), + ), + ), +) + +select( + DataFrame(Diagnostics.explain_writers(writer_model)), + :object_id, + :variable, + :application_ids, + :update_application_ids, + :update_after, +) +``` + +`initial_stock` owns the first canonical write and `adjusted_stock` explicitly +updates it afterward. The alternative value is useful as a retained comparison +but must not replace canonical status, so `output_routing` marks it +`:stream_only`. + +```@example journey_advanced_execution +writer_simulation = run!(writer_model; outputs=:all) +( + canonical_stock=final_state(writer_simulation).stock, + published=collect_outputs( + writer_simulation, + :reserve, + :stock; + sink=nothing, + ), +) +``` + +The canonical result is `8`; the three application-specific streams retain +`4`, `8`, and `99`. A stream-only output is not a fallback writer and is not +selected by an application-free `OutputRequest`; request its application +explicitly when retaining only selected outputs. + +## Page recap + +- **You added:** one declared hard call, selective trials, one accepted + publication, explicit update ordering, and one stream-only alternative. +- **PlantSimEngine inferred:** the call-only schedule, concrete targets, + canonical writer ownership, and update edge. +- **You keep explicit:** when each target runs, `publish`, per-target forcing, + intentional duplicate writers, and non-canonical streams. +- **New API names:** `calls`, `call_targets`, `run_call!`, `CallTargets`, + `Updates`, `output_routing`, and `:stream_only`. diff --git a/docs/src/journeys/users/cadences.md b/docs/src/journeys/users/cadences.md new file mode 100644 index 000000000..b5d0184fa --- /dev/null +++ b/docs/src/journeys/users/cadences.md @@ -0,0 +1,203 @@ +# Give Models Different Cadences + +## New concept: application clocks and temporal input policies + +Running a whole composite over many timesteps was introduced on the first +journey. This page changes one thing: applications no longer all run at the +environment base step. + +## Hold a daily state for an hourly model + +Reuse the thermal-time, LAI, and light chain. The environment advances hourly; +thermal time and LAI run daily; light interception runs hourly. `HoldLast` +makes each hourly light execution read the latest published daily LAI. + +```@example journey_cadences +using PlantSimEngine, Dates, DataFrames +using PlantSimEngine.Examples + +hourly_forcing = [ + (T=20.0, Ri_PAR_f=300.0, duration=Hour(1)) + for _ in 1:25 +] + +model = CompositeModel( + Object(:plant; scale=:Plant, kind=:plant); + applications=( + ModelSpec( + ToyDegreeDaysCumulModel(); + name=:degree_days, + on=One(scale=:Plant), + every=Day(1), + ), + ModelSpec( + ToyLAIModel(); + name=:lai, + on=One(scale=:Plant), + every=Day(1), + ), + ModelSpec( + Beer(0.6); + name=:light, + on=One(scale=:Plant), + inputs=( + :LAI => One( + within=Self(), + application=:lai, + var=:LAI, + policy=HoldLast(), + window=Day(1), + ), + ), + every=Hour(1), + ), + ), + environment=hourly_forcing, +) + +simulation = run!(model; steps=25, outputs=:all) +``` + +The schedule reports physical cadence in seconds and in base steps: + +```@example journey_cadences +select( + DataFrame(Diagnostics.explain_schedule(model)), + :application_id, + :dt_seconds, + :dt_steps, +) +``` + +The temporal binding is explicit even though the producer and consumer share +an object: + +```@example journey_cadences +select( + DataFrame(Diagnostics.explain_bindings(model)), + :application_id, + :input, + :policy, + :window, + :carrier_kind, +) +``` + +The daily applications publish at steps 1 and 25; the hourly application +publishes on all 25 steps: + +```@example journey_cadences +select( + DataFrame(Diagnostics.explain_outputs(simulation)), + :application_id, + :variable, + :nsamples, +) +``` + +`HoldLast` is appropriate because LAI is a state: between daily updates, its +latest value remains meaningful. + +## Integrate a rate into an amount + +`Integrate` has a different physical meaning. If a leaf publishes a constant +rate in units per second, integrating 24 hourly samples produces a daily +amount. The consumer below sums the independently integrated amounts from two +leaves. + +```@example journey_cadences +PlantSimEngine.@process "cadence_hourly_flux" verbose = false +PlantSimEngine.@process "cadence_daily_amount" verbose = false + +struct CadenceHourlyFlux <: AbstractCadence_Hourly_FluxModel end +struct CadenceDailyAmount <: AbstractCadence_Daily_AmountModel end + +PlantSimEngine.inputs_(::CadenceHourlyFlux) = (rate=Required(Real),) +PlantSimEngine.outputs_(::CadenceHourlyFlux) = (flux=0.0,) +PlantSimEngine.run!( + ::CadenceHourlyFlux, + status, + environment, + constants, + context, +) = (status.flux = status.rate) + +PlantSimEngine.inputs_(::CadenceDailyAmount) = ( + leaf_amounts=Required(AbstractVector{<:Real}), +) +PlantSimEngine.outputs_(::CadenceDailyAmount) = (amount=0.0,) +PlantSimEngine.run!( + ::CadenceDailyAmount, + status, + environment, + constants, + context, +) = (status.amount = sum(status.leaf_amounts)) +``` + +```@example journey_cadences +flux_model = CompositeModel( + Object(:plant; scale=:Plant), + Object( + :leaf_1; + scale=:Leaf, + parent=:plant, + status=Status(rate=1.0), + ), + Object( + :leaf_2; + scale=:Leaf, + parent=:plant, + status=Status(rate=2.0), + ); + applications=( + ModelSpec( + CadenceHourlyFlux(); + name=:hourly_flux, + on=Many(scale=:Leaf), + every=Hour(1), + ), + ModelSpec( + CadenceDailyAmount(); + name=:daily_amount, + on=One(scale=:Plant), + inputs=( + :leaf_amounts => Many( + scale=:Leaf, + within=Subtree(), + application=:hourly_flux, + var=:flux, + policy=Integrate(), + window=Day(1), + ), + ), + every=Day(1), + ), + ), + environment=[(duration=Hour(1),) for _ in 1:25], +) + +flux_simulation = run!(flux_model; steps=25) +final_state(flux_simulation, One(scale=:Plant)).amount +``` + +The result is `(1 + 2) × 24 × 3600 = 259200` rate-seconds. Use +`Aggregate(reducer)` instead when the desired quantity is a mean, minimum, +maximum, or another reduction of observations rather than a time integral. + +There is no same-step feedback cycle in either example, so +`PreviousTimeStep` is not needed. It should be introduced only when a real +scientific dependency intentionally reads the preceding step to break such a +cycle. + +## Page recap + +- **You added:** daily and hourly application clocks, `HoldLast` for a state, + and then `Integrate` for a rate. +- **PlantSimEngine inferred:** the base-step ratios, publication schedule, and + bounded temporal storage needed by the consumers. +- **You keep explicit:** each application cadence, the physical meaning of its + temporal policy, and the integration window. +- **New API names:** `every`, `HoldLast`, `Integrate`, `Aggregate`, + `window`, `Diagnostics.explain_schedule`, and + `Diagnostics.explain_outputs`. diff --git a/docs/src/journeys/users/environments.md b/docs/src/journeys/users/environments.md new file mode 100644 index 000000000..d3ab194d7 --- /dev/null +++ b/docs/src/journeys/users/environments.md @@ -0,0 +1,166 @@ +# Understand Environments + +## New concept: declared sampling from global and spatial sources + +The first simulation used a weather file as supplied forcing. This page now +makes that contract explicit. A model declares the names it reads from its +model-facing environment: + +```@example journey_environments +using PlantSimEngine, Dates, DataFrames +using PlantSimEngine.Examples + +( + degree_days=PlantSimEngine.environment_inputs_( + ToyDegreeDaysCumulModel(), + ), + light=PlantSimEngine.environment_inputs_(Beer(0.6)), +) +``` + +`ToyDegreeDaysCumulModel` reads `environment.T`; `Beer` reads +`environment.Ri_PAR_f`. These are not status inputs and are not outputs owned +by the target object. + +## Global sampling and source names + +The source does not need to use the model-facing names. Here a global provider +has `air_temperature` and `incident_par`; `Environment(...; sources=...)` +remaps them for the two model applications. + +```@example journey_environments +forcing = ( + air_temperature=20.0, + incident_par=300.0, + duration=Day(1), +) + +global_model = CompositeModel( + Object(:plant; scale=:Plant, kind=:plant); + applications=( + ModelSpec( + ToyDegreeDaysCumulModel(); + name=:degree_days, + on=One(scale=:Plant), + environment=Environment( + provider=:global, + sources=(T=:air_temperature,), + ), + ), + ModelSpec( + ToyLAIModel(); + name=:lai, + on=One(scale=:Plant), + ), + ModelSpec( + Beer(0.6); + name=:light, + on=One(scale=:Plant), + environment=Environment( + provider=:global, + sources=(Ri_PAR_f=:incident_par,), + ), + ), + ), + environment=forcing, +) + +validate_environment_inputs(global_model) +global_simulation = run!(global_model) +global_state = final_state(global_simulation) +(TT_cu=global_state.TT_cu, LAI=global_state.LAI, aPPFD=global_state.aPPFD) +``` + +The environment diagnostic distinguishes the variables seen by each model from +the actual source names: + +```@example journey_environments +select( + DataFrame(Diagnostics.explain_environment_bindings(global_model)), + :application_id, + :object_id, + :required_inputs, + :source_inputs, + :handle, +) +``` + +Global sampling has no spatial handle. The forcing above is intentionally +strict: apart from timeline `duration`, it exposes only the two remapped source +variables. Removing either source makes `validate_environment_inputs` fail +before simulation. + +## Spatial sampling + +Spatial backends keep the same model-facing declaration. They additionally +compile an opaque handle for each application/object target. The small +`ToySpatialEnvironment` example maps object geometry to either a sunny or +shaded cell: + +```@example journey_environments +spatial_environment = ToySpatialEnvironment( + Dict( + :sun => (Ri_PAR_f=400.0,), + :shade => (Ri_PAR_f=100.0,), + ); + step_seconds=3600.0, +) + +spatial_model = CompositeModel( + Object( + :sun_leaf; + scale=:Leaf, + kind=:leaf, + geometry=(cell=:sun,), + status=Status(LAI=2.0), + ), + Object( + :shade_leaf; + scale=:Leaf, + kind=:leaf, + geometry=(cell=:shade,), + status=Status(LAI=2.0), + ); + applications=( + ModelSpec( + Beer(0.6); + name=:light, + on=Many(scale=:Leaf), + environment=Environment(backend=spatial_environment), + ), + ), +) + +spatial_simulation = run!(spatial_model) +spatial_states = final_state(spatial_simulation, Many(scale=:Leaf)) +Dict(id => state.aPPFD for (id, state) in spatial_states) +``` + +The one `Many` application retains two distinct compiled handles: + +```@example journey_environments +select( + DataFrame(Diagnostics.explain_environment_bindings(spatial_model)), + :application_id, + :object_id, + :geometry_source, + :handle, +) +``` + +The scientific `Beer` kernel is unchanged. It sees only +`environment.Ri_PAR_f`; the backend owns the meaning of each handle. Backend +authors can inspect the implementation of `ToySpatialEnvironment` in the +environment extension reference. + +## Page recap + +- **You added:** explicit environment declarations, global source remapping, + and then a spatial backend with object geometry. +- **PlantSimEngine inferred:** global sampling, validation of required source + names, and one cached spatial handle per application/object target. +- **You keep explicit:** model-facing environment names, scenario source + remaps, provider/backend choice, and geometry used by a spatial backend. +- **New API names:** `environment_inputs_`, `Environment`, + `validate_environment_inputs`, `ToySpatialEnvironment`, and + `Diagnostics.explain_environment_bindings`. diff --git a/docs/src/journeys/users/maespa_synthesis.md b/docs/src/journeys/users/maespa_synthesis.md new file mode 100644 index 000000000..3b298f3a1 --- /dev/null +++ b/docs/src/journeys/users/maespa_synthesis.md @@ -0,0 +1,242 @@ +# MAESPA-Style Synthesis + +## New concept: synthesis without another runtime mechanism + +This page is an integrated reference, not an onboarding example. It combines +the ideas developed independently in the earlier journeys into a small +MAESPA-style stand: two species, five leaves, hourly canopy and soil exchange, +daily allocation and LAI, iterative leaf calls, and accepted mutable canopy +air. + +If any individual mechanism is unfamiliar, follow its focused link in +[How the pieces compose](@ref) before reading the implementation. + +## Run the reference case + +The complete, tested source lives in +`examples/maespa_model_example.jl`. Run 25 hours so both hourly and daily +applications cross a day boundary: + +```@example journey_maespa_synthesis +using PlantSimEngine, DataFrames + +include(joinpath( + pkgdir(PlantSimEngine), + "examples", + "maespa_model_example.jl", +)) + +result = run_maespa_example(; nhours=25, check=true) +simulation = result.simulation +model = result.model +nothing +``` + +The model contains one scene, one soil object, and two template instances with +different species parameters and leaf counts: + +```@example journey_maespa_synthesis +( + instances=DataFrame(Diagnostics.explain_instances(model)), + plants=length(model_objects(model; scale=:Plant)), + leaves=length(model_objects(model; scale=:Leaf)), + species_A=length(model_objects(model; scale=:Leaf, species=:A)), + species_B=length(model_objects(model; scale=:Leaf, species=:B)), +) +``` + +## Inspect the compiled architecture + +The execution schedule makes the two cadences and parent-controlled +applications visible. Leaf energy balance and soil water are call-only under +the scene controller; allocation and LAI run daily: + +```@example journey_maespa_synthesis +schedule = DataFrame(Diagnostics.explain_schedule(result.compiled)) +select( + filter( + row -> row.application_id in ( + :scene_eb, + :soil_water, + :lai_dynamic, + :plant_A__energy_balance, + :plant_A__allocation, + :plant_B__allocation, + ), + schedule, + ), + :application_id, + :root_scheduled, + :manual_call_only, + :dt_steps, +) +``` + +The scene energy-balance application resolves all five leaves through one +`Many` hard call and the soil through one `One` hard call: + +```@example journey_maespa_synthesis +calls = DataFrame(Diagnostics.explain_calls(result.compiled)) +select( + filter(row -> row.application_id == :scene_eb, calls), + :call, + :callee_application_ids, + :callee_object_ids, + :publication_policy, +) +``` + +Each plant allocation application receives a live vector of only its own +descendant leaves. The scene receives stand-wide vectors and one scalar soil +potential: + +```@example journey_maespa_synthesis +bindings = DataFrame(Diagnostics.explain_bindings(result.compiled)) +select( + filter( + row -> ( + row.application_id in ( + :plant_A__allocation, + :plant_B__allocation, + ) && row.input == :leaf_carbon + ) || ( + row.application_id == :scene_eb && + row.input in (:leaf_areas, :psi_soil) + ), + bindings, + ), + :application_id, + :input, + :source_ids, + :carrier_kind, + :copy_semantics, +) +``` + +## Follow trial canopy air to its accepted state + +The scene controller reads above-canopy `:forcing`, iterates leaf models +against typed trial canopy air with `publish=false`, commits the converged +state to `sink=:canopy`, and then publishes one accepted leaf execution. Leaf +applications read the committed `:canopy` provider. Those routes are compiled +into opaque handles: + +```@example journey_maespa_synthesis +environment_bindings = DataFrame( + Diagnostics.explain_environment_bindings(result.environment), +) +select( + filter( + row -> row.application_id in ( + :scene_eb, + :plant_A__energy_balance, + :plant_B__energy_balance, + ), + environment_bindings, + ), + :application_id, + :object_id, + :handle, + :required_inputs, + :produced_outputs, +) +``` + +`MaespaSingleLayerEnvironment` is intentionally a one-layer canopy backend. +Its handle still separates forcing, canopy, and commit-sink routes per +application/object. A voxel or multilayer backend can replace it without +changing the model-facing environment contract; the two-cell proof is in +[Modify The Environment](@ref), and backend implementation belongs in +[Environment Backend Extensions](@ref). + +## Check the scientific handoffs + +The final snapshots expose canonical state independently of retained history: + +```@example journey_maespa_synthesis +scene = final_state(simulation, :model) +soil = final_state(simulation, :soil) +plants = final_state(simulation, Many(scale=:Plant)) + +( + lai=scene.lai, + canopy_temperature=scene.canopy_tair, + transpiration=scene.scene_transpiration, + soil_water_potential=soil.psi_soil, + daily_growth=Dict( + id => state.daily_growth + for (id, state) in plants + ), +) +``` + +Retained output counts confirm the cadence boundary: hourly scene and leaf +variables have 25 samples, while daily LAI and allocation variables have two: + +```@example journey_maespa_synthesis +output_summary = DataFrame(Diagnostics.explain_outputs(simulation)) +select( + filter( + row -> ( + row.object_id == :model && + row.variable in (:scene_transpiration, :lai) + ) || ( + row.object_id in (:plant_A, :plant_B) && + row.variable == :daily_growth + ) || ( + row.object_id == :plant_A_leaf_1 && + row.variable == :λE + ), + output_summary, + ), + :application_id, + :object_id, + :variable, + :nsamples, +) +``` + +## How the pieces compose + +| Construct in this synthesis | Role here | Focused journey | +|---|---|---| +| `CompositeModelTemplate` and two `ObjectInstance`s | Reuse one species-specific application set across several plants | [Instantiate Several Plants](@ref) | +| Scene, plant, internode, leaf, and soil objects | Represent one registry without prescribing plant architecture | [Build One Multiscale Plant](@ref) | +| Scalar and `Many` live-reference bindings | Couple soil-to-scene and leaf-to-plant/scene values | [Build One Multiscale Plant](@ref) | +| Hourly and daily applications with `HoldLast` | Keep canopy exchange and allocation on scientific cadences | [Give Models Different Cadences](@ref) | +| Forcing and canopy providers with compiled handles | Sample global forcing and committed canopy state through one contract | [Understand Environments](@ref) | +| Typed trials and explicit accepted commit | Iterate canopy air without publishing rejected states | [Modify The Environment](@ref) | +| Nested hard calls and accepted publication | Let scene energy balance control leaf and soil execution | [Control Advanced Execution](@ref) | +| `Simulation`, final state, and retained streams | Separate current canonical state from requested history | [Couple Models On One Object](@ref) | + +This 25-hour reference keeps plant topology fixed because organogenesis is not +part of its scientific question. A growth model can add, reparent, or remove +organs through the same registry and refresh machinery; that independent +lifecycle is demonstrated in [Modify Plant Structure](@ref). Keeping it out of +this synthesis prevents canopy iteration, daily allocation, and topology +mutation from becoming one inseparable example. + +## Reference invariants + +The automated example test verifies the important handoffs rather than exact +floating-point trajectories: + +- the stand contains two isolated instances and five correctly routed leaves; +- plant allocation vectors contain only descendant leaves; +- the scene call resolves every leaf and the shared soil application; +- hourly and daily output counts match their cadences; +- accepted canopy air is committed separately from above-canopy forcing; +- leaf fluxes are finite and aggregate consistently at scene scale; +- both species grow, while their parameterized allocations remain distinct. + +## Page recap + +- **You added:** no new primitive; you assembled the earlier topology, + cadence, hard-call, environment, and output mechanisms into one stand. +- **PlantSimEngine inferred:** application order, plant-local bindings, + concrete call targets, environment handles, and the hourly/daily schedule. +- **You keep explicit:** species parameters, topology, scientific iteration, + accepted state, output requests, and the invariants used to validate the + result. +- **New API names:** none. Every API in this synthesis was introduced on a + focused earlier journey. diff --git a/docs/src/journeys/users/mental_model.md b/docs/src/journeys/users/mental_model.md new file mode 100644 index 000000000..ffec0a6b2 --- /dev/null +++ b/docs/src/journeys/users/mental_model.md @@ -0,0 +1,55 @@ +# A Mental Model For PlantSimEngine + +## New concept: composition + +PlantSimEngine is a framework for composing and running scientific models. It +does not prescribe a plant architecture, and it is not itself a library of +crop, tree, or organ equations. Model packages provide those equations; +PlantSimEngine connects them to simulated entities, orders their execution, and +manages time, environments, and retained results. + +Seven ideas are enough to read a PlantSimEngine simulation: + +| Idea | Meaning | +|:--|:--| +| **Process** | A scientific responsibility, such as thermal time or light interception | +| **Model** | One reusable implementation of a process | +| **Application** | One configured use of a model in a simulation | +| **Object** | A simulated entity with stable identity, such as a scene, plant, leaf, or soil layer | +| **Status** | The current values owned by an object | +| **Environment** | Values sampled from outside object status, such as weather or microclimate | +| **Simulation** | A running timeline, including the live model, current step, and any retained output streams | + +The distinction between a model and an application is important. A model +author writes an equation once. A simulation author can then apply it to one +whole plant, every leaf, selected soil layers, or several named groups without +putting an object loop inside the equation. + +Objects are equally general. Scales and parent/child links describe the +topology chosen by the simulation author; PlantSimEngine does not require a +particular hierarchy. A simple simulation can have one object. A detailed one +can have scenes, several plants, organs, voxels, and shared resources. + +Values reach a model in two ways: + +- status inputs come from the target object or from outputs of other model + applications; +- environment inputs are sampled from the environment selected for that + application and object. + +Before running, PlantSimEngine compiles applications into concrete +application/object targets, resolves value connections, and determines a valid +execution order. During the timestep loop, model kernels work with their own +parameters, the resolved status view, the sampled environment, constants, and +a runtime context. + +## Page recap + +- **You added:** no configuration yet—only the vocabulary used by every later + journey. +- **PlantSimEngine infers:** application order and unambiguous value + connections once a simulation is assembled. +- **You keep explicit:** scientific equations, object topology, ambiguous + cross-object connections, time policies, and requested output history. +- **New API names:** none yet. The next page introduces `CompositeModel`, + `run!`, `Simulation`, `final_state`, and `collect_outputs`. diff --git a/docs/src/journeys/users/mutable_environments.md b/docs/src/journeys/users/mutable_environments.md new file mode 100644 index 000000000..6840a6214 --- /dev/null +++ b/docs/src/journeys/users/mutable_environments.md @@ -0,0 +1,181 @@ +# Modify The Environment + +## New concept: trial state versus accepted state + +The previous environment journey sampled read-only global and spatial values. +Now a controller evaluates one typed trial state, accepts a different state, +and commits it explicitly. + +Start with one cell. `ToyEnvironmentReaderModel` declares `T` as an environment +input. The controller declares `T` as an environment output: this is permission +to commit that variable, not an ordinary object-status output. + +```@example journey_mutable_environment +using PlantSimEngine, DataFrames +using PlantSimEngine.Examples + +( + reader_inputs=PlantSimEngine.environment_inputs_( + ToyEnvironmentReaderModel(), + ), + controller_commit_permissions=PlantSimEngine.environment_outputs_( + ToyEnvironmentControllerModel(30.0, 22.0), + ), +) +``` + +The controller's kernel uses the current typed trial-state path. A trial call +changes the callee status for inspection but does not publish output history or +commit backend state: + +```@example journey_mutable_environment +function run_trial!(context, trial_environment) + return only(run_call!( + context, + :reader; + environment=trial_environment, + publish=false, + )) +end +``` + +Accepted state is explicit and separate: + +```@example journey_mutable_environment +function commit_and_publish!(context, accepted_environment) + commit_environment!(context, accepted_environment) + return only(run_call!( + context, + :reader; + environment=accepted_environment, + publish=true, + )) +end +``` + +`ToyEnvironmentControllerModel` applies those two operations in its kernel. +Configure the reader as its one hard-call target and give only the controller a +commit sink: + +```@example journey_mutable_environment +environment = ToySpatialEnvironment( + Dict(:canopy => (T=20.0,)); + step_seconds=3600.0, +) + +model = CompositeModel( + Object( + :leaf; + scale=:Leaf, + kind=:leaf, + geometry=(cell=:canopy,), + ); + applications=( + ModelSpec( + ToyEnvironmentReaderModel(); + name=:reader, + on=One(scale=:Leaf), + environment=Environment(backend=environment), + ), + ModelSpec( + ToyEnvironmentControllerModel(30.0, 22.0); + name=:controller, + on=One(scale=:Leaf), + calls=( + :reader => One( + scale=:Leaf, + application=:reader, + ), + ), + environment=Environment( + backend=environment, + sink=:cells, + ), + ), + ), +) + +simulation = run!(model; outputs=:all) +state = final_state(simulation) +( + trial_seen=state.trial_temperature_seen, + accepted_seen=state.accepted_temperature_seen, + committed=environment.cells[:canopy].T, +) +``` + +The trial was `30`, but the accepted and committed temperature is `22`. +Only the accepted reader call published: + +```@example journey_mutable_environment +select( + DataFrame(Diagnostics.explain_outputs(simulation)), + :application_id, + :variable, + :nsamples, +) +``` + +## Preserve distinct handles under `Many` + +Extend the same backend to two spatial cells. One `Many` application samples +both, while each target retains its own compiled handle: + +```@example journey_mutable_environment +spatial_environment = ToySpatialEnvironment( + Dict( + :sun => (T=26.0,), + :shade => (T=18.0,), + ); + step_seconds=3600.0, +) + +spatial_model = CompositeModel( + Object( + :sun_leaf; + scale=:Leaf, + geometry=(cell=:sun,), + ), + Object( + :shade_leaf; + scale=:Leaf, + geometry=(cell=:shade,), + ); + applications=( + ModelSpec( + ToyEnvironmentReaderModel(); + name=:temperature, + on=Many(scale=:Leaf), + environment=Environment(backend=spatial_environment), + ), + ), +) + +spatial_simulation = run!(spatial_model) +spatial_states = final_state(spatial_simulation, Many(scale=:Leaf)) +Dict(id => state.temperature_seen for (id, state) in spatial_states) +``` + +```@example journey_mutable_environment +select( + DataFrame(Diagnostics.explain_environment_bindings(spatial_model)), + :object_id, + :handle, +) +``` + +This ordinary user page does not require the backend implementation protocol. +Framework builders can follow [Environment Backend Extensions](@ref); the +complete MAESPA-style synthesis later combines mutable microclimate, several +plants, and iterative leaf calls. + +## Page recap + +- **You added:** one typed trial, one explicit accepted commit, one accepted + publication, and then two spatial cells. +- **PlantSimEngine inferred:** the reader call target, publication boundary, + commit permission check, and distinct `Many` handles. +- **You keep explicit:** trial and acceptance logic, `publish`, the committed + variables, controller sink, and backend state type. +- **New API names:** `environment_outputs_`, `run_call!`, + `commit_environment!`, `publish`, and `calls`. diff --git a/docs/src/journeys/users/one_object.md b/docs/src/journeys/users/one_object.md new file mode 100644 index 000000000..25091a6fe --- /dev/null +++ b/docs/src/journeys/users/one_object.md @@ -0,0 +1,96 @@ +# Couple Models On One Object + +## New concept: automatic same-object coupling over time + +This first executable simulation couples three existing models on one object: + +1. `ToyDegreeDaysCumulModel` reads temperature and accumulates thermal time. +2. `ToyLAIModel` reads cumulative thermal time and computes LAI. +3. `Beer` reads LAI and radiation and computes absorbed PAR. + +The weather file is supplied forcing data for now. Environments get their own +journey later. + +```@example journey_one_object +using PlantSimEngine, PlantMeteo, Dates, DataFrames +using PlantSimEngine.Examples + +weather = read_weather( + joinpath(pkgdir(PlantSimEngine), "examples/meteo_day.csv"); + duration=Day, +) + +model = CompositeModel( + ToyDegreeDaysCumulModel(), + ToyLAIModel(), + Beer(0.6); + environment=weather, +) +``` + +No `ModelSpec` or selector is needed when all models run on the one object made +by the concise constructor. Run thirty daily steps and retain the model +outputs: + +```@example journey_one_object +simulation = run!(model; steps=30, outputs=:all) +results = collect_outputs(simulation) + +thermal_time = results[results.variable .== :TT_cu, :value] +lai = results[results.variable .== :LAI, :value] +evolution = DataFrame( + step=1:length(thermal_time), + TT_cu=thermal_time, + LAI=lai, +) +vcat(first(evolution, 3), last(evolution, 3)) +``` + +The table is retained history. The latest values are also available directly, +whether or not history was requested: + +```@example journey_one_object +state_at_day_30 = final_state(simulation) +( + current_step=current_step(simulation), + TT_cu=state_at_day_30.TT_cu, + LAI=state_at_day_30.LAI, + aPPFD=state_at_day_30.aPPFD, + retained_streams=length(outputs(simulation)), +) +``` + +PlantSimEngine inferred both status connections because each has one +unambiguous producer on the same object. This focused diagnostic shows the +resolved sources and the live reference carriers: + +```@example journey_one_object +select( + DataFrame(Diagnostics.explain_bindings(model)), + :application_id, + :input, + :source_application_ids, + :carrier_kind, +) +``` + +A `Simulation` owns a continuing timeline. Advancing it does not rebuild a +separate result object: + +```@example journey_one_object +step!(simulation) +state_at_day_31 = final_state(simulation) +(current_step=current_step(simulation), TT_cu=state_at_day_31.TT_cu) +``` + +## Page recap + +- **You added:** three models, supplied weather, a 30-step run, and retained + outputs. +- **PlantSimEngine inferred:** the one object, three applications, their + execution order, and the `TT_cu` and `LAI` connections. +- **You keep explicit:** model parameters, forcing data, number of steps, and + whether output history is retained. +- **New API names:** `CompositeModel`, `run!`, `Simulation`, `final_state`, + `collect_outputs`, `outputs`, `current_step`, `step!`, and + `Diagnostics.explain_bindings`. diff --git a/docs/src/journeys/users/one_plant.md b/docs/src/journeys/users/one_plant.md new file mode 100644 index 000000000..cbb13eae8 --- /dev/null +++ b/docs/src/journeys/users/one_plant.md @@ -0,0 +1,200 @@ +# Build One Multiscale Plant + +## New concept: topology and cross-object values + +The previous journey used independent objects at one scale. A multiscale plant +adds parent/child topology: one plant object owns two leaf objects. + +The scope picture for this page is: + +> `:plant` — `Subtree()` from here contains `:plant`, `:leaf_1`, and `:leaf_2`
+> ├─ `:leaf_1` — `Self()` is `:leaf_1`; `SelfPlant()` resolves to `:plant`
+> └─ `:leaf_2` — `Self()` is `:leaf_2`; `SelfPlant()` resolves to `:plant` + +Selectors still filter that scope. For example, +`Many(scale=:Leaf, within=Subtree())` selects the two leaves when evaluated for +the plant application. + +## First pass: one scalar value from plant to leaves + +Start with leaf surfaces and total plant surface supplied as status. The only +new value connection sends the plant-level absorbed light to each leaf. + +```@example journey_one_plant +using PlantSimEngine, DataFrames +using PlantSimEngine.Examples + +objects = ( + Object( + :plant; + scale=:Plant, + kind=:plant, + status=Status(aPPFD=120.0, surface=3.0), + ), + Object( + :leaf_1; + scale=:Leaf, + kind=:leaf, + parent=:plant, + status=Status(surface=1.0), + ), + Object( + :leaf_2; + scale=:Leaf, + kind=:leaf, + parent=:plant, + status=Status(surface=2.0), + ), +) + +scalar_model = CompositeModel( + objects...; + applications=( + ModelSpec( + ToyLightPartitioningModel(); + name=:leaf_light, + on=Many(scale=:Leaf), + inputs=( + :aPPFD_larger_scale => One( + scale=:Plant, + within=SelfPlant(), + var=:aPPFD, + ), + :total_surface => One( + scale=:Plant, + within=SelfPlant(), + var=:surface, + ), + ), + ), + ), +) + +scalar_simulation = run!(scalar_model; outputs=:all) +scalar_states = final_state(scalar_simulation, Many(scale=:Leaf)) +Dict(id => state.aPPFD for (id, state) in scalar_states) +``` + +The leaf model reads its own `surface` directly from each leaf status. +`SelfPlant()` makes the other two scalar sources plant-local: + +```@example journey_one_plant +select( + DataFrame(Diagnostics.explain_bindings(scalar_model)), + :consumer_id, + :input, + :source_ids, + :carrier_kind, +) +``` + +## Second pass: compute and aggregate leaf surfaces + +Now replace the supplied surfaces with two existing models: + +- `ToyLeafSurfaceModel` computes each leaf surface from its carbon biomass; +- `ToyPlantLeafSurfaceModel` sums those leaf surfaces on the plant. + +This is the first vector-like cross-object input. It comes after the scalar +connection above, and differs only in the new `:leaf_surfaces` binding. + +```@example journey_one_plant +computed_objects = ( + Object( + :plant; + scale=:Plant, + kind=:plant, + status=Status(aPPFD=120.0), + ), + Object( + :leaf_1; + scale=:Leaf, + kind=:leaf, + parent=:plant, + status=Status(carbon_biomass=50.0), + ), + Object( + :leaf_2; + scale=:Leaf, + kind=:leaf, + parent=:plant, + status=Status(carbon_biomass=100.0), + ), +) + +computed_model = CompositeModel( + computed_objects...; + applications=( + ModelSpec( + ToyLeafSurfaceModel(0.02); + name=:leaf_surface, + on=Many(scale=:Leaf), + ), + ModelSpec( + ToyPlantLeafSurfaceModel(); + name=:plant_surface, + on=One(scale=:Plant), + inputs=( + :leaf_surfaces => Many( + scale=:Leaf, + within=Subtree(), + application=:leaf_surface, + var=:surface, + ), + ), + ), + ModelSpec( + ToyLightPartitioningModel(); + name=:leaf_light, + on=Many(scale=:Leaf), + inputs=( + :aPPFD_larger_scale => One( + scale=:Plant, + within=SelfPlant(), + var=:aPPFD, + ), + :total_surface => One( + scale=:Plant, + within=SelfPlant(), + application=:plant_surface, + var=:surface, + ), + ), + ), + ), +) + +computed_simulation = run!(computed_model; outputs=:all) +plant_state = final_state(computed_simulation, One(scale=:Plant)) +leaf_states = final_state(computed_simulation, Many(scale=:Leaf)) +( + plant_surface=plant_state.surface, + leaf_surfaces=Dict(id => state.surface for (id, state) in leaf_states), + leaf_light=Dict(id => state.aPPFD for (id, state) in leaf_states), +) +``` + +The plant aggregation uses a live `RefVector`; the scalar connections remain +single references: + +```@example journey_one_plant +select( + DataFrame(Diagnostics.explain_bindings(computed_model)), + :application_id, + :consumer_id, + :input, + :source_ids, + :carrier_kind, +) +``` + +## Page recap + +- **You added:** parent/child topology, plant-to-leaf scalar connections, and + one plant-local vector aggregation. +- **PlantSimEngine inferred:** same-leaf `surface` coupling, application order, + and live scalar/vector reference carriers. +- **You keep explicit:** object parentage, the scope of cross-object searches, + and the source application when selecting a produced value. +- **New API names:** `parent`, `Self`, `SelfPlant`, `Subtree`, and the + `application` and `var` selector fields. diff --git a/docs/src/journeys/users/several_objects.md b/docs/src/journeys/users/several_objects.md new file mode 100644 index 000000000..19fba3432 --- /dev/null +++ b/docs/src/journeys/users/several_objects.md @@ -0,0 +1,102 @@ +# Run The Coupling On Several Objects + +## New concept: stable object identity and `Many` + +The previous page ran one model chain on one automatically created object. The +smallest extension is to create two same-scale objects and target both with one +reusable `Many` selector. + +```@example journey_several_objects +using PlantSimEngine, PlantMeteo, Dates, DataFrames +using PlantSimEngine.Examples + +weather = read_weather( + joinpath(pkgdir(PlantSimEngine), "examples/meteo_day.csv"); + duration=Day, +) + +plants = ( + Object( + :plant_a; + scale=:Plant, + kind=:plant, + status=Status(TT_cu=0.0), + ), + Object( + :plant_b; + scale=:Plant, + kind=:plant, + status=Status(TT_cu=200.0), + ), +) +plant_targets = Many(scale=:Plant) + +model = CompositeModel( + plants...; + applications=( + ModelSpec( + ToyDegreeDaysCumulModel(); + name=:degree_days, + on=plant_targets, + ), + ModelSpec(ToyLAIModel(); name=:lai, on=plant_targets), + ModelSpec(Beer(0.6); name=:light, on=plant_targets), + ), + environment=weather, +) +``` + +`:plant_a` and `:plant_b` are stable object identities. Their initial +cumulative thermal times differ, but the same three model kernels execute for +both. The model implementations contain no loop over plants. + +The application diagnostic confirms that each application compiled to both +objects: + +```@example journey_several_objects +select( + DataFrame(Diagnostics.explain_applications(model)), + :application_id, + :target_ids, +) +``` + +Run five steps and inspect each independent final status: + +```@example journey_several_objects +simulation = run!(model; steps=5, outputs=:all) +states = final_state(simulation, Many(scale=:Plant)) +Dict( + id => (TT_cu=state.TT_cu, LAI=state.LAI, aPPFD=state.aPPFD) + for (id, state) in states +) +``` + +Retained streams are keyed by application, object, and variable, so the two +objects do not overwrite one another: + +```@example journey_several_objects +rows = collect_outputs(simulation) +lai_rows = rows[rows.variable .== :LAI, [ + :timestep, + :application_id, + :object_id, + :value, +]] +first(lai_rows, 6) +``` + +This remains a same-scale simulation. Parent/child topology and cross-object +value selection are introduced on the next journey, after independent object +execution is established. + +## Page recap + +- **You added:** two explicit `Object`s, stable ids, one shared `Many` selector, + and named `ModelSpec` applications. +- **PlantSimEngine inferred:** two targets per application plus independent + same-object `TT_cu` and `LAI` connections for each plant. +- **You keep explicit:** which objects exist, their initial status, application + names, and the selector describing the target set. +- **New API names:** `Object`, `Status`, `ModelSpec`, `Many`, and + `Diagnostics.explain_applications`. diff --git a/docs/src/journeys/users/several_plants.md b/docs/src/journeys/users/several_plants.md new file mode 100644 index 000000000..a468532c1 --- /dev/null +++ b/docs/src/journeys/users/several_plants.md @@ -0,0 +1,204 @@ +# Instantiate Several Plants + +## New concept: templates, instances, and overrides + +The previous journey configured one plant explicitly. Its three applications +can become a `CompositeModelTemplate`, then be mounted on several independent +object topologies without duplicating that model configuration. + +```@example journey_several_plants +using PlantSimEngine, DataFrames +using PlantSimEngine.Examples + +plant_template = CompositeModelTemplate(( + ModelSpec( + ToyLeafSurfaceModel(0.02); + name=:leaf_surface, + on=Many(scale=:Leaf), + ), + ModelSpec( + ToyPlantLeafSurfaceModel(); + name=:plant_surface, + on=One(scale=:Plant), + inputs=( + :leaf_surfaces => Many( + scale=:Leaf, + within=Subtree(), + application=:leaf_surface, + var=:surface, + ), + ), + ), + ModelSpec( + ToyLightPartitioningModel(); + name=:leaf_light, + on=Many(scale=:Leaf), + inputs=( + :aPPFD_larger_scale => One( + scale=:Plant, + within=SelfPlant(), + var=:aPPFD, + ), + :total_surface => One( + scale=:Plant, + within=SelfPlant(), + application=:plant_surface, + var=:surface, + ), + ), + ), +)) +``` + +An `ObjectInstance` supplies the concrete root and organs. These two instances +reuse the same template while keeping different initial plant radiation and +leaf biomasses: + +```@example journey_several_plants +plant_a = ObjectInstance( + :plant_a, + plant_template; + root=Object( + :plant_a_root; + scale=:Plant, + kind=:plant, + status=Status(aPPFD=120.0), + ), + objects=( + Object( + :plant_a_leaf_1; + scale=:Leaf, + kind=:leaf, + parent=:plant_a_root, + status=Status(carbon_biomass=50.0), + ), + Object( + :plant_a_leaf_2; + scale=:Leaf, + kind=:leaf, + parent=:plant_a_root, + status=Status(carbon_biomass=100.0), + ), + ), +) + +plant_b = ObjectInstance( + :plant_b, + plant_template; + root=Object( + :plant_b_root; + scale=:Plant, + kind=:plant, + status=Status(aPPFD=200.0), + ), + objects=( + Object( + :plant_b_leaf_1; + scale=:Leaf, + kind=:leaf, + parent=:plant_b_root, + status=Status(carbon_biomass=50.0), + ), + Object( + :plant_b_leaf_2; + scale=:Leaf, + kind=:leaf, + parent=:plant_b_root, + status=Status(carbon_biomass=50.0), + ), + ), +) + +model = CompositeModel(plant_a, plant_b) +simulation = run!(model; outputs=:all) +plant_states = final_state(simulation, Many(scale=:Plant)) +Dict(id => (surface=state.surface, aPPFD=state.aPPFD) for (id, state) in plant_states) +``` + +Plant A aggregates surfaces `1 + 2 = 3`; plant B aggregates `1 + 1 = 2`. +Those totals prove that `Subtree()` did not mix leaves between instances. +Likewise, each pair of leaf-level light outputs sums to its own plant's +supplied light: + +```@example journey_several_plants +leaf_states = final_state(simulation, Many(scale=:Leaf)) +( + plant_a_light=sum( + leaf_states[id].aPPFD + for id in (:plant_a_leaf_1, :plant_a_leaf_2) + ), + plant_b_light=sum( + leaf_states[id].aPPFD + for id in (:plant_b_leaf_1, :plant_b_leaf_2) + ), +) +``` + +The instance diagnostic shows the mounted object and application ids. Template +application names are prefixed automatically, so the two mounted graphs remain +unambiguous: + +```@example journey_several_plants +select( + DataFrame(Diagnostics.explain_instances(model)), + :name, + :root_id, + :object_ids, + :application_ids, +) +``` + +## Override one instance + +Only after the two unchanged instances work, override one application for a +new instance. This plant uses a larger specific leaf area while retaining the +same logical `:leaf_surface` application and all other template wiring: + +```@example journey_several_plants +plant_c = ObjectInstance( + :plant_c, + plant_template; + root=Object( + :plant_c_root; + scale=:Plant, + kind=:plant, + status=Status(aPPFD=120.0), + ), + objects=( + Object( + :plant_c_leaf_1; + scale=:Leaf, + kind=:leaf, + parent=:plant_c_root, + status=Status(carbon_biomass=50.0), + ), + Object( + :plant_c_leaf_2; + scale=:Leaf, + kind=:leaf, + parent=:plant_c_root, + status=Status(carbon_biomass=100.0), + ), + ), + overrides=(leaf_surface=ToyLeafSurfaceModel(0.04),), +) + +override_simulation = run!(CompositeModel(plant_c)) +override_state = final_state(override_simulation, One(scale=:Plant)) +override_state.surface +``` + +There is no `SceneScope()` in this example because nothing is deliberately +shared between plants. Introduce scene-wide scope only when adding a real +shared source, such as a soil object or scene-level forcing controller. + +## Page recap + +- **You added:** one reusable `CompositeModelTemplate`, two independent + `ObjectInstance`s, and then one application override. +- **PlantSimEngine inferred:** instance-local selector scopes, prefixed mounted + application ids, and the same compiled coupling graph for each plant. +- **You keep explicit:** each instance's objects and initial values, plus the + exact application replaced by an override. +- **New API names:** `CompositeModelTemplate`, `ObjectInstance`, `overrides`, + and `Diagnostics.explain_instances`. diff --git a/docs/src/journeys/users/structure_changes.md b/docs/src/journeys/users/structure_changes.md new file mode 100644 index 000000000..f745b2b8c --- /dev/null +++ b/docs/src/journeys/users/structure_changes.md @@ -0,0 +1,209 @@ +# Modify Plant Structure + +## New concept: lifecycle changes refresh compiled targets + +Start with one plant, one branch, and two leaves. Each leaf computes carbon +demand, then treats that fully met demand as accepted carbon allocation for +`ToyCBiomassModel`. This small chain gives us a conserved quantity to check +while topology changes. + +```@example journey_structure +using PlantSimEngine, DataFrames +using PlantSimEngine.Examples + +model = CompositeModel( + Object(:plant; scale=:Plant, kind=:plant), + Object(:branch; scale=:Axis, kind=:axis, parent=:plant), + Object( + :leaf_1; + scale=:Leaf, + kind=:leaf, + parent=:plant, + status=Status(TT=10.0), + ), + Object( + :leaf_2; + scale=:Leaf, + kind=:leaf, + parent=:plant, + status=Status(TT=15.0), + ); + applications=( + ModelSpec( + ToyCDemandModel( + optimal_biomass=12.0, + development_duration=120.0, + ); + name=:carbon_demand, + on=Many(scale=:Leaf), + ), + ModelSpec( + ToyCBiomassModel(1.2); + name=:biomass, + on=Many(scale=:Leaf), + inputs=( + :carbon_allocation => One( + within=Self(), + application=:carbon_demand, + var=:carbon_demand, + ), + ), + ), + ), +) + +simulation = run!(model; outputs=:all) +initial_targets = only( + row for row in Diagnostics.explain_applications(simulation) + if row.application_id == :biomass +).target_ids +``` + +## Add one leaf + +Registering an object mutates the live model and marks affected compiled state +dirty. Because this call happens between simulation steps, the new leaf is +compiled before the next step: + +```@example journey_structure +register_object!( + model, + Object( + :leaf_3; + scale=:Leaf, + kind=:leaf, + status=Status(TT=20.0), + ); + parent=:plant, +) + +targets_before_refresh = only( + row for row in Diagnostics.explain_applications(simulation) + if row.application_id == :biomass +).target_ids + +continue!(simulation) + +targets_after_refresh = only( + row for row in Diagnostics.explain_applications(simulation) + if row.application_id == :biomass +).target_ids + +( + initial_targets=initial_targets, + before_refresh=targets_before_refresh, + after_refresh=targets_after_refresh, + leaf_3_parent=only( + object.parent.value + for object in model_objects(model) + if object.id == ObjectId(:leaf_3) + ), +) +``` + +When a lifecycle operation occurs *inside* a model kernel, PlantSimEngine +refreshes after that application. A newly registered object may therefore run +applications that remain later in the same timestep, but it never +retroactively runs applications that already completed. + +## Reparent, then remove + +Creation now works, so make two further changes in order. First move the new +leaf under the branch and advance: + +```@example journey_structure +reparent_object!(model, :leaf_3, :branch) +continue!(simulation) + +leaf_3_parent = only( + object.parent.value + for object in model_objects(model) + if object.id == ObjectId(:leaf_3) +) +``` + +Then remove `:leaf_2` and advance once more: + +```@example journey_structure +removed = remove_object!(model, :leaf_2) +continue!(simulation) + +( + removed=removed.id.value, + current_leaves=sort!([ + object.id.value + for object in model_objects(model; scale=:Leaf) + ]), + leaf_3_parent=leaf_3_parent, + current_targets=only( + row for row in Diagnostics.explain_applications(simulation) + if row.application_id == :biomass + ).target_ids, +) +``` + +## Check conservation and history + +For every retained leaf sample, accepted carbon allocation equals demand. The +biomass model partitions it into biomass increment plus growth respiration: + +```@example journey_structure +rows = collect_outputs(simulation; sink=nothing) + +demand = Dict( + (row.timestep, row.object_id) => row.value + for row in rows + if row.application_id == :carbon_demand && + row.variable == :carbon_demand +) +increment = Dict( + (row.timestep, row.object_id) => row.value + for row in rows + if row.application_id == :biomass && + row.variable == :carbon_biomass_increment +) +respiration = Dict( + (row.timestep, row.object_id) => row.value + for row in rows + if row.application_id == :biomass && + row.variable == :growth_respiration +) + +all( + demand[key] ≈ increment[key] + respiration[key] + for key in keys(demand) +) +``` + +Removed-object history remains queryable even though the object is no longer +in the registry: + +```@example journey_structure +history_counts = Dict( + id => length(collect_outputs( + simulation, + id, + :carbon_biomass; + sink=nothing, + )) + for id in (:leaf_1, :leaf_2, :leaf_3) +) +``` + +`:leaf_2` keeps the three samples published before removal; `:leaf_3` begins at +step 2, after registration, and also has three samples. + +`ToyCAllocationModel` is useful when supply is limiting and a plant controller +must divide carbon among many organ demands. This journey deliberately assumes +all demand is accepted so lifecycle timing and conservation stay visible +without introducing a controller or hard calls. + +## Page recap + +- **You added:** one leaf, then one reparenting operation, then one removal. +- **PlantSimEngine inferred:** the affected application targets, status views, + reference binding, execution batch extension, and retained stream keys. +- **You keep explicit:** initialized status for a new object, its parent, + conservation assumptions, and when removal or reparenting occurs. +- **New API names:** `register_object!`, `reparent_object!`, `remove_object!`, + and `Diagnostics.explain_applications(simulation)`. diff --git a/docs/src/migration_composite_model.md b/docs/src/migration_composite_model.md new file mode 100644 index 000000000..8dec94b75 --- /dev/null +++ b/docs/src/migration_composite_model.md @@ -0,0 +1,497 @@ +# Migrating To The CompositeModel/Object API + +## Refining early CompositeModel/Object code + +The stabilized public surface makes several early CompositeModel/Object behaviors +explicit: + +| Early spelling or behavior | Stabilized API | +| --- | --- | +| `Self()` searched self and descendants | `Self()` selects only the current object; use `Subtree()` for self plus descendants | +| omitted `tracked_outputs` retained everything | use explicit `outputs=:all`; the safe default is `outputs=:none` | +| `tracked_outputs=requests` | `outputs=requests` | +| `OutputRequest(:Leaf, :x; process=:p)` | `OutputRequest(Many(scale=:Leaf), :x; application=:app)` | +| repeated unnamed applications gained numbered IDs | name every repeated application with `ModelSpec(...; name=...)` | +| calling `run!(model)` again implicitly looked like continuation | use `continue!(simulation)` or `step!(simulation)` | +| compiler/cache types imported from the default namespace | qualify them through `PlantSimEngine.Advanced` | + +`tracked_outputs` has been removed. Use `outputs=:all`, `outputs=:none`, or +`outputs=requests` directly. Singular scenario `inputs` and `calls`, +`OutputRequest`, object overrides, and `Updates(...; after=...)` now identify +the target by canonical `application=...` or application ID. Model-authored +`Input`/`Call` defaults may still discover a process because they cannot know +scenario application names, and `Many(process=...)` remains an explicit +multi-application discovery query. + +Calling `run!(model; ...)` always creates a fresh result timeline starting at +step one, even when object status has already been mutated by an earlier run. +Continue the same timeline, environment position, temporal histories, and +multirate phase with: + +```julia +simulation = run!(model; steps=24, outputs=requests) +continue!(simulation; steps=24) +step!(simulation) +@assert current_step(simulation) == 49 +``` + +The composite-model/object API replaces the historical multiscale mapping system with +one object-address graph. + +New scenario code should be organized around: + +```julia +CompositeModel +Object +ModelSpec +Updates +Environment +``` + +Process-model implementations do not need to know about composite models, plants, objects, or +timesteps. They keep the existing kernel contract: + +```julia +inputs_(model) +outputs_(model) +dep(model) +environment_inputs_(model) +run!(model, status, environment, constants, context) +``` + +This page maps the legacy configuration concepts to their composite-model/object +equivalents. + +## Explicit Input Initialization + +Input literals no longer double as ambiguous placeholder values. Declare +whether each model input is required or genuinely has a fallback: + +```julia +# Old, ambiguous +inputs_(::GrowthModel) = ( + temperature=-Inf, + efficiency=0.8, +) + +# Current +inputs_(::GrowthModel) = ( + temperature=Required(Float64), + efficiency=Default(0.8), +) +``` + +`Required(T)` means object state or another application must supply the value. +`Default(value)` means PlantSimEngine may initialize it when absent. Output +literals remain initial output-state values. Plain input literals are rejected; +there is no compatibility interpretation of `-Inf` or another sentinel. + +Replace helpers that previously merged every input literal into initial state +with `init_variables(model)`. It returns only real input defaults and output +initial values, omitting required inputs. + +## Scenario Structure + +Legacy simulations split configuration between `ModelMapping` and +`MultiScaleModel`. The unified API stores runtime entities in one `CompositeModel`: + +`ModelMapping` has been removed. Historical code must be translated to the +composite-model/object form below. + +```julia +model = CompositeModel( + Object(:scene; scale=:Scene, kind=:scene), + Object(:plant_1; scale=:Plant, kind=:plant, parent=:scene), + Object(:leaf_1; scale=:Leaf, kind=:plant, parent=:plant_1), + Object(:soil; scale=:Soil, kind=:soil, parent=:scene); + applications=( + ModelSpec(LeafModel(); name=:leaf_model, on=Many(scale=:Leaf)), + + ModelSpec(SoilModel(); name=:soil_model, on=One(scale=:Soil)), + ), + environment=(T=25.0, Rh=0.6, Wind=1.0), +) +``` + +`Object` labels describe runtime entities. They do not prescribe plant +topology. A plant may use any hierarchy of plants, axes, internodes, segments, +leaves, roots, fruits, or application-specific objects. + +### Existing MTG Topologies + +An existing MTG can be adapted without rebuilding its topology manually: + +```julia +model = CompositeModel( + mtg; + applications=applications, + environment=environment, + kind=node_kind, + species=node_species, + geometry=node_geometry, +) +``` + +`objects_from_mtg(mtg; ...)` exposes the intermediate object list when it is +useful to inspect or modify labels before constructing the model. By default, +the adapter uses MTG node ids and scales, and reuses an existing +`:plantsimengine_status` attribute when present. + +## Multiscale Inputs + +Replace `MultiScaleModel(...)` variable mappings with consumer-side +`ModelSpec(...; inputs=...)`. + +Legacy: + +```julia +MultiScaleModel( + AllocationModel(), + [:leaf_carbon => [:Leaf => :leaf_carbon]], +) +``` + +Unified: + +```julia +ModelSpec( + AllocationModel(); + name=:allocation, + on=Many(scale=:Plant), + inputs=( + :leaf_carbon => Many( + scale=:Leaf, + within=Subtree(), + var=:leaf_carbon, + ), + ), +) +``` + +`Self()` selects only the object where the consumer runs. A plant-scale +allocation model uses `Subtree()` to read leaves below that plant. Use +`SceneScope()` for model-wide aggregation and `SelfPlant()` to select the +nearest containing plant and its subtree from an organ. + +Same-object renaming uses the same syntax: + +```julia +ModelSpec( + ConsumerModel(); + inputs=( + :consumer_name => One( + within=Self(), + application=:producer, + var=:producer_name, + ), + ), +) +``` + +Same-rate bindings use shared references or reference vectors when possible. +Cross-rate bindings use typed temporal streams. + +## CompositeModel-Wide Values + +Use an input selector on the consuming application: + +```julia +ModelSpec(SceneWaterBalance(); name=:scene_water, on=One(scale=:Scene), inputs=(:leaf_transpiration => Many( + kind=:plant, + scale=:Leaf, + within=SceneScope(), + application=:transpiration, + var=:transpiration, + ),)) +``` + +The compiler chooses the carrier. Scenario authors declare the source objects, +source variable, and temporal policy rather than a route implementation. + +## Manual Hard Calls + +Use `ModelSpec(...; calls=...)` when a parent model must control child execution. + +```julia +ModelSpec(SceneEnergyBalance(); name=:scene_energy, on=One(scale=:Scene), calls=(:leaf_energy => Many( + kind=:plant, + scale=:Leaf, + within=SceneScope(), + application=:energy_balance, + ), + :soil => One( + kind=:soil, + scale=:Soil, + within=SceneScope(), + application=:soil_water, + ),)) +``` + +The parent model controls execution: + +```julia +function PlantSimEngine.run!(model::SceneEnergyBalance, status, environment, + constants, context) + for iteration in 1:model.max_iterations + trial = trial_environment(model, status) + run_call!(context, :leaf_energy; environment=trial, publish=false) + converged(model, status) && break + end + + accepted = accepted_environment(model, status) + commit_environment!(context, accepted) + run_call!(context, :leaf_energy; publish=true) + return nothing +end +``` + +`run_call!` defaults to `publish=false`. Trial calls mutate target status but +do not publish temporal samples or commit mutable environment updates. +do not append temporal samples or write environment outputs. The accepted +state must use `publish=true`. + +## Multiple Plants And Species + +Represent repeated plant configurations with `CompositeModelTemplate` and +`ObjectInstance`. + +```julia +oil_palm = CompositeModelTemplate( + ( + ModelSpec(LeafEnergy(); on=Many(scale=:Leaf)), + + ModelSpec(Allocation(); on=One(scale=:Plant), inputs=(:leaf_carbon => Many( + scale=:Leaf, + within=Subtree(), + var=:leaf_carbon, + ),)), + ); + kind=:plant, + species=:oil_palm, +) + +palm_1 = ObjectInstance( + :palm_1, + oil_palm; + root=Object(:plant_1; scale=:Plant, parent=:scene), + objects=(Object(:palm_1_leaf_1; scale=:Leaf, parent=:plant_1),), +) + +palm_2 = ObjectInstance( + :palm_2, + oil_palm; + root=Object(:plant_2; scale=:Plant, parent=:scene), + objects=(Object(:palm_2_leaf_1; scale=:Leaf, parent=:plant_2),), +) + +model = CompositeModel( + Object(:scene; scale=:Scene, kind=:scene), + palm_1, + palm_2, +) +``` + +Unmodified instances share model objects and parameters. Use instance +overrides for one plant and `Override(...)` for exceptional organs. + +## Multirate Inputs + +Replace `TimeStepModel(...)` with `ModelSpec(...; every=...)`. Put temporal policy and +window information on the consuming `ModelSpec(...; inputs=...)` selector. + +```julia +ModelSpec(HourlyLeafModel(); name=:leaf_flux, on=Many(scale=:Leaf), every=Hour(1)) + +ModelSpec(DailyPlantModel(); name=:daily_plant, on=Many(scale=:Plant), inputs=(:leaf_fluxes => Many( + scale=:Leaf, + within=Subtree(), + application=:leaf_flux, + var=:flux, + policy=Integrate(), + window=Day(1), + ),), every=Day(1)) +``` + +Use `HoldLast()`, `Interpolate()`, `Integrate()`, or `Aggregate()` according to +the physical meaning of the input. `PreviousTimeStep(:x) => selector` expresses +an explicit lag and breaks a same-timestep dependency cycle. + +If the input selector omits `policy=...`, the model compiler uses the +producer's `output_policy(...)` trait for the selected source variable when the +publisher is unique. An explicit selector policy always wins over the trait. + +If a model defines `timespec(::Type{<:MyModel})`, the model scheduler uses that +cadence when the application has no explicit `ModelSpec(...; every=...)`. A scenario-level +`ModelSpec(...; every=...)` always wins over the model trait. + +If the clock falls back to the model base step, `timestep_hint(...)` required +bounds are validated against that base step. The hint is a compatibility +constraint, not a scheduling override. + +## Ordered Variable Updates + +When several models intentionally write the same variable, declare the order +on the later application: + +```julia +ModelSpec(CarbonAllocation(); name=:allocation, on=Many(scale=:Leaf)) + +ModelSpec(LeafPruning(); name=:pruning, on=Many(scale=:Leaf), updates=Updates(:leaf_biomass; after=:allocation)) +``` + +Do not encode this coupling in either model implementation. The scenario owns +the writer order. + +## Environment And Microclimate + +Models declare sampled environment variables with `environment_inputs_`. The scenario +binds each object/application to the active environment backend: + +```julia +ModelSpec(LeafEnergy(); name=:leaf_energy, on=Many(scale=:Leaf), environment=Environment(provider=:grid)) +``` + +Spatial bindings are cached. The default resolver uses the object's geometry, +then the nearest ancestor geometry, then the backend's global behavior. +Changing geometry invalidates only affected environment bindings. + +Per-model source remapping also moves to `Environment(...)`: + +```julia +ModelSpec(LeafGasExchange(); name=:gas_exchange, on=Many(scale=:Leaf), environment=Environment(provider=:global, sources=(CO2=:Ca,))) +``` + +The model still declares and reads `CO2`; the model samples `Ca` from the +active environment backend and exposes it to the model as `environment.CO2`. +`Diagnostics.explain_environment_bindings(...)` reports both `required_inputs` and +`source_inputs`, so remapped meteorology is visible to users and agents. + +Model authors can also provide default source remaps with +`environment_hint(::Type{<:Model}) = (bindings=(CO2=(source=:Ca,),),)`. CompositeModel +applications use those defaults when the scenario does not provide an explicit +source for the same variable. `Environment(; sources=...)` remains the +scenario-level override. + +For global `Weather` tables, sampling follows the application's +`ModelSpec(...; every=...)`. A slower model receives a PlantMeteo windowed sample using its +`environment_hint` reducer and window instead of receiving only the current raw +weather row. A scenario source override preserves that reducer: + +```julia +environment_hint(::Type{<:GasExchange}) = ( + bindings=(CO2=(source=:Ca, reducer=MeanReducer()),), +) + +ModelSpec(GasExchange(); on=Many(scale=:Leaf), every=Hour(2), environment=Environment(provider=:global, sources=(CO2=:canopy_CO2,))) +``` + +Every leaf still reads `environment.CO2`; the two-hour mean is computed from +`:canopy_CO2`. The sampled row is computed once per application and timestep, +then reused for all selected leaves. + +## Growth, Pruning, And Movement + +Use the public lifecycle operations: + +```julia +register_object!(model, new_leaf; parent=:plant_1) +new_leaf_status = add_organ!( + parent_node, + model, + :+, + :Leaf, + 3; + initial_status=(biomass=0.0,), +) +remove_object!(model, :old_leaf) +reparent_object!(model, :leaf_2, :axis_3) +move_object!(model, :leaf_3, new_geometry) +``` + +For MTG-backed growth, prefer `add_organ!`: it creates the MTG node and its +model object together and reuses the status initialization policy from +`CompositeModel(mtg; status=...)`. Use `register_object!` when adapting another topology +backend or when a complete `Object` already exists. + +Structural changes refresh application targets, input carriers, call targets, +writer validation, and schedules after the application that made the change. +New objects can therefore run applications that remain later in the current +timestep, but never applications that already ran. Geometry-only changes +refresh environment bindings without rebuilding unrelated structural bindings. + +The refreshed runtime also rebuilds homogeneous execution batches. Use +`Diagnostics.explain_execution_plan(scene_or_simulation)` to inspect the concrete +model/status/carrier types and the objects grouped into each specialized inner +loop. Exceptional per-object model overrides appear as separate ordered +batches. + +## Output Collection + +`run!(model; steps=...)` returns a `Simulation`. Use `final_state(sim)` for the +latest one-object state, `outputs(sim)` for retained typed streams, +`Diagnostics.explain_outputs(sim)` for structured diagnostics, and +`collect_outputs(sim)` for tabular rows. + +```julia +request = OutputRequest( + Many(scale=:Leaf), + :transpiration; + name=:leaf_transpiration_daily, + application=:leaf_energy, + policy=Integrate(), + clock=Day(1), +) + +sim = run!(model; steps=48, outputs=request) +daily = collect_outputs(sim, :leaf_transpiration_daily) +``` + +CompositeModel output requests are materialized from retained temporal streams after +the run. They use the same temporal policies as multirate inputs and export +dynamic objects only over the interval where that object published samples. +If several model applications implement the same process, add +`application=:application_name` to select one explicitly. This is also the +way to request a named `:stream_only` publisher. +`outputs=:none` retains no user streams. Passing explicit requests retains only +their application/variable streams plus streams needed by temporal +`ModelSpec(...; inputs=...)`. Use `Diagnostics.explain_output_retention(sim)` +to inspect why each retained stream was kept. Dependency-only streams retain a +bounded policy-specific horizon, while requested streams keep complete +histories for post-run export. Export is not yet a fully online path. + +## Inspecting The Compiled Scenario + +Use structured explanations instead of inspecting internal dictionaries: + +```julia +Diagnostics.explain_objects(model) +Diagnostics.explain_instances(model) +Diagnostics.explain_scopes(model) +Diagnostics.explain_applications(model) +Diagnostics.explain_bindings(model) +Diagnostics.explain_calls(model) +Diagnostics.explain_environment_bindings(model) +Diagnostics.explain_schedule(model) +Diagnostics.explain_writers(model) +``` + +These functions return structured rows with concrete object ids, application +ids, processes, variables, temporal policies, carrier semantics, and resolved +targets. They are intended for both users and coding agents. + +## Migration Table + +| Legacy configuration | CompositeModel/object replacement | +| --- | --- | +| `ModelMapping` scale assembly | `CompositeModel` objects plus model applications | +| `MultiScaleModel(...)` | consumer `ModelSpec(...; inputs=...)` | +| `TimeStepModel(...)` | `ModelSpec(...; every=...)` | +| `InputBindings(...)` | source, policy, and window on `ModelSpec(...; inputs=...)` | +| `MeteoBindings(...)` | automatic environment binding or `Environment(...)` | +| `ScopeModel(...)` | `ModelSpec(...; on=...)` and selector scopes | +| `SameScale()` rename | `inputs=(:local => One(within=Self(), var=:source),)` | + +The executable MAESPA migration in +`examples/maespa_model_example.jl` demonstrates two plant species, shared +soil, plant-local aggregation, model-wide iterative energy balance, hourly and +daily models, and automatic environment binding. diff --git a/docs/src/model_coupling/model_coupling_user.md b/docs/src/model_coupling/model_coupling_user.md deleted file mode 100644 index b24be6931..000000000 --- a/docs/src/model_coupling/model_coupling_user.md +++ /dev/null @@ -1,173 +0,0 @@ -# Model coupling for users - -```@setup usepkg -using PlantSimEngine, PlantMeteo, Dates -# Import the example models defined in the `Examples` sub-module: -using PlantSimEngine.Examples - -m = ModelMapping( - Process1Model(2.0), - Process2Model(), - Process3Model(), - Process4Model(), - Process5Model(), - Process6Model(), - Process7Model(), -) -``` - -`PlantSimEngine.jl` is designed to make model coupling simple for both the modeler and the user. For example, `PlantBiophysics.jl` implements the [`Fvcb`](https://vezy.github.io/PlantBiophysics.jl/stable/functions/#PlantBiophysics.Fvcb) model to simulate the photosynthesis process. This model needs the stomatal conductance process to be simulated, so it calls again `run!` inside its implementation at some point. Note that it does not force any kind of conductance model over another, just that there is one to simulate the process. This ensures that users can choose whichever model they want to use for this simulation, independent of the photosynthesis model. - -We provide an example script that implements seven dummy processes in [`examples/dummy`](https://github.com/VirtualPlantLab/PlantSimEngine.jl/blob/main/examples/dummy.jl). The processes are simply called "process1", "process2"..., and the model implementations are called `Process1Model`, `Process2Model`... - -## Hard coupled models - -The `Process3Model` calls `Process2Model`, and `Process2Model` calls `Process1Model`. This explicit call is called a hard-dependency in PlantSimEngine. - -The other models for the other processes are called `Process4Model`, `Process5Model`... and they do not call explicitly other models when running, but some outputs of the models are used as inputs of other models. This is called a soft-dependency in PlantSimEngine. - -!!! tip - Hard-coupling of models is usually done when there are some kind of iterative computation in one of the models that depend on one another. This is not the case in our example here as it is obviously just a simple one. In this case the coupling is not really necessary as models could just be called sequentially one after the other. For a more representative example, you can look at the energy balance computation of Monteith in `PlantBiophysics.jl`, which is hard-coupled to a photosynthesis model. - -Back to our example, using `Process3Model` requires a "process2" model, and in our case the only model available is `Process2Model`. The latter also requires a "process1" model, and again we only have one model implementation for this process, which is `Process1Model`. - -Let's use the `Examples` sub-module so we can play around: - -```julia -# Import the example models defined in the `Examples` sub-module: -using PlantSimEngine.Examples -``` - -!!! tip - Use subtype(x) to know which models are available for a process, e.g. for "process1" you can do `subtypes(AbstractProcess1Model)`. - -Here is how we can make the model coupling: - -```@example usepkg -m = ModelMapping(Process1Model(2.0), Process2Model(), Process3Model()) -nothing # hide -``` - -We can see that only the first model has a parameter. You can usually know that by looking at the help of the structure (*e.g.* `?Process1Model`), else, you can still look at the field names of the structure like so `fieldnames(Process1Model)`. - -Note that the user only declares the models, not the way the models are coupled because `PlantSimEngine.jl` deals with that automatically. - -Now the example above returns some warnings saying we need to initialize some variables: `var1` and `var2`. `PlantSimEngine.jl` automatically computes which variables should be initialized based on the inputs and outputs of all models, considering their hard or soft-coupling. - -For example, `Process1Model` requires the following variables as inputs: - -```@example usepkg -inputs(Process1Model(2.0)) -``` - -And `Process2Model` requires the following variables: - -```@example usepkg -inputs(Process2Model()) -``` - -We see that `var1` is needed as inputs of both models, but we also see that `var3` is an output of `Process2Model`: - -```@example usepkg -outputs(Process2Model()) -``` - -So considering those two models, we only need `var1` and `var2` to be initialized, as `var3` is computed. This is why we recommend [`to_initialize`](@ref) instead of [`inputs`](@ref), because it returns only the variables that need to be initialized, considering that some inputs are duplicated between models, and some are computed by other models (they are outputs of a model): - -```@example usepkg -m = ModelMapping( - Process1Model(2.0), - Process2Model(), - Process3Model(), - variables_check=false # Just so we don't have the warning printed out -) - -to_initialize(m) -``` - -The most straightforward way of initializing a model list is by giving the initializations to the `status` keyword argument during instantiation: - -```@example usepkg -m = ModelMapping( - Process1Model(2.0), - Process2Model(), - Process3Model(), - status = (var1=15.0, var2=0.3) -) -nothing # hide -``` - -Our component models structure is now fully parameterized and initialized for a simulation! - -Let's simulate it: - -```@example usepkg -using PlantMeteo -meteo = Atmosphere(T = 22.0, Wind = 0.8333, P = 101.325, Rh = 0.4490995) - -run!(m, meteo) - -m[:var5] -``` - - -## Soft coupled models - -All following models (`Process4Model` to `Process7Model`) do not call explicitly other models when running, but some outputs of the models are used as inputs of other models. This is called a soft-dependency in PlantSimEngine. - -Let's make a new model list including the soft-coupled models: - -```@example usepkg -m = ModelMapping( - Process1Model(2.0), - Process2Model(), - Process3Model(), - Process4Model(), - Process5Model(), - Process6Model(), - Process7Model(), -) -nothing # hide -``` - -With this list of models, we only need to initialize `var0`, that is an input of `Process4Model` and `Process7Model`: - -```@example usepkg -to_initialize(m) -``` - -We can initialize it like so: - -```@example usepkg -m = ModelMapping( - Process1Model(2.0), - Process2Model(), - Process3Model(), - Process4Model(), - Process5Model(), - Process6Model(), - Process7Model(), - status = (var0=15.0,) -) -nothing # hide -``` - -Let's simulate it: - -```@example usepkg -using PlantMeteo -meteo = Atmosphere(T = 22.0, Wind = 0.8333, P = 101.325, Rh = 0.4490995) - -run!(m, meteo) - -status(m) -``` - -## Simulation order - -When calling `run!`, the models are run in the right order using a dependency graph that is computed automatically based on the hard and soft dependencies of the models following a simple set of rules: - -1. Independent models are run first. A model is independent if it can be run alone, or only using initializations. It is not dependent on any other model. -2. From their children dependencies: - 1. Hard dependencies are always run before soft dependencies. Inner hard dependency graphs are considered as a whole, *i.e.* as a single soft dependency. - 2. Soft dependencies are then run sequentially. If a soft dependency has several parent nodes (*i.e.* its inputs are computed by several models), it is run only if all its parent nodes have been run already. In practice, when we visit a node that has one of its parent that did not run already, we stop the visit of this branch. The node will eventually be visited from the branch of the last parent that was run. diff --git a/docs/src/model_execution.md b/docs/src/model_execution.md index 3d1c575f3..0a0352dd7 100644 --- a/docs/src/model_execution.md +++ b/docs/src/model_execution.md @@ -1,219 +1,404 @@ -# Model execution +# Model Execution -## Simulation order +This page describes how the native composite-model/object runtime executes model +applications. Use this path for new multi-object, multi-plant, soil, +microclimate, and multirate simulations. -`PlantSimEngine.jl` uses the [`ModelMapping`](@ref) to automatically compute a dependency graph between the models and run the simulation in the correct order. When running a simulation with [`run!`](@ref), the models are then executed following this simple set of rules: +The public configuration surface has one application constructor: -1. Independent models are run first. A model is independent if it can be run independently from other models, only using initializations (or nothing). -2. Then, models that have a dependency on other models are run. The first ones are the ones that depend on an independent model. Then the ones that are children of the second ones, and then their children ... until no children are found anymore. There are two types of children models (*i.e.* dependencies): hard and soft dependencies: - 1. Hard dependencies are always run before soft dependencies. A hard dependency is a model that is directly called by another model. It is declared as such by its parent that lists its hard-dependencies as `dep`. See [this example](https://github.com/VirtualPlantLab/PlantSimEngine.jl/blob/3d91bb053ddbd087d38dcffcedd33a9db35a0fcc/examples/dummy.jl#L39) that shows `Process2Model` defining a hard dependency on any model that simulates `process1`. - 2. Soft dependencies are then run sequentially. A model has a soft dependency on another model if one or more of its inputs is computed by another model. If a soft dependency has several parent nodes (*e.g.* two different models compute two inputs of the model), it is run only if all its parent nodes have been run already. In practice, when we visit a node that has one of its parent that did not run already, we stop the visit of this branch. The node will eventually be visited from the branch of the last parent that was run. +```julia +ModelSpec( + model; + name=:application, + on=Many(scale=:Leaf), + inputs=(...), + calls=(...), + every=Dates.Hour(1), + environment=Environment(...), + output_routing=(...), + updates=Updates(...), +) +``` -## Multi-rate model configuration (experimental) - -For multiscale simulations, model usage is configured in the mapping through `ModelSpec` transforms: - -- `TimeStepModel(...)`: sets model execution clock. -- `InputBindings(...)`: sets producer, source variable, optional source scale, and policy for each consumer input. -- `MeteoBindings(...)`: sets weather aggregation rules at the model clock for meteo variables. -- `MeteoWindow(...)`: sets weather row selection strategy (`RollingWindow()` or `CalendarWindow(...)`). -- `OutputRouting(...)`: sets whether an output is canonical (`:canonical`) or stream-only (`:stream_only`). -- `ScopeModel(...)`: partitions producer streams by scope (`:global`, `:plant`, `:scene`, `:self`) for multi-entity simulations. +Scenarios start from `CompositeModel` and model applications. -For a compact overview of all model traits and precedence rules, see [Model traits](model_traits.md). +## Model Kernels And Applications -If users do not provide `MeteoBindings(...)` or `MeteoWindow(...)`, -the runtime can infer defaults from model traits: -- `timespec(::Type{<:MyModel})` -- `output_policy(::Type{<:MyModel})` -- `timestep_hint(::Type{<:MyModel})` -- `meteo_hint(::Type{<:MyModel})` +A model kernel is still an ordinary PlantSimEngine model: -For timestep specifically, runtime is meteo-first (see decision flow below): `timestep_hint` -is used for compatibility validation (and user guidance), not to auto-assign model clocks. +- `inputs_(model)` declares each status input as `Required(T)` or + `Default(value)`; +- `outputs_(model)` declares variables the model computes and their initial + output-state values; +- `environment_inputs_(model)` declares environment variables it reads; +- `commit_environment!(context, state)` commits accepted mutable environment + state when the model intentionally controls microclimate; +- `dep(model)` may declare model-author defaults; +- `run!(model, status, environment, constants, context)` contains the model +equations. -If users do not provide `InputBindings(...)`, runtime infers same-name bindings: -- first from a unique producer at the same scale; -- otherwise from a unique producer at another scale; -- if no producer exists, input stays unresolved (so initialization/forced values can be used); -- if multiple producers are possible, runtime errors and asks for explicit `InputBindings(...)`. +`Required(T)` has no initialization value: object state or a producer +application must satisfy it. `Default(value)` is installed only when the target +does not already have the input. Plain input literals are rejected because +they are ambiguous. -For inferred bindings, default policy is resolved as: -- producer `output_policy` for the source output when defined; -- otherwise `HoldLast()`. +The composite-model/object layer does not change that kernel contract. It adds a +scenario-specific application around the kernel: -`output_policy` is a default hint, applied only when an output stream is actually read -by another model input (or output export). Unused outputs do not trigger integration/reduction work. +```julia +ModelSpec( + LeafEnergyBalance(); + name=:leaf_energy, + on=Many(kind=:plant, scale=:Leaf), + inputs=(...), + calls=(...), + every=Dates.Hour(1), + environment=Environment(provider=:canopy), +) +``` -Explicit mapping policies still have priority (`InputBindings(..., policy=...)`) and can -complement trait defaults by defining additional bindings with different policies. +`ModelSpec` decides where the model runs, where its inputs come from, which +models it may call manually, which timestep it uses, and which environment +provider is bound to it. The model implementation stays reusable. -For timestep hints: -- `timestep_hint.required` is a hard compatibility constraint when runtime uses meteo-derived timestep. -- `timestep_hint.preferred` is informational only (it does not set runtime timestep by itself). -- Explicit `TimeStepModel(...)` always takes precedence. +## Compilation Before Runtime -For meteo hints: -- return `(; bindings=..., window=...)` where `bindings` matches `MeteoBindings(...)` - and `window` matches `MeteoWindow(...)`. -- Explicit `MeteoBindings(...)` / `MeteoWindow(...)` always take precedence. +Before the timestep loop, PlantSimEngine compiles the model into concrete +runtime carriers: -Inspection helpers: -- `resolved_model_specs(mapping)` returns resolved specs after inference/validation. -- `explain_model_specs(mapping_or_sim)` prints a compact summary (`timestep`, - `input_bindings`, `meteo_bindings`, `meteo_window`) for each model process. +1. `ModelSpec(...; on=...)` selectors are resolved to stable object ids. +2. `ModelSpec(...; inputs=...)` selectors are resolved to source object/application ids. +3. Same-rate inputs are wired as shared `Ref`s, `RefVector`s, or + heterogeneous object-reference vectors. +4. Temporal inputs are compiled as stream lookups with a policy such as + `HoldLast`, `Interpolate`, `Integrate`, or `Aggregate`. +5. `ModelSpec(...; calls=...)` declarations are compiled to callable target lists. +6. `Environment(...)` is bound to backend cells, layers, voxels, or global + weather providers. +7. The root application order is topologically sorted from value inputs and + `Updates(...)` ordering. +8. Root execution batches are grouped by concrete model/status/environment + types where possible. -Policy parameterization: -- `Integrate()` defaults to `SumReducer()`; you can pass another reducer, e.g. `Integrate(MeanReducer())` or `Integrate(vals -> maximum(vals) - minimum(vals))`. -- `Aggregate()` defaults to `MeanReducer()`; you can pass reducers such as `Aggregate(MaxReducer())`. -- Difference between `Integrate` and `Aggregate`: with the same reducer they are runtime-equivalent. - In practice, only defaults and naming intent differ (`Integrate` for accumulation, `Aggregate` for summary statistics). -- `Interpolate()` defaults to `mode=:linear, extrapolation=:linear`; use `Interpolate(; mode=:hold, extrapolation=:hold)` for hold behavior. -- The same reducer objects are reused by meteo sampling (`MeteoBindings`) and by windowed policies (`Integrate`, `Aggregate`). -- Custom reducers/callables can accept either `(values)` or `(values, durations_seconds)`. -- For flux-to-amount conversions, use `Integrate(PlantMeteo.DurationSumReducer())` - (equivalent to `sum(values .* durations_seconds)`), instead of hardcoding a fixed factor. +Selectors are not resolved in the hot loop. Runtime execution uses the +compiled indexes and carriers. -`TimeStepModel(...)` accepts either step counts (`Real`), `ClockSpec`, or fixed `Dates` periods -(for example `Dates.Hour(1)`, `Dates.Day(1)`). Fixed periods are converted internally using -the meteo base timestep duration. +Useful inspection helpers: -### Timestep decision flow +```julia +Diagnostics.explain_applications(model) +Diagnostics.explain_bindings(model) +Diagnostics.explain_calls(model) +Diagnostics.explain_environment_bindings(model) +Diagnostics.explain_schedule(model) +Diagnostics.explain_execution_plan(model) +Diagnostics.explain_writers(model) +``` -When meteo is provided, `duration` is mandatory for each row (or the simulation errors). +These explanations are intended for both users and agents. They report the +compiled object ids, applications, carriers, clocks, environment bindings, and +manual-call targets that the runtime will use. -Runtime picks each model effective clock with this order: +## Soft Dependencies With Inputs -1. If `ModelSpec` has `TimeStepModel(...)`, use it. -2. Else if `timespec(model)` is non-default, use it. -3. Else use meteo base timestep (`duration`) for that model. +Soft dependencies are value dependencies. A consumer model reads a variable +produced by another model through `ModelSpec(...; inputs=...)`. -Then runtime applies constraints: +```julia +ModelSpec(SceneLAI(ground_area); name=:scene_lai, on=One(scale=:Scene), inputs=(:leaf_areas => Many( + kind=:plant, + scale=:Leaf, + within=SceneScope(), + application=:leaf_state, + var=:leaf_area, + ),)) +``` + +For same-rate inputs, the runtime installs a reference carrier into the +consumer status during compilation. A model-scale model reading all leaf areas +therefore sees a `RefVector`-like object: reading pulls current values from +source leaf statuses, and writing through the carrier mutates source refs when +the carrier supports it. + +If an input is not explicitly declared with `ModelSpec(...; inputs=...)`, the compiler can +infer simple same-object bindings when exactly one producer on the same object +outputs the same variable. Ambiguous producers are errors and should be +disambiguated with `application=...` and, when names differ, `var=...`. -1. If the model clock is meteo-derived (rule 3), `timestep_hint.required` is validated: - - fixed required period: meteo timestep must match exactly; - - required range: meteo timestep must be inside the range. -2. `timestep_hint.preferred` never overrides the clock when timestep is unset. -3. Meteo aggregation/integration is applied only when effective model timestep is coarser than meteo timestep. +Use `PreviousTimeStep(:x) => selector` when a feedback dependency should read +the previous sample instead of creating a same-timestep scheduling edge. -Practical consequences: +## Hard Calls With Calls -- Unset `TimeStepModel` + required includes meteo + preferred is coarser: - model still runs at meteo timestep. -- Explicit coarser `TimeStepModel(Dates.Hour(2))` with hourly meteo: - model runs every 2 hours and receives aggregated meteo over that window. -- Unset `TimeStepModel` + required excludes meteo: - runtime errors with an actionable compatibility message. - -Developer note on period conversion: -- Runtime time is indexed on a 1-based timeline (`t = 1, 2, 3, ...`). -- `TimeStepModel(Dates.Day(1))` is converted to a clock step count using: - `dt = day_seconds / meteo_step_seconds`. -- For hourly meteo (`duration = Dates.Hour(1)`), this gives `dt = 24` and the default phase is `1`, - so the model runs at `t = 1, 25, 49, ...`. -- This is equivalent to `ClockSpec(24.0, 1.0)`. -- If you need runs at `t = 24, 48, 72, ...`, set an explicit phase with `ClockSpec(24.0, 0.0)`. - -Typical pipeline form: +Hard dependencies are manual calls. Use `ModelSpec(...; calls=...)` when a parent model must +control the call stack, for example during an iterative energy-balance solve. ```julia -ModelSpec(MyModel()) |> -TimeStepModel(ClockSpec(24.0, 1.0)) |> -MeteoWindow(CalendarWindow(:day; anchor=:current_period, week_start=1, completeness=:strict)) |> -MeteoBindings(; T=MeanWeighted()) |> -InputBindings(; x=(process=:producer, var=:y, policy=HoldLast())) |> -OutputRouting(; z=:stream_only) +ModelSpec(SceneEnergyBalance(); name=:scene_energy, on=One(scale=:Scene), calls=(:leaf_energy => Many( + kind=:plant, + scale=:Leaf, + within=SceneScope(), + application=:energy_balance, + ), + :soil => One( + kind=:soil, + scale=:Soil, + within=SceneScope(), + application=:soil_water, + ),), every=Dates.Hour(1)) ``` -### Calendar-aligned meteo windows +Inside `run!`, the parent can execute every resolved target directly. The +return value is always vector-like: `One` returns one element, `OptionalOne` +returns zero or one, and `Many` returns zero or more. -`MeteoWindow(...)` controls how rows are selected before reducers are applied: -- `RollingWindow()` (default): trailing window based on `dt` (for example "last 24 steps"). -- `CalendarWindow(period; anchor, week_start, completeness)`: -: `period` in `:day`, `:week`, `:month` -: `anchor` in `:current_period`, `:previous_complete_period` -: `week_start` in `1:7` (1 = Monday) -: `completeness` in `:allow_partial`, `:strict` +```julia +soil_targets = run_call!(context, :soil; publish=true) +soil_status = only(soil_targets).status +``` -`CalendarWindow(:day; anchor=:current_period, ...)` guarantees that a model running inside a day sees -aggregates over that civil day (including later timesteps from that day when available). +For finer-grained iterative control, retrieve targets without executing them +and decide when to publish the accepted state: -### Hold-last coupling (default policy) +```julia +function PlantSimEngine.run!(model::SceneEnergyBalance, status, environment, + constants, context) + trial = trial_environment(model, status) + run_call!(context, :leaf_energy; environment=trial, publish=false) + + accepted = accepted_environment(model, status) + commit_environment!(context, accepted) + run_call!(context, :leaf_energy; publish=true) + + return nothing +end +``` + +`run_call!` defaults to `publish=false`. Trial calls mutate target statuses but +do not publish temporal samples or commit mutable environment updates. Use +`environment=trial_state` when hard-called descendants should sample temporary +state through their compiled environment handles. Call `commit_environment!` and +`run_call!(...; publish=true)` once for the accepted state. + +Applications selected only by `ModelSpec(...; calls=...)` are marked manual-call-only in +`Diagnostics.explain_schedule(model)` and are skipped by the root `run!(model)` loop. + +## Duplicate Writers With Updates + +By default, one application owns each `(object, output variable)` canonical +writer. If a scenario intentionally lets several models update the same +variable, later writers must declare that order explicitly: ```julia -mapping = ModelMapping( - :Leaf => ( - ModelSpec(LeafSourceModel()) |> TimeStepModel(1.0), - ModelSpec(LeafConsumerModel()) |> - TimeStepModel(ClockSpec(2.0, 1.0)) |> - InputBindings(; C=(process=:leafsource, var=:S)), - ), -) +ModelSpec(CarbonAllocation(); name=:carbon_allocation, on=Many(scale=:Leaf)) + +ModelSpec(LeafPruning(); name=:leaf_pruning, on=Many(scale=:Leaf), updates=Updates(:leaf_biomass; after=:carbon_allocation)) ``` -### Daily integration from hourly stream +This keeps ordinary duplicate outputs as errors while allowing cases such as +allocation followed by pruning. `Diagnostics.explain_writers(model)` reports writer +groups and the `Updates(...)` declarations that validate them. +The `after` value is the canonical application identifier shown by +`Diagnostics.explain_applications(model)`, not the process name. + +## Multirate Execution + +Use `ModelSpec(...; every=...)` with `Dates.Period` values for model application clocks: ```julia -mapping = ModelMapping( - :Leaf => ( - ModelSpec(HourlyAssimModel()) |> TimeStepModel(1.0), - ), - :Plant => ( - ModelSpec(DailyCarbonOfferModel()) |> - TimeStepModel(ClockSpec(24.0, 1.0)) |> - InputBindings(; A=(process=:hourlyassim, var=:A, scale=:Leaf, policy=Integrate())), - ), -) +ModelSpec(HourlyLeafAssimilation(); name=:leaf_assim, on=Many(scale=:Leaf), every=Dates.Hour(1)) + +ModelSpec(DailyPlantAllocation(); name=:allocation, on=Many(scale=:Plant), inputs=(:leaf_assimilation => Many( + scale=:Leaf, + within=Subtree(), + application=:leaf_assim, + var=:A, + policy=Integrate(), + window=Dates.Day(1), + ),), every=Dates.Day(1)) +``` + +Clock precedence is: + +1. explicit `ModelSpec(...; every=...)` on the `ModelSpec`; +2. non-default `timespec(model)` trait; +3. the model environment base step. + +`timestep_hint(model)` is a compatibility constraint and explanation hint. It +does not silently choose a clock. If a model uses the environment base step and +that step violates `timestep_hint.required`, model compilation errors. + +Temporal input policy precedence is: + +1. explicit selector policy, such as `policy=Integrate()`; +2. producer `output_policy(model)` for that output; +3. `HoldLast()`. + +Supported policies are: + +- `HoldLast()`: use the latest producer sample; +- `Interpolate()`: interpolate or extrapolate from producer samples; +- `Integrate()`: reduce values over a window, defaulting to `SumReducer()`; +- `Aggregate()`: reduce values over a window, defaulting to `MeanReducer()`. + +`Integrate(...)` and `Aggregate(...)` accept reducer objects or callables that +take either `(values)` or `(values, durations_seconds)`. +For duration-aware reducers, each producer value is held until the next +producer execution and weighted by the portion of that interval overlapping +the consumer window. This includes the last value published before the window +when it remains active inside the window. + +Temporal windows are duration-based rolling windows. Calendar-aligned civil +days and "previous complete period" selection are not part of the public API; +there is no `CalendarWindow` compatibility type. + +## Environment Sampling + +`Environment(...)` chooses a provider and optional source-variable remapping: + +```julia +ModelSpec(CO2Probe(); name=:co2_probe, on=Many(scale=:Leaf), environment=Environment(provider=:canopy, sources=(CO2=:Ca,))) ``` -### Interpolate slow producer to fast consumer +The compiler binds each application/object pair to the selected backend before +runtime. Constant weather, global tabular meteorology, grid, layer, voxel, or +octree-style microclimate backends all use the same contract: + +- `environment_inputs_(model)` says what the model reads; +- `environment_outputs_(model)` says what the model may commit; +- `commit_environment!(context, accepted_environment)` commits accepted mutable + meteorology from a controller model; +- `run_call!(context, name; environment=trial_state)` exposes non-committing + trial state while preserving every target's compiled backend handle; +- `Environment(; sources=...)` maps model-facing names to backend names; +- geometry and position are used by spatial backends when available; +- object-to-environment links are cached and refreshed when objects move. + +Backend authors implement an opaque-handle protocol: ```julia -mapping = ModelMapping( - :Leaf => ( - ModelSpec(SlowSourceModel()) |> TimeStepModel(ClockSpec(2.0, 1.0)), - ModelSpec(FastConsumerModel()) |> - TimeStepModel(1.0) |> - InputBindings(; X=(process=:slowsource, var=:X, policy=Interpolate())), - ), -) +handle = EnvironmentAPI.bind_environment(backend, object, context, config) + +EnvironmentAPI.sample(backend, handle, variable, time) # committed state +EnvironmentAPI.sample(backend, handle, trial_state, variable, time) # transient state +commit_environment!(backend, handle, accepted_state, time) ``` -When the `ModelMapping` declares multirate configuration, the runtime resolves inputs from producer temporal streams according to these policies. -Meteo rows are also sampled at each model clock. By default, meteo variables are aggregated from -the finest weather step (for example `T` and `Rh` as weighted means, `Tmin/Tmax`, and radiation -quantity aliases such as `Ri_SW_q` in MJ m-2). You can override these rules with `MeteoBindings(...)` -on each `ModelSpec`. +`EnvironmentAPI.EnvironmentContext` identifies the application, object, scale, and process +while the handle is compiled. Runtime status and geometry are not passed to +sampling: a spatial backend resolves them once in `EnvironmentAPI.bind_environment` and stores +the resulting provider, layer, voxel, or other routing data in its concrete +handle. A controller that reads from one provider and commits to another should +encode both routes in the handle, for example +`Environment(provider=:forcing, sink=:canopy)`. + +Model-level `environment_hint(...)` can provide default source bindings and +aggregation rules. Scenario-level `Environment(...)` keeps precedence for +source names, while explicit sampling policy on `ModelSpec(...; inputs=...)` controls +model-to-model temporal values. -### Current limitations +## Running And Outputs -- Multi-rate MTG runs currently execute sequentially. Passing `executor=ThreadedEx()` or `executor=DistributedEx()` falls back to sequential execution with a warning. -- Sub-step execution is currently unsupported: model timesteps shorter than the meteo base step (for example `TimeStepModel(Dates.Minute(30))` with hourly meteo) raise an error. +Run a model with: -## Multi-rate output export (experimental) +```julia +sim = run!(model; steps=30) +``` -You can export selected variables at a requested rate from temporal streams: +The returned `Simulation` contains the mutated model, compiled bindings, +environment bindings, execution plan, and retained temporal output streams. + +By default, model runs retain no user output streams. Pass `outputs=:all` to +retain every published stream, or pass `OutputRequest` values to retain only +selected outputs and required temporal dependency streams: ```julia -req = OutputRequest(:Leaf, :carbon_assimilation; - name=:A_daily, - process=:toyassim, +request = OutputRequest( + Many(scale=:Leaf), + :A; + name=:leaf_assimilation_daily, + application=:leaf_assimilation, policy=Integrate(), - clock=ClockSpec(24.0, 1.0) + clock=Dates.Day(1), ) -run!(sim, meteo; tracked_outputs=[req], executor=SequentialEx()) -exported = collect_outputs(sim; sink=DataFrame) +sim = run!(model; steps=72, outputs=request) +collect_outputs(sim, :leaf_assimilation_daily; sink=nothing) +Diagnostics.explain_output_retention(sim) +``` + +When several applications publish the same process and variable, use +`application=:application_name` in the request. This selects the named +application directly and can also request an explicitly named +`:stream_only` publisher. + +`outputs=:none` retains no user output streams. Histories required by temporal +dependencies are still maintained with bounded retention. + +`run!(model; ...)` always starts a fresh result timeline. Continue an existing +simulation without resetting its step index, environment position, multirate +phase, or temporal histories with: + +```julia +continue!(sim; steps=24) +step!(sim) +current_step(sim) ``` -`tracked_outputs` accepts `OutputRequest` values for these resampled exports. -You can also return them directly from `run!`: +Temporal dependency streams that are not explicitly requested retain only the +history required by their input policy. `HoldLast` keeps the latest sample, +`Integrate` and `Aggregate` keep their input window, and `Interpolate` and +`PreviousTimeStep` keep sufficient recent source samples. Requested streams +retain complete histories for post-run export. `Diagnostics.explain_output_retention(sim)` +reports `retention_steps` for bounded dependency-only streams and `nothing` +for full-history streams. + +## Lifecycle Changes + +CompositeModel objects may be added, removed, reparented, moved, or have their geometry +updated between or during timesteps: ```julia -out_status, exported = run!( - sim, - meteo; - tracked_outputs=[req], - return_requested_outputs=true, +register_object!(model, Object(:new_leaf; scale=:Leaf); parent=:plant_1) +leaf_status = add_organ!( + parent_node, + model, + :+, + :Leaf, + 3; + index=4, + attributes=(area=0.01,), + initial_status=(biomass=0.0,), ) +remove_object!(model, :old_leaf) +reparent_object!(model, :leaf_3, :plant_2) +move_object!(model, :leaf_4, new_geometry) +update_geometry!(model, :leaf_5, new_geometry) ``` + +Use `add_organ!` for an MTG-backed model. It creates the MTG node, initializes +and attaches its `Status` with the model's MTG policy, registers the model +object, and invalidates the affected bindings. `register_object!` is the +low-level operation for callers that already own a complete `Object`. + +Structural changes invalidate compiled object/model bindings. Movement and +geometry changes invalidate environment bindings without rebuilding structural +input carriers. The next `run!` or `continue!` timestep refreshes the necessary +caches. + +Do not mutate `Object` topology, labels, or geometry fields directly. Direct +field mutation bypasses registry indexes and cache invalidation and is +unsupported. Use the lifecycle functions above. They validate prerequisites +before mutating; in particular, `reparent_object!` rejects self-parenting and +descendant cycles without changing existing links. `ObjectInstance` roots are +immutable lifecycle anchors: removing or reparenting a root, or an ancestor +whose subtree contains one, is rejected atomically. Ordinary descendants may +still be added, removed, or reparented. + +Inside a lifecycle-capable model kernel, use `runtime_model(context)` to obtain +the live model. Objects created during a kernel call do not recursively execute +inside that call. Structural targets, value carriers, call targets, writer +validation, schedules, and output-request matches are refreshed at the next +timestep boundary. Geometry-only mutations refresh affected environment +bindings at that boundary; already published streams remain available for +removed objects. diff --git a/docs/src/model_traits.md b/docs/src/model_traits.md index 6c9633451..58288c237 100644 --- a/docs/src/model_traits.md +++ b/docs/src/model_traits.md @@ -1,154 +1,123 @@ -# Model traits +# Model Traits -This page centralizes the model-level traits that can be defined in `PlantSimEngine`. -It complements: +Model traits describe intrinsic model behavior. Scenario-specific coupling +belongs in `ModelSpec` through `on`, `inputs`, `calls`, `every`, +`Environment`, `output_routing`, and `Updates`. -- [Model execution](model_execution.md) for runtime behavior, -- [Parallelization](step_by_step/parallelization.md) for execution over objects/time-steps. +## Variables -## Trait inventory for models - -### `timespec(::Type{<:MyModel})` - -Defines the default execution clock of a model. - -Default: +Implement `inputs_(model)` with an explicit declaration for every status input: ```julia -PlantSimEngine.timespec(::Type{<:AbstractModel}) = ClockSpec(1.0, 0.0) +PlantSimEngine.inputs_(::MyModel) = ( + leaf_area=Required(Float64), + efficiency=Default(0.8), +) +PlantSimEngine.outputs_(::MyModel) = (assimilation=0.0,) ``` -Use it when your model has a natural native clock (for example daily by default). +`Required(T)` means the value must be present on the target object's `Status` +or bound from another application. `T` is an expected type, not a placeholder +value. It may be abstract or parametric, so use the scientific type contract +instead of forcing `Float64`. -### `output_policy(::Type{<:MyModel})` +`Default(value)` means the model can run without user initialization or a +producer for that input. PlantSimEngine installs a private copy of `value` on +each target object when the value is absent. Mutable defaults are therefore +not shared between objects. -Defines per-output default schedule policy for produced streams. +Output literals remain initial output-state values. In the example, +`assimilation` starts at `0.0` before the first accepted model call. -Default: +These declarations are used for status initialization, dependency inference, +validation, and type construction. Plain input literals are rejected because +they do not say whether the value is required or genuinely optional. -```julia -PlantSimEngine.output_policy(::Type{<:AbstractModel}) = NamedTuple() -``` - -Behavior: +Use `init_variables(model)` to inspect only values PlantSimEngine can +initialize by itself: `Default` input values and output initial values. +Required inputs are intentionally omitted. -- unspecified outputs fall back to `HoldLast()`; -- used by runtime when resolving cross-clock reads; -- used as default policy for inferred `InputBindings(...)` when users do not provide explicit bindings; -- hint-only and lazy: policy is applied only for outputs that are actually consumed/exported. - Declaring a policy for an unused output does not trigger integration work. +Before running a scenario, `Diagnostics.explain_initialization(model)` classifies inputs as +`:required`, `:defaulted`, `:supplied`, or `:producer_bound`. A +`:required` row must be resolved before compilation can succeed. -Example: - -```julia -PlantSimEngine.output_policy(::Type{<:MyModel}) = ( - carbon_assimilation=Integrate(), - leaf_temperature=Aggregate(MeanReducer()), -) -``` +## Manual Dependencies -Users can always override or complement this trait at mapping level: +Implement `dep(model)` only when the model directly calls another process from +inside its own `run!` method: ```julia -ModelSpec(MyConsumerModel()) |> -InputBindings( - ; - carbon_assimilation=(process=:myproducer, var=:carbon_assimilation, policy=HoldLast()), # override trait default - carbon_assimilation_max=(process=:myproducer, var=:carbon_assimilation, policy=Aggregate(MaxReducer())), # complement with extra derived input +PlantSimEngine.dep(::EnergyBalance) = ( + photosynthesis=AbstractPhotosynthesisModel, ) ``` -### `timestep_hint(::Type{<:MyModel})` +The scenario binds the dependency with `ModelSpec(...; calls=...)`. The parent executes all +resolved targets with `run_call!(context, :photosynthesis)`, which always returns +a vector-like collection. Use `call_targets` plus `run_call!(target)` when the +parent needs selective trials and accepted publication. -Optional compatibility hint when `TimeStepModel(...)` is not provided. +## Timing -Default: +`timespec(model)` declares the model's default clock. The default is +`ClockSpec(1.0, 0.0)`. ```julia -PlantSimEngine.timestep_hint(::Type{<:AbstractModel}) = nothing +PlantSimEngine.timespec(::Type{<:DailyGrowth}) = ClockSpec(Dates.Day(1)) ``` -Supported forms include: +`output_policy(model)` declares the default temporal policy per output: -- fixed period: `Dates.Hour(1)`; -- range: `(Dates.Minute(30), Dates.Hour(2))`; -- named tuple: `(; required=..., preferred=...)`. +```julia +PlantSimEngine.output_policy(::Type{<:MyModel}) = ( + assimilation=Integrate(), + leaf_temperature=Aggregate(MeanReducer()), +) +``` -`required` is enforced when runtime uses meteo-derived timestep. -`preferred` is informational only. +Unspecified outputs use `HoldLast()`. A scenario can select another clock with +`ModelSpec(...; every=...)` and another input policy in `ModelSpec(...; inputs=...)`. -### `meteo_hint(::Type{<:MyModel})` +`timestep_hint(model)` can declare required or preferred timestep constraints. +`environment_hint(model)` can provide default environment sampling configuration. -Optional inference trait for weather sampling configuration. +## Environment Variables -Default: +Use `environment_inputs_(model)` for variables sampled from the active environment +backend: ```julia -PlantSimEngine.meteo_hint(::Type{<:AbstractModel}) = nothing +PlantSimEngine.environment_inputs_(::LeafEnergyBalance) = ( + T=0.0, + Rh=0.0, + Wind=0.0, + Ri_PAR_f=0.0, + CO2=400.0, +) ``` -Expected value: +Mutable microclimate updates should be committed explicitly by controller +models: ```julia -(; bindings=..., window=...) +commit_environment!(context, accepted_environment) ``` -Where: - -- `bindings` is compatible with `MeteoBindings(...)`, -- `window` is compatible with `MeteoWindow(...)`. - -### `TimeStepDependencyTrait(::Type{<:MyModel})` -### `ObjectDependencyTrait(::Type{<:MyModel})` - -Parallelization traits (single-scale runtime): - -- `TimeStepDependencyTrait`: depends or not on other timesteps; -- `ObjectDependencyTrait`: depends or not on other objects. - -Defaults are conservative (`dependent`) and can be overridden when safe. - -## Precedence rules - -Runtime precedence is intentionally explicit: - -1. Input policy: - explicit `InputBindings(..., policy=...)` > inferred from producer `output_policy` > `HoldLast()`. -1. Timestep: - `TimeStepModel(...)` > `timespec(model)` when non-default > meteo base step. -1. Meteo sampling: - explicit `MeteoBindings(...)`/`MeteoWindow(...)` > `meteo_hint(...)` > runtime defaults. +For trial solves, pass a backend-specific state with `environment` so each +hard-called model keeps its compiled provider or spatial handle: -## Is everything documented? - -For model-level traits, the documented set is now: - -- `timespec`, -- `output_policy`, -- `timestep_hint`, -- `meteo_hint`, -- `TimeStepDependencyTrait`, -- `ObjectDependencyTrait`. - -Outside model traits, `PlantSimEngine` also exposes data-format traits such as `DataFormat` for input containers (see [Input types](working_with_data/inputs.md)). - -## Naming conventions and API consistency - -Current API uses two naming styles on purpose: - -- snake_case for trait/query functions (`timespec`, `output_policy`, `timestep_hint`, `meteo_hint`); -- CamelCase for `ModelSpec` pipeline transforms (`TimeStepModel`, `InputBindings`, `MeteoBindings`, `MeteoWindow`, `OutputRouting`, `ScopeModel`). +```julia +run_call!(context, :leaf_energy; environment=trial_environment, publish=false) +``` -This distinction reflects role: +Diagnostic variables such as canopy temperature or vapor-pressure deficit can +still be regular `outputs_`, but status fields are not the transport mechanism +for mutable environment state. -- snake_case: "what the model declares"; -- CamelCase: "what the mapping config applies". +## Precedence -For future unification, a non-breaking path would be: +Scenario configuration has precedence over model defaults: -1. keep existing names as stable API, -1. avoid plain snake_case aliases that would collide with existing getter names - (`input_bindings`, `meteo_bindings`, `output_routing`, `model_scope`), -1. if needed, add explicit config-oriented aliases with distinct names - (for example `*_config` forms) and keep current constructors, -1. evaluate deprecations only after one full release cycle and user feedback. +1. `ModelSpec(...; inputs=...)` policy, then producer `output_policy`, then `HoldLast()`. +2. `ModelSpec(...; every=...)`, then `timespec(model)`, then the environment base step. +3. `Environment(...)`, then `environment_hint(model)`, then backend defaults. diff --git a/docs/src/multirate/advanced_configuration.md b/docs/src/multirate/advanced_configuration.md deleted file mode 100644 index 28197648b..000000000 --- a/docs/src/multirate/advanced_configuration.md +++ /dev/null @@ -1,208 +0,0 @@ -# Advanced multi-rate configuration - -This page collects the multi-rate features that were intentionally kept in the -background on the first two pages: - -- [Introduction to multi-rate execution](introduction.md) explains the core - scheduling rules; -- [Step-by-step multi-rate tutorial](multirate_tutorial.md) shows a complete - hourly/daily/weekly MTG example with minimal configuration; -- this page covers the explicit configuration tools you reach for when defaults - are no longer enough. - -The goal here is not to build another full simulation from scratch. Instead, the -objective is to explain when and why you should add more explicit multi-rate -declarations to a mapping. - -## 1. When the defaults are enough - -PlantSimEngine tries to keep simple mappings concise: - -- if a model does not declare `TimeStepModel(...)`, it follows the meteo - cadence; -- if an input has a unique producer, `InputBindings(...)` can often be omitted; -- if a model consumes common `Atmosphere` variables at a coarser cadence, - PlantMeteo default transforms can often replace explicit `MeteoBindings(...)`; -- if an exported variable has a unique canonical publisher, `OutputRequest(...)` - can often omit `process=`. - -The sections below focus on the cases where that implicit behavior becomes too -ambiguous or too limiting. - -## 2. Explicit model-to-model bindings with `InputBindings(...)` - -The tutorial pages rely on unique-producer inference plus `output_policy(...)` -declared on the source models. That is the simplest setup, but it stops being -enough as soon as several candidate producers exist or when you want to override -the default resampling rule. - -Use explicit `InputBindings(...)` when: - -- several models can produce the same input variable; -- the same process exists at several reachable scales; -- the source variable has a different name than the consumer input; -- the producer default policy is not the policy you want for this particular - connection. - -For example, a daily plant model may need to say explicitly that it consumes the -hourly leaf assimilation stream from the `:Leaf` scale and integrates it over -the day: - -```julia -plant_daily_spec = ModelSpec(TutorialPlantDailyModel()) |> - TimeStepModel(ClockSpec(24.0, 0.0)) |> - InputBindings(; - leaf_assim_h=( - process=:tutorialleafhourly, - scale=:Leaf, - var=:leaf_assim_h, - policy=Integrate(), - ), - ) -``` - -This is more verbose than inference, but the resulting mapping is also more -explicit: anyone reading it can see exactly where the data comes from and how it -is reduced. - -## 3. Explicit meteorological aggregation with `MeteoBindings(...)` - -For common `Atmosphere` variables, PlantSimEngine delegates weather sampling to -PlantMeteo, and PlantMeteo already defines default transforms. In practice, this -means you often do not need `MeteoBindings(...)` for variables such as `T`, -`Rh`, or aliases like `Ri_SW_q`. - -Add explicit `MeteoBindings(...)` when: - -- you want a non-default reducer; -- the target variable should come from a differently named source variable; -- the variable is not covered by PlantMeteo defaults; -- you want the mapping itself to document the intended weather aggregation rule. - -For example, this daily model makes the defaults explicit for temperature and -shortwave radiation energy: - -```julia -plant_daily_spec = ModelSpec(TutorialPlantDailyModel()) |> - TimeStepModel(ClockSpec(24.0, 0.0)) |> - MeteoBindings( - ; - T=MeanWeighted(), - Ri_SW_q=(source=:Ri_SW_f, reducer=RadiationEnergy()), - ) -``` - -And this variant shows a more genuinely custom rule: - -```julia -plant_daily_spec = ModelSpec(TutorialPlantDailyModel()) |> - TimeStepModel(ClockSpec(24.0, 0.0)) |> - MeteoBindings( - ; - T=(source=:T, reducer=MaxReducer()), - rad_peak=(source=:Ri_SW_f, reducer=MaxReducer()), - ) -``` - -The important point is that `MeteoBindings(...)` is not only about reducing -weather from fast to slow. It is also a way to state the semantics of that -reduction explicitly. - -## 4. Calendar-aligned windows with `MeteoWindow(...)` - -By default, coarser meteo sampling uses rolling windows that follow the model -clock. That is often sufficient, but some models are tied to civil periods such -as "the current day" or "the current week". - -In those cases, use `MeteoWindow(...)` to replace the default trailing window -with a calendar-aligned one: - -```julia -plant_daily_spec = ModelSpec(TutorialPlantDailyModel()) |> - TimeStepModel(ClockSpec(24.0, 0.0)) |> - MeteoWindow( - CalendarWindow( - :day; - anchor=:current_period, - week_start=1, - completeness=:strict, - ), - ) -``` - -This becomes important when a daily or weekly model should aggregate over civil -days or weeks rather than over "the last 24 hours" or "the last 168 hours". - -## 5. Exporting streams with `OutputRequest(...)` - -The second tutorial page uses `OutputRequest(...)` to materialize clean -hourly/daily/weekly tables from the simulation streams. The simple form works -well when the requested variable has a unique canonical publisher: - -```julia -req_plant_daily = OutputRequest(:Plant, :plant_assim_d; - name=:plant_assim_daily, - clock=ClockSpec(24.0, 0.0), -) -``` - -More complex mappings often need more explicit requests. In particular, add -`process=` when several models can publish the same variable, and add `policy=` -when you need a specific export-time resampling behavior: - -```julia -req_daily_energy = OutputRequest(:Leaf, :leaf_assim_h; - name=:leaf_energy_daily, - process=:tutorialleafhourly, - policy=Integrate(), - clock=ClockSpec(24.0, 0.0), -) - -req_hourly_hold = OutputRequest(:Plant, :plant_assim_d; - name=:plant_assim_hold_hourly, - process=:tutorialplantdaily, - policy=HoldLast(), - clock=ClockSpec(1.0, 0.0), -) -``` - -So `OutputRequest(...)` is not just a way to rename a column. It is also a -declaration of which stream you want, at which cadence, and with which -resampling policy. - -## 6. Inspect resolved configuration - -When a mapping mixes inferred bindings, explicit bindings, custom meteo -aggregation, scopes, and export requests, it becomes difficult to reason about -the final resolved configuration by inspection alone. - -That is where `explain_model_specs(...)` and `resolved_model_specs(...)` become -useful: - -```julia -explain_model_specs(mapping) - -resolved = resolved_model_specs(mapping) -resolved[:Plant] -``` - -These helpers let you confirm: - -- the effective timestep of each model; -- the resolved input bindings; -- the resolved meteo bindings; -- the active meteo window. - -In practice, this is often the fastest way to debug a multi-rate mapping before -running a larger simulation. - -## 7. How to choose between the three pages - -Use the pages in this order: - -1. start with [Introduction to multi-rate execution](introduction.md) if you - want to understand the scheduling rules; -2. continue with [Step-by-step multi-rate tutorial](multirate_tutorial.md) for - a complete but compact MTG example; -3. come back to this page when you need explicit bindings, explicit meteo - aggregation, custom export requests, scopes, or debugging helpers. diff --git a/docs/src/multirate/introduction.md b/docs/src/multirate/introduction.md deleted file mode 100644 index a0556ceae..000000000 --- a/docs/src/multirate/introduction.md +++ /dev/null @@ -1,200 +0,0 @@ -# Introduction to multi-rate execution - -This page introduces the basic ideas behind multi-rate execution in -PlantSimEngine. - -The goal here is not to build a realistic plant model. Instead, the objective is -to make the mechanics of multi-rate execution easy to see: - -- how PlantSimEngine decides when a model runs; -- how values are transferred from a faster model to a slower one; -- how meteorological inputs are reduced over a coarse time window. - -Once those ideas are clear, the -[step-by-step multi-rate tutorial](multirate_tutorial.md) shows how to assemble -a more complete hourly/daily/weekly MTG simulation. - -## Decision flow quick examples - -Before building a larger example, it helps to establish two important rules: - -1. if a model does not declare an explicit timestep, it follows the meteo cadence; -2. if a model is forced to run more coarsely than its inputs, then explicit input - and meteo binding policies determine how information is aggregated. - -### Simple example with implicit meteo cadence - -Model may define a trait calles `timestep_hint` that describes the acceptable and preferred cadences for that model. However, that trait is purely descriptive: it does not force the model to run at any particular rate. If you want to force a model to run at a specific cadence, you must declare an explicit `TimeStepModel(...)` in the mapping. Otherwise, the model will simply run whenever the meteo cadence allows it to, and the `timestep_hint` can be used for validation or explanation but does not silently reschedule the model. - -Let's define a tiny model that simply counts how many times it ran, then feed it -three 30-minute weather rows: - -```@example multirate_timestep_flow -using PlantSimEngine -using PlantMeteo -using MultiScaleTreeGraph -using DataFrames -using Dates - -mtg = Node(NodeMTG("/", :Scene, 1, 0)) -plant = Node(mtg, NodeMTG("+", :Plant, 1, 1)) -internode = Node(plant, NodeMTG("/", :Internode, 1, 2)) -Node(internode, NodeMTG("+", :Leaf, 1, 2)) - -PlantSimEngine.@process "tutorialmeteodriven" verbose=false -struct TutorialMeteoDrivenModel <: AbstractTutorialmeteodrivenModel - n::Base.RefValue{Int} -end -PlantSimEngine.inputs_(::TutorialMeteoDrivenModel) = NamedTuple() -PlantSimEngine.outputs_(::TutorialMeteoDrivenModel) = (count=-Inf,) -function PlantSimEngine.run!(m::TutorialMeteoDrivenModel, models, status, meteo, constants=nothing, extra=nothing) - m.n[] += 1 - status.count = float(m.n[]) -end -PlantSimEngine.timestep_hint(::Type{<:TutorialMeteoDrivenModel}) = (; required=(Minute(30), Hour(2)), preferred=Hour(1)) -``` - -This model is designed to run between every 30 minutes and every 2 hours, with a preferred cadence of 1 hour. Let's make a mapping with the model but without an explicit `TimeStepModel(...)`: - -```@example multirate_timestep_flow -mapping = ModelMapping(:Leaf => (TutorialMeteoDrivenModel(Ref(0)),)) -``` - -Let's define a 30-minute weather table with three rows: - -```@example multirate_timestep_flow -meteo_30min = Weather([ - Atmosphere(date=DateTime(2025, 6, 12, 12, 0, 0), duration=Minute(30), T=20.0, Wind=1.0, Rh=0.6), - Atmosphere(date=DateTime(2025, 6, 12, 12, 30, 0), duration=Minute(30), T=21.0, Wind=1.0, Rh=0.6), - Atmosphere(date=DateTime(2025, 6, 12, 13, 0, 0), duration=Minute(30), T=22.0, Wind=1.0, Rh=0.6), -]) -``` - -Now we run the model and check how many times it ran over those three 30-minute rows: - -```@example multirate_timestep_flow -out_meteo_driven = run!( - mtg, - mapping, - meteo_30min; - executor=SequentialEx(), - tracked_outputs=Dict(:Leaf => (:count,)), -) -out_meteo_driven[:Leaf][end] -``` - -The last value for `:count` is `3.0`, showing the model ran on all three 30-minute meteo rows, -even though `preferred=Hour(1)`. - -That is the key point: without `TimeStepModel`, the model still follows the -incoming meteo table. The preferred timestep can be used for validation or for -explanation, but it does not silently reschedule the model. - -### Using `TimeStepModel` to manage multi-rate coupling - -The second example shows the complementary case. Here we explicitly ask one model -to run hourly, even though its source data arrives every 30 minutes. Once we do -that, PlantSimEngine needs instructions for two distinct questions: - -- how to combine the 30-minute source output into an hourly model input; -- how to combine 30-minute meteorological rows into the hourly meteo seen by the - coarse model. - -That is what `InputBindings(...)` and `MeteoBindings(...)` are for. -In this tiny example, we keep the mapping simple by declaring the default -reduction policy on the source model itself with `output_policy(...)`. Since `A` -has a unique producer on the same scale, PlantSimEngine can infer the source -automatically and reuse that policy. - -Let's define a simple 30-minute source model that produces a constant value `A=1.0` every time it runs, and declare that its output should be integrated when consumed by a slower model: - -```@example multirate_timestep_flow -PlantSimEngine.@process "tutorialhalfhoursource" verbose=false -struct TutorialHalfHourSourceModel <: AbstractTutorialhalfhoursourceModel - n::Base.RefValue{Int} -end -PlantSimEngine.inputs_(::TutorialHalfHourSourceModel) = NamedTuple() -PlantSimEngine.outputs_(::TutorialHalfHourSourceModel) = (A=-Inf,) -function PlantSimEngine.run!(m::TutorialHalfHourSourceModel, models, status, meteo, constants=nothing, extra=nothing) - m.n[] += 1 - status.A = 1.0 # umol m-2 s-1 -end -PlantSimEngine.output_policy(::Type{<:TutorialHalfHourSourceModel}) = (; A=Integrate(DurationSumReducer())) -``` - -Note that `output_policy(...)` says that when a slower model consumes `A`, the default is to integrate it over the coarser time window, using the duration of each source row as weights. - -Now we define a simple hourly model that consumes `A` and also reads hourly mean temperature from the meteo: - -```@example multirate_timestep_flow -PlantSimEngine.@process "tutorialhourlyintegrator" verbose=false -struct TutorialHourlyIntegratorModel <: AbstractTutorialhourlyintegratorModel end -PlantSimEngine.inputs_(::TutorialHourlyIntegratorModel) = (A=-Inf,) -PlantSimEngine.outputs_(::TutorialHourlyIntegratorModel) = (A_hourly=-Inf, T_hourly=-Inf,) -function PlantSimEngine.run!(::TutorialHourlyIntegratorModel, models, status, meteo, constants=nothing, extra=nothing) - status.A_hourly = status.A - status.T_hourly = meteo.T -end -``` - -!!! note - We make two deliberate simplifications here to keep the example compact: - 1. The hourly model simply copies the integrated `A` value into a new variable called `A_hourly`. This is bad design in a real model because it creates unnecessary variables and makes the data flow less transparent. In a real model, you would typically consume `A` directly and let the integrated value be called `A` as well. However, here we create a separate variable to make it obvious that the hourly model is receiving an aggregated version of the original `A`. - 2. We don't define an `output_policy(...)` for the hourly model, because it is not consumed by any slower model. Usually, developers are encouraged to define `output_policy(...)` for all models, but here we omit it for the hourly model to keep the example compact. - -Now we can declare a mapping that says the hourly model runs every hour, even though its source data arrives every 30 minutes. We also declare how to reduce the meteorological inputs to match the hourly cadence: - -```@example multirate_timestep_flow -mapping_coarse = ModelMapping( - :Leaf => ( - ModelSpec(TutorialHalfHourSourceModel(Ref(0))), - ModelSpec(TutorialHourlyIntegratorModel()) |> - TimeStepModel(Hour(1)) |> - MeteoBindings(; T=MeanWeighted()), - ), -) -``` - -Setting the `TimeStepModel(Hour(1))` forces the second model to run hourly. Since it consumes `A` from the first model, PlantSimEngine looks at the source model's `output_policy(...)` and sees that it should integrate `A` over the hour using the duration of each 30-minute row as weights. - -!!! note - If we had omitted `TimeStepModel(Hour(1))`, the hourly model would have simply run on each 30-minute row, and the `output_policy(...)` on the source model would not have been triggered. The hourly model would have received the original 30-minute `A` values instead of an hourly aggregate. This illustrates the key point: `TimeStepModel(...)` is what triggers the multi-rate coupling and the use of reduction policies. - -In our example, the hourly model does not declare a `timestep_hint`, so it can run at any cadence. By declaring `TimeStepModel(Hour(1))`, we explicitly force it to run hourly, which means it will receive aggregated inputs and meteo. - -!!! note - Because our hourly model does not declare a `timestep_hint`, it is flexible and can run at any cadence. However, if we had declared a `timestep_hint` that did not include hourly as an acceptable cadence, then PlantSimEngine would have raised an error when we tried to force it to run hourly. Consequently, it is usually a good practice to declare a `timestep_hint` when writing a model, because it helps to ensure that the model is used in a way that is consistent with its design and intended use. - -Let's now run the simulation: - -```@example multirate_timestep_flow -meteo_30min_4 = Weather([ - Atmosphere(date=DateTime(2025, 6, 12, 12, 0, 0), duration=Minute(30), T=20.0, Wind=1.0, Rh=0.6), - Atmosphere(date=DateTime(2025, 6, 12, 12, 30, 0), duration=Minute(30), T=22.0, Wind=1.0, Rh=0.6), - Atmosphere(date=DateTime(2025, 6, 12, 13, 0, 0), duration=Minute(30), T=24.0, Wind=1.0, Rh=0.6), - Atmosphere(date=DateTime(2025, 6, 12, 13, 30, 0), duration=Minute(30), T=26.0, Wind=1.0, Rh=0.6), -]) - -out_coarse = run!( - mtg, - mapping_coarse, - meteo_30min_4; - executor=SequentialEx(), - tracked_outputs=Dict(:Leaf => (:A_hourly, :T_hourly)), -) -out_coarse[:Leaf][end] -``` - -The final timestep outputs are `3600.0` for `A_hourly` and `23.0` for `T_hourly`: hourly integrated assimilation -(`sum(A .* duration_seconds)` over two 30-minute rows) and hourly mean temperature over the coarse window. - -So this example already captures the core multi-rate idea: the fast model still -runs at the fine cadence, while the coarse model sees explicitly reduced inputs -and meteorology at its own cadence. - -From here, there are two natural next steps: - -- [Step-by-step multi-rate tutorial](multirate_tutorial.md) for a more complete - MTG example; -- [Advanced multi-rate configuration](advanced_configuration.md) for explicit - bindings, meteo windows, export requests, scopes, and debugging helpers. diff --git a/docs/src/multirate/multirate_tutorial.md b/docs/src/multirate/multirate_tutorial.md deleted file mode 100644 index 49c76dd58..000000000 --- a/docs/src/multirate/multirate_tutorial.md +++ /dev/null @@ -1,429 +0,0 @@ -# Step-by-step multi-rate tutorial (hourly + daily + weekly) - -This page builds a more complete MTG simulation that mixes three model rates: -- hourly at `Leaf`, -- daily at `Plant`, -- weekly at `Plant`. - -It runs for one week and exports clean series at each rate. - -If you want the conceptual overview first, start with -[Introduction to multi-rate execution](introduction.md). This page assumes you -already understand the two basic ideas introduced there: - -1. without `TimeStepModel(...)`, a model follows the meteo cadence; -2. once a model is forced to run more coarsely than its inputs, PlantSimEngine - must reduce both model outputs and meteorological inputs to match that slower - cadence. - -The goal of this second page is to put those ideas into a more contextualized -MTG example, where we mix hourly, daily, and weekly models in the same -simulation and export clean time series at each rate. - -## 1. Setup and example data - -This tutorial is more contextualized than the previous one. To keep the mechanics -readable, we work with a minimal MTG containing only one plant and one leaf. That -way the exported tables stay small enough to inspect directly. - -We also reuse package example assets instead of inventing new input files. In particular, we use a weather file available from the package examples: - -- `examples/meteo_day.csv` for weather. - -We start by importing the packages we need and by creating a very small MTG with -only four nodes: a `Scene`, a `Plant`, one `Internode`, and one `Leaf`. - -```@example multirate_tutorial -using PlantSimEngine -using PlantMeteo -using MultiScaleTreeGraph -using DataFrames -using CSV -using Dates - -# Minimal plant: Scene -> Plant -> Internode -> Leaf -mtg = Node(NodeMTG("/", :Scene, 1, 0)) -plant = Node(mtg, NodeMTG("+", :Plant, 1, 1)) -internode = Node(plant, NodeMTG("/", :Internode, 1, 2)) -Node(internode, NodeMTG("+", :Leaf, 1, 2)) -``` - -Next, we point to the bundled weather file and confirm that it exists: - -```@example multirate_tutorial -meteo_path = joinpath(pkgdir(PlantSimEngine), "examples", "meteo_day.csv") -@assert isfile(meteo_path) -``` - -The weather file bundled with the package is daily. Since this tutorial is about -mixing several rates, we first convert one week of daily weather into an -hourly weather table. The values are simply repeated within each day, which is -perfectly fine here because the purpose is to illustrate scheduling and data flow -rather than to create a realistic forcing dataset. - -The first step is to read the file and keep only one week of rows: - -```@example multirate_tutorial -daily_df = CSV.read(meteo_path, DataFrame, header=18) -week_df = first(daily_df, 7) -``` - -We then expand each day into 24 hourly `Atmosphere` rows: - -```@example multirate_tutorial -hourly_rows = Atmosphere[] -for row in eachrow(week_df) - for h in 0:23 - push!(hourly_rows, - Atmosphere( - date=DateTime(row.date) + Hour(h), - duration=Hour(1), - T=row.T, - Wind=row.Wind, - P=row.P, - Rh=row.Rh, - Ri_PAR_f=row.Ri_PAR_f, - Ri_SW_f=row.Ri_SW_f, - ) - ) - end -end -``` - -Finally, we wrap those rows into a `Weather` object, which is what `run!` expects: - -```@example multirate_tutorial -meteo_hourly = Weather(hourly_rows) -meteo_hourly[1:3] # show the first 3 rows of the hourly weather table -``` - -## 2. Defining simple models - -Next we define three deliberately simple models: - -- an hourly `Leaf` model that turns incoming radiation into an hourly - assimilation value; -- a daily `Plant` model that sums hourly leaf assimilation over a day and also - consumes daily meteorological aggregates; -- a weekly `Plant` model that sums daily plant assimilation into one weekly - value. - -These models are intentionally minimal. Their role is to make the rate changes -and aggregation policies obvious. - -We begin with the hourly leaf model. It reads hourly meteorological radiation and -produces an hourly assimilation value: - -```@example multirate_tutorial -PlantSimEngine.@process "tutorialleafhourly" verbose=false -struct TutorialLeafHourlyModel <: AbstractTutorialleafhourlyModel end -PlantSimEngine.inputs_(::TutorialLeafHourlyModel) = NamedTuple() -PlantSimEngine.outputs_(::TutorialLeafHourlyModel) = (leaf_assim_h=0.0,) -function PlantSimEngine.run!(::TutorialLeafHourlyModel, models, status, meteo, constants=nothing, extra=nothing) - status.leaf_assim_h = 0.004 * meteo.Ri_PAR_f -end -PlantSimEngine.output_policy(::Type{<:TutorialLeafHourlyModel}) = (; leaf_assim_h=Integrate()) -``` - -The `output_policy(...)` declaration matters for multi-rate use: it says that -when a slower model consumes `leaf_assim_h`, the natural default is to integrate -it over the coarser time window. - -Now we define the daily plant model. It receives leaf assimilation values, -aggregates them over a day, and also reads daily reduced meteo variables: - -```@example multirate_tutorial -PlantSimEngine.@process "tutorialplantdaily" verbose=false -struct TutorialPlantDailyModel <: AbstractTutorialplantdailyModel end -PlantSimEngine.inputs_(::TutorialPlantDailyModel) = (leaf_assim_h=[0.0],) -PlantSimEngine.outputs_(::TutorialPlantDailyModel) = (plant_assim_d=0.0, rad_sw_day=0.0, T=0.0) -function PlantSimEngine.run!(::TutorialPlantDailyModel, models, status, meteo, constants=nothing, extra=nothing) - status.plant_assim_d = sum(status.leaf_assim_h) - status.rad_sw_day = meteo.Ri_SW_q - status.T = meteo.T -end -PlantSimEngine.output_policy(::Type{<:TutorialPlantDailyModel}) = (; plant_assim_d=Integrate()) -``` - -Again, `output_policy(...)` is used so that a coarser consumer can infer the -appropriate default behavior for `plant_assim_d`. - -Finally, we define the weekly plant model. It simply sums the daily plant -assimilation values over one week: - -```@example multirate_tutorial -PlantSimEngine.@process "tutorialplantweekly" verbose=false -struct TutorialPlantWeeklyModel <: AbstractTutorialplantweeklyModel end -PlantSimEngine.inputs_(::TutorialPlantWeeklyModel) = (plant_assim_d=[0.0],) -PlantSimEngine.outputs_(::TutorialPlantWeeklyModel) = (plant_assim_w=0.0,) -function PlantSimEngine.run!(::TutorialPlantWeeklyModel, models, status, meteo, constants=nothing, extra=nothing) - status.plant_assim_w = sum(status.plant_assim_d) -end -``` - -At this point nothing is multi-rate yet. We have simply defined three processes -whose intended cadences are hourly, daily, and weekly. The multi-rate behavior is -declared in the mapping. - -## 3. Configure multi-rate mapping - -This is the heart of the tutorial. The mapping below does three things at once: - -1. it assigns each model to a scale; -2. it declares the timestep at which each model should run; -3. it defines how values move between rates and between scales. - -Two pieces are especially important here: - -- `TimeStepModel(...)` states the model cadence; -- PlantMeteo reduces meteorological inputs automatically when a model runs more - coarsely than the weather data. - -For model-to-model bindings, this tutorial relies on automatic source inference -plus `output_policy(...)` on the source models. That keeps the main example -compact while still exercising multi-rate input aggregation. - -We start by defining the three clocks used in the simulation. These are the -cadences that will later be assigned to the three models: - -```@example multirate_tutorial -hourly = 1.0 -daily = ClockSpec(24.0, 0.0) -weekly = ClockSpec(168.0, 0.0) -``` - -The leaf model is straightforward: it runs hourly and is scoped to the current -plant. There is no multiscale mapping or meteo reduction to declare here, because -the leaf model is the fastest model in this example and directly consumes the -hourly weather rows: - -```@example multirate_tutorial -leaf_spec = TutorialLeafHourlyModel() |> ModelSpec |> TimeStepModel(hourly) -``` - -So at this point we have simply said: "run the leaf model every hour" - -The daily plant model is where multi-rate coupling becomes visible. It: - -- receives `leaf_assim_h` from the `:Leaf` scale through `MultiScaleModel(...)`; -- runs daily; -- receives daily meteorological aggregates from the hourly weather automatically. - -The important idea is that this model does not read the raw hourly values -directly. Instead, it sees a daily view of those data: - -- `leaf_assim_h` is integrated over the daily window because of the source - model's `output_policy(...)`; -- `T` is turned into a daily mean by the default PlantMeteo sampling rules; -- `Ri_SW_q` is computed by integrating `Ri_SW_f` over the day. - -```@example multirate_tutorial -plant_daily_spec = - TutorialPlantDailyModel() |> - ModelSpec |> - MultiScaleModel([:leaf_assim_h => :Leaf]) |> - TimeStepModel(daily) -``` - -This block is the first place where the "multi-rate" behavior is really visible: -one model consumes fine-grained biological outputs and fine-grained meteorology, -but only after both have been reduced to the model's own daily cadence. - -The weekly plant model is simpler again: it only needs to run weekly and receive -the daily plant output automatically. Since `plant_assim_d` has a unique producer -and already declares its own `output_policy(...)`, we do not need to add any -explicit binding here: - -```@example multirate_tutorial -plant_weekly_spec = - TutorialPlantWeeklyModel() |> - ModelSpec |> - TimeStepModel(weekly) -``` - -So this weekly model effectively says: "take the daily plant assimilation stream, -reduce it again to my weekly cadence, and run once per week." - -We can now assemble the full mapping: - -```@example multirate_tutorial -mapping = ModelMapping( - :Leaf => (leaf_spec,), - :Plant => (plant_daily_spec, plant_weekly_spec), -) -``` - -Reading this mapping from top to bottom: - -- the `Leaf` model runs hourly and produces `leaf_assim_h`; -- the daily `Plant` model receives leaf values from the `Leaf` scale through - `MultiScaleModel([:leaf_assim_h => :Leaf])`, then integrates them over a day; -- that same daily model also receives daily meteorological summaries through the - default PlantMeteo sampling rules; -- the weekly `Plant` model integrates the daily plant output into one weekly - value. - -!!! note - In this tutorial, explicit `InputBindings(...)` are omitted because each - input has a unique, inferable producer and the default reduction policy is - declared on the source model with `output_policy(...)`. - - In more complex mappings, you should use explicit `InputBindings(process=..., scale=..., var=..., policy=...)` when: - - several models can produce the same input variable; - - the same process exists at several reachable scales; - - the source variable has a different name than the consumer input; - - you want to override the producer's default policy for a specific mapping. - -!!! note - `MeteoBindings(...)` is also omitted on purpose in the main example. - PlantSimEngine delegates weather sampling to PlantMeteo, which already - defines default transformations for common `Atmosphere` variables such as - `T`, `Rh`, and radiation aliases like `Ri_SW_q`. - - Add explicit `MeteoBindings(...)` when: - - you want a non-default reducer; - - the model expects a target variable with a different source name; - - the variable is not covered by PlantMeteo default transforms; - - you want the mapping to state the weather aggregation rule explicitly. - - ```@example multirate_tutorial - # The same daily model, with weather aggregation rules written explicitly. - plant_daily_spec_explicit_meteo = ModelSpec(TutorialPlantDailyModel()) |> - MultiScaleModel([:leaf_assim_h => :Leaf]) |> - TimeStepModel(daily) |> - MeteoBindings( - ; - T=MeanWeighted(), - Ri_SW_q=(source=:Ri_SW_f, reducer=RadiationEnergy()), - ) - ``` - -## 4. Run and export hourly/daily/weekly series - -Now we run the simulation and request three exported series. This is a good place -to distinguish two related outputs returned by `run!`: - -- the regular simulation outputs (`out_status` below), which still contain the - model outputs tracked during the run; -- the explicitly requested exported series (`exported` below), which are the - clean hourly/daily/weekly tables we asked PlantSimEngine to materialize. - -We use `OutputRequest(...)` to say which variable we want and on which clock. -Here again we keep the example minimal: `process=` is omitted because each -requested output has a unique canonical publisher. - -We first declare the export requests. One request keeps the hourly leaf series, -another exports the daily plant series, and the last one exports the weekly plant -series. - -The point of these requests is to obtain three clean tables that each live at a -single rate, instead of having to reconstruct those time series manually from -the full simulation outputs: - -```@example multirate_tutorial -req_leaf_hourly = OutputRequest(:Leaf, :leaf_assim_h; - name=:leaf_assim_hourly, -) - -req_plant_daily = OutputRequest(:Plant, :plant_assim_d; - name=:plant_assim_daily, - clock=daily, -) - -req_plant_weekly = OutputRequest(:Plant, :plant_assim_w; - name=:plant_assim_weekly, - clock=weekly, -) -``` - -Then we run the simulation and ask PlantSimEngine to return both the regular -simulation outputs and the explicitly requested exported series: - -- `out_status` contains the regular tracked outputs of the simulation; -- `exported` contains the resampled, per-request tables defined above. - -```@example multirate_tutorial -out_status, exported = run!( - mtg, - mapping, - meteo_hourly; - executor=SequentialEx(), - tracked_outputs=[req_leaf_hourly, req_plant_daily, req_plant_weekly], - return_requested_outputs=true, -) -``` - -Finally, we extract the exported tables we want to inspect. At this point we are -no longer dealing with abstract stream definitions: we now have actual `DataFrame` -objects containing hourly, daily, and weekly series. - -```@example multirate_tutorial -leaf_hourly_df = exported[:leaf_assim_hourly] -plant_daily_df = exported[:plant_assim_daily] -plant_weekly_df = exported[:plant_assim_weekly] -``` - -The exported tables already have the cadence we asked for, so they are much -easier to inspect than a single mixed output table. - -We can start with a few basic checks on the number of rows. These checks are a -simple way to confirm that the export clocks did what we expected: - -```@example multirate_tutorial -@show nrow(leaf_hourly_df) # 168 (1 leaf x 168 hours) -@show nrow(plant_daily_df) # 7 (1 plant x 7 days) -@show nrow(plant_weekly_df) # 1 (1 plant x 1 week) -``` - -The hourly table has one row per hour, the daily table one row per day, and the -weekly table one row for the whole run. - -To compare the hourly and daily outputs directly, we group the hourly series by -day and sum it manually. This lets us check that the daily plant model really did -receive the integrated hourly leaf assimilation: - -```@example multirate_tutorial -leaf_hourly_df.day = repeat(1:7, inner=24) -leaf_hourly_sum = combine(groupby(leaf_hourly_df, :day), :value => sum => :leaf_assim_h_sum) -``` - -Those row counts match the intended design of the example: one hourly series for -seven days, one daily series for seven days, and one weekly aggregate for the -whole run. - -We can also manually recompute the daily sums from the hourly exported series and -compare them with the daily model output: - -```@example multirate_tutorial -plant_daily_df -``` - -This confirms that the daily assimilation values correspond to the sum of the -hourly leaf assimilation collected over each day. - -The regular outputs returned by `run!` are still available as well, and can be -converted to `DataFrame`s in the usual way. This is useful when you want both: - -- clean resampled exports for analysis; -- the usual simulation outputs for debugging or broader inspection. - -```@example multirate_tutorial -outs = convert_outputs(out_status, DataFrame) -outs[:Plant][1:3,:] -``` - -## 5. Where to go next - -This page keeps the main walkthrough focused on a complete but still compact -example. Once that example is clear, the next step is usually to learn the -explicit configuration tools that become useful in larger mappings: - -- `InputBindings(...)` when inference is ambiguous or too implicit; -- `MeteoBindings(...)` when PlantMeteo defaults are not enough; -- `MeteoWindow(...)` for calendar-aligned aggregation; -- `OutputRequest(...)` when you want explicit export-time clocks and policies; -- `ScopeModel(...)`, `explain_model_specs(...)`, and `resolved_model_specs(...)` - for larger and harder-to-debug MTGs. - -Those topics are grouped in -[Advanced multi-rate configuration](advanced_configuration.md). diff --git a/docs/src/multiscale/multiscale.md b/docs/src/multiscale/multiscale.md deleted file mode 100644 index 062520811..000000000 --- a/docs/src/multiscale/multiscale.md +++ /dev/null @@ -1,255 +0,0 @@ -# Multi-scale variable mapping - -The previous page showed how to convert a single-scale simulation to multi-scale. - -This page provides another example showcasing the nuances in variable mapping, with a more complex fully multiscale version of a prior simulation. The models will all be taken form the [examples folder](https://github.com/VirtualPlantLab/PlantSimEngine.jl/tree/main/examples). - -```@contents -Pages = ["multiscale.md"] -Depth = 3 -``` - -## Starting with a single-model mapping - -Let's import the `PlantSimEngine` package and all the example models we will use in this tutorial: - -```@example usepkg -using PlantSimEngine -using PlantSimEngine.Examples # Import some example models -``` - -Let's create a simple mapping with only one initial model, the carbon assimilation process ToyAssimModel, which will operate on leaves. -It resembles the ToyAssimGrowth model used in the single-scale simulation [Model switching](@ref) subsection. - -Our mapping between scale and model is therefore: - -```@example usepkg -mapping = ModelMapping(:Leaf => ToyAssimModel()) -``` - -Just like in single-scale simulations, we can call `to_initialize` to check whether variables need to be initialised. It will this time index by scale: - -```@example usepkg -to_initialize(mapping) -``` - -In this example, the ToyAssimModel needs `:aPPFD` and `:soil_water_content` as inputs, which aren't initialised in our mapping. - -The initialization values for the variables can be passed along via a [`Status`](@ref) object: - -```@example usepkg -mapping = ModelMapping( - :Leaf => ( - ToyAssimModel(), - Status(aPPFD=1300.0, soil_water_content=0.5), - ), -) -``` - -If we call [`to_initialize`](@ref) on this new mapping, it returns an empty dictionary, meaning the mapping is valid, and we can start the simulation: - -```@example usepkg -to_initialize(mapping) -``` - -## Multiscale mapping between models and scales - -The `soil_water_content` variable was provided via the mapping. No model affects it, so it is constant in the above example. We could instead provide a model that computes it based on weather data, and/or a more realistic physical process. - -It also makes sense to have that model operate at a different scale than the :Leaf scale. There is a dummy soil model called `ToySoilModel` in the examples folder. Let's put it at a new :Soil scale level. - -ToyAssimModel is now makes use of the `soil_water_content` variable from the `:Soil` scale, instead of at its own scale via the `Status` initialization. We therefore need to map `soil_water_content` from the :Soil to the :Leaf scale by wrapping `ToyAssimModel` in a `MultiScaleModel`: - -```@example usepkg -mapping = ModelMapping( - :Soil => ToySoilWaterModel(), - :Leaf => ( - MultiScaleModel( - model=ToyAssimModel(), - mapped_variables=[:soil_water_content => :Soil => :soil_water_content,], - ), - Status(aPPFD=1300.0), - ), -); -nothing # hide -``` - -In this example, we map the `soil_water_content` variable at scale :Leaf to the `soil_water_content` variable at the `:Soil` scale. If the name of the variable is the same between both scales, we can omit the variable name at the origin scale, *e.g.* `[:soil_water_content => :Soil]`. - -The variable `aPPFD` is still provided in the `Status` type as a constant value. - -We can check again if the mapping is valid by calling [`to_initialize`](@ref): - -```@example usepkg -to_initialize(mapping) -``` - -Once again, `to_initialize` returns an empty dictionary, meaning the mapping is valid. - -## A more elaborate multiscale model mapping - -Let's now expand this mapping, to showcase other ways in which variables can be mapped from one scale to another. We'll keep the first two models, and add several more to simulate a couple of other processes within our plant. - -```@example usepkg -mapping = ModelMapping( - :Scene => ToyDegreeDaysCumulModel(), - :Plant => ( - MultiScaleModel( - model=ToyLAIModel(), - mapped_variables=[ - :TT_cu => :Scene, - ], - ), - Beer(0.6), - MultiScaleModel( - model=ToyCAllocationModel(), - mapped_variables=[ - :carbon_assimilation => [:Leaf], - :carbon_demand => [:Leaf, :Internode], - :carbon_allocation => [:Leaf, :Internode] - ], - ), - MultiScaleModel( - model=ToyPlantRmModel(), - mapped_variables=[:Rm_organs => [:Leaf => :Rm, :Internode => :Rm],], - ), - ), - :Internode => ( - MultiScaleModel( - model=ToyCDemandModel(optimal_biomass=10.0, development_duration=200.0), - mapped_variables=[:TT => :Scene,], - ), - ToyMaintenanceRespirationModel(1.5, 0.06, 25.0, 0.6, 0.004), - Status(carbon_biomass=1.0), - ), - :Leaf => ( - MultiScaleModel( - model=ToyAssimModel(), - mapped_variables=[:soil_water_content => :Soil, :aPPFD => :Plant], - ), - MultiScaleModel( - model=ToyCDemandModel(optimal_biomass=10.0, development_duration=200.0), - mapped_variables=[:TT => :Scene,], - ), - ToyMaintenanceRespirationModel(2.1, 0.06, 25.0, 1.0, 0.025), - Status(carbon_biomass=0.5), - ), - :Soil => ( - ToySoilWaterModel(), - ), -); -nothing # hide -``` - -This mapping might seem a little more daunting than previous examples, but several models should be recognizable in passing. In fact, you can consider this mapping to be an enhanced and more complex multi-scale version of a previous single-scale example, the coupling between photosynthesis model, a LAI model and a carbon biomass increment model, used in the [Model switching](@ref) subsection. - -```julia -models2 = ModelMapping( - ToyLAIModel(), - Beer(0.5), - ToyAssimGrowthModel(); - status=(TT_cu=cumsum(meteo_day.TT),), -) -``` - -The multi-scale models simulate carbon capture via photosynthesis and carbon allocation for the plant organs' maintenance respiration and development. - -The LAI and photosynthesis models are the same as in the single-scale mapping example. The [`ToyDegreeDaysCumulModel`](@ref) provides the Cumulative Thermal Time to the plant. - -The newly introduced models have the following dynamic : - -Carbon allocation is determined (ToyCAllocationModel) for the different organs of the plant (`:Leaf` and `:Internode`) from the assimilation at the `:Leaf` scale (*i.e.* the offer) and their carbon demand (ToyCDemandModel). The `:Soil` scale is used to compute the soil water content (`ToySoilWaterModel`](@ref)), which is needed to calculate the assimilation at the `:Leaf` scale (ToyAssimModel). Also note that maintenance respiration at computed at the `:Leaf` and `:Internode` scales (ToyMaintenanceRespirationModel), and aggregated to compute the total maintenance respiration at the `:Plant` scale (ToyPlantRmModel). - -## Different possible variable mappings - -The above mapping showcases the different ways to define how the variables are mapped in a `MultiScaleModel` : - -```julia - mapped_variables=[:TT_cu => :Scene,], -``` - -- At the :Plant scale, the TT_cu variable is mapped as a scalar from the :Scene scale. There is only a single :Scene node in the MTG, and only a single "TT_cu" value per timestep for the simulation. - -```julia -:carbon_allocation => [:Leaf] -``` - -- On the other hand, we have `:carbon_allocation => [:Leaf]` at the plant scale for `ToyCAllocationModel`. The `carbon_assimilation` variable is mapped as a vector: there are multiple :Leaf nodes, but only one :Plant node, which aggregrates the value over every single leaf. This gives us a 'many-to-one' vector mapping, and in the [`run!`](@ref) functions for models at that scale `carbon_allocation` will be available in the `status` as a vector. - -```julia -:carbon_allocation => [:Leaf, :Internode] -``` - -- A third type of the mapping would be `:carbon_allocation => [:Leaf, :Internode]`, which provides values for a variable from several other scales simultaneously. In this case, the values are also available as a vector in the `carbon_assimilation` variable of the [`status`](@ref) inside the model, sorted in the same order as nodes are traversed in the graph. - -```julia -:Rm_organs => [:Leaf => :Rm, :Internode => :Rm] -``` - -- Finally, to map to a specific variable name at the target scale, *e.g.* `:Rm_organs => [:Leaf => :Rm, :Internode => :Rm]`. This syntax is useful when the variable name is different between scales, and we want to map to a specific variable name at the target scale. In this example, the variable `Rm_organs` at plant scale takes its values (is mapped) from the variable `Rm` at the `:Leaf` and `:Internode` scales. - -## Running a simulation - -Now that we have a valid mapping, we can run a simulation. Running a multiscale simulation requires a plant graph and the definition of the output variables we want dynamically for each scale. - -### Plant graph - -We can import an example multi-scale tree graph like so: - -```@example usepkg -mtg = import_mtg_example() -``` - -!!! note - You can use `import_mtg_example` only if you previously imported the `Examples` sub-module of PlantSimEngine, *i.e.* `using PlantSimEngine.Examples`. - -This graph has a root node that defines a scene, then a soil, and a plant with two internodes and two leaves. - -### Output variables - -For long simulations on plants with many organs, the output data can be very significant. It's possible to restrict the output variables that are tracked for the whole simulation to a subset of all the variables: - -```@example usepkg -outs = Dict( - :Scene => (:TT, :TT_cu,), - :Plant => (:aPPFD, :LAI), - :Leaf => (:carbon_assimilation, :carbon_demand, :carbon_allocation, :TT), - :Internode => (:carbon_allocation,), - :Soil => (:soil_water_content,), -) -``` - -This dictionary can be passed to the simulation via the optional `tracked_outputs` keyword argument to the [`run!`](@ref) function (see the next part). If no dictionary is provided, every variable will be tracked. - -These variables will be available in the output returned by [`run!`](@ref), with a value for each time step. The corresponding timestep and node in the MTG are also returned. - -### Meteorological data - -As for mono-scale models, we need to provide meteorological data to run a simulation. We can use the `PlantMeteo` package to generate some dummy data for two time steps: - -```@example usepkg -meteo = Weather( - [ - Atmosphere(T=20.0, Wind=1.0, Rh=0.65, Ri_PAR_f = 200.0), - Atmosphere(T=25.0, Wind=0.5, Rh=0.8, Ri_PAR_f = 180.0) -] -) -``` - -### Simulation - -Let's make a simulation using the graph and outputs we just defined: - -```@example usepkg -outputs_sim = run!(mtg, mapping, meteo, tracked_outputs = outs); -nothing # hide -``` - -And that's it! We can now access the outputs for each scale as a dictionary of vectors of NamedTuple objects. - -Or as a `DataFrame` dictionary using the [`DataFrames`](https://dataframes.juliadata.org) package: - -```@example usepkg -using DataFrames -df_dict = convert_outputs(outputs_sim, DataFrame) -``` diff --git a/docs/src/multiscale/multiscale_considerations.md b/docs/src/multiscale/multiscale_considerations.md deleted file mode 100644 index 091cf32e6..000000000 --- a/docs/src/multiscale/multiscale_considerations.md +++ /dev/null @@ -1,163 +0,0 @@ -# Multi-scale considerations - -```@contents -Pages = ["multiscale_considerations.md"] -Depth = 3 -``` - -This page briefly details the subtle ways in which multi-scale simulations differ from prior single-scale simulations. The next few pages will showcase some of these subtleties with examples. - -Declaring and running a multi-scale simulation follows the same general workflow as the single-scale version, but multi-scale simulations do have some differences : - -- a simulation requires a Multi-scale Tree Graph (MTG) to run and operates on that graph -- when running, models are tied to a scale and only access local information -- models can run multiple times per timestep - -The simulation dependency graph will still be computed automatically and handle most couplings, meaning users don't need to specify the order of model execution once the extra code to declare the models is written. You will still need to declare hard dependencies, with extra considerations for multi-scale hard dependencies. - -Multi-scale simulations also tend to require more extra ad hoc models to prepare some variables for some models. - -## Related pages - -Other pages in the multiscale section describe : - -- How convert a single-scale ModelMapping to a multi-scale one: [Converting a single-scale simulation to multi-scale](@ref), -- A more complex multi-scale version of the single-scale simulation showcasing different variable mappings between scales: [Multi-scale variable mapping](@ref), -- A three-part tutorial describing how to build up a combination of models to simulate a growing toy plant: [Writing a multiscale simulation](@ref), -- Ways to handle situations where a variable ends up causing a cyclic dependency: [Avoiding cyclic dependencies](@ref), -- Multi-scale specific coupling considerations and subtleties:[Handling dependencies in a multiscale context](@ref) - -## Multi-scale tree graphs - -Functional-Structural Plant Models are often about simulating plant growth. A multi-scale simulation is implicitely expected to operate on a plant-like object, represented by a multi-scale tree graph. - -A multi-scale tree graph (MTG) object (see the [Multi-scale Tree Graphs](@ref) subsection for a quick description) is therefore required to run a multi-scale simulations. It can be a dummy MTG if the simulation doesn't actually affect it, but is nevertheless a required argument to the multi-scale [`run!`](@ref) function. - -All the multi-scale examples make use of the companion package [MultiScaleTreeGraph.jl](https://github.com/VEZY/MultiScaleTreeGraph.jl), which we therefore recommend for running your own multi-scale simulations. Visualizing a Multi-scale Tree Graph can be done using [PlantGeom](https://github.com/VEZY/PlantGeom.jl). - -!!! note - Multi-scale Tree Graphs make use of conflicting terminology with PlantSimEngine's concepts, which is discussed in [Scale/symbol terminology ambiguity](@ref). If you are new to those concepts, make sure to read that section and keep note of it. - -## Models run once per organ instance, not once per organ level - -Some models, like the ones we've seen in single-scale simulations, work on a very simple model of a whole plant. - -More fine-grained models can be tied to a specific plant organ. - -For instance, a model computing a leaf's surface area depending on its age would operate at the `:Leaf` scale, and be called **for every leaf** at every timestep. On the other hand, a model computing the plant's total leaf area only needs to be run once per timestep, and can be run at the `:Plant` scale. - -This is a major difference between a single-scale simulation and a multi-scale one. By default, any model in a single-scale simulation will only run **once** per timestep. However, in multi-scale, if a plant has several instances of an organ type -say it has a hundred leaves- then any model operating at the :Leaf scale will by default run one hundred times per timestep, unless it is explicitely controlled by another model (which can happen in hard dependency configurations). - -## Mappings - -When users define which models they use, PlantSimEngine cannot determine in advance which scale level they operate at. This is partly because the plant organs in an MTG do not have standardized names, and partly because some plant organs might not be part of the initial MTG, so parsing it isn't enough to infer what scales are used. - -The user therefore needs to indicate for a simulation's which models are related to which scale. - -A multi-scale mapping links models to the scale at which they operate, and is also implemented in a [`ModelMapping`](@ref), tying a scale, such as :Leaf to models operating at that scale, such as "LeafSurfaceAreaModel". - -Multi-scale models can be similar models to the ones found in earlier sections, or, if they need to make use of variables at other scales, may need to be wrapped as part of a [`MultiScaleModel`](@ref) object. Many models are not tied to a particular scale, which means those models can be reused at different scales or in single-scale simulations. - -## The simulation operates on an MTG - -Unlike in single-scale simulations, which make use of a [`Status`](@ref) object to store the current state of every variable in a simulation, multi-scale simulations operate on a per-organ basis. - -This means every organ instance has its own [`Status`](@ref), with scale-specific attributes. - -This has two **important** consequences in terms of running a simulation : - -- First, **any scale absent from the MTG will not be run**. If your MTG contains no leaves, then no model operating at the scale :Leaf will be able to run until a :Leaf organ is created and a node is added in the MTG. Otherwise, it has no MTG node to operate on. The only exceptions are hard dependency models which can be called from a different scale, since they can be called directly by a model on a node at a different existing scale, even if there is no node at their own scale. - -- Secondly, models only have access to **local** organ information. The [`status`](@ref) argument in the [`run!`](@ref) function only contains variables **at the model's scale**, unless variables from other scales are mapped via a [`MultiScaleModel`](@ref) wrapping. - -## The run! function's signature - -The [`run!`](@ref) function differs slightly from its single-scale version. The current structure (excluding a couple of advanced/deprecated kwargs) is the following: - -```julia -run!(mtg, mapping::ModelMapping, meteo, constants, extra; nsteps, tracked_outputs) -``` - -Instead of a just the [`ModelMapping`](@ref), it also takes an MTG as the first argument. The optional `meteo` and `constants` argument are identical to the single-scale version. The `extra` argument is now reserved and should not be used. A new `nsteps` keyword argument is available to restrict the simulation to a specified number of steps. - -## Multi-scale output data structure - -The output structure, like the mapping, is a Julia `Dict` structure indexed by the scale name. Values are a per-scale `Vector{NamedTuple}` which lists the requested variables for every node at that scale, for every timestep in the simulation. Timestep and Multiscale Tree Graph nodes are also added to the output data, as a `:timestep`and a `:node` entry. - -This dictionary structure makes the outputs as-is a little more verbose to inspect than in single-scale, but the general usage is similar, and it is both compact, and fast to convert to a `Dict{String, DataFrame}` which can make queries easier. - -!!! note - Some of the mapped variables -those that map from scalar to vector- will not be added to the outputs to save some memory and space since they are redundant. - -To illustrate, here's an example output from part 3 of the Toy plant tutorial, zeroing in on a variable at the :Root scale: [Fixing bugs in the plant simulation](@ref): - -```julia -julia> outs - -Dict{String, Vector} with 5 entries: - :Internode => @NamedTuple{timestep::Int64, node::Node{NodeMTG, Dict{Symbol, Any}}, carbon_root_creation_consumed::Float64, TT_cu::Float64, carbon_… - :Root => @NamedTuple{timestep::Int64, node::Node{NodeMTG, Dict{Symbol, Any}}, carbon_root_creation_consumed::Float64, water_absorbed::Float64… - :Scene => @NamedTuple{timestep::Int64, node::Node{NodeMTG, Dict{Symbol, Any}}, TT_cu::Float64, TT::Float64}[(timestep = 1, node = / 1: Scene… - :Plant => @NamedTuple{timestep::Int64, node::Node{NodeMTG, Dict{Symbol, Any}}, carbon_root_creation_consumed::Float64, carbon_stock::Float64, … - :Leaf => @NamedTuple{timestep::Int64, node::Node{NodeMTG, Dict{Symbol, Any}}, carbon_captured::Float64}[(timestep = 1, node = + 4: Leaf… - -julia> outs[:Root] -3257-element Vector{@NamedTuple{timestep::Int64, node::Node{NodeMTG, Dict{Symbol, Any}}, carbon_root_creation_consumed::Float64, water_absorbed::Float64, root_water_assimilation::Float64}}: - (timestep = 1, node = + 9: Root -└─ < 10: Root - └─ < 11: Root - └─ < 12: Root - └─ < 13: Root - └─ < 14: Root - └─ < 15: Root - └─ < 16: Root - └─ < 17: Root -, carbon_root_creation_consumed = 50.0, water_absorbed = 0.5, root_water_assimilation = 1.0) - ⋮ -``` - -Values are more complex to query than in a single-scale simulation since the indexing isn't straightforward to map to a timestep: - -```julia -julia> [Pair(outs[:Root][i][:timestep], outs[:Root][i][:carbon_root_creation_consumed]) for i in 1:length(outs[:Root])] -3257-element Vector{Pair{Int64, Float64}}: - 1 => 50.0 - 1 => 50.0 - 2 => 50.0 - 2 => 50.0 - 2 => 50.0 - ⋮ - 365 => 50.0 - 365 => 50.0 - 365 => 50.0 - 365 => 50.0 - 365 => 50.0 - 365 => 50.0 - 365 => 50.0 - 365 => 50.0 - 365 => 50.0 -``` - -Converting to a dictionary of DataFrame objects can make such queries easier to write. - -!!! warning - Currently, the `:node` entry only shallow copies nodes. The `:node` values at each scale for every timestep actually reflect the final state of the node, meaning attribute values may not correspond to the value at that timestep. You may need to output these values via a dedicated model to keep track of them properly. - Also note that there currently is no way of removing nodes. Nodes corresponding to organs considered to be pruned/dead/aborted are still present in the output data structure. - -Multi-scale simulations, especially for plants which have thousands of leaves, internodes, root branches, buds and fruits, may compute huge amounts of data. Just like in single-scale simulations, it is possible to keep only variables whose values you want to track for every timestep, and filter the rest out, using the `tracked_outputs` keyword argument for the [`run!`](@ref) function. - -Those tracked variables also need to be indexed by scale to avoid ambiguity: - -```julia -outs = ModelMapping( - :Scene => (:TT, :TT_cu,), - :Plant => (:aPPFD, :LAI), - :Leaf => (:carbon_assimilation, :carbon_demand, :carbon_allocation, :TT), - :Internode => (:carbon_allocation,), - :Soil => (:soil_water_content,), -) -``` - -## Coupling and multi-scale hard dependencies - -Multi-scale brings new types of coupling: mappings are part of the approach used to handle variables used by models at different scales. A model can also have a hard dependency on another model that operates at another scale. This multi-scale-specific complexity is discussed in [Handling dependencies in a multiscale context](@ref) diff --git a/docs/src/multiscale/multiscale_coupling.md b/docs/src/multiscale/multiscale_coupling.md deleted file mode 100644 index 15d75ec29..000000000 --- a/docs/src/multiscale/multiscale_coupling.md +++ /dev/null @@ -1,171 +0,0 @@ - -# Handling dependencies in a multiscale context - -```@contents -Pages = ["multiscale_coupling.md"] -Depth = 3 -``` - -## Scalar and vector variable mappings - -In the detailed example discussed previously [Multi-scale variable mapping](@ref), there were several instances of mapping a variable from one scale to another, which we'll briefly describe again to help transition to the next and more advanced subsection. Here's a relevant exerpt from the mapping : - -```julia -:Plant => ( - MultiScaleModel( - model=ToyLAIModel(), - mapped_variables=[ - :TT_cu => :Scene, - ], - ), - ... - MultiScaleModel( - model=ToyCAllocationModel(), - mapped_variables=[ - :carbon_assimilation => [:Leaf], - :carbon_demand => [:Leaf, :Internode], - :carbon_allocation => [:Leaf, :Internode] - ], - ), - ... - ), -``` - -For flexibility reasons, instead of explicitely linking most models from different scales together, one only declares which variables are meant to be taken from another scale (or more accurately, a model at a different scale outputting those variables). This keeps the convenience of switching models while making few changes to the mapping. - -However, PlantSimEngine cannot infer which scales have multiple instances, and which are single-instance, as the scale names are user-defined. - -In the above example, there is only one scene at the :Scene, and one plant at the :Plant scale, meaning the `TT_cu` variable mapped between the two has a one-to-one scalar-to-scalar correspondance. - -On the other hand, the `carbon_assimilation` variable is computed for **every** leaf, of which there could be hundreds, or thousands, giving a scalar-to-vector correspondance. The carbon assimilation model runs many times every timestep, whereas the carbon allocation model only runs once per timestep. There may be initially be only a single leaf, though, meaning PlantSimEngine cannot currently guess from the initial configuration that there might be multiple leaves created during the simulation. - -Hence the difference in mapping declaration : `TT_cu`is declared as a scalar correspondence : -```julia -:TT_cu => :Scene, -``` -whereas `carbon_assimilation` (and other variables) will be declared as a vector correspondence : -```julia -:carbon_assimilation => [:Leaf], -``` - -Note that there may be instances where you might wish to write your own model to aggregate a variable from a multi-instance scale. - -## Hard dependencies between models at different scale levels - -If a model requires some input variable that is computed at another scale, then providing the appropriate mapping for that variable will resolve name conflicts and enable that model to run with no further steps for the user or the modeler when the coupling is a 'soft dependency'. - -In the case of a hard dependency that operates **at the same scale as its parent**, declaring the hard dependency is exactly the same as in single-scale simulations and there are also no new extra steps on the user-side: - -- The parent model directly handles the call to its hard dependency model(s), meaning they are not explicitely managed by the top-level dependency graph. -- This means only the owning model of that dependency is visible in the graph, and its hard dependency nodes are internal. -- When the caller (or any downstream model that requires some variables from the hard dependency model) operates at the same scale, variables are easily accessible, and no mapping is required. - -On the other hand, modelers do need to bear in mind a couple of subtleties when developing models that possess hard dependencies that operate **at a different organ level from their parent**: - -If an model needs to be directly called by a parent but operates at a different scale/organ level, a modeler must declare hard dependencies with their respective organ level, similarly to the way the user provides a mapping. - -Conceptually : - -```julia - PlantSimEngine.dep(m::ParentModel) = ( - name_provided_in_the_mapping=AbstractHardDependencyModel => [:Organ_Name_1], -) -``` - -### An example from the toy plant simulation tutorial - -You can find an example of a hard dependency discussed in the [A multi-scale hard dependency appears](@ref) subsection of the third part of toy plant tutorial. - -### An example from XPalm.jl - -Here's a concrete example in [XPalm](https://github.com/PalmStudio/XPalm.jl), an oil palm model developed on top of PlantSimEngine. - Organs are produced at the phytomer scale, but need to run an age model and a biomass model at the reproductive organs' scales. - -```julia - PlantSimEngine.dep(m::ReproductiveOrganEmission) = ( - initiation_age=AbstractInitiation_AgeModel => [m.male_symbol, m.female_symbol], - final_potential_biomass=AbstractFinal_Potential_BiomassModel => [m.male_symbol, m.female_symbol], -) -``` - -The user-mapping includes the required models at specific organ levels. Here's the relevant portion of the mapping for the male reproductive organ : - -```julia -mapping = ModelMapping( - ... - :Male => - MultiScaleModel( - model=XPalm.InitiationAgeFromPlantAge(), - mapped_variables=[:plant_age => :Plant,], - ), - ... - XPalm.MaleFinalPotentialBiomass( - p.parameters[:male][:male_max_biomass], - p.parameters[:male][:age_mature_male], - p.parameters[:male][:fraction_biomass_first_male], - ), - ... -) -``` - -The model's constructor provides convenient default names for the scale corresponding to the reproductive organs. A user may override that if their naming schemes or MTG attributes differ. - -```julia -function ReproductiveOrganEmission(mtg::MultiScaleTreeGraph.Node; phytomer_symbol=:Phytomer, male_symbol=:Male, female_symbol=:Female) - ... -end -``` - -## Implementation details: accessing a hard dependency's variables from a different scale - -But how does a model M calling a hard dependency H provide H's variables when calling H's [`run!`](@ref) function ? The [`status`](@ref) argument the user provides M operates at M's organ level, so if used to call H's run! function any required variable for H will be missing. - -PlantSimEngine provides what are called Status Templates in the simulation graph. Each organ level has its own Status template listing the available variables at that scale. -So when a model M calls a hard dependency H's [`run!`](@ref) function, any required variables can be accessed through the status template of H's organ level. - -### Back to the XPalm example - -Using the same example in XPalm, the oil palm FSPM: - -```julia -# Note that the function's 'status' parameter does NOT contain the variables required by the hard dependencies as the calling model's organ level is "Phytomer", not :Male or "Female" - -function PlantSimEngine.run!(m::ReproductiveOrganEmission, models, status, meteo, constants, sim_object) - ... - status.graph_node_count += 1 - - # Create the new organ as a child of the phytomer: - st_repro_organ = add_organ!( - status.node[1], # The phytomer's internode is its first child - sim_object, # The simulation object, so we can add the new status - "+", status.sex, 4; - index=status.phytomer_count, - id=status.graph_node_count, - attributes=Dict{Symbol,Any}() - ) - - # Compute the initiation age of the organ: - PlantSimEngine.run!(sim_object.models[status.sex].initiation_age, sim_object.models[status.sex], st_repro_organ, meteo, constants, sim_object) - PlantSimEngine.run!(sim_object.models[status.sex].final_potential_biomass, sim_object.models[status.sex], st_repro_organ, meteo, constants, sim_object) -end -``` - -In the above example the organ and its status template are created on the fly. -When that isn't the case, the status template can be accessed through the simulation graph : - -```julia -function PlantSimEngine.run!(m::ReproductiveOrganEmission, models, status, meteo, constants, sim_object) - - ... - - if status.sex == :Male - - status_male = sim_object.statuses[:Male][1] - run!(sim_object.models[:Male].initiation_age, models, status_male, meteo, constants, sim_object) - run!(sim_object.models[:Male].final_potential_biomass, models, status_male, meteo, constants, sim_object) - else - # Female - ... - end -end -``` diff --git a/docs/src/multiscale/multiscale_cyclic.md b/docs/src/multiscale/multiscale_cyclic.md deleted file mode 100644 index f0c62bb72..000000000 --- a/docs/src/multiscale/multiscale_cyclic.md +++ /dev/null @@ -1,115 +0,0 @@ -# Avoiding cyclic dependencies - -When defining a mapping between models and scales, it is important to avoid cyclic dependencies. A cyclic dependency occurs when a model at a given scale depends on a model at another scale that depends on the first model. Cyclic dependencies are bad because they lead to an infinite loop in the simulation (the dependency graph keeps cycling indefinitely). - -PlantSimEngine will detect cyclic dependencies and raise an error if one is found. The error message indicates the models involved in the cycle, and the model that is causing the cycle will be highlighted in red. - -For example the following mapping will raise an error: - -!!! details - Example mapping - - ```julia - mapping_cyclic = ModelMapping( - :Plant => ( - MultiScaleModel( - model=ToyCAllocationModel(), - mapped_variables=[ - :carbon_demand => [:Leaf, :Internode], - :carbon_allocation => [:Leaf, :Internode] - ], - ), - MultiScaleModel( - model=ToyPlantRmModel(), - mapped_variables=[:Rm_organs => [:Leaf => :Rm, :Internode => :Rm],], - ), - Status(total_surface=0.001, aPPFD=1300.0, soil_water_content=0.6), - ), - :Internode => ( - ToyCDemandModel(optimal_biomass=10.0, development_duration=200.0), - ToyMaintenanceRespirationModel(1.5, 0.06, 25.0, 0.6, 0.004), - Status(TT=10.0, carbon_biomass=1.0), - ), - :Leaf => ( - ToyCDemandModel(optimal_biomass=10.0, development_duration=200.0), - ToyMaintenanceRespirationModel(2.1, 0.06, 25.0, 1.0, 0.025), - ToyCBiomassModel(1.2), - Status(TT=10.0), - ) - ) - ``` - -Let's see what happens when we try to build the dependency graph for this mapping: - -```julia -julia> dep(mapping_cyclic) -ERROR: Cyclic dependency detected in the graph. Cycle: - Plant: ToyPlantRmModel - └ Leaf: ToyMaintenanceRespirationModel - └ Leaf: ToyCBiomassModel - └ Plant: ToyCAllocationModel - └ Plant: ToyPlantRmModel - - You can break the cycle using the `PreviousTimeStep` variable in the mapping. -``` - -How can we interpret the message? We have a list of five models involved in the cycle. The first model is the one causing the cycle, and the others are the ones that depend on it. In this case, the `ToyPlantRmModel` is the one causing the cycle, and the others are inter-dependent. We can read this as follows: - -1. `ToyPlantRmModel` depends on `ToyMaintenanceRespirationModel`, the plant-scale respiration sums up all organs respiration; -2. `ToyMaintenanceRespirationModel` depends on `ToyCBiomassModel`, the organs respiration depends on the organs biomass; -3. `ToyCBiomassModel` depends on `ToyCAllocationModel`, the organs biomass depends on the organs carbon allocation; -4. And finally `ToyCAllocationModel` depends on `ToyPlantRmModel` again, hence the cycle because the carbon allocation depends on the plant scale respiration. - -The models can not be ordered in a way that satisfies all dependencies, so the cycle can not be broken. To solve this issue, we need to re-think how models are mapped together, and break the cycle. - -There are several ways to break a cyclic dependency: - -- **Merge models**: If two models depend on each other because they need *e.g.* recursive computations, they can be merged into a third model that handles the computation and takes the two models as hard dependencies. Hard dependencies are models that are explicitly called by another model and do not participate on the building of the dependency graph. -- **Change models**: Of course models can be interchanged to avoid cyclic dependencies, but this is not really a solution, it is more a workaround. -- **PreviousTimeStep**: We can break the dependency graph by defining some variables as taken from the previous time step. A very well known example is the computation of the light interception by a plant that depends on the leaf area, which is usually the result of a model that also depends on the light interception. The cyclic dependency is usually broken by using the leaf area from the previous time step in the interception model, which is a good approximation for most cases. - -We can fix our previous mapping by computing the organs respiration using the carbon biomass from the previous time step instead. Let's see how to fix the cyclic dependency in our mapping (look at the leaf and internode scales): - -!!! details - ```@julia - mapping_nocyclic = ModelMapping( - :Plant => ( - MultiScaleModel( - model=ToyCAllocationModel(), - mapping=[ - :carbon_demand => [:Leaf, :Internode], - :carbon_allocation => [:Leaf, :Internode] - ], - ), - MultiScaleModel( - model=ToyPlantRmModel(), - mapped_variables=[:Rm_organs => [:Leaf => :Rm, :Internode => :Rm],], - ), - Status(total_surface=0.001, aPPFD=1300.0, soil_water_content=0.6, carbon_assimilation=5.0), - ), - :Internode => ( - ToyCDemandModel(optimal_biomass=10.0, development_duration=200.0), - MultiScaleModel( - model=ToyMaintenanceRespirationModel(1.5, 0.06, 25.0, 0.6, 0.004), - mapped_variables=[PreviousTimeStep(:carbon_biomass),], #! this is where we break the cyclic dependency (first break) - ), - Status(TT=10.0, carbon_biomass=1.0), - ), - :Leaf => ( - ToyCDemandModel(optimal_biomass=10.0, development_duration=200.0), - MultiScaleModel( - model=ToyMaintenanceRespirationModel(2.1, 0.06, 25.0, 1.0, 0.025), - mapped_variables=[PreviousTimeStep(:carbon_biomass),], #! this is where we break the cyclic dependency (second break) - ), - ToyCBiomassModel(1.2), - Status(TT=10.0), - ) - ); - nothing # hide - ``` - -The `ToyMaintenanceRespirationModel` models are now defined as [`MultiScaleModel`](@ref), and the `carbon_biomass` variable is wrapped in a `PreviousTimeStep` structure. This structure tells PlantSimEngine to take the value of the variable from the previous time step, breaking the cyclic dependency. - -!!! note - [`PreviousTimeStep`](@ref) tells PlantSimEngine to take the value of the previous time step for the variable it wraps, or the value at initialization for the first time step. The value at initialization is the one provided by default in the models inputs, but is usually provided in the [`Status`](@ref) structure to override this default. - A [`PreviousTimeStep`](@ref) is used to wrap the **input** variable of a model, with or without a mapping to another scale *e.g.* `PreviousTimeStep(:carbon_biomass) => :Leaf`. \ No newline at end of file diff --git a/docs/src/multiscale/multiscale_example_1.md b/docs/src/multiscale/multiscale_example_1.md deleted file mode 100644 index 19dd671e0..000000000 --- a/docs/src/multiscale/multiscale_example_1.md +++ /dev/null @@ -1,289 +0,0 @@ -# Writing a multiscale simulation - -This three-part subsection walks you through building a multi-scale simulation from scratch. It is meant as an illustration of the iterative process you might go through when building and slowly tuning a Functional-Structural Plant Model, where previous multi-scale examples focused more on the API syntax. - -You can find the full script for the first part's toy simulation in the [ToyMultiScalePlantModel](https://github.com/VirtualPlantLab/PlantSimEngine.jl/blob/main/examples/ToyMultiScalePlantModel/ToyPlantSimulation1.jl) subfolder of the examples folder. - -```@contents -Pages = ["multiscale_example_1.md"] -Depth = 3 -``` - -## Disclaimer - -The actual plant being created, as well as some of the custom models, have no real physical meaning and are very much ad hoc (which is why most of them aren't standalone in the examples folder). Similarly, some of the parameter values are pulled out of thin air, and have no ties to research papers or data. - -The main purpose here is to showcase PlantSimEngine's multi-scale features and how to structure your models, not accuracy, realism or performance. - -## Initial setup - -We'll need to make use of a few packages, as usual, after adding them to our Julia environment: - -```@example usepkg -using PlantSimEngine -using PlantSimEngine.Examples # to import the ToyDegreeDaysCumulModel model -using PlantMeteo, Dates -using MultiScaleTreeGraph # multi-scale -``` - -## A basic growing plant - -At minimum, to simulate some kind of fake growth, we need : - -- A Multi-scale Tree Graph representing the plant -- Some way of adding organs to the plant -- Some kind of temporality to spread this growth over multiple timesteps - -Let's have some concept of 'leaves' that capture the (carbon) resource necessary for organ growth, and let's have the organ emergence happen at the 'internode' level, to illustrate multiple organs with different behavior. - -We'll make the assumption that the internodes make use of carbon from a common pool. We'll also make use of thermal time as a growth delay factor. - -To sum up, we have: -- a MTG with growing internodes and leaves -- Individual leaves that capture carbon fed into a common pool -- Internodes which take from that pool to create new organs, with a thermal time constraint. - -One way of modeling this approach translates into several scales and models: - -- a Scene scale, for thermal time. The [`ToyDegreeDaysCumulModel`](@ref) from the [examples folder](https://github.com/VirtualPlantLab/PlantSimEngine.jl/blob/main/examples/ToyDegreeDays.jl) provides thermal time from temperature data -- a Plant scale, where we'll define the carbon pool -- an Internode scale, which draws from the pool to create new organs -- a Leaf scale, which captures carbon - -Let's also add a very artificial limiting factor: if the total leaf surface area is above a threshold no new organs are created. - -We can expect the simulation mapping to look like a more complex version of the following: - -```julia -mapping = ModelMapping( -:Scene => ToyDegreeDaysCumulModel(), -:Plant => ToyStockComputationModel(), -:Internode => ToyCustomInternodeEmergence(), -:Leaf => ToyLeafCarbonCaptureModel(), -) -``` - -Some of the models will need to gather variables from scales other than their own, meaning they will need to be converted into MultiScaleModels. - -## Implementation - -### Carbon Capture - -Let's start with the simplest model. Our fake leaves will continuously capture some constant amount of carbon every timestep. No inputs or parameters are required. - -```@example usepkg -PlantSimEngine.@process "leaf_carbon_capture" verbose = false - -struct ToyLeafCarbonCaptureModel<: AbstractLeaf_Carbon_CaptureModel end - -function PlantSimEngine.inputs_(::ToyLeafCarbonCaptureModel) - NamedTuple() # No inputs -end - -function PlantSimEngine.outputs_(::ToyLeafCarbonCaptureModel) - (carbon_captured=0.0,) -end - -function PlantSimEngine.run!(::ToyLeafCarbonCaptureModel, models, status, meteo, constants, extra) - status.carbon_captured = 40 -end -``` - -### Resource storage - -The model storing resources for the whole plant needs a couple of inputs: the amount of carbon captured by the leaves, as well as the amount consumed by the creation of new organs. It outputs the current stock. - -```@example usepkg -PlantSimEngine.@process "resource_stock_computation" verbose = false - -struct ToyStockComputationModel <: AbstractResource_Stock_ComputationModel -end - -PlantSimEngine.inputs_(::ToyStockComputationModel) = -(carbon_captured=0.0,carbon_organ_creation_consumed=0.0) - -PlantSimEngine.outputs_(::ToyStockComputationModel) = (carbon_stock=-Inf,) - -function PlantSimEngine.run!(m::ToyStockComputationModel, models, status, meteo, constants=nothing, extra=nothing) - status.carbon_stock += sum(status.carbon_captured) - sum(status.carbon_organ_creation_consumed) -end -``` - -### Organ creation - -This model is a modified version of the ToyInternodeEmergence model found [in the examples folder](https://github.com/VirtualPlantLab/PlantSimEngine.jl/blob/main/examples/ToyInternodeEmergence.jl). An internode produces two leaves and a new internode. - -Let's first define a helper function that iterates across a Multiscale Tree Graph and returns the number of leaves : - -```@example usepkg -function get_n_leaves(node::MultiScaleTreeGraph.Node) - root = MultiScaleTreeGraph.get_root(node) - nleaves = length(MultiScaleTreeGraph.traverse(root, x->1, symbol=:Leaf)) - return nleaves -end -``` - -Now that we have that, let's define a few parameters to the model. It requires : -- a thermal time emergence threshold -- a carbon cost for organ creation - -We'll also add a couple of other parameters, which could go elsewhere : -- the surface area of a leaf (no variation, no growth stages) -- the max leaf surface area beyond which organ creation stops - -```@example usepkg -PlantSimEngine.@process "organ_emergence" verbose = false - -struct ToyCustomInternodeEmergence{T} <: AbstractOrgan_EmergenceModel - TT_emergence::T - carbon_internode_creation_cost::T - leaf_surface_area::T - leaves_max_surface_area::T -end -``` - -!!! note - We make use of parametric types instead of the intuitive Float64 for flexibility. See [Parametric types](@ref) for a more in-depth explanation - -And give them some default values : - -```@example usepkg -ToyCustomInternodeEmergence(;TT_emergence=300.0, carbon_internode_creation_cost=200.0, leaf_surface_area=3.0, leaves_max_surface_area=100.0) = ToyCustomInternodeEmergence(TT_emergence, carbon_internode_creation_cost, leaf_surface_area, leaves_max_surface_area) -``` - -Our internode model requires thermal time, and the amount of available carbon, and outputs the amount of carbon consumed, as well as the last thermal time where emergence happened (this is useful when new organs can be produced multiple times, which won't be the case here). - -```@example usepkg -PlantSimEngine.inputs_(m::ToyCustomInternodeEmergence) = (TT_cu=0.0, carbon_stock=0.0) -PlantSimEngine.outputs_(m::ToyCustomInternodeEmergence) = (TT_cu_emergence=0.0, carbon_organ_creation_consumed=0.0) -``` -Finally, the [`run!`](@ref) function checks that conditions are met for new organ creation : -- thermal time threshold exceeded -- total leaf surface area not above limit -- carbon available -- no organs already created by that internode - -and then updates the MTG. - -```@example usepkg -function PlantSimEngine.run!(m::ToyCustomInternodeEmergence, models, status, meteo, constants=nothing, sim_object=nothing) - - leaves_surface_area = m.leaf_surface_area * get_n_leaves(status.node) - status.carbon_organ_creation_consumed = 0.0 - - if leaves_surface_area > m.leaves_max_surface_area - return nothing - end - - # if not enough carbon, no organ creation - if status.carbon_stock < m.carbon_internode_creation_cost - return nothing - end - - if length(MultiScaleTreeGraph.children(status.node)) == 2 && - status.TT_cu - status.TT_cu_emergence >= m.TT_emergence - status_new_internode = add_organ!(status.node, sim_object, "<", :Internode, 2, index=1) - add_organ!(status_new_internode.node, sim_object, "+", :Leaf, 2, index=1) - add_organ!(status_new_internode.node, sim_object, "+", :Leaf, 2, index=1) - - status_new_internode.TT_cu_emergence = m.TT_emergence - status.TT_cu - status.carbon_organ_creation_consumed = m.carbon_internode_creation_cost - end - - return nothing -end -``` - -### Updated mapping - -We can now define the final mapping for this simulation. - -The carbon capture and thermal time models don't need to be changed from the earlier version. -The organ creation model at the :Internode scale needs the carbon stock from the :Plant scale, as well as thermal time from the :Scene scale. -The resource storing model at the :Plant scale needs the carbon captured by **every** leaf, and the carbon consumed by **every** internode that created new organs this timestep. This requires mapping vector variables : - -```julia - mapped_variables=[ - :carbon_captured=>[:Leaf], - :carbon_organ_creation_consumed=>[:Internode] - ], -``` -as opposed to the single-valued carbon stock mapped variable : - -```julia - mapped_variables=[:TT_cu => :Scene, - PreviousTimeStep(:carbon_stock)=>:Plant], -``` - -And of course, some variables need to be initialized in the status: - -```@example usepkg -mapping = ModelMapping( -:Scene => ToyDegreeDaysCumulModel(), -:Plant => ( - MultiScaleModel( - model=ToyStockComputationModel(), - mapped_variables=[ - :carbon_captured=>[:Leaf], - :carbon_organ_creation_consumed=>[:Internode] - ], - ), - Status(carbon_stock = 0.0) - ), -:Internode => ( - MultiScaleModel( - model=ToyCustomInternodeEmergence(),#TT_emergence=20.0), - mapped_variables=[:TT_cu => :Scene, - PreviousTimeStep(:carbon_stock)=>:Plant], - ), - Status(carbon_organ_creation_consumed=0.0), - ), -:Leaf => ToyLeafCarbonCaptureModel(), -) -``` - -!!! note - This excerpt (and the complete script file) showcase the final properly initialized mapping, but when developing, you are encouraged to make liberal use of the helper function [`to_initialize`](@ref) and check the PlantSimEngine user errors. - -### Running a simulation - -We only need an MTG, and some weather data, and then we'll be set. Let's create a simple MTG : - -```@example usepkg -mtg = MultiScaleTreeGraph.Node(MultiScaleTreeGraph.NodeMTG("/", :Scene, 1, 0)) -plant = MultiScaleTreeGraph.Node(mtg, MultiScaleTreeGraph.NodeMTG("+", :Plant, 1, 1)) - -internode1 = MultiScaleTreeGraph.Node(plant, MultiScaleTreeGraph.NodeMTG("/", :Internode, 1, 2)) -MultiScaleTreeGraph.Node(internode1, MultiScaleTreeGraph.NodeMTG("+", :Leaf, 1, 2)) -MultiScaleTreeGraph.Node(internode1, MultiScaleTreeGraph.NodeMTG("+", :Leaf, 1, 2)) - -internode2 = MultiScaleTreeGraph.Node(internode1, MultiScaleTreeGraph.NodeMTG("<", :Internode, 1, 2)) -MultiScaleTreeGraph.Node(internode2, MultiScaleTreeGraph.NodeMTG("+", :Leaf, 1, 2)) -MultiScaleTreeGraph.Node(internode2, MultiScaleTreeGraph.NodeMTG("+", :Leaf, 1, 2)) -``` - -Import some weather data: - -```@example usepkg -meteo_day = read_weather(joinpath(pkgdir(PlantSimEngine), "examples/meteo_day.csv"), duration=Dates.Day) -nothing # hide -``` - -And we're good to go ! - -```@example usepkg -outs = run!(mtg, mapping, meteo_day) -``` - -If you query or display the MTG after simulation, you'll see it expanded and grew multiple internodes and leaves : - -```@example usepkg -mtg -#get_n_leaves(mtg) -``` - -And that's it ! Feel free to tinker with the parameters and see when things break down, to get a feel for the simulation. - -Of course, this is a very crude and unrealistic simulation, with many dubious assumptions and parameters. But significantly more complex modelling is possible using the same approach : XPalm runs using a few dozen models spread out over nine scales. - -This is a three-part tutorial and continues in the [Expanding on the multiscale simulation](@ref) page. \ No newline at end of file diff --git a/docs/src/multiscale/multiscale_example_2.md b/docs/src/multiscale/multiscale_example_2.md deleted file mode 100644 index 539399ddf..000000000 --- a/docs/src/multiscale/multiscale_example_2.md +++ /dev/null @@ -1,266 +0,0 @@ -# Expanding on the multiscale simulation - -Let's build on the previous example and add some other organ growth, as well as some very mild coupling between the two. - -You can find the full script for this simulation in the [ToyMultiScalePlantModel](https://github.com/VirtualPlantLab/PlantSimEngine.jl/blob/main/examples/ToyMultiScalePlantModel/ToyPlantSimulation2.jl) subfolder of the examples folder. - -```@contents -Pages = ["multiscale_example_2.md"] -Depth = 3 -``` - -## Setup - -Once again, with a properly set-up Julia environment: - -```@example usepkg -using PlantSimEngine -using PlantSimEngine.Examples -using PlantMeteo, Dates, Dates -using MultiScaleTreeGraph - -PlantSimEngine.@process "leaf_carbon_capture" verbose = false - -struct ToyLeafCarbonCaptureModel<: AbstractLeaf_Carbon_CaptureModel end - -function PlantSimEngine.inputs_(::ToyLeafCarbonCaptureModel) - NamedTuple() # No inputs -end - -function PlantSimEngine.outputs_(::ToyLeafCarbonCaptureModel) - (carbon_captured=0.0,) -end - -function PlantSimEngine.run!(::ToyLeafCarbonCaptureModel, models, status, meteo, constants, extra) - status.carbon_captured = 40 -end - -function get_n_leaves(node::MultiScaleTreeGraph.Node) - root = MultiScaleTreeGraph.get_root(node) - nleaves = length(MultiScaleTreeGraph.traverse(root, x->1, symbol=:Leaf)) - return nleaves -end -``` - -## Adding roots to our plant - -We'll add a root that extracts water and adds it to the stock. Initial water stocks are low, so root growth is prioritized, then the plant also grows leaves and a new internode like it did before. Roots only grow up to a certain point, and don't branch. - -This leads to adding a new scale, :Root to the mapping, as well as two more models, one for water absorption, the other for root growth. Other models are updated here and there to account for water. The carbon capture model remains unchanged, and so is the `get_n_leaves` helper function. - -## Root models - -### Water absorption - -Let's implement a very fake model of root water absorption. It'll capture the amount of precipitation in the weather data multiplied by some assimilation factor. - -```@example usepkg -PlantSimEngine.@process "water_absorption" verbose = false - -struct ToyWaterAbsorptionModel <: AbstractWater_AbsorptionModel -end - -PlantSimEngine.inputs_(::ToyWaterAbsorptionModel) = (root_water_assimilation=1.0,) -PlantSimEngine.outputs_(::ToyWaterAbsorptionModel) = (water_absorbed=0.0,) - -function PlantSimEngine.run!(m::ToyWaterAbsorptionModel, models, status, meteo, constants=nothing, extra=nothing) - status.water_absorbed = meteo.Precipitations * status.root_water_assimilation -end -``` - -### Root growth - -The root growth model is similar to the internode growth one : it checks for a water threshold and that there is enough carbon, and adds a new organ to the MTG if the maximum length hasn't been reached. - -It also makes use of a couple of helper functions to find the end root and compute root length : - -```@example usepkg -function get_root_end_node(node::MultiScaleTreeGraph.Node) - root = MultiScaleTreeGraph.get_root(node) - return MultiScaleTreeGraph.traverse(root, x->x, symbol=:Root, filter_fun = MultiScaleTreeGraph.isleaf) -end - -function get_roots_count(node::MultiScaleTreeGraph.Node) - root = MultiScaleTreeGraph.get_root(node) - return length(MultiScaleTreeGraph.traverse(root, x->x, symbol=:Root)) -end - -PlantSimEngine.@process "root_growth" verbose = false - -struct ToyRootGrowthModel{T} <: AbstractRoot_GrowthModel - water_threshold::T - carbon_root_creation_cost::T - root_max_len::Int -end - -PlantSimEngine.inputs_(::ToyRootGrowthModel) = (water_stock=0.0,carbon_stock=0.0,) -PlantSimEngine.outputs_(::ToyRootGrowthModel) = (carbon_root_creation_consumed=0.0,) - -function PlantSimEngine.run!(m::ToyRootGrowthModel, models, status, meteo, constants=nothing, extra=nothing) - if status.water_stock < m.water_threshold && status.carbon_stock > m.carbon_root_creation_cost - - root_end = get_root_end_node(status.node) - - if length(root_end) != 1 - throw(AssertionError("Couldn't find MTG leaf node with symbol \"Root\"")) - end - root_len = get_roots_count(root_end[1]) - if root_len < m.root_max_len - st = add_organ!(root_end[1], extra, "<", :Root, 2, index=1) - status.carbon_root_creation_consumed = m.carbon_root_creation_cost - end - else - status.carbon_root_creation_consumed = 0.0 - end -end -``` - -## Updating other models to account for water - -### Resource storage - -Water absorbed must now be accumulated, and root carbon creation costs taken into account. - -```@example usepkg -PlantSimEngine.@process "resource_stock_computation" verbose = false - -struct ToyStockComputationModel <: AbstractResource_Stock_ComputationModel -end - -PlantSimEngine.inputs_(::ToyStockComputationModel) = -(water_absorbed=0.0,carbon_captured=0.0,carbon_organ_creation_consumed=0.0,carbon_root_creation_consumed=0.0) - -PlantSimEngine.outputs_(::ToyStockComputationModel) = (water_stock=-Inf,carbon_stock=-Inf) - -function PlantSimEngine.run!(m::ToyStockComputationModel, models, status, meteo, constants=nothing, extra=nothing) - status.water_stock += sum(status.water_absorbed) - status.carbon_stock += sum(status.carbon_captured) - sum(status.carbon_organ_creation_consumed) - sum(status.carbon_root_creation_consumed) -end -``` - -### Internode creation - -The minor change is that new organs are now created only if the water stock is above a given threshold. - -```@example usepkg -struct ToyCustomInternodeEmergence{T} <: AbstractOrgan_EmergenceModel - TT_emergence::T - carbon_internode_creation_cost::T - leaf_surface_area::T - leaves_max_surface_area::T - water_leaf_threshold::T -end - -ToyCustomInternodeEmergence(;TT_emergence=300.0, carbon_internode_creation_cost=200.0, leaf_surface_area=3.0,leaves_max_surface_area=100.0, -water_leaf_threshold=30.0) = ToyCustomInternodeEmergence(TT_emergence, carbon_internode_creation_cost, leaf_surface_area, leaves_max_surface_area, water_leaf_threshold) - -PlantSimEngine.inputs_(m::ToyCustomInternodeEmergence) = (TT_cu=0.0,water_stock=0.0, carbon_stock=0.0) -PlantSimEngine.outputs_(m::ToyCustomInternodeEmergence) = (TT_cu_emergence=0.0, carbon_organ_creation_consumed=0.0) - -function PlantSimEngine.run!(m::ToyCustomInternodeEmergence, models, status, meteo, constants=nothing, sim_object=nothing) - - leaves_surface_area = m.leaf_surface_area * get_n_leaves(status.node) - status.carbon_organ_creation_consumed = 0.0 - - if leaves_surface_area > m.leaves_max_surface_area - return nothing - end - - # if water levels are low, prioritise roots - if status.water_stock < m.water_leaf_threshold - return nothing - end - - # if not enough carbon, no organ creation - if status.carbon_stock < m.carbon_internode_creation_cost - return nothing - end - - if length(MultiScaleTreeGraph.children(status.node)) == 2 && - status.TT_cu - status.TT_cu_emergence >= m.TT_emergence - status_new_internode = add_organ!(status.node, sim_object, "<", :Internode, 2, index=1) - add_organ!(status_new_internode.node, sim_object, "+", :Leaf, 2, index=1) - add_organ!(status_new_internode.node, sim_object, "+", :Leaf, 2, index=1) - - status_new_internode.TT_cu_emergence = m.TT_emergence - status.TT_cu - status.carbon_organ_creation_consumed = m.carbon_internode_creation_cost - end - - return nothing -end -``` - -## Updating the mapping - -The resource storage and internode emergence models now need a couple of extra water-related mapped variables. -The :Root organ is added to the mapping with its own models. New parameters need to be initialized. - -```@example usepkg -mapping = ModelMapping( -:Scene => ToyDegreeDaysCumulModel(), -:Plant => ( - MultiScaleModel( - model=ToyStockComputationModel(), - mapped_variables=[ - :carbon_captured=>[:Leaf], - :water_absorbed=>[:Root], - :carbon_root_creation_consumed=>[:Root], - :carbon_organ_creation_consumed=>[:Internode] - - ], - ), - Status(water_stock = 0.0, carbon_stock = 0.0) - ), -:Internode => ( - MultiScaleModel( - model=ToyCustomInternodeEmergence(),#TT_emergence=20.0), - mapped_variables=[:TT_cu => :Scene, - PreviousTimeStep(:water_stock)=>:Plant, - PreviousTimeStep(:carbon_stock)=>:Plant], - ), - Status(carbon_organ_creation_consumed=0.0), - ), -:Root => ( MultiScaleModel( - model=ToyRootGrowthModel(10.0, 50.0, 10), - mapped_variables=[PreviousTimeStep(:carbon_stock)=>:Plant, - PreviousTimeStep(:water_stock)=>:Plant], - ), - ToyWaterAbsorptionModel(), - Status(carbon_root_creation_consumed=0.0, root_water_assimilation=1.0), - ), -:Leaf => ( ToyLeafCarbonCaptureModel(),), -) -``` - -## Running the simulation - -Running this new simulation is almost the same as before. The weather data is unchanged, but a new :Root node was added to the MTG. - -```@example usepkg -mtg = MultiScaleTreeGraph.Node(MultiScaleTreeGraph.NodeMTG("/", :Scene, 1, 0)) - plant = MultiScaleTreeGraph.Node(mtg, MultiScaleTreeGraph.NodeMTG("+", :Plant, 1, 1)) - - internode1 = MultiScaleTreeGraph.Node(plant, MultiScaleTreeGraph.NodeMTG("/", :Internode, 1, 2)) - MultiScaleTreeGraph.Node(internode1, MultiScaleTreeGraph.NodeMTG("+", :Leaf, 1, 2)) - MultiScaleTreeGraph.Node(internode1, MultiScaleTreeGraph.NodeMTG("+", :Leaf, 1, 2)) - - internode2 = MultiScaleTreeGraph.Node(internode1, MultiScaleTreeGraph.NodeMTG("<", :Internode, 1, 2)) - MultiScaleTreeGraph.Node(internode2, MultiScaleTreeGraph.NodeMTG("+", :Leaf, 1, 2)) - MultiScaleTreeGraph.Node(internode2, MultiScaleTreeGraph.NodeMTG("+", :Leaf, 1, 2)) - - plant_root_start = MultiScaleTreeGraph.Node( - plant, - MultiScaleTreeGraph.NodeMTG("+", :Root, 1, 3), - ) - -meteo_day = read_weather(joinpath(pkgdir(PlantSimEngine), "examples/meteo_day.csv"), duration=Dates.Day) - -outs = run!(mtg, mapping, meteo_day) -mtg -``` - -And that's it ! - -...Or is it ? - -If you inspect the code and output data closely, you may notice some distinctive problems with the way the simulation runs... Some things aren't quite right. If you wish to know more, onwards to the next chapter: [Fixing bugs in the plant simulation](@ref) \ No newline at end of file diff --git a/docs/src/multiscale/multiscale_example_3.md b/docs/src/multiscale/multiscale_example_3.md deleted file mode 100644 index 582ec984c..000000000 --- a/docs/src/multiscale/multiscale_example_3.md +++ /dev/null @@ -1,503 +0,0 @@ -# Fixing bugs in the plant simulation - -```@setup usepkg -using PlantSimEngine -using PlantSimEngine.Examples -using PlantMeteo, Dates -using MultiScaleTreeGraph -function get_root_end_node(node::MultiScaleTreeGraph.Node) - root = MultiScaleTreeGraph.get_root(node) - return MultiScaleTreeGraph.traverse(root, x->x, symbol=:Root, filter_fun = MultiScaleTreeGraph.isleaf) -end - -function get_roots_count(node::MultiScaleTreeGraph.Node) - root = MultiScaleTreeGraph.get_root(node) - return length(MultiScaleTreeGraph.traverse(root, x->x, symbol=:Root)) -end - -function get_n_leaves(node::MultiScaleTreeGraph.Node) - root = MultiScaleTreeGraph.get_root(node) - nleaves = length(MultiScaleTreeGraph.traverse(root, x->1, symbol=:Leaf)) - return nleaves -end - -PlantSimEngine.@process "organ_emergence" verbose = false - -struct ToyCustomInternodeEmergence{T} <: AbstractOrgan_EmergenceModel - TT_emergence::T - carbon_internode_creation_cost::T - leaf_surface_area::T - leaves_max_surface_area::T - water_leaf_threshold::T -end - -ToyCustomInternodeEmergence(;TT_emergence=300.0, carbon_internode_creation_cost=200.0, leaf_surface_area=3.0,leaves_max_surface_area=100.0, -water_leaf_threshold=30.0) = ToyCustomInternodeEmergence(TT_emergence, carbon_internode_creation_cost, leaf_surface_area, leaves_max_surface_area, water_leaf_threshold) - -PlantSimEngine.inputs_(m::ToyCustomInternodeEmergence) = (TT_cu=0.0,water_stock=0.0, carbon_stock=0.0) -PlantSimEngine.outputs_(m::ToyCustomInternodeEmergence) = (TT_cu_emergence=0.0, carbon_organ_creation_consumed=0.0) - -function PlantSimEngine.run!(m::ToyCustomInternodeEmergence, models, status, meteo, constants=nothing, sim_object=nothing) - - leaves_surface_area = m.leaf_surface_area * get_n_leaves(status.node) - status.carbon_organ_creation_consumed = 0.0 - - if leaves_surface_area > m.leaves_max_surface_area - return nothing - end - - # if water levels are low, prioritise roots - if status.water_stock < m.water_leaf_threshold - return nothing - end - - # if not enough carbon, no organ creation - if status.carbon_stock < m.carbon_internode_creation_cost - return nothing - end - - if length(MultiScaleTreeGraph.children(status.node)) == 2 && - status.TT_cu - status.TT_cu_emergence >= m.TT_emergence - status_new_internode = add_organ!(status.node, sim_object, "<", :Internode, 2, index=1) - add_organ!(status_new_internode.node, sim_object, "+", :Leaf, 2, index=1) - add_organ!(status_new_internode.node, sim_object, "+", :Leaf, 2, index=1) - - status_new_internode.TT_cu_emergence = m.TT_emergence - status.TT_cu - status.carbon_organ_creation_consumed = m.carbon_internode_creation_cost - end - - return nothing -end - -############################ -# Naive water absorption model -# Absorbs precipitation water depending on quantity of roots -############################ -PlantSimEngine.@process "water_absorption" verbose = false - -struct ToyWaterAbsorptionModel <: AbstractWater_AbsorptionModel -end - -PlantSimEngine.inputs_(::ToyWaterAbsorptionModel) = (root_water_assimilation=1.0,) -PlantSimEngine.outputs_(::ToyWaterAbsorptionModel) = (water_absorbed=0.0,) - -function PlantSimEngine.run!(m::ToyWaterAbsorptionModel, models, status, meteo, constants=nothing, extra=nothing) - #root_end = get_root_end_node(status.node) - #root_len = root_end[:Root_len] - status.water_absorbed = meteo.Precipitations * status.root_water_assimilation #* root_len -end - -PlantSimEngine.TimeStepDependencyTrait(::Type{<:ToyWaterAbsorptionModel}) = PlantSimEngine.IsTimeStepIndependent() -PlantSimEngine.ObjectDependencyTrait(::Type{<:ToyWaterAbsorptionModel}) = PlantSimEngine.IsObjectIndependent() - - -########################## -### Root growth : when water stocks are low, expand root -########################## - -PlantSimEngine.@process "root_growth" verbose = false - -struct ToyRootGrowthModel{T} <: AbstractRoot_GrowthModel - water_threshold::T - carbon_root_creation_cost::T - root_max_len::Int -end - -PlantSimEngine.inputs_(::ToyRootGrowthModel) = (water_stock=0.0,carbon_stock=0.0,) -PlantSimEngine.outputs_(::ToyRootGrowthModel) = (carbon_root_creation_consumed=0.0,) - -function PlantSimEngine.run!(m::ToyRootGrowthModel, models, status, meteo, constants=nothing, extra=nothing) - if status.water_stock < m.water_threshold && status.carbon_stock > m.carbon_root_creation_cost - - root_end = get_root_end_node(status.node) - - if length(root_end) != 1 - throw(AssertionError("Couldn't find MTG leaf node with symbol \"Root\"")) - end - root_len = get_roots_count(root_end[1]) - if root_len < m.root_max_len - st = add_organ!(root_end[1], extra, "<", :Root, 2, index=1) - status.carbon_root_creation_consumed = m.carbon_root_creation_cost - end - else - status.carbon_root_creation_consumed = 0.0 - end -end - -########################## -### Model accumulating carbon and water resources -########################## - -PlantSimEngine.@process "resource_stock_computation" verbose = false - -struct ToyStockComputationModel <: AbstractResource_Stock_ComputationModel -end -#status.water_stock += meteo.precipitations * root_water_assimilation_ratio - -PlantSimEngine.inputs_(::ToyStockComputationModel) = -(water_absorbed=0.0,carbon_captured=0.0,carbon_organ_creation_consumed=0.0,carbon_root_creation_consumed=0.0) - -PlantSimEngine.outputs_(::ToyStockComputationModel) = (water_stock=-Inf,carbon_stock=-Inf) - -function PlantSimEngine.run!(m::ToyStockComputationModel, models, status, meteo, constants=nothing, extra=nothing) - status.water_stock += sum(status.water_absorbed) #- status.water_transpiration - status.carbon_stock += sum(status.carbon_captured) - sum(status.carbon_organ_creation_consumed) - sum(status.carbon_root_creation_consumed) - - if status.water_stock < 0.0 - status.water_stock = 0.0 - end -end - -PlantSimEngine.TimeStepDependencyTrait(::Type{<:ToyStockComputationModel}) = PlantSimEngine.IsTimeStepIndependent() -PlantSimEngine.ObjectDependencyTrait(::Type{<:ToyStockComputationModel}) = PlantSimEngine.IsObjectIndependent() - -######################## -## Leaf model capturing some arbitrary carbon quantity -######################## - -PlantSimEngine.@process "leaf_carbon_capture" verbose = false - -struct ToyLeafCarbonCaptureModel<: AbstractLeaf_Carbon_CaptureModel end - -function PlantSimEngine.inputs_(::ToyLeafCarbonCaptureModel) - NamedTuple()#(TT_cu=-Inf) -end - -function PlantSimEngine.outputs_(::ToyLeafCarbonCaptureModel) - (carbon_captured=0.0,) -end - -function PlantSimEngine.run!(::ToyLeafCarbonCaptureModel, models, status, meteo, constants, extra) - # very crude approximation with LAI of 1 and constant PPFD - status.carbon_captured = 200.0 *(1.0 - exp(-0.2)) -end - -PlantSimEngine.ObjectDependencyTrait(::Type{<:ToyLeafCarbonCaptureModel}) = PlantSimEngine.IsObjectIndependent() -PlantSimEngine.TimeStepDependencyTrait(::Type{<:ToyLeafCarbonCaptureModel}) = PlantSimEngine.IsTimeStepIndependent() - -mapping = ModelMapping( -:Scene => ToyDegreeDaysCumulModel(), -:Plant => ( - MultiScaleModel( - model=ToyStockComputationModel(), - mapped_variables=[ - :carbon_captured=>[:Leaf], - :water_absorbed=>[:Root], - :carbon_root_creation_consumed=>[:Root], - :carbon_organ_creation_consumed=>[:Internode] - - ], - ), - Status(water_stock = 0.0, carbon_stock = 0.0) - ), -:Internode => ( - MultiScaleModel( - model=ToyCustomInternodeEmergence(),#TT_emergence=20.0), - mapped_variables=[:TT_cu => :Scene, - PreviousTimeStep(:water_stock)=>:Plant, - PreviousTimeStep(:carbon_stock)=>:Plant], - ), - Status(carbon_organ_creation_consumed=0.0), - ), -:Root => ( MultiScaleModel( - model=ToyRootGrowthModel(10.0, 50.0, 10), - mapped_variables=[PreviousTimeStep(:carbon_stock)=>:Plant, - PreviousTimeStep(:water_stock)=>:Plant], - ), - ToyWaterAbsorptionModel(), - Status(carbon_root_creation_consumed=0.0, root_water_assimilation=1.0), - ), -:Leaf => ( ToyLeafCarbonCaptureModel(),), -) - -mtg = MultiScaleTreeGraph.Node(MultiScaleTreeGraph.NodeMTG("/", :Scene, 1, 0)) - -plant = MultiScaleTreeGraph.Node(mtg, MultiScaleTreeGraph.NodeMTG("+", :Plant, 1, 1)) - -internode1 = MultiScaleTreeGraph.Node(plant, MultiScaleTreeGraph.NodeMTG("/", :Internode, 1, 2)) -MultiScaleTreeGraph.Node(internode1, MultiScaleTreeGraph.NodeMTG("+", :Leaf, 1, 2)) -MultiScaleTreeGraph.Node(internode1, MultiScaleTreeGraph.NodeMTG("+", :Leaf, 1, 2)) - -internode2 = MultiScaleTreeGraph.Node(internode1, MultiScaleTreeGraph.NodeMTG("<", :Internode, 1, 2)) -MultiScaleTreeGraph.Node(internode2, MultiScaleTreeGraph.NodeMTG("+", :Leaf, 1, 2)) -MultiScaleTreeGraph.Node(internode2, MultiScaleTreeGraph.NodeMTG("+", :Leaf, 1, 2)) - -plant_root_start = MultiScaleTreeGraph.Node( - plant, - MultiScaleTreeGraph.NodeMTG("+", :Root, 1, 3), -) - -meteo_day = read_weather(joinpath(pkgdir(PlantSimEngine), "examples/meteo_day.csv"), duration=Dates.Day) - -``` - -There are two major issues hinted at in last chapter's implementation, which we'll discuss and resolve here. - -You can find the full script for this simulation in the [ToyMultiScalePlantModel](https://github.com/VirtualPlantLab/PlantSimEngine.jl/blob/main/examples/ToyMultiScalePlantModel/ToyPlantSimulation3.jl) subfolder of the examples folder. - -```@contents -Pages = ["multiscale_example_3.md"] -Depth = 3 -``` - -## An organ creation problem - -There is one quirk you may have noticed when inspecting the data : when a root expands, the new root is immediately active, and some models may act on it immediately... including the root growth model. Meaning this new root may also sprout another root in the same timestep, and so on. - -You can notice this by looking at the simulation's state during the first two timesteps: - -```@example usepkg -outs = run!(mtg, mapping, first(meteo_day, 2)) - -root_nodes_per_timestep = [0, 0] -for i in 1:length(outs[:Root]) - if outs[:Root][i].timestep < 3 - root_nodes_per_timestep[outs[:Root][i].timestep] += 1 - end -end - -root_nodes_per_timestep -``` - -Our root grew to full length within one timestep. Oops. - -This is an implementation decision in PlantSimEngine. **By default, newly created organs are active**, and models can affect them **as soon as they are created**. - -In our case, internode growth depends on a threshold thermal time value, which accumulates over several timesteps, so even though new internodes are immediately active, they can't themselves grow new organs within the same timestep. But as we've just showcased, we have a root problem. - -This quirk is also handled in [XPalm.jl](https://github.com/PalmStudio/XPalm.jl), a package using PlantSimEngine: some organs make use of state machines, and are considered "immature" when they are created. Immature organs cannot grow new organs until some conditions are met for their state to change. There are also other conditions governing organ emergence, such as specific threshold values relating to Thermal Time (see [here](https://github.com/PalmStudio/XPalm.jl/blob/433e1c47c743e7a53e764672818a43ed8feb10c6/src/plant/phytomer/leaves/phyllochron.jl#L46) for an example). - -!!! note - This implementation decision for new organs to be immediately active may be subject to change in future versions of PlantSimEngine. Also note that the way the dependency graph is structured determines the order in which models run. Meaning that which models are run before or after organ creation might change with new additions and updates to your mapping. Some models might run "one timestep later", see [Simulation order instability when adding models](@ref) for more details. - -!!! note - MTG node output data has a couple of subtleties, see [Multi-scale output data structure](@ref) for more details - -### Delaying organ maturity - -How do we avoid this extreme instant growth ? We can, of course, add some thermal time constraint. We could arbitrarily tinker with water resources. - -We can otherwise add a simple state machine variable to our root and internodes in the MTG, indicating a newly added organ is immature and cannot grow on the same timestep. Since our root doesn't branch, we can simply keep track of a single state variable. See the [State machines](@ref) section for some examples. - -In fact, we could change the scale at which the check is made to extend the root, and have another model call this one directly. This enables running this model only for the end root when those occasional timesteps when root growth is possible, instead of at every timestep for every root node. - -## A resource distribution bug - -Another problem you may have noticed, is that the water and carbon stock are computed by aggregating photosynthesis over leaves and absorption over roots... But they aren't always properly decremented when consumed ! - -If the end root grows, it outputs a `carbon_root_creation_consumed` value, but under certain conditions, we might also create other roots and internodes even when there shouldn't be enough carbon left for them. - -Indeed, if both the root and leaf water thresholds are met, and there is enough carbon for a single root or internode but not for both, and the root model runs before the internode model, both will use the carbon_stock variable prior to organ emission. The internode emission model won't account for the root carbon consumption. - -This occurs because `carbon_stock` is only computed once, and won't update until the next timestep. - -### Fixing resource computation: a root growth decision model - -To avoid that problem in our specific case, we can couple the root growth model and the internode emission model, and pass the `carbon_root_creation_consumed` variable to the internode emission model so that it can use an updated carbon stock. Or we could have an intermediate model recompute the new stock to pass along to the internode emission model. - -There is a section in the [Tips and workarounds] page discussing this situation and other potential solutions: [Having a variable simultaneously as input and output of a model](@ref). - -We'll go for the first option and couple the root growth and internode emission model. - -### Internode emission adjustments - -The only change required for our internode emission model is to take into account `carbon_root_creation_consumed` as a new input, map that variable from the :Root scale in our mapping, and compute the adjusted carbon stock. Here's the relevant excerpt in the [`run!`](@ref) function. - -```julia - # take into account that the stock may already be depleted - carbon_stock_updated_after_roots = status.carbon_stock - status.carbon_root_creation_consumed - - # if not enough carbon, no organ creation - if carbon_stock_updated_after_roots < m.carbon_internode_creation_cost - return nothing - end -``` - -### A multi-scale hard dependency appears - -Our root growth decision model inherits some of the responsibility from last chapter's root growth model, so inputs, parameters and condition checks will be similar. We'll let the root growth model keep the length check and only focus on resources. - -Since the decision model is now directly responsible for calling the actual root growth model, we need to declare that it requires a root growth model as a hard dependency and cannot be run standalone. - -This hard dependency is in fact multiscale, since both models operate at different scales, :Plant and :Root. You can read more about multi-scale hard dependencies in the [Handling dependencies in a multiscale context](@ref) page. - -Compared to the single-scale equivalent, the multi-scale declaration additionally requires mapping the scale: - -```julia -PlantSimEngine.dep(::ToyRootGrowthDecisionModel) = (root_growth=AbstractRoot_GrowthModel=>[:Root],) -``` - -The `status` argument [`run!`](@ref) function of the root growth decision model only contains variables from the :Plant scale, or explicitely mapped to this scale, which isn't the case for the root growth's variables. To make use of the root growth model's variables, we need to recover the [`status`](@ref) at the :Root scale. It is accessible from the `extra` argument in [`run!`](@ref)'s signature. - -In multi-scale simulations, this `extra` argument implicitely contains an object storing the simulation state. It contains the statuses at various scales, and all the models indexed per scale and process name. - -Access to the :Root status within the root growth decision model [`run!`](@ref) function is done like so: - -```julia -status_Root= extra_args.statuses[:Root][1] -``` - -It is then possible to call the root growth model from the parent's [`run!`](@ref) function: - -```julia -PlantSimEngine.run!(extra.models[:Root].root_growth, models, status_Root, meteo, constants, extra) -``` - -Which will enable writing the rest of the [`run!`](@ref) function. - -### Root growth decision model implementation - -With that new coupling consideration properly handled, we can complete the full model implementation: - -```julia -PlantSimEngine.@process "root_growth_decision" verbose = false - -struct ToyRootGrowthDecisionModel{T} <: AbstractRoot_Growth_DecisionModel - water_threshold::T - carbon_root_creation_cost::T -end - -PlantSimEngine.inputs_(::ToyRootGrowthDecisionModel) = -(water_stock=0.0,carbon_stock=0.0) - -PlantSimEngine.outputs_(::ToyRootGrowthDecisionModel) = NamedTuple() - -PlantSimEngine.dep(::ToyRootGrowthDecisionModel) = (root_growth=AbstractRoot_GrowthModel=>[:Root],) - -# "status" is at the :Plant scale -function PlantSimEngine.run!(m::ToyRootGrowthDecisionModel, models, status, meteo, constants=nothing, extra=nothing) - - if status.water_stock < m.water_threshold && status.carbon_stock > m.carbon_root_creation_cost - # Obtain "status" at :Root scale - status_Root= extra_args.statuses[:Root][1] - # Call the hard dependency model directly with its status - PlantSimEngine.run!(extra.models[:Root].root_growth, models, status_Root, meteo, constants, extra) - end -end -``` - -The root growth model will output the `carbon_root_creation_consumed` computation, but it'll still be exposed to downstream models despite the root growth model being a 'hidden' model in the dependency graph due to its hard dependency nature. - -With this new coupling, we will only be creating at most a single new root per timestep, as the root growth decision will only be called once per timestep. - -### Root growth - -This iteration turns into a simplifed version of last chapter's. - -```julia -PlantSimEngine.@process "root_growth" verbose = false - -struct ToyRootGrowthModel <: AbstractRoot_GrowthModel - root_max_len::Int -end - -PlantSimEngine.inputs_(::ToyRootGrowthModel) = NamedTuple() -PlantSimEngine.outputs_(::ToyRootGrowthModel) = (carbon_root_creation_consumed=0.0,) - -function PlantSimEngine.run!(m::ToyRootGrowthModel, models, status, meteo, constants=nothing, extra=nothing) - status.carbon_root_creation_consumed = 0.0 - - root_end = get_root_end_node(status.node) - - if length(root_end) != 1 - throw(AssertionError("Couldn't find MTG leaf node with symbol \"Root\"")) - end - - root_len = get_roots_count(root_end[1]) - if root_len < m.root_max_len - st = add_organ!(root_end[1], extra, "<", :Root, 2, index=1) - status.carbon_root_creation_consumed = m.carbon_root_creation_cost - end -end -``` - -### Mapping adjustments - -The new mapping only has straightforward changes. Some models cease to be multi-scale, others require new variables to be mapped for them. `carbon_root_creation_consumed` ceases to be a vector mapping and is a scalar variable. - -```julia -mapping = ModelMapping( -:Scene => ToyDegreeDaysCumulModel(), -:Plant => ( - MultiScaleModel( - model=ToyStockComputationModel(), - mapped_variables=[ - :carbon_captured=>[:Leaf], - :water_absorbed=>[:Root], - :carbon_root_creation_consumed=>:Root, - :carbon_organ_creation_consumed=>[:Internode] - - ], - ), - MultiScaleModel( - model=ToyRootGrowthDecisionModel(10.0, 50.0), - ), - Status(water_stock = 0.0, carbon_stock = 0.0) - ), -:Internode => ( - MultiScaleModel( - model=ToyCustomInternodeEmergence(),#TT_emergence=20.0), - mapped_variables=[:TT_cu => :Scene, - :water_stock=>:Plant, - :carbon_stock=>:Plant, - :carbon_root_creation_consumed=>:Root], - ), - Status(carbon_organ_creation_consumed=0.0), - ), -:Root => (ToyRootGrowthModel(10), - ToyWaterAbsorptionModel(), - Status(carbon_root_creation_consumed=0.0, root_water_assimilation=1.0), - ), -:Leaf => ( ToyLeafCarbonCaptureModel(),), -) -``` - -We can now run our simulation as we did previously... or can we ? - -```julia -ERROR: Cyclic dependency detected for process resource_stock_computation: resource_stock_computation for organ Plant depends on root_growth from organ Root, which depends on the first one. This is not allowed, you may need to develop a new process that does the whole computation by itself. -``` - -Ah, it looks like our additional usage of the root carbon cost creates a cyclic dependency. - -### Breaking the dependency cycle - -Fortunately, the logic here is quite straightforward. We can't be computing our current timestep's resource stock with `carbon_root_creation_consumed`, and then updating it right after root creation again using a new value of `carbon_root_creation_consumed`. - -The solution is hopefully quite intuitive : when we compute resource stocks, we should be computing it using the previous timestep's values. Then root creation happens (or doesn't), and the computed `carbon_root_creation_consumed` corresponds to the current timestep value. We could also do the same for water to be consistent. - -### Updated mapping - -The relevant part of the mapping that needs to be updated is the following: - -```julia -mapping = ModelMapping( -... -:Plant => ( - MultiScaleModel( - model=ToyStockComputationModel(), - mapped_variables=[ - :carbon_captured=>[:Leaf], - :water_absorbed=>[:Root], - PreviousTimeStep(:carbon_root_creation_consumed)=>:Root, - PreviousTimeStep(:carbon_organ_creation_consumed)=>[:Internode], - ], - ), - ToyRootGrowthDecisionModel(10.0, 50.0), - Status(water_stock = 0.0, carbon_stock = 0.0) - ), -... -) -``` - -## Final words - -And you're now ready to run the simulation. - -The full script can be found [here](https://github.com/VirtualPlantLab/PlantSimEngine.jl/blob/main/examples/ToyMultiScalePlantModel/ToyPlantSimulation3.jl), in the ToyMultiScalePlantModel subfolder of the examples folder. - -We now have a plant with two different growth directions. Roots are added at the beginning, until water is considered abundant enough. - -Of course, there are still several design issues with this implementation. It is as utterly unrealistic as the previous one, and doesn't even consume water. Some condition checking is a little ad hoc and could be made more robust. More sanity checks could be added, and the model and variable names could definitely be made more clear. - -But once again, this example is only made to illustrate what is possible with this framework, and doesn't strive for ecophysiological consistency. And the approach can be made increasingly more complex by refining models and simulation parameters, and feeding in new information about your plant, and ramp up to realistic, production-ready and predictive simulations. diff --git a/docs/src/multiscale/multiscale_example_4.md b/docs/src/multiscale/multiscale_example_4.md deleted file mode 100644 index f5105e84b..000000000 --- a/docs/src/multiscale/multiscale_example_4.md +++ /dev/null @@ -1,226 +0,0 @@ -# Visualizing a plant using PlantGeom - -We've created our toy plant, part of the fun is to actually visualize it ! - -Let's see how to do so with the [PlantGeom](https://github.com/VEZY/PlantGeom.jl) companion package. - -We'll be reusing the mtg from part 3 of the plant tutorial: [Fixing bugs in the plant simulation](@ref), so you need to run that simulation first, or to include the script file into your current code (which is what we'll do here): - -```julia -using PlantSimEngine -using MultiScaleTreeGraph -using PlantSimEngine.Examples -using Pkg -Pkg.add("CSV") -using CSV -include("ToyPlantSimulation3.jl") -``` - -You'll need to add PlantGeom and a compatible visualization package to your environment. We'll use Plots: - -```julia -using Plots -using PlantGeom -``` - -That's enough to get a nicer display of the MTG than the console-based printing. You'll only need to type the following line: - -```julia -RecipesBase.plot(mtg) -``` - -This provides the following visualization: -![MTG Plots visualization](../www/mtg_plot_1.svg) - -And that's it ! - -We can see the root expansion in one direction, and the internodes with their leaves in the other. - -Of course, that's good and all, but going beyond that would be nice. - -PlantGeom is able to render geometry from what it finds in the MTG. If a node in the tree graph has a `:geometry` attribute with a mesh and a transformation, it can make use of that to build a plant. That mesh can be unique per node, or based on a reference mesh that is copied and transformed for every node. - -!!! note - This page simply aims to illustrate PlantGeom's features and doesn't aim for a particularly realistic or aesthetic look. A little randomness could go a long way to make the plant look a little more life-like, but would also be very ad-hoc and make the code less clear. - -Our MTG doesn't have any such attribute, so we'll need to iterate on our nodes, provide them with a mesh and calculate appropriate transformations. We'll use one reference mesh for each plant-related scale, Internode, Root and Leaf. - -We'll make use of some of the Meshes primitives and transformations, as well as some helper functions from the packages TransformsBase and Rotations. For leaves, we'll read a .ply file using the PlyIO package, which contains a very unrealistic leaf + petiole mesh. - -We'll also make our plant opposite decussate: leaves come in pairs, and pairs are rotated by 90 degrees along the stem. - -The function that'll provide the geometry to the node is: -```julia -PlantGeom.Geometry(; ref_mesh<:RefMesh, transformation=Identity(), dUp=1.0, dDwn=1.0, mesh::Union{SimpleMesh,Nothing}=nothing) -``` - -We only care about the first two parameters in our case, and we can use a simple cylinder for each node of our single Internode stem and single Root. - -```julia -using PlantGeom.Meshes - -# Internodes and roots will use a cylinder as a mesh - -cylinder() = Meshes.CylinderSurface(1.0) |> Meshes.discretize |> Meshes.simplexify - -refmesh_internode = PlantGeom.RefMesh(:Internode, cylinder()) -refmesh_root = PlantGeom.RefMesh(:Root, cylinder()) -``` - -A simple function to read the vertices and faces from the .ply file for our leaves: - -```julia -Pkg.add("PlyIO") -using PlyIO -function read_ply(fname) - ply = PlyIO.load_ply(fname) - x = ply["vertex"]["x"] - y = ply["vertex"]["y"] - z = ply["vertex"]["z"] - points = Meshes.Point.(x, y, z) - connec = [Meshes.connect(Tuple(c .+ 1)) for c in ply["face"]["vertex_indices"]] - Meshes.SimpleMesh(points, connec) -end - -leaf_ply = read_ply("examples/leaf_with_petiole.ply") -refmesh_leaf = PlantGeom.RefMesh(:Leaf, leaf_ply) -``` - -```julia -Pkg.add("TransformsBase") -Pkg.add("Rotations") -import TransformsBase: → -import Rotations: RotY, RotZ, RotX -``` - -!!! note - We'll use X, Y, Z as standard cartersian coordinate axes, with Z pointing upwards. - -We can then write the function that adds the geometry to our MTG. - -It traverses the MTG, starting from the base, and adds a transformation for each encountered node. - -The following just operates on internodes, for clarity: - -```julia -# Add the geometry to the MTG, with transformations -function add_geometry!(mtg, refmesh_internode) - - # incremental offset - internode_height = 0.0 - - # relative scale of the base mesh - internode_width = 0.5 - - # length of the base mesh - internode_length = 1.0 - - traverse!(mtg) do node - if symbol(node) == :Internode - # Set to scale, then translate by the total height - mesh_transformation = Meshes.Scale(internode_width, internode_width, internode_length) → Meshes.Translate(0.0, 0.0, internode_height) - node.geometry = PlantGeom.Geometry(ref_mesh=refmesh_internode, transformation=mesh_transformation) - - internode_height += node_length - end - end -end -``` - -We simply need to choose a given width for our stem, and increment the height to place our next internode at as we traverse it. - -Note that the default cylinder provided by Meshes.jl points upwards, which is why there is no need for rotation. Roots function likewise, but are simply translated down, and need to start below the origin. - -We can visualize this simple stem, using GLMakie as a rendering backend: - -```julia -add_geometry!(mtg, refmesh_internode) - -# Visualize the mesh -using GLMakie -viz(mtg) -``` - -![Toy Plant - stem only](../www/toy_plant_stem_only.png) - -On the other hand, the leaf mesh will need to be rotated, but it is aligned along the X axis, so there is no need for an initial reorientation (which would have been required if it was pointing upwards like the cylinders). The petiole starts at the origin, so on top of translating them to leaf height we also need to translate them away from the Z axis by the internode radius. The mesh also needs to be scaled, as it is only 0.1 unit lengths long compared to our 0.5-width internode. - -Let's also rotate our leaves so that they point upwards slightly. - -If you make use of other meshes, bear in mind the initial starting translation, orientation and scale. You may need to test and calibrate scales and transformations before you get it right. - -The full code that generates geometry for all the organs of our toy plant is the following: -```julia -# Add the geometry to the MTG, with transformations -function add_geometry!(mtg, refmesh_internode, refmesh_root, refmesh_leaf) - - # incremental offset - internode_height = 0.0 - root_depth = 0.0 - - # relative scale of the base mesh (base cylinder is of height 1 and radius 1) - internode_width = 0.5 - root_width = 0.2 - - # length of the base mesh - internode_length = 1.0 - root_length = 1.0 - - # ad hoc value to adjust the leaf mesh to the scene scale - leaf_mesh_scale = 25 - - leaf_scale_width = 0.4*leaf_mesh_scale - leaf_scale_height = 0.4*leaf_mesh_scale - - # Helpers to make the leaves opposite decussate - leaf_rotation = MathConstants.pi / 2.0 - i = 0 - - traverse!(mtg) do node - if symbol(node) == :Internode - # Set to scale, then translate by the total height - mesh_transformation = Meshes.Scale(internode_width, internode_width, internode_length) → Meshes.Translate(0.0, 0.0, internode_height) - node.geometry = PlantGeom.Geometry(ref_mesh=refmesh_internode, transformation=mesh_transformation) - - internode_height += internode_length - - # Leaves are placed relatively to the parent internode, halfway along it - for chnode in children(node) - if symbol(chnode) == :Leaf - mesh_transformation = Meshes.Scale(leaf_scale_width, leaf_scale_width, leaf_scale_height) → Meshes.Rotate(RotX(-MathConstants.pi / 6.0)) → Meshes.Translate(0.0, -internode_width, internode_height - internode_length / 2.0) → Meshes.Rotate(RotZ(leaf_rotation)) - chnode.geometry = PlantGeom.Geometry(ref_mesh=refmesh_leaf, transformation=mesh_transformation) - # Set the second leaf in a pair opposite to the first one => add a 180° rotation - leaf_rotation += MathConstants.pi - end - end - - # Opposite decussate => 90° rotation between pairs - i += 1 - if i % 2 == 0 - leaf_rotation = MathConstants.pi / 2.0 - else - leaf_rotation = MathConstants.pi - end - - elseif symbol(node) == :Root - mesh_transformation = Meshes.Scale(root_width, root_width, root_length) → Meshes.Translate(0.0, 0.0, root_depth) → Meshes.Rotate(RotZ(MathConstants.pi)) - node.geometry = PlantGeom.Geometry(ref_mesh=refmesh_root, transformation=mesh_transformation) - root_depth -= root_length - end - end -end -``` - -And now, let's visualize our fully-grown, fully-featured plant: - -```julia -# Visualize the mesh -using GLMakie -viz(mtg) -``` - -Which gives us the following image scene: - -![Toy Plant with root and leaves](../www/toy_plant.png) - -Feel free to try and make this plant prettier, more colourful, or more physically realistic, using more realistic models on the PlantSimEngine side, or better geometry on the Plantgeom end. \ No newline at end of file diff --git a/docs/src/multiscale/single_to_multiscale.md b/docs/src/multiscale/single_to_multiscale.md deleted file mode 100644 index 7e8af7caf..000000000 --- a/docs/src/multiscale/single_to_multiscale.md +++ /dev/null @@ -1,233 +0,0 @@ -# Converting a single-scale simulation to multi-scale - -```@meta -CurrentModule = PlantSimEngine -``` - -```@setup usepkg -using PlantMeteo, Dates -using PlantSimEngine -using PlantSimEngine.Examples -using MultiScaleTreeGraph -meteo_day = read_weather(joinpath(pkgdir(PlantSimEngine), "examples/meteo_day.csv"), duration=Dates.Day) -models_singlescale = ModelMapping( - ToyLAIModel(), - Beer(0.5), - ToyRUEGrowthModel(0.2); - status=(TT_cu=cumsum(meteo_day.TT),), -) -``` - -A single-scale simulation can be turned into a 'pseudo-multi-scale' simulation by providing a simple multi-scale tree graph, and declaring a mapping linking all models to a unique scale level. - -This page showcases how to do the conversion, and then adds a model at a new scale to make the simulation genuinely multi-scale. - -The full script for the example can be found in the examples folder, [here](https://github.com/VirtualPlantLab/PlantSimEngine.jl/blob/main/examples/ToySingleToMultiScale.jl) - -```@contents -Pages = ["single_to_multiscale.md"] -Depth = 3 -``` - -# From single to multi-scale mapping - -For example, let's return to the [`ModelMapping`](@ref) coupling a light interception model, a Leaf Area Index model, and a carbon biomass increment model that was discussed in the [Model switching](@ref) subsection: - -```@example usepkg -using PlantMeteo, Dates -using PlantSimEngine -using PlantSimEngine.Examples - -meteo_day = read_weather(joinpath(pkgdir(PlantSimEngine), "examples/meteo_day.csv"), duration=Dates.Day) - -models_singlescale = ModelMapping( - ToyLAIModel(), - Beer(0.5), - ToyRUEGrowthModel(0.2); - status=(TT_cu=cumsum(meteo_day.TT),), -) - -outputs_singlescale = run!(models_singlescale, meteo_day) -outputs_singlescale[1:3,:] # show the first 3 rows of the output -``` - -Those models all operate on a simplified model of a single plant, without any organ-local information. We can therefore consider them to be working at the 'whole plant' scale. Their variables also operate at that `:Plant` scale, so there is no need to map any variable to other scales. - -We can therefore convert this into the following mapping: - -```@example usepkg -mapping = ModelMapping( -:Plant => ( - ToyLAIModel(), - Beer(0.5), - ToyRUEGrowthModel(0.2), - Status(TT_cu=cumsum(meteo_day.TT),) - ), -) -``` - -Note the slight difference in syntax for the [`Status`](@ref). This is because each scale has its own variables, so we must provide the values to each scale independently. - -## Adding a new package for our plant graph - -None of these models operate on a multi-scale tree graph, either. There is no concept of organ creation or growth. We still need to provide a multi-scale tree graph to a multi-scale simulation, so we can -for now- declare a very simple MTG, with a single node: - -```@example usepkg -using MultiScaleTreeGraph - -mtg = MultiScaleTreeGraph.Node(MultiScaleTreeGraph.NodeMTG("/", :Plant, 0, 0),) -``` - -!!! note - You will need to add the `MultiScaleTreeGraph` package to your environment. See [Installing and running PlantSimEngine](@ref) if you are not yet comfortable with Julia or need a refresher. - -## Running the multi-scale simulation ? - -We now have **almost** everything we need to run the multiscale simulation. - -This first conversion step can be a starting point for a more elaborate multi-scale simulation. - -The signature of the [`run!`](@ref) function in multi-scale differs slightly from the single-scale version: - -```julia -out_multiscale = run!(mtg, mapping, meteo_day) -``` - -(Some of the optional arguments also change slightly) - -Passing in a vector through the [`Status`](@ref) field is still possible in multi-scale mode, but more involving than in single-scale mode. If you need to go this way, you can find a detailed example [here](@ref multiscale_vector), although we don't recommend it for beginners. In any case, it's simpler to write a model to provide the thermal time per timestep as a variable, instead of as a single vector in the [`Status`](@ref). - -Our 'pseudo-multiscale' first approach will therefore turn into a genuine multi-scale simulation. - -## Adding a second scale - -Let's have a model provide the Cumulated Thermal Time to our Leaf Area Index model, instead of initializing it through the [`Status`](@ref). - -Let's instead implement our own `ToyTT_cuModel`. - -### TT_cu model implementation - -This model doesn't require any outside data or input variables, it only operates on the weather data and outputs our desired TT_cu. The implementation doesn't require any advanced coupling and is very straightforward. - -```@example usepkg -PlantSimEngine.@process "tt_cu" verbose = false - -struct ToyTt_CuModel <: AbstractTt_CuModel -end - -function PlantSimEngine.run!(::ToyTt_CuModel, models, status, meteo, constants, extra=nothing) - status.TT_cu += - meteo.TT -end - -function PlantSimEngine.inputs_(::ToyTt_CuModel) - NamedTuple() # No input variables -end - -function PlantSimEngine.outputs_(::ToyTt_CuModel) - (TT_cu=0.0,) -end -``` - -!!! note - The only accessible variables in the [`run!`](@ref) function via the status are the ones that are local to the :Scene scale. This isn't explicit at first glance, but very important to keep in mind when developing models, or using them at different scales. If variables from other scales are required, then they need to be mapped via a [`MultiScaleModel`](@ref), or sometimes a more complex coupling is necessary. - -### Linking the new TT_cu model to a scale in the mapping - -We now have our model implementation. How does it fit into our mapping ? - -Our new model doesn't really relate to a specific organ of our plant. In fact, this model doesn't represent a physiological process of the plant, but rather an environmental process affecting its physiology. We could therefore have it operate at a different scale unrelated to the plant, which we'll call :Scene. This makes sense. - -Note that we now need to add a :Scene node to our Multi-scale Tree Graph, otherwise our model will not run, since no other model calls it and :Plant nodes will only call models at the :Plant scale. See [Empty status vectors in multi-scale simulations](@ref) for more details. - -```@example usepkg -mtg_multiscale = MultiScaleTreeGraph.Node(MultiScaleTreeGraph.NodeMTG("/", :Scene, 0, 0),) - plant = MultiScaleTreeGraph.Node(mtg_multiscale, MultiScaleTreeGraph.NodeMTG("+", :Plant, 1, 1)) -``` - -### Mapping between scales : the MultiScaleModel wrapper - -The cumulated thermal time (`:TT_cu`) which was previously provided to the LAI model as a simulation parameter now needs to be mapped from the :Scene scale level. - -This is done by wrapping our ToyLAIModel in a dedicated structure called a [`MultiScaleModel`](@ref). A [`MultiScaleModel`](@ref) requires two keyword arguments : `model`, indicating the model for which some variables are mapped, and `mapped_variables`, indicating which scale link to which variables, and potentially renaming them. - -There can be different kinds of variable mapping with slightly different syntax, but in our case, only a single scalar value of the TT_cu is passed from the :Scene to the :Plant scale. - -This gives us the following declaration with the [`MultiScaleModel`](@ref) wrapper for our LAI model: - -```@example usepkg -MultiScaleModel( - model=ToyLAIModel(), - mapped_variables=[ - :TT_cu => :Scene, - ], - ) -``` -and the new mapping with two scales: - -```@example usepkg -mapping_multiscale = ModelMapping( - :Scene => ToyTt_CuModel(), - :Plant => ( - MultiScaleModel( - model=ToyLAIModel(), - mapped_variables=[ - :TT_cu => :Scene, - ], - ), - Beer(0.5), - ToyRUEGrowthModel(0.2), - ), -) -``` - -### Running the multi-scale simulation - -We can then run the multiscale simulation, with our two-node MTG : - -```@example usepkg -outputs_multiscale = run!(mtg_multiscale, mapping_multiscale, meteo_day) -``` - -### Comparing outputs between single- and multi-scale - -The outputs structures are slightly different : multi-scale outputs are indexed by scale, and a variable has a value for every node of the scale it operates at (for instance, there would be a "leaf_surface" value for every leaf in a plant), stored in an array. - -In our simple example, we only have one MTG scene node and one plant node, so the arrays for each variable in the multi-scale output only contain one value. - -We can access the output variables at the :Scene scale by indexing our outputs: - -```@example usepkg -outputs_multiscale[:Scene] -``` -We have a `Vector{NamedTuple}`structure. Our single-scale output is a `Vector{T}`: -```@example usepkg -outputs_singlescale.TT_cu -``` - - Let's extract the multi-scale `:TT_cu`: -```@example usepkg -computed_TT_cu_multiscale = [outputs_multiscale[:Scene][i].TT_cu for i in 1:length(outputs_multiscale[:Scene])] -``` - -We can now compare them value-by-value and do a piecewise approximate equality test : -```@example usepkg -for i in 1:length(computed_TT_cu_multiscale) - if !(computed_TT_cu_multiscale[i] ≈ outputs_singlescale.TT_cu[i]) - println(i) - end -end -``` -or equivalently, with broadcasting, we can write : -```@example usepkg -is_approx_equal = length(unique(computed_TT_cu_multiscale .≈ outputs_singlescale.TT_cu)) == 1 -``` - -!!! note - You may be wondering why we check for approximate equality rather than strict equality. The reason for that is due to floating-point accumulation errors, which are discussed in more detail in [Floating-point considerations](@ref). - -## ToyDegreeDaysCumulModel - -There is a model able to provide Thermal Time based on weather temperature data, [`ToyDegreeDaysCumulModel`](@ref), which can also be found in the examples folder. - -We didn't make use of it here for learning purposes. It also computes a thermal time based on default parameters that don't correspond to the thermal time in the example weather data, so results differ from the thermal time already present in the weather data without tinkering with the parameters. diff --git a/docs/src/planned_features.md b/docs/src/planned_features.md index ba02656e2..af2e89cc4 100644 --- a/docs/src/planned_features.md +++ b/docs/src/planned_features.md @@ -1,51 +1,53 @@ # Roadmap -This page summarizes work that is still in progress or intentionally left for -future releases. It is not a guarantee of delivery order. +PlantSimEngine now has one composite-model/object runtime for single-object, multiscale, +multi-plant, soil, microclimate, and multirate simulations. -## Current focus areas +Current priorities are: -### Multi-rate MTG simulations +- migrate downstream model packages to `CompositeModel`, `CompositeModelTemplate`, + `ObjectInstance`, and `ModelSpec`; +- strengthen type-stability and allocation tests for million-object workloads; +- add broader lifecycle tests for object creation, removal, movement, and + environment-index refresh; +- improve diagnostics for ambiguous selectors, writer conflicts, and temporal + policies; +- validate mutable voxel, layer, and octree microclimate backends; +- expand downstream release gates and performance benchmarks; +- evaluate parallel execution for independent compiled application batches. -Model-level varying timesteps are available experimentally for MTG simulations -through mapping-declared multi-rate execution and `ModelSpec` transforms such as -`TimeStepModel`, `InputBindings`, `OutputRouting`, and `ScopeModel`. +## Environment and microclimate work -Known gaps in the current implementation: +### Trial environment sampling -- no sub-step execution below the meteorological base-step duration; -- no dedicated event scheduler for irregular or non-fixed calendar execution; -- no threaded or distributed multi-rate MTG execution path yet. +Coupled microclimate solvers can iterate on local environmental state before +accepting a timestep. A canopy energy-balance model, for example, may need to: -### Multi-plant and multi-species simulations +1. propose a trial canopy air temperature and humidity; +2. run leaf models against that trial air state; +3. update the trial air state from leaf sensible and latent heat fluxes; +4. repeat until convergence; +5. commit only the accepted canopy or voxel air state to the mutable environment + backend. -PlantSimEngine can already express multi-scale simulations, but practical support -for scenes containing several plants or several species with overlapping model -sets is still limited. Future work in this area is expected to focus on more -flexible mapping and parameter declaration. +Pass non-committing trial state through `run_call!`: -## API and ergonomics +```julia +run_call!(context, :leaf_energy; environment=trial_environment, publish=false) +``` -- a more consistent mapping API and clearer multiscale dependency declaration; -- improved user-facing errors and diagnostics; -- better dependency graph visualization and traversal helpers; -- broader examples for fitting, type conversion, and error propagation; -- clearer weather-data validation when a simulation requires meteorological inputs. +Then commit the accepted state through the model-facing environment API: -## Testing and release engineering +```julia +commit_environment!(context, accepted_environment) +run_call!(context, :leaf_energy; publish=true) +``` -- broader downstream coverage and better release gating; -- additional checks for memory usage and type stability; -- state-machine or invariant-style validation for runtime outputs; -- graph fuzzing for multiscale corner cases. +The transient state is interpreted by each target backend through its opaque +compiled handle, so one call can sample different cells for different leaves. +`commit_environment!` commits only the accepted state to a mutable backend. +Future work is to validate full voxel, layer, and octree implementations on +this same model-side API. -## Lower-priority ideas - -- API support for iterative construction and validation of `ModelMapping`; -- optional code-generation or build steps for validated mappings; -- improved parallel execution strategies; -- reintroducing multi-object parallelism in single-scale runs if the execution - model can stay predictable and testable. - -The full list of open issues is available on +The full issue list is available on [GitHub](https://github.com/VirtualPlantLab/PlantSimEngine.jl/issues). diff --git a/docs/src/prerequisites/installing_plantsimengine.md b/docs/src/prerequisites/installing_plantsimengine.md index d992f7a20..67c135dbf 100644 --- a/docs/src/prerequisites/installing_plantsimengine.md +++ b/docs/src/prerequisites/installing_plantsimengine.md @@ -1,78 +1,49 @@ -# Installing and running PlantSimEngine +# Installing PlantSimEngine -```@contents -Pages = ["installing_plantsimengine.md"] -Depth = 3 -``` - -This page is meant to help along people newer to Julia. If you are quite accustomed to Julia, installing PlantSimEngine should be par for the course, and you can [move on to the next section](#step_by_step), or read about PlantSimEngine's [Key Concepts](@ref). - -## Installing Julia - -The direct download link can be found [here](https://julialang.org/downloads/), and some additional pointers [in the official manual](https://docs.julialang.org/en/v1/manual/installation/). - -## Installing VSCode - -You can get by using a REPL, but if writing a larger piece of software you may prefer using an IDE. PlantSimEngine is developed using VSCode, which you can install by following instruction [on this page](https://code.visualstudio.com/docs/setup/setup-overview). A documentation section specific to using Julia in VSCode can be found [here](https://code.visualstudio.com/docs/languages/julia). - -## Installing PlantSimEngine and its dependencies - -### Julia environments - -Julia package management is done via the Pkg.jl package. You can find more in-depth sections detailing its usage, and working with Julia environments [in its documentation](https://pkgdocs.julialang.org/v1/) - -If you find this page insufficient to get started, [this tutorial](https://jkrumbiegel.com/pages/2022-08-26-pkg-introduction/) explains in detail the subtleties of Julia environments. - -### Running an environment - -Once your environment is set up, you can launch a command prompt and type `julia`. This will launch Julia, and you should see `julia>` in the command prompt. - -You can always type `?` from there to enter help mode, and type the name of a function or language feature you wish to know more about. - -You can find out which directory you are in by typing `pwd()` in a Julia session. - -Handling environments and dependencies is done in Julia through a specific Package called Pkg, which comes with the base install. You can either call Pkg features the same way you would for another package, or enter Pkg mode by typing `]`, which will change the display from `julia>` to something like `(@v1.11)` pkg>, indicating your current environment (in this case, the default julia environment, which we don't recommend bloating). +Install Julia from the +[official download page](https://julialang.org/downloads/), create a project +environment, and add PlantSimEngine: -Once in Pkg mode, you can choose to create an environment by typing `activate path/to/environment`. - -You can then add packages that have been added to Julia's online global registry by typing `add packagename` and you can remove them by typing `remove packagename`. Typing `status` or `st` will indicate what your current environment is comprised of. To update packages in need of updating (a `^` symbol will display next to their name), type `update`… or `up`. - -If you are editing/developing a package or using one locally, typing `develop path/to/package source/` (or `dev path/to/package/source`) will cause your environment to use that version instead of the registered one. - -Typing `instantiate` will download all the packages declared in the manifest file (if it exists) of an environment. - -For instance, PlantSimEngine has a test folder used in development. If you wanted to run tests, you would type `]` then `activate ../path/to/PlantSimEngine/test` then `instantiate` -and then you would be ready to run some scripts. - -So if you wish to use PlantSimEngine, you can enter Pkg mode (`]`), choose an environment folder, then activate that environment with `activate ../path/to/your_environment`, add PlantSimEngine to it with `add PlantSimEngine` then download the package and its dependencies with `instantiate`. - -### Companion packages - -You'll also, for most of our examples, need `PlantMeteo`. For several multi-scale simulations, you'll need `MultiScaleTreeGraph`. - -Some of the weather data examples make use of the `CSV` package, some output data is manipulated as a DataFrame, which is part of the `DataFrames` package. - -### Using the example models +```julia +using Pkg +Pkg.activate("my_simulation") +Pkg.add("PlantSimEngine") +``` -Example models are exported as a distinct submodule of PlantSimEngine, meaning they aren't part of the main API. You can use them by typing: +Most simulations also use PlantMeteo: ```julia -using PlantSimEngine.Examples +Pkg.add("PlantMeteo") ``` -## Running a test simulation - -Assuming you've setup you're environement, correctly added `PlantMeteo` and `PlantSimEngine` to that environment, and downloaded everything with `instantiate`, you'll be able to run a test example in your REPL by typing line-by-line: +## First Simulation -```@example mypkg +```@example install using PlantSimEngine, PlantMeteo, Dates using PlantSimEngine.Examples -meteo = Atmosphere(T = 20.0, Wind = 1.0, Rh = 0.65, Ri_PAR_f = 500.0) -leaf = ModelMapping(Beer(0.5), status = (LAI = 2.0,)) -out_sim = run!(leaf, meteo) + +meteo = Atmosphere( + T=20.0, + Wind=1.0, + Rh=0.65, + Ri_PAR_f=500.0, + duration=Hour(1), +) + +model = CompositeModel( + Beer(0.5); + status=(LAI=2.0,), + id=:leaf, + scale=:Leaf, + environment=meteo, +) + +simulation = run!(model) +final_state(simulation, One(scale=:Leaf)).aPPFD ``` -## Environments in VSCode +Example models are provided by the `PlantSimEngine.Examples` submodule. They +are useful for learning and tests but are not part of the core modeling API. -There is detailed documentation explaining how to make use of Julia with VSCode with one section indicating how to handle environments in VSCode: [https://www.julia-vscode.org/docs/stable/userguide/env/](https://www.julia-vscode.org/docs/stable/userguide/env/) - \ No newline at end of file +For local package development, use `Pkg.develop(path="...")`. Run the package +tests with `Pkg.test("PlantSimEngine")`. diff --git a/docs/src/prerequisites/julia_basics.md b/docs/src/prerequisites/julia_basics.md index bb22f92ee..707ad6122 100644 --- a/docs/src/prerequisites/julia_basics.md +++ b/docs/src/prerequisites/julia_basics.md @@ -15,7 +15,7 @@ It is not meant as a full-fledged from-scratch Julia tutorial. If you are comple ## Installing packages and setting up and environment For PlantSimEngine, you can check our documentation page on the topic: -[Installing and running PlantSimEngine](@ref) +[Installing PlantSimEngine](installing_plantsimengine.md). ## Cheatsheets @@ -23,8 +23,6 @@ You can also find a few cheatsheets [here](https://palmstudio.github.io/Biophysi ## Troubleshooting -There is a documentation page showcasing some of the common errors than can occur when using PlantSimEngine, which may be worth checking if you are encountering issues: [Troubleshooting error messages](@ref). - For more Julia learning-related difficulties, you will find quick responses on the Discourse forum: [https://discourse.julialang.org](https://discourse.julialang.org). ### Noteworthy differences with other languages: @@ -52,4 +50,4 @@ Also of importance: Many of these are also briefly presented in [this Julia Data Science](https://juliadatascience.io/julia_basics) guide, which also happens to focus on the DataFrames.jl package. -Understanding more about methods, parametric types and the typing system is usually worthwhile, when working with Julia packages. \ No newline at end of file +Understanding more about methods, parametric types and the typing system is usually worthwhile, when working with Julia packages. diff --git a/docs/src/prerequisites/key_concepts.md b/docs/src/prerequisites/key_concepts.md index 93bef82e6..2f254e75c 100644 --- a/docs/src/prerequisites/key_concepts.md +++ b/docs/src/prerequisites/key_concepts.md @@ -1,185 +1,108 @@ # Key Concepts -You'll find a brief description of some of the main concepts and terminology related to and used in PlantSimEngine. +## Processes And Models -```@contents -Pages = ["key_concepts.md"] -Depth = 4 -``` - -## Crop models - -## FSPM - -## PlantSimEngine terminology - -This page provides a general description of the concepts and terminology used in PlantSimEngine. For a more implementation-guided description of the design and some of the terms presented here, see the [Detailed walkthrough of a simple simulation](@ref detailed-walkthrough-of-a-simple-simulation) - -!!! Note - Some terminology has different meanings in different contexts. This is particularly true of the terms organ, scale and symbol, which have a different meaning for [Multi-scale Tree Graphs](@ref) than the rest of PlantSimEngine (see [Scale/symbol terminology ambiguity](@ref) further down). Make sure to double-check those subsections, and relevant examples if you encounter issues relating to these terms. - -### Processes - -A process in this package defines a biological or physical phenomena. Think of any process happening in a system, such as light interception, photosynthesis, water, carbon and energy fluxes, growth, yield or even electricity produced by solar panels. - -See [Implementing a new process](@ref) for a brief explanation on how to declare a new process. - -### Models - -A model is a particular implementation for the simulation of a process. - -There may be different models that can be used for the same process; for instance, there are multiple hypotheses and ways of modeling photosynthesis, with different granularity and accuracy. A simple photosynthesis model might apply a simple formula and apply it to the total leaf surface, a more complex one might calculate interception and light extinction. - -!!! note - The companion package PlantBiophysics.jl provides the [`Beer`](https://vezy.github.io/PlantBiophysics.jl/stable/functions/#PlantBiophysics.Beer) structure for the implementation of the Beer-Lambert law of light extinction. The process of `light_interception` and the `Beer` model are provided as an example script in this package too at [`examples/Beer.jl`](https://github.com/VirtualPlantLab/PlantSimEngine.jl/blob/master/examples/Beer.jl). - -Models can also be used for ad hoc computations that aren't directly tied to a specific literature-defined physiological process. In PlantSimEngine, everything is a model. There are many instances where a custom model might be practical to aggregate some computations or handle other information. To illustrate, XPalm, the Oil Palm model, has a few models that handle the state of different organs, and a model to handle leaf pruning, which you can find [here](https://github.com/PalmStudio/XPalm.jl/blob/main/src/plant/phytomer/leaves/leaf_pruning.jl). - -To prepare a simulation, you declare a ModelMapping with whatever models you wish to make use of and initialize necessary parameters: see the [step by step](@ref detailed-walkthrough-of-a-simple-simulation) section to learn how to use them in practice. - -For multi-scale simulations, models need to be tied to a particular scale when used. See the [Multiscale modeling](@ref) section below, or the [Multi-scale considerations](@ref) page for a more detailed description of multi-scale peculiarities. - -### Variables, inputs, outputs, and model coupling - -A model used in a simulation requires some input data and parameters, and will compute some other data which may be used by other models. Depending on what models are combined in a simulation, some variables may be inputs of some models, outputs of other models, only be part of intermediary computations, or be a user input to the whole simulation. - -Here's a conceptual model coupling; each "node" is equivalent to a distinct PlantSimEngine model, "compute()" is equivalent to the model's "run!" function: - -![Model coupling example](../www/GUID-12E2DDAD-7B20-4FE2-AA36-7FAC950382A6-low.png) -(Source: [Autodesk](https://help.autodesk.com/view/MAYAUL/2016/ENU/?guid=__files_GUID_A9070270_9B5D_4511_8012_BC948149884D_htm")) - -### Dependency graphs - -Coupling models together in this fashion creates what is known as a [Directed Acyclic Graph](https://en.wikipedia.org/wiki/Directed_acyclic_graph) or DAG, a type of [dependency graph](https://en.wikipedia.org/wiki/Dependency_graph). The order in which models are run is determined by the ordering of these models in that graph. - -![Example DAG](../www/dags_acyclic_vs_cyclic-d1a669bf1b8b6bfa8ac3041788e81171.png) -A simple Directed Acyclic Graph, note the required absence of cycles. Source: [Astronomer](https://www.astronomer.io/docs/learn/dags/) (Note: "Not Acyclic" is simply "Cyclic"). - -PlantSimEngine creates this Directed Acyclic Graph automatically by plugging the right variables in the right models. Users therefore only need to declare models, they do not need to write the code to connect them as PlantSimEngine does that work for them, as long as the model coupling has no cyclic dependency. - -### ["Hard" and "Soft" dependencies](@id hard_dependency_def) - -Linking models by setting output variables from one model as input of another model handles many typical couplings (with more situations occurring with multi-scale models and variables), but what if two models are interdependent? What if they need to iterate on some computation and pass variables back and forth? - -You can find a typical example in a companion package: [PlantBioPhysics.jl](https://github.com/VEZY/PlantBiophysics.jl). An energy balance model, the [Monteith model](https://github.com/VEZY/PlantBiophysics.jl/blob/master/src/processes/energy/Monteith.jl), needs to [iteratively run a photosynthesis model](https://github.com/VEZY/PlantBiophysics.jl/blob/c1a75f294109d52dc619f764ce51c6ca1ea897e8/src/processes/energy/Monteith.jl#L154) in its [`run!`](@ref) function. - -See the illustration below of the way these models are interdependent: +A process identifies a biological or physical phenomenon, such as +photosynthesis, growth, water balance, or energy balance. A model is one +implementation of a process. -![Example of a coupling with cycles](../www/ecophysio_coupling_diagram.png) +Models subtype `AbstractModel` and declare: -Example of a coupling with a cycle. Source: PlantBioPhysics.jl +- `inputs_`: values read from object status, each declared as `Required(T)` or + `Default(value)`; +- `outputs_`: values written to object status; +- `environment_inputs_`: values sampled from the environment; +- `environment_outputs_`: environment variables a controller may commit; +- `commit_environment!`: accepted meteorological state committed to a mutable + environment by controller models; +- `dep`: processes called manually by the model, when required. -Model couplings that cause simulation to flow both ways break the 'acyclic' assumption of the dependency graph. - -PlantSimEngine handles this internally by not having those "heavily-coupled" models -called **hard dependencies** from now on- be part of the main dependency graph. Instead, modelers should call these models manually from within a model. This way, they are made to be children nodes of the parent/ancestor model, which handles them internally, so they aren't tied to other nodes of the dependency graph. The resulting higher-level graph therefore only links models without any two-way interdependencies, and remains a directed graph, enabling a cohesive simulation order. The simpler couplings in that top-level graph are called "soft dependencies". - -![Hard dependency coupling visualization in PlantSimEngine](../www/PBP_dependency_graph.png) -The previous coupling, handled by PlantSimEngine - -How PlantSimEngine links these models under the hood. The red models ("hard dependencies") are not exposed in the final dependency graph, which only contains the blue "soft dependencies", and has no cycles. - -This approach does have implications when developing interdependent models: hard dependencies need to be made explicit, and the ancestor needs to call the hard dependency model's [`run!`](@ref) function explicitely in its own [`run!`](@ref) function. Hard dependency models therefore must have only one parent model. - -This reliance on another process makes these models slightly more complex to develop and validate, but keep the versatility of the implementation, as any model implementing the hard-dependency process can be passed by the user. - -Note that hard dependencies can also have their own hard dependencies, and some complex couplings can happen. - -### Weather data - -To run a simulation, we usually need the climatic/meteorological conditions measured close to the object or component. - -Users are strongly encouraged to use [`PlantMeteo.jl`](https://github.com/PalmStudio/PlantMeteo.jl), the companion package that helps manage such data, with default pre-computations and structures for efficient computations. We will make constant use of it throughout the documentation, and recommend working with it. - -The most basic data structure from this package is a type called [`Atmosphere`](https://palmstudio.github.io/PlantMeteo.jl/stable/#PlantMeteo.Atmosphere), which defines steady-state atmospheric conditions, *i.e.* the conditions are considered at equilibrium. Another structure is available to define different consecutive time-steps: [`TimeStepTable`](https://palmstudio.github.io/PlantMeteo.jl/stable/#PlantMeteo.TimeStepTable). - -The mandatory variables to provide for an [`Atmosphere`](https://palmstudio.github.io/PlantMeteo.jl/stable/#PlantMeteo.Atmosphere) are: `T` (air temperature in °C), `Rh` (relative humidity, 0-1) and `Wind` (the wind speed, m s⁻¹). - -In the example below, we also pass in the -optional- incoming photosynthetically active radiation flux (`Ri_PAR_f`, W m⁻²). We can declare such conditions like so: - -```@example usepkg -using PlantMeteo -meteo = Atmosphere(T = 20.0, Wind = 1.0, Rh = 0.65, Ri_PAR_f = 500.0) -``` - -More details are available from the [package documentation](https://vezy.github.io/PlantMeteo.jl/stable). If you do not wish to make use of this package, you can alternately provide your own data, as long as it respects the [Tables.jl interface](https://tables.juliadata.org/stable/#Implementing-the-Interface-(i.e.-becoming-a-Tables.jl-source)) (*e.g.* use a `DataFrame`). - -If you wish to make use of more fine-grained weather data, it will likely require more advanced model creation and MTG manipulation, and more involved work on the modeling side. - -### Organ/Scale - -Plants have different organs with distinct physiological properties and processes. When doing more fine-grained simulations of plant growth, many models will be tied to a particular organ of a plant. Models handling flowering state or root water absorption are such examples. Others, such as carbon allocation and demand, might be reused in slightly different ways for multiple organs of the plant. - -PlantSimEngine documentation tends to use the terms "organ" and "scale" mostly interchangeably. "Scale" is a bit more general and accurate, since some models might not operate at a specific organ level, but (for example) at the scene level, so a "Scene" scale might be present in the MTG, and in the user-provided data. - -When working with multi-scale data, the scale will often need to be specified to map variables, or to indicate at what scale level models work out. You will see some code resembling this : +The numerical kernel is implemented with: ```julia -:Root => (RootGrowthModel(), OrganAgeModel()), -:Leaf => (LightInterceptionModel(), OrganAgeModel()), -:Plant => (TotalBiomassModel(),), +PlantSimEngine.run!(model, status, environment, constants, context) ``` -This example excerpt links from specific models to a specific scale. Note that one model is reused at two different scales, and note that `:Plant` isn't an actual organ, hence the preferred usage of the term "scale". - -### Multiscale modeling - -Multi-scale modeling is the process of simulating a system at multiple levels of detail simultaneously. Some models might run at the organ scale while others run at the plot scale. Each model can access variables at its scale and other scales if needed, allowing for a more comprehensive system representation. It can also help identify emergent properties that are not apparent at a single level of detail. - -For example, a model of photosynthesis at the leaf scale can be combined with a model of carbon allocation at the plant scale to simulate the growth and development of the plant. Another example is a combination of models to simulate the energy balance of a forest. To simulate it, you need a model for each organ type of the plant, another for the soil, and finally, one at the plot scale, integrating all others. - -When running multi-scale simulations which contain models operating at different organ levels for the plant, extra information needs to be provided by the user to run models. Since some models are reused at different organ levels, it is necessary to indicate which organ level a model operates at. - -This is why multi-scale simulations make use of a 'mapping' in the `ModelMapping`, as well as links between models/variables in different scales, *e.g.* if an input variable comes from another scale, it is required to indicate which scale it is mapped from. - -You can read more about some practical differences as a user between single- and multi-scale simulations here: [Multi-scale considerations](@ref). - -### Multi-scale Tree Graphs +`Required(T)` describes an input that must be supplied by object state or +another application. `Default(value)` is a true model fallback that +PlantSimEngine can initialize automatically. Output literals are initial +output-state values. -![Grassy plant and equivalent MTG](../www/Grassy_plant_MTG_vertical.svg) +## Composite Models And Objects -A Grassy plant and its equivalent MTG +A `CompositeModel` contains objects and model applications. An `Object` can represent a +model, plant, soil volume, axis, internode, leaf, sensor, or any other simulated +entity. PlantSimEngine does not impose one plant architecture. -Multi-scale Tree Graphs (MTG) are a data structure used to represent plants. A more detailed introduction to the format and its attributes can be found [in the MultiScaleTreeGraph.jl package documentation](https://vezy.github.io/MultiScaleTreeGraph.jl/stable/the_mtg/mtg_concept/). +Objects can carry: -Multi-scale simulations can operate on MTG objects; new nodes are added corresponding to new organs created during the plant's growth. +- a stable identifier; +- scale, kind, species, and name metadata; +- parent-child relationships; +- geometry and position; +- mutable `Status`; +- object-local model applications. -You can see a basic display of an MTG by simply typing its name in the REPL: +`CompositeModelTemplate` packages reusable applications for a species or object type. +`ObjectInstance` mounts the template in a model. Several instances can share +models and parameters while declaring targeted overrides for exceptional +objects. -![example display of an MTG in PlantSimEngine](../www/MTG_output.png) +## Model Applications -!!! note - Another companion package, [PlantGeom.jl](https://github.com/VEZY/PlantGeom.jl), can also create MTG objects from .opf files (corresponding to the [Open Plant Format](https://amap-dev.cirad.fr/projects/xplo/wiki/The_opf_format_(*opf)), an alternate means of describing plants computationally). +`ModelSpec` configures one use of a model: -#### Scale/symbol terminology ambiguity +- `ModelSpec(...; on=...)` selects target objects; +- `ModelSpec(...; inputs=...)` selects producers for value dependencies; +- `ModelSpec(...; calls=...)` binds manually controlled model calls; +- `ModelSpec(...; every=...)` selects the execution cadence; +- `Environment(...)` configures environment sampling; +- `Updates(...; after=:application_id)` orders intentional additional writers; +- `ModelSpec(...; output_routing=...)` controls output publication. -Multi-scale tree graphs have different terminology (see [Organ/Scale](@ref)): +This keeps model implementations generic. Models do not need to know which +model, object, timestep, or coupling scenario will use them. -- the MTG node **symbol** represents "something" like a `:Plant`, `:Root`, `:Scene` or `:Leaf`. It corresponds to a PlantSimEngine *scale* and has nothing to do with the Julia programming language's definition of symbol (*e.g.* `:var`) -- the MTG node **scale**, is an integer passed to the Node constructor, and describes the level of description of the tree graph object. They don't always have a one-to-one correspondence to the symbol (or PlantSimEngine's scale), but are similar. +## Soft And Manual Dependencies -![Three scale levels on an MTG, which differ from typical PlantSimEngine concept of scale](../www/Grassy_plant_scales.svg) +Ordinary dependencies are inferred by matching model inputs with outputs and +are compiled into an acyclic execution order. `ModelSpec(...; inputs=...)` is used when the +source is cross-object, renamed, temporal, or otherwise ambiguous. -You can find a brief description of the MTG concepts [here](https://vezy.github.io/MultiScaleTreeGraph.jl/stable/the_mtg/mtg_concept/#Node-MTG-and-attributes). +Some algorithms need direct call-stack control. For example, a model energy +balance may repeatedly call leaf energy-balance models until canopy +microclimate converges. Such dependencies are bound with `ModelSpec(...; calls=...)`; the +parent invokes them with `run_call!`. -Other words are unfortunately reused in various contexts with different meanings: tree/leaf/root have a different meaning when talking about computer science data structure (*e.g.*, graphs, dependency graphs and trees). +## Status And References -!!! note - In the majority of cases, you can assume the tree-related terminology refers to the biological terms, and that "organ" refer to plant organs, and "single-scale", "multi-scale" and "scale" to PlantSimEngine's concept of scales described in [Organ/Scale](@ref). MTG objects are mostly manipulated on a per-node basis (the graph node, not the botanical node), unless a model makes use of functions relating to MTG traversal, in which case you may expect computer science terminology. +`Status` stores variables in references. Same-rate coupling normally shares +those references instead of copying values. A many-object input uses a +reference vector, so aggregation models read current source values directly. -#### TLDR +Temporal coupling uses published streams when producer and consumer clocks +differ. Policies include `HoldLast`, `Interpolate`, `Integrate`, `Aggregate`, +and `PreviousTimeStep`. -In summary: +## Environment -- In PlantSimEngine a scale is a level of description defined by a name (`String`). In MTG, a scale is an integer describing the level of description of the node, and a symbol is a name for that node. So symbol in the MTG == scale in PlantSimEngine; -- The word "node" is always used to refer to the Multiscale Tree Graph node, not the botanical node. +The active environment backend may be: -### State machines +- one constant atmosphere shared by all objects; +- a time-indexed weather table; +- a mutable layer, voxel, grid, or octree microclimate. -A state machine is a computational concept used to model mechanisms and devices, which may be of interest for your simulations. +Object-to-environment support is compiled and cached. Geometry changes mark the +binding dirty so it can be refreshed without recomputing spatial lookup at +every timestep. -![State machine image](../www/Turnstile_state_machine_colored.svg.png) -A simple state machine. See the [wikipedia page](https://en.wikipedia.org/wiki/Finite-state_machine) for more examples. +## Multiscale Plant Structure -State machines can be useful to model organ state: some organs in [XPalm.jl](https://github.com/PalmStudio/XPalm.jl), a package modelling the oil palm using PlantSimEngine, have a `state` variable behaving like a state machine, indicating whether an organ is mature, pruned, flowering, etc. +PlantSimEngine treats scale and object hierarchy as scenario data. A plant may +use leaves directly under a plant, or axes, segments, internodes, roots, and +other intermediate levels. Selectors express relationships such as one source, +many descendants, the current plant, an ancestor, or all matching objects in +the model. -You can find an example model (amongst other such models) affecting the `state` variable of some organs depending on their age and thermal time in the XPalm oil palm FSPM [here](https://github.com/PalmStudio/XPalm.jl/blob/main/src/plant/phytomer/phytomer/state.jl). +MultiScaleTreeGraph objects can be imported with `objects_from_mtg`, but the +runtime operates on the same composite-model/object representation afterward. diff --git a/docs/src/step_by_step/advanced_coupling.md b/docs/src/step_by_step/advanced_coupling.md index 07b81c8bb..907953a44 100644 --- a/docs/src/step_by_step/advanced_coupling.md +++ b/docs/src/step_by_step/advanced_coupling.md @@ -1,64 +1,167 @@ # Coupling more complex models -```@setup usepkg -using PlantSimEngine, PlantMeteo, Dates -# Import the example models defined in the `Examples` sub-module: +```@setup scene_advanced_coupling +using PlantSimEngine, PlantMeteo, Dates, DataFrames using PlantSimEngine.Examples -m = ModelMapping( - Process1Model(2.0), - Process2Model(), - Process3Model(), - Process4Model(), - Process5Model(), - Process6Model(), - Process7Model(), +meteo_day = read_weather( + joinpath(pkgdir(PlantSimEngine), "examples/meteo_day.csv"); + duration=Dates.Day, ) ``` -When two or more models have a two-way interdependency (rather than variables flowing out only one-way from one model into the next), we describe it as a [hard dependency](@ref hard_dependency_def). +Most model coupling is a value dependency: one model writes an output, another +model reads it as an input. Some models need tighter control. For example, an +energy-balance model may call photosynthesis and stomatal-conductance models +several times while it iterates leaf temperature. -This kind of interdependency requires a little more work from the user/modeler for PlantSimEngine to be able to automatically create the dependency graph. +That second case is a manual call dependency. In the composite-model/object API it is +declared with `ModelSpec(...; calls=...)`. -## Declaring hard dependencies +## Soft inputs and manual calls -A model that explicitly and directly calls another process in its [`run!`](@ref) function is part of a hard dependency, or a hard-coupled model. +Use `ModelSpec(...; inputs=...)` or inferred same-object bindings when a model only needs a +value. Use `ModelSpec(...; calls=...)` when the parent model must directly run another model +inside its own `run!` method. -Let's go through the example processes and models from a script provided by the package here [examples/dummy.jl](https://github.com/VirtualPlantLab/PlantSimEngine.jl/blob/main/examples/dummy.jl) +The example process models in `examples/dummy.jl` contain both patterns: -In this script, we declare seven processes and seven models, one for each process. The processes are simply called "process1", "process2"..., and the model implementations are called `Process1Model`, `Process2Model`... +- `Process4Model` computes `var1` and `var2`; +- `Process1Model` consumes `var1` and `var2` and computes `var3`; +- `Process2Model` manually calls process 1, then computes `var4` and `var5`; +- `Process3Model` manually calls process 2, then computes `var6`; +- `Process5Model`, `Process6Model`, and `Process7Model` use regular soft + value dependencies. -When run, `Process2Model` calls another process's [`run!`](@ref) function explicitely, which requires defining that process as a hard-dependency of `Process2Model` : +## Declaring manual calls in the scenario -```julia -function PlantSimEngine.run!(::Process2Model, models, status, meteo, constants, extra) - # computing var3 using process1: - run!(models.process1, models, status, meteo, constants) - # computing var4 and var5: - status.var4 = status.var3 * 2.0 - status.var5 = status.var4 + 1.0 * meteo.T + 2.0 * meteo.Wind + 3.0 * meteo.Rh -end +`ModelSpec(...; calls=...)` is scenario-level wiring. The model kernel remains generic; the +scenario decides which concrete application is called. + +Use `application=...` in scenario-level `ModelSpec(...; calls=...)` and `ModelSpec(...; inputs=...)` when you +know which mounted model application should provide the value or be called. Use +process identities in model-level contracts such as `dep(model)`, where the +model author only declares that a compatible process is required and cannot know +the names chosen by future scenarios. + +This split avoids ambiguity when several applications implement the same +process. For example, two soil-water applications can share the same process but +represent different layers, parameter sets, objects, or time steps. A scenario +selector should name the application that has the intended role. + +```@example scene_advanced_coupling +complex_scene = CompositeModel( + Object(:scene; scale=:Scene, kind=:scene, status=Status(var0=2.0)); + applications=( + ModelSpec(Process4Model(); name=:prepare_inputs, on=One(scale=:Scene), every=Day(1)), + + ModelSpec(Process1Model(2.0); name=:process1, on=One(scale=:Scene), every=Day(1)), + + ModelSpec(Process2Model(); name=:process2, on=One(scale=:Scene), calls=(:process1 => One(scale=:Scene, application=:process1)), every=Day(1)), + + ModelSpec(Process3Model(); name=:process3, on=One(scale=:Scene), calls=(:process2 => One(scale=:Scene, application=:process2)), every=Day(1)), + + ModelSpec(Process5Model(); name=:process5, on=One(scale=:Scene), every=Day(1)), + + ModelSpec(Process7Model(); name=:process7, on=One(scale=:Scene), every=Day(1)), + + ModelSpec(Process6Model(); name=:process6, on=One(scale=:Scene), every=Day(1)), + ), + environment=meteo_day, +) + +select( + DataFrame(Diagnostics.explain_calls(complex_scene)), + :application_id, + :call, + :callee_application_ids, + :callee_object_ids, + :publication_policy, +) ``` -`Process2Model` is coupled to another process (`process1`), and calls its model's `run` function. The [`run!`](@ref) function is called with the same arguments as the [`run!`](@ref) function of the model that calls it, except that we pass the process we want to simulate as the first argument. +Applications selected by `ModelSpec(...; calls=...)` are not scheduled as independent root +applications under their caller. They run only when the parent calls them. +This gives the parent full call-stack control. -!!! note - We don't enforce any type of model to simulate `process1`. This is the reason why we can switch so easily between model implementations for any process, by just changing the model in the [`ModelMapping`](@ref). +## Running the coupled model -A hard-dependency must always be declared to PlantSimEngine. This is done by adding a method to the `dep` function when implementing the model. For example, the hard-dependency to `process1` into `Process2Model` is declared as follows: +The regular soft dependencies are still inferred from `inputs_` and +`outputs_`. The scheduler combines those soft edges with the call ownership +rules: + +```@example scene_advanced_coupling +select( + DataFrame(Diagnostics.explain_schedule(complex_scene)), + :application_id, + :manual_call_only, + :execution_index, + :clock, +) +``` + +Run one timestep: + +```@example scene_advanced_coupling +complex_sim = run!(complex_scene; steps=1) +complex_status = final_state(complex_sim) +( + var3=complex_status.var3, + var5=complex_status.var5, + var6=complex_status.var6, + var8=complex_status.var8, +) +``` + +## Writing new hard-coupled models + +For new composite-model/object models, execute all targets directly when they +share meteorology and publication policy: ```julia -PlantSimEngine.dep(::Process2Model) = (process1=AbstractProcess1Model,) +targets = run_call!(context, :leaf_energy; publish=true) ``` -This way PlantSimEngine knows that `Process2Model` needs a model for the simulation of the `process1` process. To avoid imposing a specific model to be coupled with `Process2Model`, the dependency only requires a model that is a subtype of the abstract parent type `AbstractProcess1Model`. This avoids constraining to the specific `Process1Model` implementation, meaning an alternate model computing the same variables for the same process is still interchangeable with `Process1Model`. +The result is always vector-like. Retrieve targets without executing them when +an algorithm needs selective execution or an already sampled environment for +each target: -While not encouraged, if you have a valid reason to force the coupling with a particular model, you can force the dependency to require that model specifically. For example, if we want to use only `Process1Model` for the simulation of `process1`, we would declare the dependency as follows: +```julia +targets = call_targets(context, :leaf_energy) +for (target, leaf_environment) in zip(targets, environments_by_leaf) + run_call!( + target; + sampled_environment=leaf_environment, + publish=false, + ) +end +``` + +For a provider-aware trial state shared by the call, keep the execute-all form. +Each target still samples through its own compiled handle: ```julia -PlantSimEngine.dep(::Process2Model) = (process1=Process1Model,) +function PlantSimEngine.run!(model::SceneEnergyBalance, status, environment, + constants, context) + trial = trial_environment(model, status) + run_call!(context, :leaf_energy; environment=trial, publish=false) + + accepted = accepted_environment(model, status) + commit_environment!(context, accepted) + run_call!(context, :leaf_energy; publish=true) + + return nothing +end ``` -## Examples in the wild +`run_call!` defaults to `publish=false`, which is useful for trial iterations. +Pass non-committing trial state with the `environment` keyword. Use +`commit_environment!` and `publish=true` for the accepted state so temporal +streams and mutable environment state are published once. + +The MAESPA-style example uses the same mechanism: a model energy-balance model +calls all selected leaf energy-balance models and the shared soil model while +it solves canopy microclimate. -You can find a typical example in a companion package: [PlantBioPhysics.jl](https://github.com/VEZY/PlantBiophysics.jl). An energy balance model, the [Monteith model](https://github.com/VEZY/PlantBiophysics.jl/blob/master/src/processes/energy/Monteith.jl), needs to [iteratively run a photosynthesis model](https://github.com/VEZY/PlantBiophysics.jl/blob/c1a75f294109d52dc619f764ce51c6ca1ea897e8/src/processes/energy/Monteith.jl#L154) in its [`run!`](@ref) function. \ No newline at end of file +Scenario wiring uses `ModelSpec(...; calls=...)`. Model authors should keep kernels generic +and only require manual calls when the model really needs call-stack control. diff --git a/docs/src/step_by_step/detailed_first_example.md b/docs/src/step_by_step/detailed_first_example.md index 068341b5e..5a762b2dd 100644 --- a/docs/src/step_by_step/detailed_first_example.md +++ b/docs/src/step_by_step/detailed_first_example.md @@ -1,17 +1,21 @@ -# [Detailed walkthrough of a simple simulation](@id detailed-walkthrough-of-a-simple-simulation) +# [Detailed Walkthrough Of A Simple Simulation](@id detailed-walkthrough-of-a-simple-simulation) -This page walks you through the ins and outs of a basic simulation, mostly aimed at people who have less experience programming, to showcase the various concepts presented earlier and requirements for a simulation in context. +This page walks through a small composite-model/object simulation. It is written for +readers who are still getting comfortable with Julia and PlantSimEngine. -A working trimmed-down script can be found further down in the [Example simulation](@ref), and other subsections in this page will detail setup and helper functions, and querying outputs. +If you only want examples to copy and modify, see [Quick examples](quick_and_dirty_examples.md). For +multi-object and multi-plant simulations, the same API scales up: add objects, +select them with `ModelSpec(...; on=...)`, connect values with `ModelSpec(...; inputs=...)`, and use +`ModelSpec(...; calls=...)` when a parent model must manually run child models. -If you simply wish to copy-paste examples and tinker with them, you can find a few examples on the [Quick examples](@ref) page. - -```@setup usepkg -using PlantSimEngine, PlantMeteo, Dates +```@setup detailed_scene +using PlantSimEngine, PlantMeteo, Dates, DataFrames using PlantSimEngine.Examples -meteo = Atmosphere(T = 20.0, Wind = 1.0, Rh = 0.65, Ri_PAR_f = 500.0) -leaf = ModelMapping(Beer(0.5), status = (LAI = 2.0,)) -out_sim = run!(leaf, meteo) + +meteo_day = read_weather( + joinpath(pkgdir(PlantSimEngine), "examples/meteo_day.csv"); + duration=Dates.Day, +) ``` ```@contents @@ -19,226 +23,203 @@ Pages = ["detailed_first_example.md"] Depth = 3 ``` -## Setting up your environment - -For every script in this documentation, you will always need a working Julia environment with PlantSimengine added to it, and usually several other companion packages. Details for getting to that point are provided on the [Installing and running PlantSimEngine](@ref) page. - -## Definitions - -### Processes - -A process in this package defines a biological or physical phenomena. Think of any process happening in a system, such as light interception, photosynthesis, water, carbon and energy fluxes, growth, yield or even electricity produced by solar panels. - -A process is "declared", meaning we define a process, and then implement models for its simulation. In this example, we will make use of a process that was already defined, and for which there already is a model implementation. - -### Models (ModelMapping) - -A process is simulated using a particular implementation, or **a model**. Each model is implemented using a structure that lists the parameters of the model. For example, PlantBiophysics provides the [`Beer`](https://vezy.github.io/PlantBiophysics.jl/stable/functions/#PlantBiophysics.Beer) structure for the implementation of the Beer-Lambert law of light extinction. The process of `light_interception` and the `Beer` model are provided as an example -script in this package too at [`examples/Beer.jl`](https://github.com/VirtualPlantLab/PlantSimEngine.jl/blob/master/examples/Beer.jl). - -Models can use several types of entries: - -- Parameters -- Meteorological information -- Variables -- Constants -- Extras - -**Parameters** are constant values that are used by the model to compute its outputs, and are exclusive to that model. - -**Meteorological information** contains values that are provided by the user and are used as inputs to the model. It is defined for one time-step, and `PlantSimEngine.jl` takes care of applying the model to each time-steps given by the user. - -**Variables** are either used or computed by the model and can optionally be initialized before the simulation. They can be part of multiple models, computed by one and then used as an input by another. They can also be a global simulation output, or be provided at the start of a simulation by the user. - -**Constants** are constant values, usually common between models, *e.g.* the universal gas constant. - -And **extras** are just extra values that can be used by a model, or serves as a placeholder for internal data. - -Users declare a set of models used for simulation, as well as the necessary parameters for each model, and whatever variables need to be initialized. This is done using a [`ModelMapping`](@ref) structure. - -For example let's instantiate a [`ModelMapping`](@ref) with a single model : the Beer-Lambert model of light extinction, used to simulate the light interception process. The model is implemented with the [`Beer`](https://github.com/VirtualPlantLab/PlantSimEngine.jl/blob/master/examples/Beer.jl) structure and only has one parameter: the extinction coefficient (`k`). - -Importing the package: - -```@example usepkg -using PlantSimEngine -``` - -Import the examples defined in the [`Examples`](https://github.com/VirtualPlantLab/PlantSimEngine.jl/blob/main/examples) sub-module (`light_interception` and `Beer`): - -```julia -using PlantSimEngine.Examples -``` +## Setting Up Your Environment -And then declare a [`ModelMapping`](@ref) with the `Beer` model: +Every script needs a Julia environment with PlantSimEngine installed. Most +examples also use companion packages such as PlantMeteo for weather data and +DataFrames for tabular outputs. Installation details are in +[Installing PlantSimEngine](../prerequisites/installing_plantsimengine.md). -```@example usepkg -m = ModelMapping(Beer(0.5)) -``` +## The Simulation Pieces -What happened here? We provided an instance of the `Beer` model to a [`ModelMapping`](@ref) to simulate the light interception process. +### Processes And Models -## Parameters +A process is something you want to simulate, such as light interception, +photosynthesis, water flux, growth, yield, or energy balance. -A parameter is a value constant for a simulation that is internal to a model and used for its computations. For example, the Beer-Lambert model uses the extinction coefficient (`k`) to compute the light extinction. The `Beer` structure in the Beer-Lambert model implementation, only has one field: `k`. We can see that using `fieldnames` on the model structure: +A model is one implementation of a process. In this page we use the example +`Beer` model, which implements a Beer-Lambert light-interception equation. +Its only parameter is the extinction coefficient `k`. -```@example usepkg +```@example detailed_scene fieldnames(Beer) ``` -## Variables (inputs, outputs) +The model implementation declares the status variables it reads and writes: -Variables are either inputs or outputs (*i.e.* computed) of models. Variables and their values are stored in the [`ModelMapping`](@ref) structure, and are initialized automatically or manually. - -For example, the `Beer` model needs the leaf area index (`LAI`, m² m⁻²) to run. - -We can see which variables are passed in as inputs using [`inputs`](@ref): - -```@example usepkg +```@example detailed_scene inputs(Beer(0.5)) ``` -and which are computed outputs of the model using [`outputs`](@ref): - -```@example usepkg +```@example detailed_scene outputs(Beer(0.5)) ``` -The [`ModelMapping`](@ref) structure will keep track of every variable's current state when running the simulation, storing them in a field called `status`. We can inspect that field with the [`status`](@ref) function and see that in our example it has two variables: `LAI` and `PPFD`. The first is an input, the second an output (*i.e.* it is computed by the model). +These declarations are the modeler's contract. The composite-model/object layer decides +where the model runs and where those values come from. -```@example usepkg -m = ModelMapping(Beer(0.5)) -keys(status(m)) -``` - -To know which variables should be initialized, we can use [`to_initialize`](@ref): +### CompositeModel Objects -```@example usepkg -m = ModelMapping(Beer(0.5)) -to_initialize(m) -``` +A `CompositeModel` contains simulated `Object`s. An object can represent a model, plant, +axis, leaf, soil layer, sensor, voxel, or any other simulated entity. -Their values are uninitialized though (hence the warnings): +For a first example, we use one object representing the whole model. The `Beer` +model reads `LAI`, so we initialize that variable on the object status. -```@example usepkg -(m[:LAI], m[:aPPFD]) +```@example detailed_scene +model = CompositeModel( + Beer(0.5); + status=(LAI=2.0,), + environment=meteo_day, + timestep=Day(1), +); +nothing ``` -Uninitialized variables are initialized to the value given in the [`inputs`](@ref) or [`outputs`](@ref) methods in the model's implementation code, which is usually equal to `typemin()`, *e.g.* `-Inf` for `Float64`. +The concise constructor creates one ordinary model object and one application +for each supplied model. `status` initializes that object, `timestep` applies a +common daily cadence, and `environment` supplies weather values such as +radiation. Use explicit `ModelSpec` and selectors when applications need +different policies or targets. -!!! tip - Prefer using [`to_initialize`](@ref) rather than [`inputs`](@ref) to check which variables should be initialized. [`inputs`](@ref) returns every variable that is needed by the model to run, but in multi-model simulations, some of them may already be computed by other models and not require initialization. [`to_initialize`](@ref) returns **only** the variables that are needed by the model to run and that are not initialized in the [`ModelMapping`](@ref). +## Inspecting The Compiled CompositeModel -We can initialize the required variables by providing their starting values to the status when declaring the `ModelMapping`: +Before runtime, PlantSimEngine resolves selectors and builds a compiled model. +This avoids resolving object selections inside the timestep loop. -```@example usepkg -m = ModelMapping(Beer(0.5), status = (LAI = 2.0,)) +```@example detailed_scene +select( + DataFrame(Diagnostics.explain_applications(model)), + :application_id, + :process, + :target_ids, +) ``` -Or after instantiation using [`init_status!`](@ref): +`Beer` has no model-to-model value input in this first model because `LAI` was +initialized directly on the object status: -```@example usepkg -m = ModelMapping(Beer(0.5)) - -init_status!(m, LAI = 2.0) +```@example detailed_scene +Diagnostics.explain_bindings(model) ``` -We can check if a component is correctly initialized using [`is_initialized`](@ref): +The schedule tells us when each application runs: -```@example usepkg -is_initialized(m) +```@example detailed_scene +select( + DataFrame(Diagnostics.explain_schedule(model)), + :application_id, + :dt_seconds, + :root_scheduled, + :manual_call_only, +) ``` -Some variables are inputs of models, but outputs of other models. When we couple models, [`to_initialize`](@ref) only requests the variables that are not computed by other models. - -## Climate forcing - -To make a simulation, we usually need the climatic/meteorological conditions measured close to the object or component. +## Running The Simulation -Users are strongly encouraged to use [`PlantMeteo.jl`](https://github.com/PalmStudio/PlantMeteo.jl), the companion package that helps manage such data, with default pre-computations and structures for efficient computations. The most basic data structure from this package is a type called [`Atmosphere`](https://palmstudio.github.io/PlantMeteo.jl/stable/#PlantMeteo.Atmosphere), which defines steady-state atmospheric conditions, *i.e.* the conditions are considered at equilibrium. Another structure is available to define different consecutive time-steps: [`TimeStepTable`](https://palmstudio.github.io/PlantMeteo.jl/stable/#PlantMeteo.TimeStepTable). +Run the model with [`run!`](@ref): -The mandatory variables to provide for an [`Atmosphere`](https://palmstudio.github.io/PlantMeteo.jl/stable/#PlantMeteo.Atmosphere) are: `T` (air temperature in °C), `Rh` (relative humidity, 0-1) and `Wind` (the wind speed, m s⁻¹). In our example, we also need the incoming photosynthetically active radiation flux (`Ri_PAR_f`, W m⁻²). We can declare such conditions like so: - -```@example usepkg -using PlantMeteo -meteo = Atmosphere(T = 20.0, Wind = 1.0, Rh = 0.65, Ri_PAR_f = 500.0) +```@example detailed_scene +sim = run!(model; steps=3, outputs=:all) +nothing ``` -This `meteo` variable will therefore provide a single weather timeframe that can be used in a simulation. - -More details are available from the [package documentation](https://vezy.github.io/PlantMeteo.jl/stable). - -## Simulation +Final state is available independently of retained output history: -### Simulation of processes - -To run a simulation, you can call the [`run!`](@ref) method on the [`ModelMapping`](@ref). If some meteorological data is required for models to be simulated over several timesteps, that can be passed in as an optional argument as well. - -Your call to the function would then look like this: - -```julia -run!(model_list, meteo) +```@example detailed_scene +scene_status = final_state(sim) +(LAI=scene_status.LAI, aPPFD=scene_status.aPPFD) ``` -The first argument is the model mapping (see [`ModelMapping`](@ref)), and the second defines the micro-climatic conditions. +The returned `Simulation` stores retained output streams: -The [`ModelMapping`](@ref) should already be initialized for the given process before calling the function. Refer to the earlier subsection [Variables (inputs, outputs)](@ref) for more details. - -### Example simulation - -For example we can simulate the `light_interception` of a leaf like so: +```@example detailed_scene +first(collect_outputs(sim; sink=nothing), 3) +``` -```@example usepkg -using PlantSimEngine, PlantMeteo, Dates +For a table, use the default `DataFrame` sink: -# Import the examples defined in the `Examples` sub-module -using PlantSimEngine.Examples +```@example detailed_scene +first(collect_outputs(sim), 3) +``` -meteo = Atmosphere(T = 20.0, Wind = 1.0, Rh = 0.65, Ri_PAR_f = 500.0) +## Adding A Model Coupling -leaf = ModelMapping(Beer(0.5), status = (LAI = 2.0,)) +Now let a daily LAI model compute `LAI` before the light-interception model +runs. `ToyLAIModel` reads cumulative thermal time `TT_cu` and writes `LAI`. +Because `Beer` reads `LAI`, the compiler can infer the same-object binding. -outputs_example = run!(leaf, meteo) +```@example detailed_scene +coupled_scene = CompositeModel( + ToyDegreeDaysCumulModel(), + ToyLAIModel(), + Beer(0.5); + status=(TT_cu=0.0,), + environment=meteo_day, + timestep=Day(1), +) -outputs_example[:aPPFD] +select( + DataFrame(Diagnostics.explain_bindings(coupled_scene)), + :application_id, + :input, + :source_application_ids, + :carrier_kind, + :copy_semantics, +) ``` -### Outputs +The `LAI` binding uses a live reference carrier, so the light-interception +model sees the value written by the LAI model without copying it. -The [`status`](@ref) field of a [`ModelMapping`](@ref) is used to initialize the variables before simulation and then to keep track of their values during and after the simulation. We can extract outputs of the very last timestep of a simulation using the [`status`](@ref) function. +Run the coupled model: -The actual full output data is returned by the [`run!`](@ref) function. Data is usually stored in a [`TimeStepTable`](@ref) structure from `PlantMeteo.jl`, which is a fast DataFrame-like structure with each time step being a [`Status`](@ref). It can be also be any `Tables.jl` structure, such as a regular `DataFrame`. The weather is also usually stored in a [`TimeStepTable`](@ref) but with each time step being an `Atmosphere`. +```@example detailed_scene +coupled_sim = run!(coupled_scene; steps=5, outputs=:all) +first(collect_outputs(coupled_sim), 8) +``` -In our example, the simulation was only provided one weather timestep, so the outputs returned by [`run!`](@ref) and the ModelMapping's [`status`](@ref) field are identical. -Let's look at the outputs structure of our previous simulated leaf: +The final object status contains the latest values from the coupled models: -```@setup usepkg -outputs_example +```@example detailed_scene +coupled_status = final_state(coupled_sim) +(TT_cu=coupled_status.TT_cu, LAI=coupled_status.LAI, aPPFD=coupled_status.aPPFD) ``` -We can extract the value of one variable by indexing into it, *e.g.* for the intercepted light: +## What Needs Initialization? -```@example usepkg -outputs_example[:aPPFD] -``` +Model `inputs_(...)` explicitly distinguishes `Required(T)` from +`Default(value)`. A required input needs user state or a producer binding; a +defaulted input needs neither. In a coupled model, an upstream application can +satisfy a required input. -Or similarly using the dot syntax: +Use the compiler explanations to distinguish the two cases: -```@example usepkg -outputs_example.aPPFD -``` +- `:supplied` means the object `Status` already provides the value; +- `:producer_bound` means another application supplies it; +- `:defaulted` means `Default(value)` initialized it; +- `:required` means it still has no source and compilation will fail. -You can then print the outputs, convert them to another format, or visualize them, using other Julia packages. You can read more on how to do that in the [Visualizing outputs and data](@ref) page. +For example, if we remove `TT_cu` from the model status, compilation fails +because no model in this model computes it before `ToyLAIModel` reads it: -Another convenient way to get the results is to transform the outputs into a `DataFrame`. Which is very easy because the [`TimeStepTable`](@ref) implements the Tables.jl interface: +```@example detailed_scene +bad_scene = CompositeModel( + ToyLAIModel(); + environment=meteo_day, +) -```@example usepkg -using DataFrames -convert_outputs(outputs_example, DataFrame) +try + Diagnostics.explain_bindings(bad_scene) +catch err + first(sprint(showerror, err), 300) +end ``` -## Model coupling - -A model can work either independently or in conjunction with other models. For example a stomatal conductance model is often associated with a photosynthesis model, *i.e.* it is called from the photosynthesis model. +## Next Steps -`PlantSimEngine.jl` is designed to make model coupling painless for modelers and users. Please see [Standard model coupling](@ref) and [Coupling more complex models](@ref) for more details, or [Handling dependencies in a multiscale context](@ref) for multi-scale specific coupling considerations. +- [Standard model coupling](@ref) shows more coupling patterns. +- [CompositeModel/Object Quickstart](../composite_model/quickstart.md) is the shortest + copy-pasteable path for the new API. +- [Model execution](../model_execution.md) explains scheduling, temporal inputs, hard calls, + output retention, and lifecycle refreshes. diff --git a/docs/src/step_by_step/graph_visualization_editor.md b/docs/src/step_by_step/graph_visualization_editor.md deleted file mode 100644 index c343919ff..000000000 --- a/docs/src/step_by_step/graph_visualization_editor.md +++ /dev/null @@ -1,236 +0,0 @@ -# Graph visualization and editing - -`PlantSimEngine` can display the dependency graph created from a [`ModelMapping`](@ref). Use it when you want to check which model computes which variable, inspect missing initial values, explain a model pipeline in documentation, or interactively build and revise a mapping. - -There are two entry points: - -- [`write_graph_view`](@ref) writes a standalone HTML viewer. This is available from `PlantSimEngine` itself and does not start a server. -- [`edit_graph`](@ref) starts a local browser editor. This is loaded by a Julia package extension when `HTTP.jl` is available and loaded in the session. - -## Static graph viewer - -The static viewer is the right tool for documentation, reports, or any read-only inspection. It contains the graph, search, the inspector, scale filters, relationship filters, and overview/detail modes, but it does not modify the [`ModelMapping`](@ref). - -```@setup graph_viewer -using PlantSimEngine -using PlantSimEngine.Examples -``` - -Here is a small pedagogical mapping with three models: - -```@example graph_viewer -mapping = ModelMapping( - ToyDegreeDaysCumulModel(), - ToyLAIModel(), - Beer(0.5), -) -nothing # hide -``` - -The thermal time model computes `TT_cu`, the LAI model consumes `TT_cu` and computes `LAI`, and the Beer model consumes `LAI` and computes `aPPFD`. The generated viewer below is the same HTML file you would get by calling [`write_graph_view`](@ref): - -```@raw html - -``` - -To write the viewer yourself: - -```julia -using PlantSimEngine -using PlantSimEngine.Examples - -mapping = ModelMapping( - ToyDegreeDaysCumulModel(), - ToyLAIModel(), - Beer(0.5), -) - -write_graph_view("dependency_graph.html", mapping) -``` - -The returned file path is absolute, so you can print it, open it in a browser, or embed it in another documentation site. - -## Interactive editor - -The interactive editor uses the same graph JSON as the static viewer, but it keeps a WebSocket connection open to Julia. Julia remains the source of truth: the browser sends edit commands, Julia applies them to the [`ModelMapping`](@ref), recompiles graph diagnostics, and sends the updated graph back to the browser. - -The editor is implemented as a package extension. Static graph files do not need `HTTP`, but the live editor does. In a project that only depends on `PlantSimEngine`, install `HTTP` first: - -```julia -using Pkg -Pkg.add("HTTP") -``` - -Then load `HTTP` before calling [`edit_graph`](@ref): - -```julia -using PlantSimEngine -using PlantSimEngine.Examples -using HTTP - -mapping = ModelMapping( - ToyLAIModel(), - Beer(0.5); - status=(TT_cu=1.0,), -) - -session = edit_graph(mapping) -session.url -session -``` - -To start from a blank graph and build a mapping from scratch, omit the mapping: - -```julia -session = edit_graph() -``` - -By default, `edit_graph` opens `session.url` in the system default browser. Pass `open_browser=false` to keep the session headless, for example in scripts or tests: - -```julia -session = edit_graph(mapping; open_browser=false) -``` - -The URL contains a session token and the server listens on `127.0.0.1` by default. Treat that URL as a local capability: anyone who can reach it can edit the live mapping. If you intentionally bind to another host, pass `allow_remote=true` only on a trusted network. Raw `julia` parameter values are disabled by default for remote sessions; pass `allow_julia_eval=true` only if you explicitly accept that risk. - -To stop the HTTP/WebSocket session, run: - -```julia -close(session) -``` - -Use [`current_mapping`](@ref) to recover the latest mapping from the session: - -```julia -edited_mapping = current_mapping(session) -close(session) -``` - -!!! note - If `HTTP` is not loaded, `edit_graph(mapping)` throws an error explaining that the interactive editor requires `using HTTP`. Static graph visualization through [`write_graph_view`](@ref), `graph_view`, and [`graph_view_json`](@ref) remains available without loading `HTTP`. - -## What you can edit - -The editor supports the same mapping operations as the Julia graph-edit API: - -- add a model by choosing a scale, a model type, parameter values, and a rate; -- update an existing model's parameter values, scale, or rate from the inspector; -- remove a model from the inspector or from the selected model node; -- add new scales while configuring a model; -- set a mapped input variable from the inspector; -- draw a connection from an output port to an input port to create a mapping; -- map a scalar source value or a vector of values from one or several source scales; -- mark or unmark a variable as [`PreviousTimeStep`](@ref); -- use undo and redo inside the live session. - -The `+` buttons beside variables are suggestions from the current model library: - -- on an input, `+` lists models that can compute that variable as an output; -- on an output, `+` lists models that can consume that variable as an input. - -Clicking a suggested model opens the add-model panel with that model preselected, so you can set its scale, parameters, and rate before adding it. - -## Cycles - -The simulation dependency graph must be acyclic when it runs. The viewer can still compile a non-throwing graph view for cyclic or incomplete mappings, so the editor can show the problem instead of failing immediately. - -When a cycle is detected: - -- cycle edges are drawn in red; -- the cycle call-to-action asks you to choose a break point in the graph; -- clicking the scissors button on a highlighted input wraps that input in [`PreviousTimeStep`](@ref). - -This means the consumer model uses the variable value from the previous timestep, so that current-step dependency is removed and the graph can run again. - -## Mapping code and saving - -The web editor also exposes a dedicated "Mapping code" panel. It shows the current [`ModelMapping`](@ref) as Julia code, and can write that code to a `.jl` file so it can be copied/pasted or reused in scripts. The generated file is intentionally plain Julia: it imports the packages needed by the selected models and defines a top-level `mapping` variable: - -```julia -using PlantSimEngine -using PlantSimEngine.Examples - -mapping = ModelMapping( - # ... -) -``` - -After writing a file once, every successful edit, undo, redo, or recent-file load automatically rewrites that same file. The session also keeps a recovery autosave in the temporary directory. The top-left "Open" button can reopen a mapping script from a file path or from the recent mapping list. Use git or another version-control system for mapping scripts that matter for a simulation workflow. - -The `Status(...)` entries in generated code are rebuilt from the current mapping. Variables computed by models are omitted, even if they were present in the original status, and only variables still required for initialization are kept. - -Because the generated script only defines `mapping`, users can include it directly from a simulation script: - -```julia -include("mapping.generated.jl") -run!(mapping, meteo) -``` - -## Models from external packages - -The editor does not use a separate model registry. It discovers models from the Julia session by traversing the loaded subtype tree under [`AbstractModel`](@ref). - -This means packages become available when you load them: - -```julia -using PlantSimEngine -using PlantSimEngine.Examples -using PlantBiophysics -using HTTP - -session = edit_graph() -``` - -After `using PlantBiophysics`, the editor can list the process and model types that `PlantBiophysics` loaded into the session, provided those models follow the normal PlantSimEngine contract: - -- process abstract types are subtypes of [`AbstractModel`](@ref); -- concrete model structs are subtypes of those process types; -- models define `inputs_` and `outputs_`; -- model parameters are stored in struct fields, with an optional zero-argument constructor for default values. - -Constructor fields become parameter rows in the add-model and edit-model panels. For parametric models, fields that share the same type parameter also share the same type dropdown. The available parameter type choices are `float`, `integer`, `boolean`, `symbol`, `string`, `nothing`, and `julia`. Julia validates the final constructor call; if construction fails, the diagnostic is returned to the editor. - -You can inspect the currently visible library from Julia: - -```@example graph_viewer -available_models(:light_interception) -``` - -If a package is not loaded with `using PackageName`, its model types are not present in the Julia session and the editor cannot list them. - -## Embedding a graph in package documentation - -For package documentation built with Documenter, generate the HTML file before `makedocs` and place it somewhere under `docs/src`, for example `docs/src/www/model_graph.html`: - -```julia -# docs/make.jl -using Documenter -using PlantSimEngine -using YourPackage - -mapping = YourPackage.default_mapping() -write_graph_view(joinpath(@__DIR__, "src", "www", "model_graph.html"), mapping) - -makedocs(; - # ... -) -``` - -Then embed it from a markdown page: - -```html - -``` - -Use the right relative path for the page where the iframe lives and remember that Documenter deploys pretty URLs by default. A page in `docs/src/multiscale/page.md` usually needs `../../www/model_graph.html`; a page at the root of `docs/src/` usually needs `www/model_graph.html`. - -!!! tip - This is the same pattern used to show large package mappings, such as the XPalm dependency graph, directly inside package documentation. The viewer is static, so it works on GitHub Pages without a Julia server. diff --git a/docs/src/step_by_step/implement_a_model.md b/docs/src/step_by_step/implement_a_model.md index afaf888f3..a3f3b6613 100644 --- a/docs/src/step_by_step/implement_a_model.md +++ b/docs/src/step_by_step/implement_a_model.md @@ -30,37 +30,31 @@ Declare the `inputs_` and `outputs_` methods for that model (note the '_', these ```@example usepkg function PlantSimEngine.inputs_(::Beer) - (LAI=-Inf,) + (LAI=Required(Float64),) end function PlantSimEngine.outputs_(::Beer) - (aPPFD=-Inf,) + (aPPFD=0.0,) end ``` Write the [`run!`](@ref) function that operates on a single timestep : ```@example usepkg -function run!(::Beer, models, status, meteo, constants, extras) - status.PPFD = - meteo.Ri_PAR_f * - exp(-models.light_interception.k * status.LAI) * +function PlantSimEngine.run!(model::Beer, status, environment, constants, context) + status.aPPFD = + environment.Ri_PAR_f * + exp(-model.k * status.LAI) * constants.J_to_umol + return nothing end ``` -Determine if parallelization is possible, and which traits to declare : - -```@example usepkg -PlantSimEngine.ObjectDependencyTrait(::Type{<:Beer}) = PlantSimEngine.IsObjectIndependent() -PlantSimEngine.TimeStepDependencyTrait(::Type{<:Beer}) = PlantSimEngine.IsTimeStepIndependent() -``` - And that is all you need to get going, for this example with a single parameter and no interdependencies. The [`@process`](@ref) macro does some boilerplate work described [here](@ref under_the_hood) -Some extra utility functions can also be interesting to implement to make users' lives simpler. See the [Model implementation additional notes](@ref) page for details. +Some context utility functions can also be interesting to implement to make users' lives simpler. See the [Model implementation additional notes](@ref) page for details. If your custom model needs to handle more complex couplings than the simple input/output described in this example, check out the [Coupling more complex models](@ref) page. ## Detailed version @@ -147,87 +141,101 @@ Parameterized types are practical because they let the user choose the type of t ### Inputs and outputs -When implementing a new model, it is necessary to declare what variables will be required, whether provided as an input to our model or computed for every timestep as an output. Input variables will either be initialized by the user in a `Status` object, or provided by another model. Output variables may be global simulation outputs and/or used by other models. +When implementing a new model, it is necessary to declare what variables it +reads and what variables it computes. Every input declaration must say whether +the input is required or has a genuine model default. A required input is +initialized by the user in a `Status` object or bound from another model. A +defaulted input needs neither. Output variables may be retained as simulation +outputs and/or used by other models. In our case, the `Beer` model, computing light interception, has one input variable and one output variable: - Inputs: `:LAI`, the leaf area index (m² m⁻²) - Outputs: `:aPPFD`, the photosynthetic photon flux density (μmol m⁻² s⁻¹) -We declare these inputs/outputs by adding a method for the [`inputs`](@ref) and [`outputs`](@ref) functions. These functions take the type of the model as argument, and return a `NamedTuple` with the names of the variables as keys, and their default values as values: +We declare these inputs/outputs by adding methods for the underscore extension +functions. `inputs_` returns a `NamedTuple` whose values are `Required(T)` or +`Default(value)` declarations. `outputs_` returns a `NamedTuple` whose values +are the initial output state: ```@example usepkg function PlantSimEngine.inputs_(::Beer) - (LAI=-Inf,) + (LAI=Required(Float64),) end function PlantSimEngine.outputs_(::Beer) - (aPPFD=-Inf,) + (aPPFD=0.0,) end ``` -These functions are internal, and end with an "\_". Users instead use [`inputs`](@ref) and [`outputs`](@ref) to query model variables. +`LAI` has no scientifically meaningful fallback, so it is required. If the +model instead had an optional efficiency of `0.8`, it would declare +`efficiency=Default(0.8)`. Do not use sentinel values such as `-Inf` to mean +"required": they are ordinary values and hide the model contract. + +`Required(Float64)` is an expected type, not an initialization value. A model +that supports a broader or parameterized type can declare that type instead. +PlantSimEngine does not convert status values to `Float64`. + +These extension functions end with an "\_". Simulation users instead use +[`inputs`](@ref), [`outputs`](@ref), [`init_variables`](@ref), and +[`Diagnostics.explain_initialization`](@ref) to inspect the contract. ### The run! method -When running a simulation with [`run!`](@ref), each model is run in turn at every timestep, following whatever order was deduced from the `ModelMapping` definition and Status. Each model also has its [`run!`](@ref) method for that purpose that update the simulation's current state, with a slightly different signature. The function takes six arguments: +When running a simulation with [`run!`](@ref), each model is run at its +scheduled timestep, following the dependency order compiled from model +applications, inputs, and manual calls. Each model has its own [`run!`](@ref) +method for updating the current state. The function takes five arguments: ```julia -function run!(::Beer, models, status, meteo, constants, extras) +function PlantSimEngine.run!(model::Beer, status, environment, constants, context) ``` -- the model's type -- models: a [`ModelMapping`](@ref) object, which contains all the models of the simulation +- model: the current model instance, used for dispatch and parameter access. - status: a [`Status`](@ref) object, which contains the current values (*i.e.* state) of the variables for **one** time-step (e.g. the value of the plant LAI at time t) -- meteo: (usually) an `Atmosphere` object, or a row of the meteorological data, which contains the current values of the meteorological variables for **one** time-step (*e.g.* the value of the PAR at time t) +- environment: the sampled model-facing environment for the current target and + timestep. - constants: a `Constants` object, or a `NamedTuple`, which contains the values of the constants for the simulation (*e.g.* the value of the Stefan-Boltzmann constant, unit-conversion constants...) -- extras: any other object you want to pass to your model, mostly for advanced usage, not detailed here +- context: PlantSimEngine's runtime context for hard calls and lifecycle + operations. -A typical [`run!`](@ref) function can therefore make use of simulation constants, input/output variables accessible through the [`Status`](@ref object, or weather data. +A typical [`run!`](@ref) function can therefore use simulation constants, +input/output variables accessible through the [`Status`](@ref) object, or +weather data. -Here is the [`run!`](@ref) implementation of the light interception for a [`ModelMapping`](@ref) component models. Note that the input and output variable are accessed through the [`status`](@ref) argument : +Here is the [`run!`](@ref) implementation of the light interception model. +Note that the input and output variables are accessed through the +`status` argument: ```@example usepkg -function run!(::Beer, models, status, meteo, constants, extras) - status.PPFD = - meteo.Ri_PAR_f * - exp(-models.light_interception.k * status.LAI) * +function PlantSimEngine.run!(model::Beer, status, environment, constants, context) + status.aPPFD = + environment.Ri_PAR_f * + exp(-model.k * status.LAI) * constants.J_to_umol + return nothing end ``` ### Additional notes -To use this model, users will have to make sure that the variables for that model are defined in the [`Status`](@ref) object, the meteorology, and the `Constants` object. +To use this model, simulation users must supply or bind every `Required` status +input. Inputs declared with `Default` are initialized automatically. Required +environment variables and constants must also be available through their +respective contracts. !!! Note [`Status`](@ref) objects contain the current state of the simulation. It is not, by default, possible to make use of earlier variable states, unless a custom model is written for that purpose. -Model parameters are available from the [`ModelMapping`](@ref) that is passed via the `models` argument. Index by the process name, then the parameter name. For example, the `k` parameter of the `Beer` model is found in `models.light_interception.k`. +Model parameters are read directly from the current model instance. For +example, the `k` parameter of the `Beer` model is `model.k`. !!! warning - You need to import all the functions you want to extend, so Julia knows your intention of adding a method to the function from PlantSimEngine, and not defining your own function. To do so, you have to prefix the said functions by the package name, or import them before *e.g.*: `import PlantSimEngine: inputs_, outputs_`. The troubleshooting subsection [Implementing a model: forgetting to import or prefix functions](@ref) showcases output errors that can occur when you forget to prefix. - -### Parallelization traits - -`PlantSimEngine` defines traits to get additional information about the models. At the moment, there are two traits implemented that help the package to know if a model can be run in parallel over space (*i.e.* objects) and/or time (*i.e.* time-steps). - -By default, all models are assumed to be **not** parallelizable over objects and time-steps, because it is the safest default. If your model is parallelizable, you should add the trait to the model. - -For example, if we want to add the trait for parallelization over objects to our `Beer` model, we would do: - -```@example usepkg -PlantSimEngine.ObjectDependencyTrait(::Type{<:Beer}) = PlantSimEngine.IsObjectIndependent() -``` - -And if we want to add the trait for parallelization over time-steps to our `Beer` model, we would do: - -```@example usepkg -PlantSimEngine.TimeStepDependencyTrait(::Type{<:Beer}) = PlantSimEngine.IsTimeStepIndependent() -``` - -!!! note - A model is parallelizable over objects if it does not call another model directly inside its code. Similarly, a model is parallelizable over time-steps if it does not get values from other time-steps directly inside its code. In practice, most of the models are parallelizable one way or another, but it is safer to assume they are not. + Prefix functions you extend with `PlantSimEngine.`, or import them first, + for example `import PlantSimEngine: inputs_, outputs_`. Otherwise Julia + defines an unrelated function in your module instead of adding a method to + PlantSimEngine's function. OK that's it! We now a full new model implementation for the light interception process! Other models might be more complex in terms of what computations they do, or how they couple with other models, but the approach remains the same. @@ -245,4 +253,14 @@ PlantSimEngine.dep(::Fvcb) = (stomatal_conductance=AbstractStomatal_ConductanceM Here we say to PlantSimEngine that the `Fvcb` model needs a model of type `AbstractStomatal_ConductanceModel` in the stomatal conductance process. +This is intentionally process-based because `dep(model)` is a model-author +contract. The model author cannot know which application name a future scenario +will choose for stomatal conductance. In a concrete scenario, users should wire +the selected producer or callee with `application=...` in `ModelSpec(...; inputs=...)` or +`ModelSpec(...; calls=...)` when that application is known: + +```julia +ModelSpec(ParentModel(); name=:parent, calls=(:stomata => One(scale=:Leaf, application=:stomatal_conductance))) +``` + You can read more about hard dependencies in [Coupling more complex models](@ref). diff --git a/docs/src/step_by_step/model_switching.md b/docs/src/step_by_step/model_switching.md index c63a31c8f..10a65fb9f 100644 --- a/docs/src/step_by_step/model_switching.md +++ b/docs/src/step_by_step/model_switching.md @@ -1,102 +1,98 @@ # Model switching -```@setup usepkg -using PlantSimEngine, PlantMeteo, Dates -# Import the examples defined in the `Examples` sub-module +```@setup scene_model_switching +using PlantSimEngine, PlantMeteo, Dates, DataFrames using PlantSimEngine.Examples -meteo_day = read_weather(joinpath(pkgdir(PlantSimEngine), "examples/meteo_day.csv"), duration=Dates.Day) - -models = ModelMapping( - ToyLAIModel(), - Beer(0.5), - ToyRUEGrowthModel(0.2), - status=(TT_cu=cumsum(meteo_day.TT),), +meteo_day = read_weather( + joinpath(pkgdir(PlantSimEngine), "examples/meteo_day.csv"); + duration=Dates.Day, ) -run!(models, meteo_day) -models2 = ModelMapping( - ToyLAIModel(), - Beer(0.5), - ToyAssimGrowthModel(), - status=(TT_cu=cumsum(meteo_day.TT),), -) -run!(models2, meteo_day) ``` -One of the main objective of PlantSimEngine is allowing users to switch between model implementations for a given process **without making any change to the PlantSimEngine codebase**. +One main objective of PlantSimEngine is to let users switch between model +implementations for a process without changing the engine or the other model +kernels. -The package was designed around this idea to make easy changes easy and efficient. Switch models in the [`ModelMapping`](@ref), and call the [`run!`](@ref) function again. No other changes are required if no new variables are introduced. +In the composite-model/object API, the switch happens at the model-application layer: +replace the model inside a `ModelSpec`, keep the same `ModelSpec(...; on=...)` +selector, and keep the same input contract when the replacement model needs the +same variables. -## A first simulation as a starting point +## A first simulation -With a working environment, let's create a [`ModelMapping`](@ref) with several models from the example scripts in the [`examples`](https://github.com/VirtualPlantLab/PlantSimEngine.jl/blob/master/examples/) folder: +This model computes degree-days, LAI, absorbed PAR, and growth on one model +object: -Importing the models from the scripts: +```@example scene_model_switching +function plant_model_with_growth(growth_model; growth_name=:growth) + CompositeModel( + Object(:scene; scale=:Scene, kind=:scene); + applications=( + ModelSpec(ToyDegreeDaysCumulModel(); name=:degree_days, on=One(scale=:Scene), every=Day(1)), -```julia -using PlantSimEngine -# Import the examples defined in the `Examples` sub-module: -using PlantSimEngine.Examples -``` + ModelSpec(ToyLAIModel(); name=:lai, on=One(scale=:Scene), every=Day(1)), -Coupling the models in a [`ModelMapping`](@ref): + ModelSpec(Beer(0.5); name=:light_interception, on=One(scale=:Scene), every=Day(1)), -```@example usepkg -models = ModelMapping( - ToyLAIModel(), - Beer(0.5), - ToyRUEGrowthModel(0.2), - status=(TT_cu=cumsum(meteo_day.TT),), -) + ModelSpec(growth_model; name=growth_name, on=One(scale=:Scene), every=Day(1)), + ), + environment=meteo_day, + ) +end -nothing # hide +rue_scene = plant_model_with_growth(ToyRUEGrowthModel(0.2)) +rue_sim = run!(rue_scene; steps=10) +rue_status = final_state(rue_sim) +(growth_model=:ToyRUEGrowthModel, biomass=rue_status.biomass) ``` -We can the simulation by calling the [`run!`](@ref) function with meteorology data. Here we use an example data set: - -```@example usepkg -meteo_day = read_weather(joinpath(pkgdir(PlantSimEngine), "examples/meteo_day.csv"), duration=Dates.Day) -nothing # hide -``` - -We can now run the simulation: - -```@example usepkg -output_initial = run!(models, meteo_day) -output_initial[1:3,:] # show the first 3 rows of the output +The compiler infers the same-object bindings from the model declarations. The +growth model reads `aPPFD`, which is produced by the light interception model: + +```@example scene_model_switching +select( + DataFrame(Diagnostics.explain_bindings(rue_scene)), + :application_id, + :input, + :source_application_ids, + :origin, + :carrier_kind, +) ``` -## Switching one model in the simulation - -Now what if we want to switch the model that computes growth ? We can do this by simply replacing the model in the [`ModelMapping`](@ref), and PlantSimEngine will automatically update the dependency graph, and adapt the simulation to the new model. - -Let's switch ToyRUEGrowthModel with ToyAssimGrowthModel: - -```@example usepkg -models2 = ModelMapping( - ToyLAIModel(), - Beer(0.5), - ToyAssimGrowthModel(), # This was `ToyRUEGrowthModel(0.2)` before - status=(TT_cu=cumsum(meteo_day.TT),), +## Switching the growth model + +`ToyAssimGrowthModel` implements the same `:growth` process, reads the same +`aPPFD` input, and computes additional outputs such as carbon assimilation and +respiration. The rest of the model does not need to change: + +```@example scene_model_switching +assim_scene = plant_model_with_growth(ToyAssimGrowthModel()) +assim_sim = run!(assim_scene; steps=10) +assim_status = final_state(assim_sim) +( + growth_model=:ToyAssimGrowthModel, + carbon_assimilation=assim_status.carbon_assimilation, + Rm=assim_status.Rm, + biomass=assim_status.biomass, ) - -nothing # hide ``` -ToyAssimGrowthModel is a little bit more complex than `ToyRUEGrowthModel`](@ref), as it also computes the maintenance and growth respiration of the plant, so it has more parameters (we use the default values here). - -We can run a new simulation and see that the simulation's results are different from the previous simulation: +The dependency graph and execution plan are rebuilt from the new application +set: -```@example usepkg -output_updated = run!(models2, meteo_day) -output_updated[1:3,:] # show the first 3 rows of the output +```@example scene_model_switching +select( + DataFrame(Diagnostics.explain_execution_plan(assim_sim)), + :application_id, + :object_ids, + :batch_size, + :inner_loop_dispatch, +) ``` -And that's it! We can switch between models without changing the code, and without having to recompute the dependency graph manually. This is a very powerful feature of PlantSimEngine!💪 - -!!! note - This was a very standard but straightforward example. Sometimes other models will require to add other models to the [`ModelMapping`](@ref). For example ToyAssimGrowthModel could have required a maintenance respiration model. In this case `PlantSimEngine` will indicate what kind of model is required for the simulation. - -!!! note - In our example we replaced what we call a [soft-dependency coupling](@ref hard_dependency_def), but the same principle applies to [hard-dependencies](@ref hard_dependency_def). Hard and Soft dependencies are concepts related to model coupling, and are discussed in more detail in [Standard model coupling](@ref) and [Coupling more complex models](@ref). - +This is the same principle used in larger composite models: switch one process +implementation by replacing one `ModelSpec` or by using an +`ObjectInstance(...; overrides=...)` when the change applies to one plant +instance or one organ. diff --git a/docs/src/step_by_step/parallelization.md b/docs/src/step_by_step/parallelization.md deleted file mode 100644 index 6c590059b..000000000 --- a/docs/src/step_by_step/parallelization.md +++ /dev/null @@ -1,39 +0,0 @@ -## Parallel execution - -!!! note - This page is likely to change and become outdated. In any case, parallel execution only currently applies to single-scale simulations (multi-scale simulations' changing MTGs and extra complexity don't allow for straightforward parallelisation) - -### FLoops - -`PlantSimEngine.jl` uses the [`Floops`](https://juliafolds.github.io/FLoops.jl/stable/) package to run the simulation in sequential, parallel (multi-threaded) or distributed (multi-process) computations over objects, time-steps and independent processes. - -That means that you can provide any compatible executor to the `executor` argument of [`run!`](@ref). By default, [`run!`](@ref) uses the [`ThreadedEx`](https://juliafolds.github.io/FLoops.jl/stable/reference/api/#executor) executor, which is a multi-threaded executor. You can also use the [`SequentialEx`](https://juliafolds.github.io/Transducers.jl/dev/reference/manual/#Transducers.SequentialEx)for sequential execution (non-parallel), or [`DistributedEx`](https://juliafolds.github.io/Transducers.jl/dev/reference/manual/#Transducers.DistributedEx) for distributed computations. - -### Parallel traits - -`PlantSimEngine.jl` uses [Holy traits](https://invenia.github.io/blog/2019/11/06/julialang-features-part-2/) to define if a model can be run in parallel. -See also [Model traits](../model_traits.md) for a full inventory of model-level traits. - -!!! note - A model is executable in parallel over time-steps if it does not uses or set values from other time-steps, and over objects if it does not uses or set values from other objects. - -You can define a model as executable in parallel by defining the traits for time-steps and objects. For example, the ToyLAIModel model from the [examples folder](https://github.com/VirtualPlantLab/PlantSimEngine.jl/tree/main/examples) can be run in parallel over time-steps and objects, so it defines the following traits: - -```julia -PlantSimEngine.TimeStepDependencyTrait(::Type{<:ToyLAIModel}) = PlantSimEngine.IsTimeStepIndependent() -PlantSimEngine.ObjectDependencyTrait(::Type{<:ToyLAIModel}) = PlantSimEngine.IsObjectIndependent() -``` - -By default all models are considered not executable in parallel, because it is the safest option to avoid bugs that are difficult to catch, so you only need to define these traits if it is executable in parallel for them. - -!!! tip - A model that is defined executable in parallel will not necessarily will. First, the user has to pass a parallel `executor` to [`run!`](@ref) (*e.g.* `ThreadedEx`). Second, if the model is coupled with another model that is not executable in parallel, `PlantSimEngine` will run all models in sequential. - -### Further executors - -You can also take a look at [FoldsThreads.jl](https://github.com/JuliaFolds/FoldsThreads.jl) for extra thread-based executors, [FoldsDagger.jl](https://github.com/JuliaFolds/FoldsDagger.jl) for -Transducers.jl-compatible parallel fold implemented using the Dagger.jl framework, and soon [FoldsCUDA.jl](https://github.com/JuliaFolds/FoldsCUDA.jl) for GPU computations -(see [this issue](https://github.com/VirtualPlantLab/PlantSimEngine.jl/issues/22)) and [FoldsKernelAbstractions.jl](https://github.com/JuliaFolds/FoldsKernelAbstractions.jl). You can also take a look at -[ParallelMagics.jl](https://github.com/JuliaFolds/ParallelMagics.jl) to check if automatic parallelization is possible. - -Finally, you can take a look into [Transducers.jl's documentation](https://github.com/JuliaFolds/Transducers.jl) for more information, for example if you don't know what is an executor, you can look into [this explanation](https://juliafolds.github.io/Transducers.jl/stable/explanation/glossary/#glossary-executor). diff --git a/docs/src/step_by_step/quick_and_dirty_examples.md b/docs/src/step_by_step/quick_and_dirty_examples.md index e871e8518..be48327f0 100644 --- a/docs/src/step_by_step/quick_and_dirty_examples.md +++ b/docs/src/step_by_step/quick_and_dirty_examples.md @@ -1,95 +1,121 @@ -# Quick examples +# Quick Examples -This page is meant for people who have set up their environment and just want to copy-paste an example or two, see what the REPL returns and start tinkering. +This page is for copy-paste experimentation with the native composite-model/object API. +If you want a slower explanation of the same ideas, see +[Detailed Walkthrough Of A Simple Simulation](@ref detailed-walkthrough-of-a-simple-simulation). -If you are less comfortable with Julia, or need to set up an environment first, see this page : [Getting started with Julia](@ref). -If you wish for a more detailed rundown of the examples, you can instead have a look at the [step by step](#step_by_step) section, which will go into more detail. +The examples use one model object, but the same pattern scales to plants, +organs, soil objects, and microclimate grids by adding more `Object`s and +selecting them with `ModelSpec(...; on=...)` and `ModelSpec(...; inputs=...)`. -These examples are all for single-scale simulations. For multi-scale modelling tutorials and examples, refer to [this section][#multiscale] +```@setup quick_model_examples +using PlantSimEngine, PlantMeteo, Dates, DataFrames +using PlantSimEngine.Examples -You can find the implementation for all the example models, as well as other toy models [in the examples folder](https://github.com/VirtualPlantLab/PlantSimEngine.jl/tree/main/examples). +meteo_day = read_weather( + joinpath(pkgdir(PlantSimEngine), "examples/meteo_day.csv"); + duration=Dates.Day, +) +``` ```@contents Pages = ["quick_and_dirty_examples.md"] Depth = 2 ``` -## Environment - -These examples assume you have a working Julia environment with PlantSimengine added to it, as well as the other packages used in these examples. Details for getting to that point are provided on the [Installing and running PlantSimEngine](@ref) page. - +## One Light Interception Model -## Example with a single light interception model and a single weather timestep +```@example quick_model_examples +model = CompositeModel( + Beer(0.5); + status=(LAI=2.0,), + environment=meteo_day, +) -```@example usepkg -using PlantSimEngine, PlantMeteo, Dates -using PlantSimEngine.Examples -meteo = Atmosphere(T = 20.0, Wind = 1.0, Rh = 0.65, Ri_PAR_f = 500.0) -leaf = ModelMapping(Beer(0.5), status = (LAI = 2.0,)) -out = run!(leaf, meteo) +sim = run!(model; steps=3, outputs=:all) +first(collect_outputs(sim), 3) ``` -## Coupling the light interception model with a Leaf Area Index model +## LAI And Light Interception -The weather data in this example contains data over 365 days, meaning the simulation will have as many timesteps. - -```@example usepkg -using PlantSimEngine -using PlantMeteo, Dates -using PlantSimEngine.Examples +Here, `ToyDegreeDaysCumulModel` computes cumulative thermal time, `ToyLAIModel` +computes `LAI`, and `Beer` consumes `LAI`. The compiler infers the same-object +value bindings from model inputs and outputs. -meteo_day = read_weather(joinpath(pkgdir(PlantSimEngine), "examples/meteo_day.csv"), duration=Dates.Day) - -models = ModelMapping( +```@example quick_model_examples +lai_scene = CompositeModel( + ToyDegreeDaysCumulModel(), ToyLAIModel(), - Beer(0.5), - status=(TT_cu=cumsum(meteo_day.TT),), + Beer(0.5); + environment=meteo_day, ) -outputs_coupled = run!(models, meteo_day) -outputs_coupled[1:3,:] # show the first 3 rows of the output +lai_sim = run!(lai_scene; steps=5, outputs=:all) +first(collect_outputs(lai_sim), 8) ``` -## Coupling the light interception and Leaf Area Index models with a biomass increment model +Inspect the inferred coupling: +```@example quick_model_examples +select( + DataFrame(Diagnostics.explain_bindings(lai_scene)), + :application_id, + :input, + :source_application_ids, + :carrier_kind, +) +``` -```@example usepkg -using PlantSimEngine -using PlantMeteo, Dates -using PlantSimEngine.Examples +## Add Biomass Growth -meteo_day = read_weather(joinpath(pkgdir(PlantSimEngine), "examples/meteo_day.csv"), duration=Dates.Day) +`ToyRUEGrowthModel` consumes absorbed light and accumulates biomass. No extra +input binding is needed because `Beer` is the unique producer of `aPPFD` on the +same object. -models = ModelMapping( +```@example quick_model_examples +growth_scene = CompositeModel( + ToyDegreeDaysCumulModel(), ToyLAIModel(), Beer(0.5), - ToyRUEGrowthModel(0.2), - status=(TT_cu=cumsum(meteo_day.TT),), + ToyRUEGrowthModel(0.2); + environment=meteo_day, ) -outputs_coupled = run!(models, meteo_day) -outputs_coupled[1:3,:] # show the first 3 rows of the output +growth_sim = run!(growth_scene; steps=5) +growth_status = final_state(growth_sim) +(LAI=growth_status.LAI, aPPFD=growth_status.aPPFD, biomass=growth_status.biomass) ``` -## Example using PlantBioPhysics +## Keep Only One Requested Output -A companion package, PlantBioPhysics, uses PlantSimEngine, and contains other models used in ecophysiological simulations. +For larger simulations, request only the streams you want to keep: -You can have a look at its documentation [here](https://vezy.github.io/PlantBiophysics.jl/stable/) +```@example quick_model_examples +request = OutputRequest( + :Scene, + :biomass; + name=:biomass_daily, + application=:growth, + policy=HoldLast(), + clock=Day(1), +) -Several example simulations are provided there. Here's one taken from [this page](https://vezy.github.io/PlantBiophysics.jl/stable/simulation/first_simulation/) : +requested_sim = run!( + growth_scene; + steps=5, + outputs=request, +) -```julia -using PlantBiophysics, PlantSimEngine +first(collect_outputs(requested_sim, :biomass_daily), 5) +``` -meteo = Atmosphere(T = 22.0, Wind = 0.8333, P = 101.325, Rh = 0.4490995) +## PlantBiophysics -leaf = ModelMapping( - Monteith(), - Fvcb(), - Medlyn(0.03, 12.0), - status = (Ra_SW_f = 13.747, sky_fraction = 1.0, aPPFD = 1500.0, d = 0.03) - ) +The same composite-model/object API can host models from companion packages such as +PlantBiophysics. A typical PlantBiophysics energy-balance setup uses +`ModelSpec(...; calls=...)` so an iterative parent model can manually run photosynthesis and +stomatal-conductance models, then call `run_call!(target; publish=true)` once +for the accepted solution. -out = run!(leaf,meteo) -``` \ No newline at end of file +See [MAESPA-style model example handoff](../dev/maespa_model_handoff.md) for +the current multi-plant energy-balance acceptance example. diff --git a/docs/src/step_by_step/simple_model_coupling.md b/docs/src/step_by_step/simple_model_coupling.md index 179b36d6f..56882d6b2 100644 --- a/docs/src/step_by_step/simple_model_coupling.md +++ b/docs/src/step_by_step/simple_model_coupling.md @@ -1,127 +1,97 @@ # Standard model coupling -```@setup usepkg +```@setup scene_coupling using PlantSimEngine using PlantSimEngine.Examples -using PlantMeteo, Dates +using PlantMeteo, Dates, DataFrames -meteo_day = read_weather(joinpath(pkgdir(PlantSimEngine), "examples/meteo_day.csv"), duration=Dates.Day) -models = ModelMapping( - ToyLAIModel(), - Beer(0.5), - ToyRUEGrowthModel(0.2), - status=(TT_cu=cumsum(meteo_day.TT),), +meteo_day = read_weather( + joinpath(pkgdir(PlantSimEngine), "examples/meteo_day.csv"); + duration=Dates.Day, ) -nothing ``` -## Setting up your environment - -Again, make sure you have a working Julia environment with PlantSimengine added to it, and the other recommended companion packages. Details for getting to that point are provided on the [Installing and running PlantSimEngine](@ref) page. +This page shows the standard coupling case: one model computes a variable that +another model reads. In the composite-model/object API, the user describes model +applications on objects, and the compiler wires the value dependencies. -## ModelMapping - -The [`ModelMapping`](@ref) is a container that holds a list of models, their parameter values, and the status of the variables associated to them. - -If one looks at prior examples, the ModelMappings so far have only contained a single model, whose input variables are initialised in the ModelMapping [`status`](@ref) keyword argument. - -Example models are all taken from the example scripts in the [`examples`](https://github.com/VirtualPlantLab/PlantSimEngine.jl/blob/master/examples/) folder. +## Setting up your environment -Here's a first [`ModelMapping`](@ref) declaration with a light interception model, requiring input Leaf Area Index (LAI): +Make sure you have a working Julia environment with PlantSimEngine and the +recommended companion packages. Details are provided on the +[Installing PlantSimEngine](../prerequisites/installing_plantsimengine.md) +page. -```julia -modellist_coupling_part_1 = ModelMapping(Beer(0.5), status = (LAI = 2.0,)) -``` +## One object and one model -Here's a second one with a Leaf Area Index model, with some example Cumulated Thermal Time as input. (This TT_cu is usually computed from weather data): +A model contains objects. A model application says where a model runs. Here a +light interception model runs on the model object, uses the environment's +daily cadence, and reads `LAI` from that object's status: -```julia -modellist_coupling_part_2 = ModelMapping( - ToyLAIModel(), - status=(TT_cu=1.0:2000.0,), # Pass the cumulated degree-days as input to the model +```@example scene_coupling +light_scene = CompositeModel( + Beer(0.5); + status=(LAI=2.0,), + environment=meteo_day, ) -``` - -## Combining models -Suppose we want our ToyLAIModel to compute the `LAI` for the light interception model. - -We can couple the two models by having them be part of a single [`ModelMapping`](@ref). The `LAI` variable will then be a coupled output computed by the ToyLAIModel, then used as input by `Beer`. It will no longer need to be declared as part of the [`status` . - -This is an instance of what we call a ["soft dependency" coupling](@ref hard_dependency_def): a model depends on another model's outputs for its inputs. +light_sim = run!(light_scene; steps=3, outputs=:all) +first(collect_outputs(light_sim; sink=DataFrame), 3) +``` -Here's a first attempt : +## Coupling two models -```@example usepkg -using PlantSimEngine -# Import the examples defined in the `Examples` sub-module: -using PlantSimEngine.Examples +Suppose we want `ToyLAIModel` to compute `LAI` for `Beer`. Both models can run +on the same object. `ToyLAIModel` produces `LAI`, and `Beer` declares `LAI` as +an input, so the model compiler infers the binding: -# A ModelMapping with two coupled models -models = ModelMapping( +```@example scene_coupling +coupled_scene = CompositeModel( + ToyDegreeDaysCumulModel(), ToyLAIModel(), - Beer(0.5), - status=(TT_cu=1.0:2000.0,), + Beer(0.5); + environment=meteo_day, ) -struct UnexpectedSuccess <: Exception end #hack to enable checking an error without failing docbuild #hide -# see https://github.com/JuliaDocs/Documenter.jl/issues/1420 #hide -try #hide -run!(models) -throw(UnexpectedSuccess()) #hide -catch err; err isa UnexpectedSuccess ? rethrow(err) : showerror(stderr, err); end #hide -``` - -Oops, we get an error related to the weather data, with the detailed output being: -```julia -ERROR: type NamedTuple has no field Ri_PAR_f -Stacktrace: - [1] getindex(mnt::Atmosphere{(), Tuple{}}, i::Symbol) - @ PlantMeteo ~/Path/to/PlantMeteo/src/structs/atmosphere.jl:147 - [2] getcolumn(row::PlantMeteo.TimeStepRow{Atmosphere{(), Tuple{}}}, nm::Symbol) - @ PlantMeteo ~/Path/to/PlantMeteo/src/structs/TimeStepTable.jl:205 - ... +select( + DataFrame(Diagnostics.explain_bindings(coupled_scene)), + :application_id, + :input, + :source_application_ids, + :origin, + :carrier_kind, + :copy_semantics, +) ``` -The `Beer` model requires a specific meteorological parameter. Let's fix that by importing the example weather data : - -```@example usepkg -using PlantSimEngine - -# PlantMeteo and CSV packages are now used -using PlantMeteo, Dates +The `:inferred_same_object` rows are soft dependencies: the consumer input is +provided by another model output. Same-rate local links use live references, so +the timestep loop does not copy values between models. -# Import the examples defined in the `Examples` sub-module: -using PlantSimEngine.Examples - -# Import example weather data -meteo_day = read_weather(joinpath(pkgdir(PlantSimEngine), "examples/meteo_day.csv"), duration=Dates.Day) - -# A ModelMapping with two coupled models -models = ModelMapping( - ToyLAIModel(), - Beer(0.5), - status=(TT_cu=cumsum(meteo_day.TT),), # We can now compute a genuine cumulative thermal time from the weather data -) +Run the coupled model: -# Add the weather data to the run! call -outputs_coupled = run!(models, meteo_day) -outputs_coupled[1:3,:] +```@example scene_coupling +coupled_sim = run!(coupled_scene; steps=5) +coupled_status = final_state(coupled_sim) +(TT_cu=coupled_status.TT_cu, LAI=coupled_status.LAI, aPPFD=coupled_status.aPPFD) ``` -And there you have it. The light interception model made its computations using the Leaf Area Index computed by ToyLAIModel. +## Adding another model -## Further coupling +Additional models are just additional applications. `ToyRUEGrowthModel` +consumes `aPPFD`, which is produced by `Beer`, so the compiler infers another +same-object binding: -Of course, one can keep adding models. Here's an example `ModelMapping` with another model, `ToyRUEGrowthModel`, which computes the carbon biomass increment caused by photosynthesis. - -```julia -models = ModelMapping( +```@example scene_coupling +growth_scene = CompositeModel( + ToyDegreeDaysCumulModel(), ToyLAIModel(), Beer(0.5), - ToyRUEGrowthModel(0.2), - status=(TT_cu=cumsum(meteo_day.TT),), + ToyRUEGrowthModel(0.2); + environment=meteo_day, ) -nothing # hide -``` \ No newline at end of file +growth_sim = run!(growth_scene; steps=5) +growth_status = final_state(growth_sim) +(LAI=growth_status.LAI, aPPFD=growth_status.aPPFD, biomass=growth_status.biomass) +``` diff --git a/docs/src/troubleshooting/common_errors.md b/docs/src/troubleshooting/common_errors.md new file mode 100644 index 000000000..a8df3b70d --- /dev/null +++ b/docs/src/troubleshooting/common_errors.md @@ -0,0 +1,13 @@ +# Common Errors + +A missing-input error means a `Required(T)` input has neither supplied state +nor a producer binding; start with `Diagnostics.explain_initialization`. A +plain-input-declaration error means `inputs_` must replace each literal with +`Required(T)` or `Default(value)`. A cardinality error lists selector matches; +correct the scope or choose the intended `OptionalOne`/`Many` multiplicity. An +ambiguity requires an explicit application/object selector. + +Duplicate-writer errors require either distinct output routing or an explicit +`Updates` order. Cadence errors require fixed `Dates` periods compatible with +the environment base step. Extend package functions as +`PlantSimEngine.run!(...)`, including the package qualification. diff --git a/docs/src/troubleshooting/dependency_cycles.md b/docs/src/troubleshooting/dependency_cycles.md new file mode 100644 index 000000000..312321816 --- /dev/null +++ b/docs/src/troubleshooting/dependency_cycles.md @@ -0,0 +1,29 @@ +# Diagnosing Dependency Cycles + +A same-step value cycle is rejected because no valid execution order exists. +Read the reported application, object, and variable edges. If the science uses +yesterday's value, put `PreviousTimeStep(:variable)` on that input. If the +science requires convergence in the current step, make one parent application +own child trials with `calls`. Otherwise reformulate the coupled equations. + +Application declaration order is not a cycle-resolution mechanism. + +For example, if application `:leaf` reads same-step `water` from `:root` while +`:root` reads same-step `carbon` from `:leaf`, compilation fails before either +kernel runs. If root water scientifically affects tomorrow's leaf carbon, +change only that edge: + +```julia +ModelSpec( + LeafModel(); + inputs=( + PreviousTimeStep(:water) => + One(scale=:Root, application=:root, var=:water), + ), +) +``` + +The receiving object's initial `water` value is used until the first accepted +historical sample exists. If both values must converge within the same step, +do not add a lag: make a parent model own `calls` to the two trial models, +iterate with `publish=false`, and publish each accepted state once. diff --git a/docs/src/troubleshooting/runtime_contracts.md b/docs/src/troubleshooting/runtime_contracts.md new file mode 100644 index 000000000..7e5fda2bd --- /dev/null +++ b/docs/src/troubleshooting/runtime_contracts.md @@ -0,0 +1,12 @@ +# Runtime Contracts And Diagnostics + +Use `Diagnostics.explain_initialization`, `Diagnostics.explain_bindings`, `Diagnostics.explain_calls`, +`Diagnostics.explain_schedule`, `Diagnostics.explain_environment_bindings`, and +`Diagnostics.explain_output_retention` as the supported inspection surface. Do not inspect +compiled internal fields. + +Targets, carriers, calls, writer checks, and schedules refresh after the +application that made a structural change. New objects join applications still +remaining in that timestep; they do not retroactively run earlier applications. +Movement and geometry changes invalidate affected spatial environment bindings. +Accepted streams are append-only. diff --git a/docs/src/troubleshooting_and_testing/implicit_contracts.md b/docs/src/troubleshooting_and_testing/implicit_contracts.md deleted file mode 100644 index b65b4a9da..000000000 --- a/docs/src/troubleshooting_and_testing/implicit_contracts.md +++ /dev/null @@ -1,96 +0,0 @@ -This page summarizes some of the assumptions, coupling constraints and inner workings of PlantSimEngine which may be particular relevant when implementing new models. - -If you are unsure of an implementation subtlety, check this page out to see whether it answers your question. - -```@contents -Pages = ["implicit_contracts.md"] -Depth = 2 -``` - -## Weather data provides the simulation timestep, but models can veer away from it - -The weather data timesteps, whether hourly or daily, provide the pace at which most other models run. - -In XPalm, weather data for most models is provided daily, meaning biomass calculations are also provided daily. - -Many models are considered to be steady-state over that timeframe, but not all : the leaf pruning model pertubes the plant in a non-steady state fashion, for example. Models that require computations over several iterations to stabilise (often part of hard dependencies) might also have a timestep unrelated to the weather data. - -!!! Note - Implicitely, this means any vector variables given as input to the simulation must be consistent with the number of weather timesteps. Providing one weather value but a larger vector variable is an exception : the weather data is replicated over each timestep. (This may be subject to change in the future when support for different timesteps in a single simulation is implemented) - -## Why does my model skip half-hour rows? - -If your meteo has 30-minute rows but a model appears to run hourly, check timestep resolution order: - -1. If model has explicit `TimeStepModel(...)`, it is used. -2. Else if model `timespec(model)` is non-default, it is used. -3. Else model uses meteo `duration`. - -Then compatibility rules apply: - -1. `timestep_hint.required` is enforced for meteo-derived clocks. -2. `timestep_hint.preferred` is informational only. -3. Meteo aggregation/integration happens only for models with coarser effective clocks. - -Common cause: -- model has explicit hourly `TimeStepModel(...)`, so 30-minute rows are intentionally aggregated to hourly runs. - -Quick diagnostics: -- Run `explain_model_specs(mapping_or_sim)` to see, per process, whether runtime clock comes from explicit `ModelSpec`, model `timespec`, or meteo base step. -- Ensure meteo `duration` is present and valid on every row (mandatory when meteo is provided). - -## Weather data must be interpolated prior to simulation - -If your weather data isn't adjusted to conform to a regular timestep, you will need to adjust it to fit that constraint. PlantSimEngine does no interpolation prior to simulation and expects regular weather timesteps. - -## No cyclic dependencies in the simplified dependency graph - -The model dependency graph used for running the simulation is comprised of soft and hard dependency nodes, and the final version only links soft dependency nodes together, and is expected to contain no cycles. - -Any user model coupling which causes a cyclic dependency to occur will require some extra tinkering to run : either design models differently, create a hard dependency with some of the problematic models, or break the cycle by having a variable take the previous timestep's value as input. - -See [Dependency graphs](@ref) and the following subsections for more discussion related to dependency graph constraints. - -Note : Only the previous timestep is accessible in PlantSimEngine without any kind of dedicated model. How to create a model to store more past timesteps of a specific variable is described in the [Tips and workarounds](@ref) page: [Making use of past states in multi-scale simulations](@ref) - -## Hard dependencies need to be declared in the model definition - -Hard dependencies are handled internally by their owning soft dependency model, ie the hard dep's run! function is directly called by the soft dependency's run!. - -The current way in which PlantSimEngine creates its dependency graph requires users to declare what process is required in the hard dependency and which scale it pulls the model and its variables from. - -## Parallelisation opportunities must be part of the model definition - -Traits that indicate that a model is independent or objects need to be part of the model definition. Modelers need to keep this in mind when implementing new models. - -This is currently mostly a concern for single-scale simulations, as multi-scale simulations are not currently parallelised ; a more involved scheduler would need to be implemented when MTGs are modified by models, and to handle more interesting parallelisation opportunities at specific scales. - -There may be new parallelisation features for multi-plant simulations further down the road. - -## Hard dependencies can only have one parent in the dependency graph - -The final dependency graph is comprised only of soft dependency nodes, and is guaranteed to contain no cycles. Hard dependencies are handled internally by their soft dependency ancestor. To avoid any ambiguity in terms of processing order, only one soft dependency node can 'own' a hard dependency And similarly, nested hard dependencies only have a single soft dependency ancestor. - -This is not solely an implementation detail of PlantSimEngine's internal mechanisms ; if your simulation requires complex coupling, you might need to carefully consider how to manage your hard dependencies, or insert an extra intermediate model to simplify things. - -## A model can only be used once per scale - -Similarly, to avoid depedency graph ambiguity (and for simulation cohesion), PlantSimEngine currently assumes a model describing a process only occurs once per scale. - -Model renaming and duplicating works around this assumption. It may change once multi-plant/multi-species features are implemented. - -## No two variables with the same name at the same scale - -This rule avoids potential ambiguity which could then cause both problems in terms of model ordering during the simulation, as well as incorrectly coupling models with the wrong variable. - -A workaround for some of the situations where this occurs is described here : [Having a variable simultaneously as input and output of a model](@ref) - -## Simulation order instability when adding models - -An important aspect to bear in mind is that PlantSimEngine automatically determines an order in which models are run from the dependency graph it generates by coupling models together. - -This order of simulation depends on the way the models link together. If you replace a model by a new set of models, or pass in new variables that create new links between models, you may change the simulation order. - -When iterating and slowly making a simulation more physiologically realistic and complex, it is therefore fully possible that the order in which two models are run is flipped by a user change. - -This design choice implementation -a concession made for ease of use and flexibility when developing a simulation- means that until your set of models is fully stabilized and you know which variables are `PreviousTimestep` and what order models run in, as you expand and change the set you might see differences of execution of one timestep for some models. It isn't a conceptual problem as most models are steady-state, and simulation order is stable for a given set of models, but it does mean PlantSimEngine will be less conveient for some types of simulation. diff --git a/docs/src/troubleshooting_and_testing/plantsimengine_and_julia_troubleshooting.md b/docs/src/troubleshooting_and_testing/plantsimengine_and_julia_troubleshooting.md deleted file mode 100644 index 602045e04..000000000 --- a/docs/src/troubleshooting_and_testing/plantsimengine_and_julia_troubleshooting.md +++ /dev/null @@ -1,515 +0,0 @@ -# Troubleshooting error messages - -PlantSimEngine attempts to be as comfortable and easy to use as possible for the user, and many kinds of user error will be caught and explanations provided to resolve them, but there are still blind spots, as well as syntax errors that will often generate a Julia error (which can be less intuitive to decrypt) rather than a PlantSimEngine error. - -To help people newer to Julia with troubleshooting, here are a few common 'easy-to-make' mistakes with the current API that might not be obvious to interpret, and pointers on how to fix them. - -They are listed by 'nature of error', rather than by error message, so you may need to search the page to find your specific error. - -If you need more help to decode Julia errors, you can find help on the [Julia Discourse forums](https://discourse.julialang.org). -If you need some advice on the FSPM side, the research community has [its own discourse forum](https://fspm.discourse.group). - -If the issue seems PlantSimEngine-related, or you have questions regarding modeling or have suggestions, you can also [file an issue](https://github.com/VirtualPlantLab/PlantSimEngine.jl/issues) on Github. - -```@contents -Pages = ["plantsimengine_and_julia_troubleshooting.md"] -Depth = 3 -``` - -## Tips and workflow - -Some errors are very specific as to their cause, and the PlantSimEngine errors tend to be explicit about which parameter / variable / organ is causing the error, helping narrow down its origin. - -Some generic-looking errors usually do contain some extra information to help focus the debugging hunt. For instance, a dispatch failure on run! caused by some issue with args/kwargs may highlight explicitely indicate which arguments are currently causing conflict. In VSCode, such arguments are highlighted in red (the first and last arguments in the example below): - -```julia -a = 1 -run!(a, simple_mtg, mapping, meteo_day, a) - -ERROR: MethodError: no method matching run!(::Int64, ::Node{NodeMTG, Dict{…}}, ::Dict{String, Tuple{…}}, ::DataFrame, ::Int64) -The function [`run!`](@ref) exists, but no method is defined for this combination of argument types. - -Closest candidates are: - run!(::ToyPlantLeafSurfaceModel, ::Any, ::Any, ::Any, ::Any, ::Any) - @ PlantSimEngine /PlantSimEngine/examples/ToyLeafSurfaceModel.jl:75 - ... -``` - -If you wish to search for a specific error in the current page, copy the part of the description that is not specific to your script, and Ctrl+F it here. In the above example, the generic part would be : -```julia -ERROR: MethodError: no method matching -``` - -## Common Julia errors - -### NamedTuples with a single value require a comma : - -This one is easy to miss. - -Empty NamedTuple objects are initialised with x = NamedTuple(). Ones with more than one variable can be initialised like this : -```julia -a = (var1 = 0, var2 = 0) -``` -or like this : -```julia -a = (var1 = 0, var2 = 0,) -``` -The second comma being optional. - -However, if there is only a single variable, notation has to be : -```julia -a = (var1 = 0,) -``` -The comma is compulsory. If it is forgotten : -```julia -a = (var1 = 0) -``` -the line will be interpreted as setting the variable a to the value var1 is set to, hence a will be an Int64 of value 0. - -This is a liability when writing custom models as some functions work with NamedTuples : -```julia -function PlantSimEngine.inputs_(::HardDepSameScaleAvalModel) - (e2 = -Inf,) -end -``` - -The error returned will likely be a Julia error along the lines of : -```julia -[ERROR: MethodError: no method matching merge(::Float64, ::@NamedTuple{g::Float64}) - -Closest candidates are: -merge(::NamedTuple{()}, ::NamedTuple) -@ Base namedtuple.jl:337 -merge(::NamedTuple{an}, ::NamedTuple{bn}) where {an, bn} -@ Base namedtuple.jl:324 -merge(::NamedTuple, ::NamedTuple, NamedTuple...) -@ Base namedtuple.jl:343 - -Stacktrace: -[1] variables_multiscale(node::PlantSimEngine.HardDependencyNode{…}, organ::String, vars_mapping::Dict{…}, st::@NamedTuple{}) -... -``` -It is sometimes properly detected and explained on PlantSimEngine's side (when passing in tracked_outputs, for instance), but may also occur when declaring statuses. - -### Incorrectly declaring empty inputs or outputs - -The syntax for an empty NamedTuple is `NamedTuple()`. If instead one types `()` or `(,)`an error returned respectively by PlantSimEngine or Julia will be returned. - -## PlantSimEngine user errors - -Most of the following errors occur exclusively in multi-scale simulations, which has a slightly more complex API, but some are common to both single- and multi-scale simulations. - -### ModelMapping: providing a type name instead of a constructed instance - -```julia -m = ModelMapping(day=MyToyModel, week=MyToyModel2) -``` -This line is incorrect and will return -```julia -MethodError: no method matching inputs_(::Type{MyToyDayModel}) -``` - -The correct syntax is (assuming the corresponding constructor exists) : -```julia -m = ModelMapping(day=MyToyModel(), week=MyToyModel2()) -``` - -### Implementing a model: forgetting to import or prefix functions - -When implementing a model, you need to make sure that your implementation is correctly recognised as extending `PlantSimEngine` methods and types, and not writing new independent ones. - -In the following working toy model implementation, note that the `inputs_`, `outputs_` and [`run!`](@ref) function are all prefixed with the module name. If there were hard dependencies to manage, the [`dep`](@ref) function would also be identically prefixed. - -```julia -using PlantSimEngine -@process "toy" verbose = false - -struct ToyToyModel{T} <: AbstractToyModel - internal_constant::T -end - -function PlantSimEngine.inputs_(::ToyToyModel) - (a = -Inf, b = -Inf, c = -Inf) -end - -function PlantSimEngine.outputs_(::ToyToyModel) - (d = -Inf, e = -Inf) -end - - -function PlantSimEngine.run!(m::ToyToyModel, models, status, meteo, constants=nothing, extra_args=nothing) - status.d = m.internal_constant * status.a - status.e += m.internal_constant -end - -meteo = Weather([ - Atmosphere(T=20.0, Wind=1.0, Rh=0.65, Ri_PAR_f=200.0), - Atmosphere(T=20.0, Wind=1.0, Rh=0.65, Ri_PAR_f=200.0), - Atmosphere(T=18.0, Wind=1.0, Rh=0.65, Ri_PAR_f=100.0), -]) - -model = ModelMapping( - ToyToyModel(1), - status = ( a = 1, b = 0, c = 0), -) -to_initialize(model) -sim = PlantSimEngine.run!(model, meteo) -``` - -If you declare these functions without importing them first, or prefixing them with the module name, they will be considered to be part of your current environment, and won't be extending PlantSimEngine methods, which means PlantSimEngine will not be able to properly make use of your functions, and simulations are likely to error, or run incorrectly. - -Forgetting to prefix the [`run!`](@ref) function definition gives the following error : -```julia -ERROR: MethodError: no method matching run!(::ModelMapping{...}, ::TimeStepTable{Atmosphere{…}}) -The function [`run!`](@ref) exists, but no method is defined for this combination of argument types. - -Closest candidates are: - run!(::ToyToyModel, ::Any, ::Any, ::Any, ::Any, ::Any) - @ Main ~/path/to/file.jl:20 -``` - -Forgetting to prefix the `inputs_`or `outputs_` functions for your model might not always generate an error, depending on whether the variables declared in this function are present in your mapping's corresponding Status. - -In cases where they do throw an error, you may get the following kind of output: -```julia -ERROR: type NamedTuple has no field d -Stacktrace: - [1] setproperty!(mnt::Status{(:a, :b, :c), Tuple{…}}, s::Symbol, x::Int64) - @ PlantSimEngine ~/path/to/package/PlantSimEngine/src/component_models/Status.jl:100 - [2] run!(m::ToyToyModel{…}, models::@NamedTuple{…}, status::Status{…}, meteo::PlantMeteo.TimeStepRow{…}, constants::Constants{…}, extra_args::Nothing) - ... -``` - -!!! note - There may be more we can do on our end in the future to make the issue more obvious, but in the meantime it is safest to consistently prefix the methods you need to declare and call with `PlantSimEngine.`, or to explicitely import the functions you wish to extend, *e.g.*: `import PlantSimEngine: inputs_, outputs_`. - -### MultiScaleModel : forgetting a kwarg in the declaration - -A MultiScaleModel requires two kwargs, model and mapped_variables : - -```julia -models = MultiScaleModel( - model=ToyLAIModel(), - mapped_variables=[:TT_cu => :Scene,], - ) -``` - -Forgetting 'model=' : - -```julia -models = MultiScaleModel( - ToyLAIModel(), - mapped_variables=[:TT_cu => :Scene,], - ) -ERROR: MethodError: no method matching MultiScaleModel(::ToyLAIModel; mapped_variables::Vector{Pair{Symbol, String}}) -The type `MultiScaleModel` exists, but no method is defined for this combination of argument types when trying to construct it. - -Closest candidates are: - MultiScaleModel(::T, ::Any) where T<:AbstractModel got unsupported keyword argument "mapped_variables" - @ PlantSimEngine PlantSimEngine/src/mtg/MultiScaleModel.jl:188 - MultiScaleModel(; model, mapped_variables) - @ PlantSimEngine PlantSimEngine/src/mtg/MultiScaleModel.jl:191 -``` - -Forgetting 'mapped_variables=' : -```julia -models = MultiScaleModel( - model=ToyLAIModel(), - [:TT_cu => :Scene,], - ) - -ERROR: MethodError: no method matching MultiScaleModel(::Vector{Pair{Symbol, String}}; model::ToyLAIModel) -The type `MultiScaleModel` exists, but no method is defined for this combination of argument types when trying to construct it. - -Closest candidates are: - MultiScaleModel(; model, mapping) - @ PlantSimEngine PlantSimEngine/src/mtg/MultiScaleModel.jl:191 - MultiScaleModel(::T, ::Any) where T<:AbstractModel got unsupported keyword argument "model" -``` - -The message 'got unsupported keyword argument "model"' can be misleading, as in the error in this case is not that a kwarg is *unsupported*, but rather that a keyword argument is *missing*. - -### MultiScaleModel : variable not defined in Module - -A possible cause for this error is that a variable was declared instead of a symbol in a mapping for a multiscale model : - -```julia -mapping = ModelMapping(:Scale => -MultiScaleModel( - model = ToyModel(), - mapped_variables = [should_be_symbol => :Other_Scale] # should_be_symbol is a variable, likely not found in the current module -), -... -), -``` - -Here's the correct version : -```julia -mapping = ModelMapping(:Scale => -MultiScaleModel( - model = ToyModel(), - mapped_variables=[:should_be_symbol => :Other_Scale] # should_be_symbol is now a symbol -), -... -), -``` - -### Kwarg and arg parameter issues when calling run! - -There are, unfortunately, multiple ways of passing in arguments to the run! functions that will confuse dynamic dispatch. Some of it is due to imperfections in type declarations on PlantSimEngine's end and may be improved upon in the future. - -Here are a few examples when modifying the usual multiscale run! call in this working example: - -```julia -meteo_day = read_weather(joinpath(pkgdir(PlantSimEngine), "examples/meteo_day.csv"), duration=Dates.Day) -mtg = Node(MultiScaleTreeGraph.NodeMTG("/", :Plant, 1, 1)) -var1 = 15.0 - -mapping = ModelMapping( - :Leaf => ( - Process1Model(1.0), - Process2Model(), - Process3Model(), - Status(var1=var1,) - ) -) - -outs = Dict( - :Leaf => (:var1,), # :non_existing_variable is not computed by any model -) - -run!(mtg, mapping, meteo_day, PlantMeteo.Constants(), tracked_outputs=outs) -``` - -The exact signature is this : -```julia -function run!( - object::MultiScaleTreeGraph.Node, - mapping::ModelMapping, - meteo=nothing, - constants=PlantMeteo.Constants(), - extra=nothing; - nsteps=nothing, - tracked_outputs=nothing, - check=true, - executor=ThreadedEx() -``` - -Arguments after the mtg and mapping all have a default value and are optional, and arguments after the ';' delimiter are kwargs and need to be named. - -If one forgets the mtg, a flaw in the way run! is defined will lead to this error : -```julia -run!(mapping, meteo_day, PlantMeteo.Constants(), tracked_outputs=outs) - -ERROR: MethodError: no method matching check_dimensions(::PlantSimEngine.TableAlike, ::Tuple{…}, ::DataFrame) -The function `check_dimensions` exists, but no method is defined for this combination of argument types. - -Closest candidates are: - check_dimensions(::Any, ::Any) - @ PlantSimEngine PlantSimEngine/src/checks/dimensions.jl:43 - ... -``` - -If one forgets the necessary 'tracked_outputs=' in the definition, outs will be interpreted as the 'extra' arg instead of a kwarg. 'extra' usually defaults to nothing, and is reserved in multiscale mode, leading to the following error : - -```julia -run!(mtg, mapping, meteo_day, PlantMeteo.Constants(), outs) - -ERROR: Extra parameters are not allowed for the simulation of an MTG (already used for statuses). -Stacktrace: - [1] error(s::String) - @ Base ./error.jl:35 - [2] run!(::PlantSimEngine.TreeAlike, object::PlantSimEngine.GraphSimulation{…}, meteo::DataFrames.DataFrameRows{…}, constants::Constants{…}, extra::Dict{…}; tracked_outputs::Nothing, check::Bool, executor::ThreadedEx{…}) -``` - -In case of a more generic error that returns a -For example, if one does the opposite and adds a non-existent kwarg, the generic dispatch failure has some more specific information : -`got unsupported keyword argument "constants"` - -```julia -run!(mtg, mapping, meteo_day, constants=PlantMeteo.Constants(), tracked_outputs=outs) - -ERROR: MethodError: no method matching run!(::Node{…}, ::Dict{…}, ::DataFrame, ::Dict{…}, ::Nothing; constants::Constants{…}) -This error has been manually thrown, explicitly, so the method may exist but be intentionally marked as unimplemented. - -Closest candidates are: - run!(::Node, ::Dict{String}, ::Any, ::Any, ::Any; nsteps, tracked_outputs, check, executor) got unsupported keyword argument "constants" -``` - -### Hard dependency process not present in the mapping - -Another weakness in the current error checking leads to an unclear Julia error if a model A is present in a mapping and has a hard dependency on a model B, but B is absent from the mapping. - -In the following example, A corresponds to Process3Model, which requires a model B implementing 'Process2Model' and referred to as 'process2'. -Looking at the source code for Process3Model, the hard dependency is declared here : -```julia -PlantSimEngine.dep(::Process3Model) = (process2=Process2Model,) -``` - -However, the model provided in the examples, Process2Model is absent from the mapping : - -```julia -simple_mtg = Node(MultiScaleTreeGraph.NodeMTG("/", :Plant, 1, 1)) -mapping = ModelMapping( - :Leaf => ( - Process3Model(), - Status(var5=15.0,) - ) -) -outs = Dict( - :Leaf => (:var5,), -) -run!(simple_mtg, mapping, meteo_day, tracked_outputs=outs) - -ERROR: type NamedTuple has no field process2 -Stacktrace: - [1] getproperty(x::@NamedTuple{process3::Process3Model}, f::Symbol) - @ Base ./Base.jl:49 - [2] run!(::Process3Model, models::@NamedTuple{…}, status::Status{…}, meteo::DataFrameRow{…}, constants::Constants{…}, extra::PlantSimEngine.GraphSimulation{…}) - ... -``` - -The fix is to add Process2Model() -or another model for the same process- to the mapping. - -### Status API ambiguity - -One current problem with PlantSimEngine's API is that declaring a simulation's Status or Statuses differs between single- and multi-scale. - -Returning to the example in [Implementing a model: forgetting to import or prefix functions](@ref), the single-scale mapping status was declared like this: - -```julia -model = ModelMapping( - ToyToyModel(1), - status = ( a = 1, b = 0, c = 0), -) -``` -If instead you replace `status = ...`with the multi-scale declaration: `Status(...)`, you will get the following error: - -```julia -ERROR: MethodError: no method matching process(::Status{(:a, :b, :c), Tuple{Base.RefValue{Int64}, Base.RefValue{Int64}, Base.RefValue{Int64}}}) -The function `process` exists, but no method is defined for this combination of argument types. - -Closest candidates are: - process(::Pair{Symbol, A}) where A<:AbstractModel - @ PlantSimEngine ~/path/to/pkg/PlantSimEngine/src/Abstract_model_structs.jl:16 - process(::A) where A<:AbstractModel - @ PlantSimEngine ~/path/to/pkg/PlantSimEngine/src/Abstract_model_structs.jl:13 - -Stacktrace: - [1] (::PlantSimEngine.var"#5#6")(i::Status{(:a, :b, :c), Tuple{Base.RefValue{…}, Base.RefValue{…}, Base.RefValue{…}}}) - @ PlantSimEngine ./none:0 - [2] iterate -``` - -If you do the opposite in a multi-scale simulation by replacing the necessary `Status(...)` with `status = ...`, you may get an `ERROR: syntax: invalid named tuple element` error. Here's some output when tinkering with the Toy Plant tutorial's mapping: - -```julia -ERROR: syntax: invalid named tuple element "MultiScaleModel(...)" around /path/to/Pkg/PlantSimEngine/examples/ToyMultiScalePlantTutorial/ToyPlantSimulation3.jl:196 -Stacktrace: - [1] top-level scope - @ ~/path/to/pkg/PlantSimEngine/examples/ToyMultiScalePlantTutorial/ToyPlantSimulation3.jl:196 -``` -or -```julia -ERROR: syntax: invalid named tuple element "ToyRootGrowthModel(50, 10)" around /path/to/Pkg/PlantSimEngine/examples/ToyMultiScalePlantTutorial/ToyPlantSimulation3.jl:196 -Stacktrace: - [1] top-level scope - @ ~/path/to/Pkg/PlantSimEngine/examples/ToyMultiScalePlantTutorial/ToyPlantSimulation3.jl:196 -``` - -## Forgetting to declare a scale in the mapping but having variables point to it - -If there is a need to collect variables at two different scales, and one scale is completely absent from the mapping, the error currently occurs on the Julia side : - -```julia -# No models at the E3 scale in the mapping ! - -:E2 => ( - MultiScaleModel( - model = HardDepSameScaleEchelle2Model(), - mapped_variables=[:c => :E1 => :c, :e3 => :E3 => :e3, :f3 => :E3 => :f3,], - ), - ), - -Exception has occurred: KeyError -* -KeyError: key :E3 not found -Stacktrace: -[1] hard_dependencies(mapping::Dict{String, Tuple{Any, Any}}; verbose::Bool) -@ PlantSimEngine ......./src/dependencies/hard_dependencies.jl:175 -... -``` - -### Parenthesis placement when declaring a mapping - -An unintuitive error encountered in the past when defining a mapping : - -```julia -ERROR: ArgumentError: AbstractDict(kv): kv needs to be an iterator of 2-tuples or pairs -``` - -may occur when forgetting the parenthesis after '=>' in a mapping declaration, and combining it with another parenthesis error. - -```julia -mapping = ModelMapping( "Scale" => (ToyAssimGrowthModel(0.0, 0.0, 0.0), ToyCAllocationModel(), Status( TT_cu=Vector(cumsum(meteo_day.TT))), ), ) -``` - -Other errors such as: - -```julia -ERROR: MethodError: no method matching Dict(::Pair{String, ToyAssimGrowthModel{Float64}}, ::ToyCAllocationModel, ::Status{(:TT_cu,), Tuple{Base.RefValue{…}}}) -The type `Dict` exists, but no method is defined for this combination of argument types when trying to construct it. - -Closest candidates are: - Dict(::Pair{K, V}...) where {K, V} -``` - -often indicate a likely syntax error somewhere in the mapping definition. - -### Empty status vectors in multi-scale simulations - -This situation won't trigger an error. Unexpectedly empty vectors can be returned as outputs if you happen to forget to a node at the corresponding scale in the MTG, and no organ creation occurs for that node. - -Here's an example taken from the [Converting a single-scale simulation to multi-scale](@ref) page. It was modified by removing the :Plant node in the dummy MTG passed into the [`run!`](@ref)function. Without that :Plant node, only :Scene-scale models can run initially, and since no nodes are created, :Plant-scale models will never be run. - -```julia -PlantSimEngine.@process "tt_cu" verbose = false - -struct ToyTt_CuModel <: AbstractTt_CuModel end - -function PlantSimEngine.run!(::ToyTt_CuModel, models, status, meteo, constants, extra=nothing) - status.TT_cu += - meteo.TT -end - -function PlantSimEngine.inputs_(::ToyTt_CuModel) - NamedTuple() # No input variables -end - -function PlantSimEngine.outputs_(::ToyTt_CuModel) - (TT_cu=-Inf,) -end - -mapping_multiscale = ModelMapping( - :Scene => ToyTt_CuModel(), - :Plant => ( - MultiScaleModel( - model=ToyLAIModel(), - mapped_variables=[ - :TT_cu => :Scene, - ], - ), - Beer(0.5), - ToyRUEGrowthModel(0.2), - ), -) - -mtg_multiscale = MultiScaleTreeGraph.Node(MultiScaleTreeGraph.NodeMTG("/", :Plant, 0, 0),) -#plant = MultiScaleTreeGraph.Node(mtg_multiscale, MultiScaleTreeGraph.NodeMTG("+", :Plant, 1, 1)) - -out_multiscale = run!(mtg_multiscale, mapping_multiscale, meteo_day) - -out_multiscale[:Plant][:LAI] -``` - -In the above code, uncommenting the second line will add a :Plant node to the MTG, and the simulation will then behave as intuitively expected. diff --git a/docs/src/troubleshooting_and_testing/tips_and_workarounds.md b/docs/src/troubleshooting_and_testing/tips_and_workarounds.md deleted file mode 100644 index 27f19a067..000000000 --- a/docs/src/troubleshooting_and_testing/tips_and_workarounds.md +++ /dev/null @@ -1,112 +0,0 @@ -# Tips and workarounds - -## PlantSimEngine is actively being developed - -PlantSimEngine, despite the somewhat abstract codebase and generic simulation ambitions, is quite grounded in reality. There IS a desire to accomodate for a wide range of possible simulations, without constraining the user too much, but most features are developed on an as-needed basis, and grow out of necessity, partly from the requirements of an increasingly complex and refined implementation of an oil palm model, [XPalm](https://github.com/PalmStudio/XPalm.jl). - -Since the oil palm model is actively being developed, and some features aren't ready in PlantSimEngine, or require a lot of rewriting that we're not certain would be worth it (especially if it ends up constraining the codebase or what the user can do), some workarounds and shortcuts are occasionally used to circumvent a limitation. - -There are also a couple of features that are quick hacks or that are meant for quick and dirty prototyping, not for production. - -We'll list a few of them here, and will likely add some entry in the future listing some built-in limitations or implicit expectations of the package. - -```@contents -Pages = ["tips_and_workarounds.md"] -Depth = 2 -``` - -## Making use of past states in multi-scale simulations - -It is possible to make use of the value of a variable in the past simulation timestep via the [`PreviousTimeStep`](@ref) mechanism in the mapping API (In fact, as mentioned elsewhere, it is the default way to break undesirable cyclic dependencies that can come up when coupling models, see : [Avoiding cyclic dependencies](@ref)). - -However, it is not possible to go beyond that through the mapping API. Something like `PreviousTimeStep(PreviousTimeStep(PreviousTimeStep(:carbon_biomass)))` is not supported. Don't do that. - -One way to access prior variable states is simply to write an ad hoc model that stores a few values into an array or however many variables you might need, which you can then update every timestep and feed into other models that might need it. - -## Having a variable simultaneously as input and output of a model - -One current limitation of `PlantSimEngine` that can be occasionally awkward is that using the same variable name as input and output in a single model is unsupported. - -(On a related note : it is not possible to have two variables with the same name *in the same scale*. They are considered as the same variable.) - -The reason being that it is usually impossible to automatically determine how the coupling is supposed to work out, when other dependencies latch onto such a model. The user would have to explicitely declare some order of simulation between several models, and some amount of programmer work would also be necessary to implement that extra API feature into `PlantSimEngine`. - -We haven't found an approach that was fully satisfactory from both a code simplicity and an API convenience POV. Especially when prototyping and adding in new models, as that might require redeclaring the simulation order for those specific variables. - -There are two workarounds : - -- One possibly awkward approach is to rename one of the variables. It is not ideal, of course, as it means you might not be able to use a predefined model 'out of the box', but it does not have any of the tradeoffs and constraints mentioned above. - -- In many other situations one can work with what PlantSimEngine already provides. - -For example, one model in [XPalm.jl](https://github.com/PalmStudio/XPalm.jl/blob/main/src/plant/phytomer/leaves/leaf_pruning.jl) handles leaf pruning, affecting biomass. A straightforward implementation would be to have a `leaf_biomass` variable as both input and output. The workaround is to instead output a variable `leaf_biomass_pruning_loss` and to have that as input in the next timestep to compute the new leaf biomass. - -[Part 3](../multiscale/multiscale_example_3.md) of the Toy Plant tutorial does something similar for its carbon stock. The `carbon_stock` variable indicates how much carbon is available for root and internode growth, but instead of updating it and passing it along after the root growth decision model decided whether or not roots should be added, that model computes a `carbon_stock_updated_after_roots` which is then used by the internode growth model. - -This change in design avoids model order ambiguity and also improves readability, and makes sense in terms of PlantSimEngine's philosophy. - -## [Multiscale : passing in a vector in a mapping status at a specific scale](@id multiscale_vector) - -!!! note - This section is a little more advanced and not recommended for beginners - -You may have noticed that sometimes a vector (1-dimensional array) variable is passed into the [`status`](@ref) component of a [`ModelMapping`](@ref) in documentation examples (An example here with cumulative thermal time : [Model switching](@ref)). - -This is practical for simple simulations, or when quickly prototyping, to avoid having to write a model specifically for it. Whatever models make use of that variable are provided with one element corresponding to the current timestep every iteration. - -In multi-scale simulations, this feature is also supported, though not part of the main API. The way outputs and statuses work is a little different, so that little convenience feature is not as straightforward. - -It remains a convenience path for prototyping, and it is still not tested for -more complex interactions, so it may interact badly with variables that are -mapped to different scales or in unusual dependency couplings. - -The way to use this is as follows: - -Call the function `replace_mapping_status_vectors_with_generated_models(mapping_with_vectors_in_status, timestep_model_organ_level, nsteps)`on your mapping. - -It will parse your mapping, generate custom models to store and feed the vector values each timestep, and return the new mapping you can then use for your simulation. It also slips in a couple of internal models that provide the timestep index to these models (so note that symbols `:current_timestep` and `:next_timestep` will be declared for that mapping). You can decide which scale/organ level you want those models to be in via the `timestep_model_organ_level`parameter. `nsteps` is used as a sanity check, and expects you to provide the amount of simulation timesteps. - -!!! warning - Only subtypes of AbstractVector present in statuses will be affected. In some cases, meteo values might need a small conversion. For instance : - ``` - meteo_day = read_weather(joinpath(pkgdir(PlantSimEngine), "examples/meteo_day.csv"), duration=Dates.Day) - status(TT_cu=cumsum(meteo_day.TT),)``` - - cumsum(meteo_day.TT) actually returns a CSV.SentinelArray.ChainedVectors{T, Vector{T}}, which is not a subtype of AbstractVector. - Replacing it with Vector(cumsum(meteo_day.TT)) will provide an adequate type. - -Here's an example usage, fixing the first attempt at [Converting a single-scale simulation to multi-scale](@ref): - -```julia -using PlantSimEngine -using PlantSimEngine.Examples -using PlantMeteo, Dates -meteo_day = read_weather(joinpath(pkgdir(PlantSimEngine), "examples/meteo_day.csv"), duration=Dates.Day) - -# Direct translation of the single-scale simulation -mapping_pseudo_multiscale = ModelMapping( -:Plant => ( - ToyLAIModel(), - Beer(0.5), - ToyRUEGrowthModel(0.2), - Status(TT_cu=cumsum(meteo_day.TT),) - ), -) - -mtg = MultiScaleTreeGraph.Node(MultiScaleTreeGraph.NodeMTG("/", :Plant, 1, 0),) - -# will generate an error as vectors can't be directly passed into a Status in multi-scale simulations -#out_pseudo_multiscale_error = run!(mtg, mapping_pseudo_multiscale, meteo_day) - -mapping_pseudo_multiscale_adjusted = PlantSimEngine.replace_mapping_status_vectors_with_generated_models(mapping_pseudo_multiscale, :Plant, PlantSimEngine.get_nsteps(meteo_day)) - -out_pseudo_multiscale_successful = run!(mtg, mapping_pseudo_multiscale_adjusted, meteo_day) - -``` - - -This feature is likely to break in simulations that make use of planned future features (such as mixing models with different timesteps), without guarantee of a fix on a short notice. Again, bear in mind it is mostly a convenient shortcut for prototyping, when doing multi-scale simulations. - -## Cyclic dependencies in single-scale simulations - -Cyclic dependencies can happen in single-scale simulations, but the PreviousTimestep feature currently isn't available. Hard dependencies are one way to deal with them, creating a multi-scale simulation with a single effective scale is also an option. diff --git a/docs/src/tutorials/growing_plant/part1_growth.md b/docs/src/tutorials/growing_plant/part1_growth.md new file mode 100644 index 000000000..37bdc6418 --- /dev/null +++ b/docs/src/tutorials/growing_plant/part1_growth.md @@ -0,0 +1,33 @@ +# Growing A Plant CompositeModel + +Begin with a plant object and leaf objects whose carbon production is gathered +by a plant application through `Many(scale=:Leaf, within=Subtree())`. A growth +model calls `register_object!` after its carbon or thermal threshold is met. + +Structural changes refresh compiled targets after the application that made +the change. A new leaf may run applications that remain later in the same +timestep, but it never retroactively runs applications that already completed. +When callers mutate structure between `step!` calls, refresh occurs before the +next step. + +Build the initial registry explicitly so ownership remains visible: + +```julia +model = CompositeModel( + Object(:plant; scale=:Plant, status=Status(carbon=0.0)), + Object(:leaf_1; scale=:Leaf, parent=:plant, status=Status(area=1.0)); + applications=(leaf_application, plant_balance, growth_application), + environment=weather, +) +``` + +The plant balance gathers leaf production with +`Many(scale=:Leaf, within=Subtree())`. The growth kernel obtains the live model +with `runtime_model(context)`, checks its carbon and thermal thresholds, creates +a fully initialized `Object`, and calls `register_object!`. It should deduct +the construction cost exactly once before registration. + +After each step, assert both biology and structure: remaining plant carbon, +the number of leaf objects, each new leaf's parent, and accepted historical +outputs. `Diagnostics.explain_applications` should show that the new leaf is absent +during its creation step and present after the between-step refresh. diff --git a/docs/src/tutorials/growing_plant/part2_roots_water.md b/docs/src/tutorials/growing_plant/part2_roots_water.md new file mode 100644 index 000000000..9ab2f3a90 --- /dev/null +++ b/docs/src/tutorials/growing_plant/part2_roots_water.md @@ -0,0 +1,37 @@ +# Adding Roots And Water + +Add root objects and gather absorption through a plant-local `Many` selector. +Keep shared carbon and water stocks on the plant, while leaf and root state +remains object-local. Environment precipitation is an environment input; root +creation is an explicit `register_object!` operation with initialized status. + +When several plants share one soil object, select it explicitly with a +model-wide `One` selector rather than relying on traversal order. + +Keep stocks at the scale that owns conservation. A root model may publish an +absorption rate per root, while the plant model integrates all root rates and +updates one plant water stock. A soil model owns soil water; plants read it +through an explicit model-wide selector. This avoids copying one stock into +every organ and makes duplicate writers visible. + +```julia +ModelSpec( + PlantWaterModel(); + inputs=( + :root_uptake => Many( + scale=:Root, within=Subtree(), application=:root_absorption, + var=:uptake, policy=Integrate(), window=Day(1), + ), + :soil_water => One( + scale=:Soil, within=SceneScope(), application=:soil_water, + var=:water, + ), + ), +) +``` + +Precipitation, temperature, and radiation remain environment variables, not +ordinary object outputs. Use `Environment(sources=...)` when provider column +names differ from model-facing names. When growth creates a root, initialize +all required root status values before `register_object!`; verify the next +timestep's carrier with `Diagnostics.input_value` or `Diagnostics.explain_bindings`. diff --git a/docs/src/tutorials/growing_plant/part3_debugging.md b/docs/src/tutorials/growing_plant/part3_debugging.md new file mode 100644 index 000000000..1c4c6bbf7 --- /dev/null +++ b/docs/src/tutorials/growing_plant/part3_debugging.md @@ -0,0 +1,32 @@ +# Debugging Growth And Resource Ordering + +If an organ appears to spend resources before it exists, inspect activation +timing and the compiled schedule. If two models intentionally update one stock, +declare `Updates(:stock; after=:producer)`. If a parent must test several child +states before accepting one, use `calls` and publish only the accepted call. + +For cycles, choose a scientific meaning: lag one edge with +`PreviousTimeStep`, put convergence under a parent-owned hard call, or +reformulate the equations. Do not resolve a cycle by incidental application +ordering. + +Use this debugging order: + +1. `Diagnostics.explain_initialization(model)` for missing state or environment values. +2. `Diagnostics.explain_bindings(model)` for source scope and multiplicity. +3. `Diagnostics.explain_writers(model)` for competing canonical outputs. +4. `Diagnostics.explain_calls(model)` for call-only targets and target cardinality. +5. `Diagnostics.explain_schedule(model)` for cadence and root ordering. +6. `Diagnostics.explain_outputs(simulation)` after execution for publication history. + +A trial call must not mutate accepted output history or scatter mutable +environment outputs. Nested trials inherit the outer publication decision. +Convergence and failure policy belongs to the parent model: it decides the +iteration limit, tolerance, fallback, and whether any state is accepted. + +Structural mutation is also transactional at the timestep boundary. A new +organ is registered immediately in the model registry but does not recursively +run during the kernel that created it. Before the next timestep, compilation +refreshes targets, carriers, calls, writer validation, schedules, and requested +outputs. Geometry-only movement refreshes only affected spatial bindings where +possible. diff --git a/docs/src/working_with_data/fitting.md b/docs/src/working_with_data/fitting.md index 0232acb21..1473f1625 100644 --- a/docs/src/working_with_data/fitting.md +++ b/docs/src/working_with_data/fitting.md @@ -1,76 +1,57 @@ -# Parameter fitting +# Parameter Fitting -```@setup usepkg -using PlantSimEngine, PlantMeteo, Dates, Statistics, DataFrames -using PlantSimEngine.Examples - -meteo = Atmosphere(T=20.0, Wind=1.0, P=101.3, Rh=0.65, Ri_PAR_f=300.0) -m = ModelMapping(Beer(0.6), status=(LAI=2.0,)) -run!(m, meteo) - -df = DataFrame(aPPFD=m[:aPPFD][1], LAI=m.status.LAI[1], Ri_PAR_f=meteo.Ri_PAR_f[1]) -``` - -## The fit method - -Models are often calibrated using data, but the calibration process is not always the same depending on the model, and the data available to the user. - -`PlantSimEngine` defines a generic [`fit`](@ref) function that allows modelers provide a fitting algorithm for their model, and for users to use this method to calibrate the model using data. - -The function does nothing in this package, it is only defined to provide a common interface for all the models. It is up to the modeler to implement the method for their model. - -The method is implemented as a function with the following design pattern: the call to the function should take the model type as the first argument (T::Type{<:AbstractModel}), the data as the second argument (as a `Table.jl` compatible type, such as `DataFrame`), and any more information as keyword arguments, *e.g.* constants or parameters initializations with default values when necessary. - -## Example with Beer - -The example script (see `src/examples/Beer.jl`) that implements the `Beer` model provides an example of how to implement the `fit` method for a model: +`PlantSimEngine.Evaluation.fit` is the shared interface for model-specific +calibration. +Model packages implement a method whose first argument is the model type and +whose second argument is Tables.jl-compatible observations. ```julia -function PlantSimEngine.fit(::Type{Beer}, df; J_to_umol=PlantMeteo.Constants().J_to_umol) - k = Statistics.mean(log.(df.Ri_PAR_f ./ (df.PPFD ./ J_to_umol)) ./ df.LAI) +function PlantSimEngine.Evaluation.fit( + ::Type{Beer}, + data; + J_to_umol=PlantMeteo.Constants().J_to_umol, +) + k = Statistics.mean( + log.(data.Ri_PAR_f ./ (data.aPPFD ./ J_to_umol)) ./ data.LAI, + ) return (k=k,) end ``` -The function takes a `Beer` type as the first argument, the data as a `Tables.jl` -compatible type, such as a `DataFrame` as the second argument, and the `J_to_umol` constant as a keyword argument, which is used to convert between μ mol m⁻² s⁻¹ and J m⁻² s⁻¹. - -`df` should contain the columns `PPFD` (μ mol m⁻² s⁻¹), `LAI` (m² m⁻²) and `Ri_PAR_f` (W m⁻²). The function then computes `k` based on these values, and returns it as a `NamedTuple` of the form `(parameter_name=parameter_value,)`. - -Here's an example of how to use the `fit` method: +The result should be a `NamedTuple` of fitted parameters. -Importing the script first: - -```julia -using PlantSimEngine, PlantMeteo, Dates, DataFrames, Statistics -# Import the examples defined in the `Examples` sub-module: +```@example fitting +using PlantSimEngine, PlantMeteo, Dates, DataFrames using PlantSimEngine.Examples -``` - -Defining the meteo data: - -```@example usepkg -meteo = Atmosphere(T=20.0, Wind=1.0, P=101.3, Rh=0.65, Ri_PAR_f=300.0) -``` - -Computing the `PPFD` values from the `Ri_PAR_f` values using the `Beer` model (with `k=0.6`): - -```@example usepkg -m = ModelMapping(Beer(0.6), status=(LAI=2.0,)) -run!(m, meteo) -``` - -Now we can define the "data" to fit the model using the simulated `PPFD` values: - -```@example usepkg -df = DataFrame(aPPFD=m[:aPPFD][1], LAI=m.status.LAI[1], Ri_PAR_f=meteo.Ri_PAR_f[1]) -``` - -And finally we can fit the model using the `fit` method: -```@example usepkg -fit(Beer, df) +meteo = Atmosphere( + T=20.0, + Wind=1.0, + P=101.3, + Rh=0.65, + Ri_PAR_f=300.0, + duration=Hour(1), +) + +model = CompositeModel( + Beer(0.6); + status=(LAI=2.0,), + id=:leaf, + scale=:Leaf, + environment=meteo, +) + +simulation = run!(model) +leaf = final_state(simulation, One(scale=:Leaf)) +data = DataFrame( + aPPFD=[leaf.aPPFD], + LAI=[leaf.LAI], + Ri_PAR_f=[meteo.Ri_PAR_f[1]], +) + +PlantSimEngine.Evaluation.fit(Beer, data) ``` -!!! note - This is a dummy example to show that the fitting method works. A real application would fit the parameter values on the data directly. \ No newline at end of file +This example recovers the parameter used to generate the synthetic +observation. Real calibration methods can use any optimizer or uncertainty +framework and may return additional diagnostics. diff --git a/docs/src/working_with_data/floating_point_accumulation_error.md b/docs/src/working_with_data/floating_point_accumulation_error.md deleted file mode 100644 index 6153fdc62..000000000 --- a/docs/src/working_with_data/floating_point_accumulation_error.md +++ /dev/null @@ -1,161 +0,0 @@ -# Floating-point considerations - -```@setup usepkg -using PlantSimEngine -using PlantSimEngine.Examples -using PlantMeteo, Dates, MultiScaleTreeGraph -meteo_day = read_weather(joinpath(pkgdir(PlantSimEngine), "examples/meteo_day.csv"), duration=Dates.Day) - -models = ModelMapping( - ToyLAIModel(), - Beer(0.5), - ToyRUEGrowthModel(0.2); - status=(TT_cu=cumsum(meteo_day.TT),), -) - -out_singlescale = run!(models, meteo_day) -``` -## Investigating a discrepancy - -In the [Converting a single-scale simulation to multi-scale](@ref) page, a single-scale simulation was converted to an equivalent multiscale simulation, and outputs were compared. One detail that was glossed over, but important to bear in mind as a PlantSimEngine user is related to floating-point approximations. - -### Single-scale simulation - -```@example usepkg -meteo_day = read_weather(joinpath(pkgdir(PlantSimEngine), "examples/meteo_day.csv"), duration=Dates.Day) - -models_singlescale = ModelMapping( - ToyLAIModel(), - Beer(0.5), - ToyRUEGrowthModel(0.2); - status=(TT_cu=cumsum(meteo_day.TT),), -) - -outputs_singlescale = run!(models_singlescale, meteo_day) -outputs_singlescale[1:3,:] # show the first 3 rows of the output -``` - -### Multi-scale equivalent - -```@example usepkg -PlantSimEngine.@process "tt_cu" verbose = false - -struct ToyTt_CuModel <: AbstractTt_CuModel end - -function PlantSimEngine.run!(::ToyTt_CuModel, models, status, meteo, constants, extra=nothing) - status.TT_cu += - meteo.TT -end - -function PlantSimEngine.inputs_(::ToyTt_CuModel) - NamedTuple() # No input variables -end - -function PlantSimEngine.outputs_(::ToyTt_CuModel) - (TT_cu=0.0,) -end - -mapping_multiscale = ModelMapping( - :Scene => ToyTt_CuModel(), - :Plant => ( - MultiScaleModel( - model=ToyLAIModel(), - mapped_variables=[ - :TT_cu => :Scene, - ], - ), - Beer(0.5), - ToyRUEGrowthModel(0.2), - ), -) - -mtg_multiscale = MultiScaleTreeGraph.Node(MultiScaleTreeGraph.NodeMTG("/", :Plant, 0, 0),) - plant = MultiScaleTreeGraph.Node(mtg_multiscale, MultiScaleTreeGraph.NodeMTG("+", :Plant, 1, 1)) - -outputs_multiscale = run!(mtg_multiscale, mapping_multiscale, meteo_day) -``` - -### Output comparison - -```@setup usepkg -mapping_multiscale = ModelMapping( - :Scene => ToyTt_CuModel(), - :Plant => ( - MultiScaleModel( - model=ToyLAIModel(), - mapped_variables=[ - :TT_cu => :Scene, - ], - ), - Beer(0.5), - ToyRUEGrowthModel(0.2), - ), -) - -mtg_multiscale = MultiScaleTreeGraph.Node(MultiScaleTreeGraph.NodeMTG("/", :Scene, 0, 0),) - plant = MultiScaleTreeGraph.Node(mtg_multiscale, MultiScaleTreeGraph.NodeMTG("+", :Plant, 1, 1)) - -outputs_multiscale = run!(mtg_multiscale, mapping_multiscale, meteo_day) -``` - -```@example usepkg - -computed_TT_cu_multiscale = [outputs_multiscale[:Scene][i].TT_cu for i in 1:length(outputs_multiscale[:Scene])] -is_approx_equal = length(unique(computed_TT_cu_multiscale .≈ outputs_singlescale.TT_cu)) == 1 -``` - -Why was the comparison only approximate ? Why `≈` instead of `==`? - -Let's try it out. What if write instead: - -```@example usepkg -computed_TT_cu_multiscale = [outputs_multiscale[:Scene][i].TT_cu for i in 1:length(outputs_multiscale[:Scene])] -is_perfectly_equal = length(unique(computed_TT_cu_multiscale .== outputs_singlescale.TT_cu)) == 1 -``` - -Why is this false? Let's look at the data. - -Looking more closely at the output, we can notice that values are identical up to timestep #105 : - -```@example usepkg -(computed_TT_cu_multiscale .== outputs_singlescale.TT_cu)[104] -``` - -```@example usepkg -(computed_TT_cu_multiscale .== outputs_singlescale.TT_cu)[105] -``` - -We have the values 132.33333333333331 (multi-scale) and 132.33333333333334 (single-scale). The final output values are : 2193.8166666666643 (multi-scale) and 2193.816666666666 (single-scale). - -The divergence isn't huge, but in other situations or over more timesteps it could start becoming a problem. - -## Floating-point summation - -The reason values aren't identical, is due to the fact that many numbers do not have an exact floating point representation. A classical example is the fact that [0.1 + 0.2 != 0.3](https://blog.reverberate.org/2016/02/06/floating-point-demystified-part2.html) : - -```@example usepkg -println(0.1 + 0.2 - 0.3) -``` - -When summing many numbers, depnding on the order in which they are summed, floating-point approximation errors may aggregate more or less quickly. - -The default summation per-timestep in our example `Toy_Tt_CuModel` was a naive summation. The `cumsum` function used in the single-scale simulation to directly compute the TT_cu uses a pairwise summation method that provides approximation error on fewer digits compared to naive summation. Errors aggregate more slowly. - -In our simple example, using Float64 values, the difference wasn't significant enough to matter, but if you are writing a simulation over many timesteps or aggregating a value over many nodes, you may need to alter models to avoid numerical errors blowing up due to floating-point accuracy. - -Depending on what value is being computed and the mathematical operations used, changes may range from applying a simple scale to a range of values, to significant refactoring. - - -## Other links related to floating-point numerical concerns - -Note that many of the examples in these blogposts discuss Float32 accuracy. Float64 values have several extra precision bits to work. - -A series of blog posts on floating-point accuracy: [https://randomascii.wordpress.com/2012/02/25/comparing-floating-point-numbers-2012-edition/](https://randomascii.wordpress.com/2012/02/25/comparing-floating-point-numbers-2012-edition/) -Floating-Point Visually Explained : [https://fabiensanglard.net/floating_point_visually_explained/](https://randomascii.wordpress.com/2012/02/25/comparing-floating-point-numbers-2012-edition/) -Examples of floating point problems: [https://jvns.ca/blog/2023/01/13/examples-of-floating-point-problems/](https://randomascii.wordpress.com/2012/02/25/comparing-floating-point-numbers-2012-edition/) - -Relating specifically to floating-point sums: - -Pairwise summation: [https://en.wikipedia.org/wiki/Pairwise_summation](https://en.wikipedia.org/wiki/Pairwise_summation) -Kahan summation: [https://en.wikipedia.org/wiki/Kahan_summation_algorithm](https://en.wikipedia.org/wiki/Kahan_summation_algorithm) -Taming Floating-Point Sums: [https://orlp.net/blog/taming-float-sums/](https://orlp.net/blog/taming-float-sums/) diff --git a/docs/src/working_with_data/inputs.md b/docs/src/working_with_data/inputs.md deleted file mode 100644 index 3c94c985b..000000000 --- a/docs/src/working_with_data/inputs.md +++ /dev/null @@ -1,94 +0,0 @@ -# Input types - -[`run!`](@ref) usually takes two inputs: a [`ModelMapping`](@ref) and data for the meteorology. The data for the meteorology is usually provided for one time step using an `Atmosphere`, or for several time-steps using a `TimeStepTable{Atmosphere}`. The [`ModelMapping`](@ref) can also be provided as a singleton, or as a vector or dictionary of. - -[`run!`](@ref) knows how to handle these data formats via the [`PlantSimEngine.DataFormat`](@ref) trait (see [this blog post](https://www.juliabloggers.com/the-emergent-features-of-julialang-part-ii-traits/) to learn more about traits). For example, we tell PlantSimEngine that a `TimeStepTable` should be handled like a table by implementing the following trait: - -```julia -DataFormat(::Type{<:PlantMeteo.TimeStepTable}) = TableAlike() -``` - -If you need to use a different data format for the meteorology, you can implement a new trait for it. For example, if you have a table-alike data format, you can implement the trait like this: - -```julia -DataFormat(::Type{<:MyTableFormat}) = TableAlike() -``` - -There are two other traits available: `SingletonAlike` for a data format representing one time-step only, and `TreeAlike` for trees, which is used for MultiScaleTreeGraphs nodes (not generic at this time). - -## Promoting status variable types - -Use the `type_promotion` keyword on [`ModelMapping`](@ref) when the default input and output values declared by models should be converted to another type: - -```julia -models = ModelMapping( - ToyLAIModel(), - Beer(0.5), - ToyRUEGrowthModel(0.2); - status=(TT_cu=cumsum(meteo_day.TT),), - type_promotion=Dict(Real => Float32), -) -``` - -For single-scale mappings, `type_promotion` is applied while the backing status is constructed. It follows the same semantics as the deprecated [`ModelList`](@ref): model-provided default values are converted, while values explicitly passed in `status` keep the type chosen by the user. If those values should also be `Float32`, pass them as `Float32` values directly. - -For multiscale mappings, the per-node statuses do not exist when [`ModelMapping`](@ref) is constructed. The promotion map is stored on the mapping and applied when the MTG simulation is initialized: - -```julia -mapping = ModelMapping( - :Scene => ToyTt_CuModel(), - :Plant => ( - MultiScaleModel( - model=ToyLAIModel(), - mapped_variables=[ - :TT_cu => :Scene, - ], - ), - Beer(0.5), - ToyRUEGrowthModel(0.2), - ); - type_promotion=Dict(Float64 => Float32, Vector{Float64} => Vector{Float32}), -) - -outputs = run!(mtg, mapping, meteo_day) -``` - -The same promotion can also be passed at MTG run time: - -```julia -outputs = run!( - mtg, - mapping, - meteo_day; - type_promotion=Dict(Float64 => Float32, Vector{Float64} => Vector{Float32}), -) -``` - -In multiscale runs, type promotion is used by `GraphSimulation` during status template creation, `RefVector` creation, output preallocation, and initialization from MTG node attributes. - - -## Special considerations for new input types - -If you want to use a custom data format for the inputs, you need to make sure some methods are implemented for your data format depending on your use-cases. - -For example if you use models that need to get data from a different time step (*e.g.* a model that needs to get the previous day's temperature), you need to make sure that the data from the other time-steps can be accessed from the current time-step. - -To do so, you need to implement the following methods for your structure that defines your rows: - -- `Base.parent`: return the parent table of the row, *e.g.* the full DataFrame -- `PlantMeteo.rownumber`: return the row number of the row in the parent table, *e.g.* the row number in the DataFrame -- (Optionnally) `PlantMeteo.row_from_parent(row, i)`: return row `i` from the parent table, *e.g.* the row `i` from the DataFrame. This is only needed if you want high performance, the default implementation calls `Tables.rows(parent(row))[i]`. - -!!! compat - `PlantMeteo.rownumber` is temporary. It soon will be replaced by `DataAPI.rownumber` instead, which will be also used by *e.g.* DataFrames.jl. See [this Pull Request](https://github.com/JuliaData/DataAPI.jl/issues/60). - -## Working with weather data - -Here's a quick example showcasing how to export the example weather data to your own file : - -```julia -meteo_day = read_weather(joinpath(pkgdir(PlantSimEngine), "examples/meteo_day.csv"), duration=Dates.Day) -PlantMeteo.write_weather("examples/meteo_day.csv", meteo_day, duration = Dates.Day) -``` - -If you wish to filter weather data, reshape it, adjust it, write it, you'll find some more examples in PlantMeteo's [API reference](https://palmstudio.github.io/PlantMeteo.jl/stable/API/). diff --git a/docs/src/working_with_data/reducing_dof.md b/docs/src/working_with_data/reducing_dof.md deleted file mode 100644 index 1a4b925de..000000000 --- a/docs/src/working_with_data/reducing_dof.md +++ /dev/null @@ -1,121 +0,0 @@ -# Reducing the DoF - -```@setup usepkg -using PlantSimEngine, PlantMeteo, Dates -# Import the examples defined in the `Examples` sub-module: -using PlantSimEngine.Examples - -meteo = Atmosphere(T = 20.0, Wind = 1.0, P = 101.3, Rh = 0.65) -struct ForceProcess1Model <: AbstractProcess1Model end -PlantSimEngine.inputs_(::ForceProcess1Model) = (var3=-Inf,) -PlantSimEngine.outputs_(::ForceProcess1Model) = (var3=-Inf,) -function PlantSimEngine.run!(::ForceProcess1Model, models, status, meteo, constants=nothing, extra=nothing) - return nothing -end -``` - -## Introduction - -### Why reduce the degrees of freedom - -Reducing the degrees of freedom in a model, by forcing certain variables to measurements, can be useful for several reasons: - -1. It can prevent overfitting by constraining the model and making it less complex. -2. It can help to better calibrate the other components of the model by reducing the co-variability of the variables (see [Parameter degeneracy](@ref)). -3. It can lead to more interpretable models by identifying the most important variables and relationships. -4. It can improve the computational efficiency of the model by reducing the number of variables that need to be estimated. -5. It can also help to ensure that the model is consistent with known physical or observational constraints and improve the credibility of the model and its predictions. -6. It is important to note that over-constraining a model can also lead to poor fits and false conclusions, so it is essential to carefully consider which variables to constrain and to what measurements. - -## Parameter degeneracy - -The concept of "degeneracy" or "parameter degeneracy" in a model occurs when two or more variables in a model are highly correlated, and small changes in one variable can be compensated by small changes in another variable, so that the overall predictions of the model remain unchanged. Degeneracy can make it difficult to estimate the true values of the variables and to determine the unique solutions of the model. It also makes the model sensitive to the initial conditions (*e.g.* the parameters) and the optimization algorithm used. - -Degeneracy is related to the concept of "co-variability" or "collinearity", which refers to the degree of linear relationship between two or more variables. In a degenerate model, two or more variables are highly co-variate, meaning that they are highly correlated and can produce similar predictions. By fixing one variable to a measured value, the model will have less flexibility to adjust the other variables, which can help to reduce the co-variability and improve the robustness of the model. - -This is an important topic in plant/crop modelling, as the models are very often degenerate. It is most often referred to as "multicollinearity" in the field. In the context of model calibration, it is also known as "parameter degeneracy" or "parameter collinearity". In the context of model reduction, it is also known as "redundancy" or "redundant variables". - -## Reducing the DoF in PlantSimEngine - -### Soft-coupled models - -PlantSimEngine provides a simple way to reduce the degrees of freedom in a model by constraining the values of some variables to measurements. - -Let's define a model list as usual with the seven processes from `examples/dummy.jl`: - -```@example usepkg -using PlantSimEngine, PlantMeteo, Dates -# Import the examples defined in the `Examples` sub-module: -using PlantSimEngine.Examples - -meteo = Atmosphere(T = 20.0, Wind = 1.0, P = 101.3, Rh = 0.65) -m = ModelMapping( - Process1Model(2.0), - Process2Model(), - Process3Model(), - Process4Model(), - Process5Model(), - Process6Model(), - Process7Model(), - status=(var0 = 0.5,) -) - -run!(m, meteo) - -status(m) -``` - -Let's say that `m` is our complete model, and that we want to reduce the degrees of freedom by constraining the value of `var9` to a measurement, which was previously computed by `Process7Model`, a soft-dependency model. It is very easy to do this in PlantSimEngine: just remove the model from the model list and give the value of the measurement in the status: - -```@example usepkg -m2 = ModelMapping( - Process1Model(2.0), - Process2Model(), - Process3Model(), - Process4Model(), - Process5Model(), - Process6Model(), - status=(var0 = 0.5, var9 = 10.0), -) - -out = run!(m2, meteo) -``` - -And that's it ! The models that depend on `var9` will now use the measured value of `var9` instead of the one computed by `Process7Model`. - -### Hard-coupled models - -It is a bit more complicated to reduce the degrees of freedom in a model that is hard-coupled to another model, because it calls the [`run!`](@ref) method of the other model. - -In this case, we need to replace the old model with a new model that forces the value of the variable to the measurement. This is done by giving the measurements as inputs of the new model, and returning nothing so the value is unchanged. - -Starting from the model list with the seven processes from above, but this time let's say that we want to reduce the degrees of freedom by constraining the value of `var3` to a measurement, which was previously computed by `Process1Model`, a hard-dependency model. It is very easy to do this in PlantSimEngine: just replace the model by a new model that forces the value of `var3` to the measurement: - -```@example usepkg -struct ForceProcess1Model <: AbstractProcess1Model end -PlantSimEngine.inputs_(::ForceProcess1Model) = (var3=-Inf,) -PlantSimEngine.outputs_(::ForceProcess1Model) = (var3=-Inf,) -function PlantSimEngine.run!(::ForceProcess1Model, models, status, meteo, constants=nothing, extra=nothing) - return nothing -end -``` - -Now we can create a new model list with the new model for `process7`: - -```@example usepkg -m3 = ModelMapping( - ForceProcess1Model(), - Process2Model(), - Process3Model(), - Process4Model(), - Process5Model(), - Process6Model(), - Process7Model(), - status = (var0=0.5,var3 = 10.0) -) - -out = run!(m3, meteo) -``` - -!!! note - We could also eventually provide the measured variable using the meteo data, but it is not recommended. The meteo data is meant to be used for the meteo variables only, and not for the model variables. It is better to use the status for that. diff --git a/docs/src/working_with_data/visualising_outputs.md b/docs/src/working_with_data/visualising_outputs.md deleted file mode 100644 index e7d833e2a..000000000 --- a/docs/src/working_with_data/visualising_outputs.md +++ /dev/null @@ -1,98 +0,0 @@ -```@setup usepkg -# ] add PlantSimEngine, PlantMeteo -using PlantSimEngine, PlantMeteo, Dates - -# Include the model definition from the examples folder: -using PlantSimEngine.Examples - -# Import the example meteorological data: -meteo_day = read_weather(joinpath(pkgdir(PlantSimEngine), "examples/meteo_day.csv"), duration=Dates.Day) - -# Define the list of models for coupling: -model = ModelMapping( - ToyLAIModel(), - Beer(0.6), - status=(TT_cu=cumsum(meteo_day[:, :TT]),), # Pass the cumulated degree-days as input to `ToyLAIModel`, this could also be done using another model -) - -# Run the simulation: -sim_out = run!(model, meteo_day) - -``` - -# Visualizing outputs and data - -## Output structure - -PlantSimEngine's run! functions return for each timestep the state of the variables that were requested using the `tracked_outputs` kwarg (or the state of every variable if this kwarg was left unspecified). Multi-scale simulations also indicate which organ and MTG node these state variables are related to. - -Here's an example indicating how to plot output data using CairoMakie, a package used for plotting. - -```@example usepkg -# ] add PlantSimEngine, PlantMeteo -using PlantSimEngine, PlantMeteo, Dates - -# Include the model definition from the examples folder: -using PlantSimEngine.Examples - -# Import the example meteorological data: -meteo_day = read_weather(joinpath(pkgdir(PlantSimEngine), "examples/meteo_day.csv"), duration=Dates.Day) - -# Define the list of models for coupling: -models = ModelMapping( - ToyLAIModel(), - Beer(0.6), - status=(TT_cu=cumsum(meteo_day[:, :TT]),), # Pass the cumulated degree-days as input to `ToyLAIModel`, this could also be done using another model -) - -# Run the simulation: -sim_outputs = run!(models, meteo_day) -sim_outputs[1:3,:] # show the first 3 rows of the output -``` - -The output data is displayed as a by default as a `TimeStepTable`. It is also possible to filter which variables are kept via the optional `tracked_outputs` keyword argument. - -## Plotting outputs - -Using CairoMakie, one can plot out selected variables : - -!!! note - You will need to add CairoMakie to your environment through Pkg mode first. - -```@example usepkg -# Plot the results: -using CairoMakie - -fig = Figure(resolution=(800, 600)) -ax = Axis(fig[1, 1], ylabel="LAI (m² m⁻²)") -lines!(ax, sim_outputs[:TT_cu], sim_outputs[:LAI], color=:mediumseagreen) - -ax2 = Axis(fig[2, 1], xlabel="Cumulated growing degree days since sowing (°C)", ylabel="aPPFD (mol m⁻² d⁻¹)") -lines!(ax2, sim_outputs[:TT_cu], sim_outputs[:aPPFD], color=:firebrick1) - -fig -``` - -## TimeStepTables and DataFrames - -```@setup usepkg -sim_out = run!(model, meteo_day) -``` - -The output data is usually stored in a `TimeStepTable` structure defined in `PlantMeteo.jl`, which is a fast DataFrame-like structure with each time step being a [`Status`](@ref). It can be also be any `Tables.jl` structure, such as a regular `DataFrame`. Weather data is also usually stored in a `TimeStepTable` but with each time step being an `Atmosphere`. - -Another simple way to get the results is to transform the outputs into a `DataFrame`. Which is very easy because the `TimeStepTable` implements the Tables.jl interface: - -```@example usepkg -using DataFrames -sim_outputs_df = PlantSimEngine.convert_outputs(sim_outputs, DataFrame) -sim_outputs_df[[1, 2, 3, 363, 364, 365], :] -``` - -It is also possible to create DataFrames from specific variables: - -```julia -df = DataFrame(aPPFD=sim_outputs[:aPPFD][1], LAI=sim_outputs.LAI[1], Ri_PAR_f=meteo.Ri_PAR_f[1]) -``` - -Which can also be useful for [Parameter fitting ](@ref). \ No newline at end of file diff --git a/docs/test/runtests.jl b/docs/test/runtests.jl new file mode 100644 index 000000000..73b4f265c --- /dev/null +++ b/docs/test/runtests.jl @@ -0,0 +1,42 @@ +using Test + +@testset "Progressive journey structure" begin + journey_root = joinpath(@__DIR__, "..", "src", "journeys") + user_pages = sort([ + joinpath(journey_root, "users", file) + for file in readdir(joinpath(journey_root, "users")) + if endswith(file, ".md") + ]) + modeler_pages = sort([ + joinpath(journey_root, "modelers", file) + for file in readdir(joinpath(journey_root, "modelers")) + if endswith(file, ".md") + ]) + + for page in user_pages + source = read(page, String) + @test occursin("New concept", source) + @test occursin("## Page recap", source) + @test occursin("**You added:**", source) + @test occursin("**PlantSimEngine infer", source) + @test occursin("**You keep explicit:**", source) + @test occursin("**New API names:**", source) + @test !occursin("```julia", source) + end + + for page in modeler_pages + source = read(page, String) + @test occursin("**New concept:**", source) + @test occursin("## Model-author recap", source) + @test occursin("**You implemented:**", source) + @test occursin("**PlantSimEngine inferred:**", source) + @test occursin("**The scenario author keeps explicit:**", source) + @test occursin("**New API names:**", source) + @test occursin("tested", lowercase(source)) + end +end + +@testset "PlantSimEngine documentation" begin + ENV["PLANTSIMENGINE_DOCS_BUILD_ONLY"] = "true" + @test include(joinpath(@__DIR__, "..", "make.jl")) === nothing +end diff --git a/examples/Beer.jl b/examples/Beer.jl index c7069c536..bc6279359 100644 --- a/examples/Beer.jl +++ b/examples/Beer.jl @@ -12,7 +12,7 @@ PlantSimEngine.@process "light_interception" verbose = false Beer-Lambert law for light interception. Required inputs: `LAI` in m² m⁻². -Required meteorology data: `Ri_PAR_f`, the incident flux of atmospheric radiation in the +Required environment input: `Ri_PAR_f`, the incident flux of atmospheric radiation in the PAR, in W m[soil]⁻² (== J m[soil]⁻² s⁻¹). Output: aPPFD, the absorbed Photosynthetic Photon Flux Density in μmol[PAR] m[leaf]⁻² s⁻¹. @@ -21,12 +21,9 @@ struct Beer{T} <: AbstractLight_InterceptionModel k::T end -# Beer is parallelizable over time-steps and objects, so we can declare it as such using the trait: -PlantSimEngine.TimeStepDependencyTrait(::Type{<:Beer}) = PlantSimEngine.IsTimeStepIndependent() -PlantSimEngine.ObjectDependencyTrait(::Type{<:Beer}) = PlantSimEngine.IsObjectIndependent() """ - run!(::Beer, object, meteo, constants=Constants(), extra=nothing) + run!(model::Beer, status, environment, constants, context) Computes the photosynthetic photon flux density (`aPPFD`, µmol m⁻² s⁻¹) absorbed by an object using the incoming PAR radiation flux (`Ri_PAR_f`, W m⁻²) and the Beer-Lambert law @@ -34,41 +31,50 @@ of light extinction. # Arguments -- `::Beer`: a Beer model, from the model list (*i.e.* m.light_interception) -- `models`: A `ModelMapping` struct holding the parameters for the model with -initialisations for `LAI` (m² m⁻²): the leaf area index. -- `status`: the status of the model, usually the model list status (*i.e.* m.status) -- `meteo`: meteorology structure, see [`Atmosphere`](https://palmstudio.github.io/PlantMeteo.jl/stable/#PlantMeteo.Atmosphere) -- `constants = PlantMeteo.Constants()`: physical constants. See `PlantMeteo.Constants` for more details -- `extra = nothing`: extra arguments, not used here. +- `model`: the current Beer model instance. +- `status`: the application-local view of the target [`Object`](@ref) status. +- `environment`: sampled environment, such as an [`Atmosphere`](https://palmstudio.github.io/PlantMeteo.jl/stable/#PlantMeteo.Atmosphere) row. +- `constants`: physical constants supplied by the [`CompositeModel`](@ref) run. +- `context`: runtime context; this kernel does not use it. # Examples ```julia -m = ModelMapping(Beer(0.5), status=(LAI=2.0,)) - -meteo = Atmosphere(T=20.0, Wind=1.0, P=101.3, Rh=0.65, Ri_PAR_q=300.0) - -run!(m, meteo) - -m[:aPPFD] +model = CompositeModel( + Beer(0.5); + status=(LAI=2.0,), + id=:leaf, + scale=:Leaf, + environment=Atmosphere( + T=20.0, + Wind=1.0, + P=101.3, + Rh=0.65, + Ri_PAR_f=300.0, + duration=Hour(1), + ), +) +run!(model) +only(model_objects(model; scale=:Leaf)).status.aPPFD ``` """ -function PlantSimEngine.run!(::Beer, models, status, meteo, constants, extra=nothing) +function PlantSimEngine.run!(model::Beer, status, environment, constants, context) status.aPPFD = - meteo.Ri_PAR_f * - (1.0 - exp(-models.light_interception.k * status.LAI)) * + environment.Ri_PAR_f * + (1.0 - exp(-model.k * status.LAI)) * constants.J_to_umol end function PlantSimEngine.inputs_(::Beer) - (LAI=-Inf,) + (LAI=Required(Real),) end -function PlantSimEngine.outputs_(::Beer) - (aPPFD=-Inf,) +function PlantSimEngine.outputs_(model::Beer) + (aPPFD=oftype(float(model.k), -Inf),) end +PlantSimEngine.environment_inputs_(::Beer) = (Ri_PAR_f=0.0,) + """ fit(::Type{Beer}, df; J_to_umol=PlantMeteo.Constants().J_to_umol) @@ -92,17 +98,27 @@ using PlantSimEngine using PlantSimEngine.Examples ``` -Create a model list with a Beer model, and fit it to the data: +Create a `CompositeModel` with one leaf object, then fit `Beer` to the data: ```julia -m = ModelMapping(Beer(0.6), status=(LAI=2.0,)) -meteo = Atmosphere(T=20.0, Wind=1.0, P=101.3, Rh=0.65, Ri_PAR_f=300.0) -run!(m, meteo) -df = DataFrame(aPPFD=m[:aPPFD][1], LAI=m.status.LAI[1], Ri_PAR_f=meteo.Ri_PAR_f[1]) -fit(Beer, df) +model = CompositeModel( + Beer(0.6); + status=(LAI=2.0,), + id=:leaf, + scale=:Leaf, + environment=environment, +) +simulation = run!(model) +leaf = final_state(simulation, One(scale=:Leaf)) +df = DataFrame(aPPFD=leaf.aPPFD, LAI=leaf.LAI, Ri_PAR_f=environment.Ri_PAR_f[1]) +Evaluation.fit(Beer, df) ``` """ -function PlantSimEngine.fit(::Type{Beer}, df; J_to_umol=PlantMeteo.Constants().J_to_umol) +function PlantSimEngine.Evaluation.fit( + ::Type{Beer}, + df; + J_to_umol=PlantMeteo.Constants().J_to_umol, +) k = Statistics.mean(-log.(1 .- df.aPPFD ./ (J_to_umol .* df.Ri_PAR_f)) ./ df.LAI) return (k=k,) -end \ No newline at end of file +end diff --git a/examples/ToyAdvancedControl.jl b/examples/ToyAdvancedControl.jl new file mode 100644 index 000000000..22c5da86e --- /dev/null +++ b/examples/ToyAdvancedControl.jl @@ -0,0 +1,121 @@ +PlantSimEngine.@process "toy_selective_call_controller" verbose = false +PlantSimEngine.@process "toy_stock_writer" verbose = false + +""" + ToySelectiveCallControllerModel( + trial_temperatures, + accepted_temperature; + selected_object, + ) + +Resolve several hard-call targets, run `selected_object` for several +unpublished trials, then publish one accepted result. +""" +struct ToySelectiveCallControllerModel{T} <: + AbstractToy_Selective_Call_ControllerModel + trial_temperatures::NTuple{2,T} + accepted_temperature::T + selected_object::Symbol +end + +function ToySelectiveCallControllerModel( + trial_temperatures::Tuple, + accepted_temperature, + ; + selected_object, +) + length(trial_temperatures) == 2 || error( + "ToySelectiveCallControllerModel needs exactly two trial temperatures.", + ) + values = promote( + float(trial_temperatures[1]), + float(trial_temperatures[2]), + float(accepted_temperature), + ) + T = typeof(values[1]) + return ToySelectiveCallControllerModel{T}( + (values[1], values[2]), + values[3], + Symbol(selected_object), + ) +end + +PlantSimEngine.inputs_(::ToySelectiveCallControllerModel) = NamedTuple() +PlantSimEngine.dep(::ToySelectiveCallControllerModel) = ( + readers=Call(Many( + scale=:Leaf, + process=:toy_environment_reader, + within=Subtree(), + )), +) +function PlantSimEngine.outputs_(model::ToySelectiveCallControllerModel) + initial = zero(model.accepted_temperature) + return ( + target_count=0, + trial_temperature_seen=initial, + accepted_temperature_seen=initial, + ) +end + +function PlantSimEngine.run!( + model::ToySelectiveCallControllerModel, + status, + environment, + constants, + context, +) + targets = call_targets(context, :readers) + status.target_count = length(targets) + selected = only(call_targets( + context, + :readers; + objects=(ObjectId(model.selected_object),), + )) + + for temperature in model.trial_temperatures + run_call!( + selected; + sampled_environment=(T=temperature,), + publish=false, + ) + end + status.trial_temperature_seen = selected.status.temperature_seen + + run_call!( + selected; + sampled_environment=(T=model.accepted_temperature,), + publish=true, + ) + status.accepted_temperature_seen = selected.status.temperature_seen + return nothing +end + +""" + ToyStockWriterModel(value) + +Write one configured stock value. Several named applications of this model can +demonstrate canonical writer ordering and stream-only output routing. +""" +struct ToyStockWriterModel{T} <: AbstractToy_Stock_WriterModel + value::T +end + +function ToyStockWriterModel(value::Real) + parameter = float(value) + return ToyStockWriterModel{typeof(parameter)}(parameter) +end + +PlantSimEngine.inputs_(::ToyStockWriterModel) = NamedTuple() +PlantSimEngine.outputs_(model::ToyStockWriterModel) = + (stock=zero(model.value),) + +function PlantSimEngine.run!( + model::ToyStockWriterModel, + status, + environment, + constants, + context, +) + status.stock = model.value + return nothing +end diff --git a/examples/ToyAssimGrowthModel.jl b/examples/ToyAssimGrowthModel.jl index cda5f167f..7c52ea6ca 100644 --- a/examples/ToyAssimGrowthModel.jl +++ b/examples/ToyAssimGrowthModel.jl @@ -41,31 +41,37 @@ end # Define inputs: function PlantSimEngine.inputs_(::ToyAssimGrowthModel) - (aPPFD=-Inf,) + (aPPFD=Required(Real),) end # Define outputs: -function PlantSimEngine.outputs_(::ToyAssimGrowthModel) - (carbon_assimilation=-Inf, Rm=-Inf, Rg=-Inf, biomass_increment=-Inf, biomass=0.0) +function PlantSimEngine.outputs_(model::ToyAssimGrowthModel) + initial = oftype(model.LUE, -Inf) + return ( + carbon_assimilation=initial, + Rm=initial, + Rg=initial, + biomass_increment=initial, + biomass=zero(model.LUE), + ) end # Tells Julia what is the type of elements: Base.eltype(x::ToyAssimGrowthModel{T}) where {T} = T # Implement the growth model: -function PlantSimEngine.run!(::ToyAssimGrowthModel, models, status, meteo, constants, extra) +function PlantSimEngine.run!(model::ToyAssimGrowthModel, status, environment, constants, context) # The assimilation is simply the absorbed photosynthetic photon flux density (aPPFD) times the light use efficiency (LUE): - status.carbon_assimilation = status.aPPFD * models.growth.LUE + status.carbon_assimilation = status.aPPFD * model.LUE # The maintenance respiration is simply a factor of the assimilation: - status.Rm = status.carbon_assimilation * models.growth.Rm_factor - # Note that we use models.growth.Rm_factor to access the parameter of the model + status.Rm = status.carbon_assimilation * model.Rm_factor # Net primary productivity of the plant (NPP) is the assimilation minus the maintenance respiration: NPP = status.carbon_assimilation - status.Rm # The NPP is used with a cost (growth respiration Rg): - status.Rg = 1 - (NPP / models.growth.Rg_cost) + status.Rg = 1 - (NPP / model.Rg_cost) # The biomass increment is the NPP minus the growth respiration: status.biomass_increment = NPP - status.Rg @@ -73,6 +79,3 @@ function PlantSimEngine.run!(::ToyAssimGrowthModel, models, status, meteo, const # The biomass is the biomass from the previous time-step plus the biomass increment: status.biomass += status.biomass_increment end - -# And optionally, we can tell PlantSimEngine that we can safely parallelize our model over space (objects): -PlantSimEngine.ObjectDependencyTrait(::Type{<:ToyAssimGrowthModel}) = PlantSimEngine.IsObjectIndependent() \ No newline at end of file diff --git a/examples/ToyAssimModel.jl b/examples/ToyAssimModel.jl index 7ad0f2ed8..84eee12db 100644 --- a/examples/ToyAssimModel.jl +++ b/examples/ToyAssimModel.jl @@ -39,24 +39,19 @@ end # Define inputs: function PlantSimEngine.inputs_(::ToyAssimModel) - (aPPFD=-Inf, soil_water_content=-Inf) + (aPPFD=Required(Real), soil_water_content=Required(Real)) end # Define outputs: -function PlantSimEngine.outputs_(::ToyAssimModel) - (carbon_assimilation=-Inf,) +function PlantSimEngine.outputs_(model::ToyAssimModel) + (carbon_assimilation=oftype(float(model.LUE), -Inf),) end # Tells Julia what is the type of elements: Base.eltype(::ToyAssimModel{T}) where {T} = T # Implement the model: -function PlantSimEngine.run!(::ToyAssimModel, models, status, meteo, constants, extra) +function PlantSimEngine.run!(model::ToyAssimModel, status, environment, constants, context) # The assimilation is simply the absorbed photosynthetic photon flux density (aPPFD) times the light use efficiency (LUE): - status.carbon_assimilation = status.aPPFD * models.carbon_assimilation.LUE * status.soil_water_content + status.carbon_assimilation = status.aPPFD * model.LUE * status.soil_water_content end - -# And optionally, we can tell PlantSimEngine that we can safely parallelize our model over space (objects): -PlantSimEngine.ObjectDependencyTrait(::Type{<:ToyAssimModel}) = PlantSimEngine.IsObjectIndependent() -# And also over time (time-steps): -PlantSimEngine.TimeStepDependencyTrait(::Type{<:ToyAssimModel}) = PlantSimEngine.IsTimeStepIndependent() \ No newline at end of file diff --git a/examples/ToyCAllocationModel.jl b/examples/ToyCAllocationModel.jl index db6666152..a14c4b754 100644 --- a/examples/ToyCAllocationModel.jl +++ b/examples/ToyCAllocationModel.jl @@ -31,7 +31,11 @@ struct ToyCAllocationModel <: AbstractCarbon_AllocationModel end # Define inputs: function PlantSimEngine.inputs_(::ToyCAllocationModel) - (carbon_assimilation=[-Inf], Rm=-Inf, carbon_demand=[-Inf],) + ( + carbon_assimilation=Required(AbstractVector{<:Real}), + Rm=Required(Real), + carbon_demand=Required(AbstractVector{<:Real}), + ) end # Define outputs: @@ -39,7 +43,7 @@ function PlantSimEngine.outputs_(::ToyCAllocationModel) (carbon_offer=-Inf, carbon_allocation=[-Inf],) end -function PlantSimEngine.run!(::ToyCAllocationModel, models, status, meteo, constants, extra_args) +function PlantSimEngine.run!(::ToyCAllocationModel, status, environment, constants, context) carbon_demand_tot = sum(status.carbon_demand) #Note: this model is multiscale, so status.carbon_demand, status.carbon_allocation, and status.carbon_assimilation are vectors. @@ -68,5 +72,5 @@ function PlantSimEngine.run!(::ToyCAllocationModel, models, status, meteo, const end end -# Can be parallelized over time-steps, but not objects (we have vectors of values coming from other objects as input): -PlantSimEngine.TimeStepDependencyTrait(::Type{<:ToyCAllocationModel}) = PlantSimEngine.IsTimeStepIndependent() +# This model reads values from several objects, so object-level independence +# must not be assumed by a future executor. diff --git a/examples/ToyCBiomassModel.jl b/examples/ToyCBiomassModel.jl index d2dd19d8d..ce2b36c9a 100644 --- a/examples/ToyCBiomassModel.jl +++ b/examples/ToyCBiomassModel.jl @@ -28,19 +28,21 @@ end # Define inputs: function PlantSimEngine.inputs_(::ToyCBiomassModel) - (carbon_allocation=-Inf,) + (carbon_allocation=Required(Real),) end # Define outputs: -function PlantSimEngine.outputs_(::ToyCBiomassModel) - (carbon_biomass_increment=-Inf, carbon_biomass=0.0, growth_respiration=-Inf,) +function PlantSimEngine.outputs_(model::ToyCBiomassModel) + initial = oftype(float(model.construction_cost), -Inf) + return ( + carbon_biomass_increment=initial, + carbon_biomass=zero(float(model.construction_cost)), + growth_respiration=initial, + ) end -function PlantSimEngine.run!(m::ToyCBiomassModel, models, status, meteo, constants, extra_args) +function PlantSimEngine.run!(m::ToyCBiomassModel, status, environment, constants, context) status.carbon_biomass_increment = status.carbon_allocation / m.construction_cost status.carbon_biomass += status.carbon_biomass_increment status.growth_respiration = status.carbon_allocation - status.carbon_biomass_increment end - -# Can be parallelized over organs (but not time-steps, as it is incrementally updating the biomass in the status): -PlantSimEngine.ObjectDependencyTrait(::Type{<:ToyCBiomassModel}) = PlantSimEngine.IsObjectIndependent() \ No newline at end of file diff --git a/examples/ToyCDemandModel.jl b/examples/ToyCDemandModel.jl index b376aa83c..1548840c5 100644 --- a/examples/ToyCDemandModel.jl +++ b/examples/ToyCDemandModel.jl @@ -31,29 +31,28 @@ end # Instantiate the `struct` with keyword arguments and default values: function ToyCDemandModel(; optimal_biomass, development_duration) - ToyCDemandModel(optimal_biomass, development_duration) + parameters = promote(float(optimal_biomass), float(development_duration)) + return ToyCDemandModel(parameters...) end # Define inputs: function PlantSimEngine.inputs_(::ToyCDemandModel) - (TT=-Inf,) + (TT=Required(Real),) end # Define outputs: -function PlantSimEngine.outputs_(::ToyCDemandModel) - (carbon_demand=-Inf,) +function PlantSimEngine.outputs_(model::ToyCDemandModel) + (carbon_demand=oftype(model.optimal_biomass, -Inf),) end # Tells Julia what is the type of elements: Base.eltype(::ToyCDemandModel{T}) where {T} = T # Implement the growth model: -function PlantSimEngine.run!(::ToyCDemandModel, models, status, meteo, constants, extra) +function PlantSimEngine.run!(model::ToyCDemandModel, status, environment, constants, context) # The carbon demand is simply the biomass under optimal conditions divided by the duration of the development: - status.carbon_demand = status.TT * models.carbon_demand.optimal_biomass / models.carbon_demand.development_duration + status.carbon_demand = + status.TT * + model.optimal_biomass / + model.development_duration end - -# And optionally, we can tell PlantSimEngine that we can safely parallelize our model over space (objects): -PlantSimEngine.ObjectDependencyTrait(::Type{<:ToyCDemandModel}) = PlantSimEngine.IsObjectIndependent() -# And also over time (time-steps): -PlantSimEngine.TimeStepDependencyTrait(::Type{<:ToyCDemandModel}) = PlantSimEngine.IsTimeStepIndependent() \ No newline at end of file diff --git a/examples/ToyDegreeDays.jl b/examples/ToyDegreeDays.jl index 72d77b70c..95d59565a 100644 --- a/examples/ToyDegreeDays.jl +++ b/examples/ToyDegreeDays.jl @@ -11,26 +11,28 @@ Computes the thermal time in degree days and cumulated degree-days based on the the initial cumulated degree days, the base temperature below which there is no growth, and the maximum temperature for growh. """ -struct ToyDegreeDaysCumulModel <: AbstractDegreedaysModel - init_TT::Float64 - T_base::Float64 - T_max::Float64 +struct ToyDegreeDaysCumulModel{T<:Real} <: AbstractDegreedaysModel + init_TT::T + T_base::T + T_max::T end # Defining default values: -ToyDegreeDaysCumulModel(; init_TT=0.0, T_base=10.0, T_max=43.0) = ToyDegreeDaysCumulModel(init_TT, T_base, T_max) +function ToyDegreeDaysCumulModel(; init_TT=0.0, T_base=10.0, T_max=43.0) + parameters = promote(float(init_TT), float(T_base), float(T_max)) + return ToyDegreeDaysCumulModel(parameters...) +end # Defining the inputs and outputs of the model: PlantSimEngine.inputs_(::ToyDegreeDaysCumulModel) = NamedTuple() -PlantSimEngine.outputs_(m::ToyDegreeDaysCumulModel) = (TT=-Inf, TT_cu=0.0,) +PlantSimEngine.outputs_(m::ToyDegreeDaysCumulModel) = ( + TT=oftype(m.init_TT, -Inf), + TT_cu=m.init_TT, +) +PlantSimEngine.environment_inputs_(m::ToyDegreeDaysCumulModel) = (T=zero(m.T_base),) # Implementing the actual algorithm by adding a method to the run! function for our model: -function PlantSimEngine.run!(m::ToyDegreeDaysCumulModel, models, status, meteo, constants=nothing, extra=nothing) - status.TT = max(0.0, min(meteo.T, m.T_max) - m.T_base) +function PlantSimEngine.run!(m::ToyDegreeDaysCumulModel, status, environment, constants, context) + status.TT = max(zero(m.T_base), min(environment.T, m.T_max) - m.T_base) status.TT_cu += status.TT end - -# The computation of ToyDegreeDaysCumulModel dependents on previous values, but it is independent of other objects. -# The default trait is that models are dependent of other time-steps and object. So we need to change the default trait -# for objects: -PlantSimEngine.ObjectDependencyTrait(::Type{<:ToyDegreeDaysCumulModel}) = PlantSimEngine.IsObjectIndependent() \ No newline at end of file diff --git a/examples/ToyInternodeEmergence.jl b/examples/ToyInternodeEmergence.jl deleted file mode 100644 index b43cfd58d..000000000 --- a/examples/ToyInternodeEmergence.jl +++ /dev/null @@ -1,36 +0,0 @@ - -# Declaring the process of LAI dynamic: -PlantSimEngine.@process "organ_emergence" verbose = false - -# Declaring the model of LAI dynamic with its parameter values: - -""" - ToyInternodeEmergence(;init_TT=0.0, TT_emergence = 300) - -Computes the organ emergence based on cumulated thermal time since last event. -""" -struct ToyInternodeEmergence <: AbstractOrgan_EmergenceModel - TT_emergence::Float64 -end - -# Defining default values: -ToyInternodeEmergence(; TT_emergence=300.0) = ToyInternodeEmergence(TT_emergence) - -# Defining the inputs and outputs of the model: -PlantSimEngine.inputs_(m::ToyInternodeEmergence) = (TT_cu=-Inf,) -PlantSimEngine.outputs_(m::ToyInternodeEmergence) = (TT_cu_emergence=0.0,) - -# Implementing the actual algorithm by adding a method to the run! function for our model: -function PlantSimEngine.run!(m::ToyInternodeEmergence, models, status, meteo, constants=nothing, sim_object=nothing) - - if length(MultiScaleTreeGraph.children(status.node)) == 1 && status.TT_cu - status.TT_cu_emergence >= m.TT_emergence - # NB: the node can produce one leaf, and one internode only, so we check that it did not produce - # any internode yet. - status_new_internode = add_organ!(status.node, sim_object, "<", :Internode, 2, index=1) - add_organ!(status_new_internode.node, sim_object, "+", :Leaf, 2, index=1) - - status_new_internode.TT_cu_emergence = status.TT_cu - end - - return nothing -end \ No newline at end of file diff --git a/examples/ToyLAIModel.jl b/examples/ToyLAIModel.jl index 081c8824f..0c7bcd821 100644 --- a/examples/ToyLAIModel.jl +++ b/examples/ToyLAIModel.jl @@ -26,51 +26,56 @@ Computes the Leaf Area Index (LAI) based on a sigmoid function of thermal time. - `LAI`: the Leaf Area Index, usually in m² m⁻² """ -struct ToyLAIModel <: AbstractLai_DynamicModel - max_lai::Float64 - dd_incslope::Int - inc_slope::Float64 - dd_decslope::Int - dec_slope::Float64 +struct ToyLAIModel{T<:Real} <: AbstractLai_DynamicModel + max_lai::T + dd_incslope::T + inc_slope::T + dd_decslope::T + dec_slope::T end # Defining a method with keyword arguments and default values: -ToyLAIModel(; max_lai=8.0, dd_incslope=800, inc_slope=110, dd_decslope=1500, dec_slope=20) = ToyLAIModel(max_lai, dd_incslope, inc_slope, dd_decslope, dec_slope) +function ToyLAIModel(; max_lai=8.0, dd_incslope=800, inc_slope=110, dd_decslope=1500, dec_slope=20) + parameters = promote( + float(max_lai), + float(dd_incslope), + float(inc_slope), + float(dd_decslope), + float(dec_slope), + ) + return ToyLAIModel(parameters...) +end # Defining the inputs and outputs of the model: -PlantSimEngine.inputs_(::ToyLAIModel) = (TT_cu=-Inf,) -PlantSimEngine.outputs_(::ToyLAIModel) = (LAI=-Inf,) +PlantSimEngine.inputs_(::ToyLAIModel) = (TT_cu=Required(Real),) +PlantSimEngine.outputs_(model::ToyLAIModel) = (LAI=oftype(model.max_lai, -Inf),) # Implementing the actual algorithm by adding a method to the run! function for our model: -function PlantSimEngine.run!(::ToyLAIModel, models, status, meteo, constants=nothing, extra=nothing) +function PlantSimEngine.run!(model::ToyLAIModel, status, environment, constants, context) status.LAI = - models.LAI_Dynamic.max_lai * - (1.0 / - (1.0 + exp((models.LAI_Dynamic.dd_incslope - status.TT_cu) / models.LAI_Dynamic.inc_slope)) - - 1.0 / (1.0 + exp((models.LAI_Dynamic.dd_decslope - status.TT_cu) / models.LAI_Dynamic.dec_slope)) + model.max_lai * + (one(model.max_lai) / + (one(model.max_lai) + exp((model.dd_incslope - status.TT_cu) / model.inc_slope)) - + one(model.max_lai) / (one(model.max_lai) + exp((model.dd_decslope - status.TT_cu) / model.dec_slope)) ) - if status.LAI < 0.0 - status.LAI = 0.0 + if status.LAI < zero(model.max_lai) + status.LAI = zero(model.max_lai) end end -# The computation of ToyLAIModel is independant of previous values and other objects. We can add this information as -# traits to the model to tell PlantSimEngine that it is safe to run the models in parallel: -PlantSimEngine.TimeStepDependencyTrait(::Type{<:ToyLAIModel}) = PlantSimEngine.IsTimeStepIndependent() -PlantSimEngine.ObjectDependencyTrait(::Type{<:ToyLAIModel}) = PlantSimEngine.IsObjectIndependent() - - +# ToyLAIModel is independent of previous values and other objects. The current +# public runtime remains sequential and owns execution policy. -# A second model at scene scale: +# A second model at model scale: """ ToyLAIfromLeafAreaModel() -Computes the Leaf Area Index (LAI) of the scene based on the plants leaf area. +Computes the Leaf Area Index (LAI) of the model based on the plants leaf area. # Arguments -- `scene_area`: the area of the scene, usually in m² +- `scene_area`: the area of the model, usually in m² # Inputs @@ -78,7 +83,7 @@ Computes the Leaf Area Index (LAI) of the scene based on the plants leaf area. # Outputs -- `LAI`: the Leaf Area Index of the scene, usually in m² m⁻² +- `LAI`: the Leaf Area Index of the model, usually in m² m⁻² - `total_surface`: the total surface of the plants, usually in m² """ struct ToyLAIfromLeafAreaModel{T} <: AbstractLai_DynamicModel @@ -86,14 +91,19 @@ struct ToyLAIfromLeafAreaModel{T} <: AbstractLai_DynamicModel end # Defining the inputs and outputs of the model: -PlantSimEngine.inputs_(::ToyLAIfromLeafAreaModel) = (plant_surfaces=[-Inf],) -PlantSimEngine.outputs_(::ToyLAIfromLeafAreaModel) = (LAI=-Inf, total_surface=-Inf) +PlantSimEngine.inputs_(::ToyLAIfromLeafAreaModel) = ( + plant_surfaces=Required(AbstractVector{<:Real}), +) +PlantSimEngine.outputs_(m::ToyLAIfromLeafAreaModel) = ( + LAI=oftype(float(m.scene_area), -Inf), + total_surface=oftype(float(m.scene_area), -Inf), +) # Implementing the actual algorithm by adding a method to the run! function for our model: -function PlantSimEngine.run!(m::ToyLAIfromLeafAreaModel, models, status, meteo, constants=nothing, extra=nothing) +function PlantSimEngine.run!(m::ToyLAIfromLeafAreaModel, status, environment, constants, context) status.total_surface = sum(status.plant_surfaces) status.LAI = status.total_surface / m.scene_area end -# The computation of ToyLAIfromLeafAreaModel is independant of previous values so we can compute it in parallel over time-steps: -PlantSimEngine.TimeStepDependencyTrait(::Type{<:ToyLAIfromLeafAreaModel}) = PlantSimEngine.IsTimeStepIndependent() +# ToyLAIfromLeafAreaModel is independent of previous values, but execution +# policy remains owned by the runtime. diff --git a/examples/ToyLeafSurfaceModel.jl b/examples/ToyLeafSurfaceModel.jl index b120745c4..cf8e6a716 100644 --- a/examples/ToyLeafSurfaceModel.jl +++ b/examples/ToyLeafSurfaceModel.jl @@ -27,21 +27,19 @@ end # Define inputs: function PlantSimEngine.inputs_(::ToyLeafSurfaceModel) - (carbon_biomass=-Inf,) + (carbon_biomass=Required(Real),) end # Define outputs: -function PlantSimEngine.outputs_(::ToyLeafSurfaceModel) - (surface=-Inf,) +function PlantSimEngine.outputs_(model::ToyLeafSurfaceModel) + (surface=oftype(float(model.SLA), -Inf),) end -function PlantSimEngine.run!(m::ToyLeafSurfaceModel, models, status, meteo, constants, extra_args) +function PlantSimEngine.run!(m::ToyLeafSurfaceModel, status, environment, constants, context) status.surface = status.carbon_biomass * m.SLA end # Can be parallelized over organs and time-steps: -PlantSimEngine.ObjectDependencyTrait(::Type{<:ToyLeafSurfaceModel}) = PlantSimEngine.IsObjectIndependent() -PlantSimEngine.TimeStepDependencyTrait(::Type{<:ToyLeafSurfaceModel}) = PlantSimEngine.IsTimeStepDependent() @@ -64,7 +62,7 @@ struct ToyPlantLeafSurfaceModel <: AbstractLeaf_SurfaceModel end # Define inputs: function PlantSimEngine.inputs_(::ToyPlantLeafSurfaceModel) - (leaf_surfaces=[-Inf],) + (leaf_surfaces=Required(AbstractVector{<:Real}),) end # Define outputs: @@ -72,9 +70,6 @@ function PlantSimEngine.outputs_(::ToyPlantLeafSurfaceModel) (surface=-Inf,) end -function PlantSimEngine.run!(m::ToyPlantLeafSurfaceModel, models, status, meteo, constants, extra_args) +function PlantSimEngine.run!(m::ToyPlantLeafSurfaceModel, status, environment, constants, context) status.surface = sum(status.leaf_surfaces) end - -# Can be parallelized over time-steps: -PlantSimEngine.TimeStepDependencyTrait(::Type{<:ToyPlantLeafSurfaceModel}) = PlantSimEngine.IsTimeStepDependent() \ No newline at end of file diff --git a/examples/ToyLightPartitioningModel.jl b/examples/ToyLightPartitioningModel.jl index 3f43c009f..77db042fa 100644 --- a/examples/ToyLightPartitioningModel.jl +++ b/examples/ToyLightPartitioningModel.jl @@ -11,7 +11,7 @@ Computes the light partitioning based on relative surface. # Inputs -- `aPPFD`: the absorbed photosynthetic photon flux density at the larger scale (*e.g.* scene), in mol[PAR] m⁻² time-step⁻¹ +- `aPPFD`: the absorbed photosynthetic photon flux density at the larger scale (*e.g.* model), in mol[PAR] m⁻² time-step⁻¹ # Outputs @@ -24,13 +24,15 @@ Computes the light partitioning based on relative surface. struct ToyLightPartitioningModel <: AbstractLight_PartitioningModel end # Define inputs: -PlantSimEngine.inputs_(::ToyLightPartitioningModel) = (aPPFD_larger_scale=-Inf, total_surface=-Inf, surface=-Inf,) +PlantSimEngine.inputs_(::ToyLightPartitioningModel) = ( + aPPFD_larger_scale=Required(Real), + total_surface=Required(Real), + surface=Required(Real), +) # Define outputs: PlantSimEngine.outputs_(::ToyLightPartitioningModel) = (aPPFD=-Inf,) -function PlantSimEngine.run!(::ToyLightPartitioningModel, models, status, meteo, constants, extra) +function PlantSimEngine.run!(::ToyLightPartitioningModel, status, environment, constants, context) status.aPPFD = status.aPPFD_larger_scale * status.surface / status.total_surface end - -PlantSimEngine.TimeStepDependencyTrait(::Type{<:ToyLightPartitioningModel}) = PlantSimEngine.IsTimeStepIndependent() \ No newline at end of file diff --git a/examples/ToyMaintenanceRespirationModel.jl b/examples/ToyMaintenanceRespirationModel.jl index 492e039e3..32c50806c 100644 --- a/examples/ToyMaintenanceRespirationModel.jl +++ b/examples/ToyMaintenanceRespirationModel.jl @@ -30,13 +30,41 @@ struct ToyMaintenanceRespirationModel{T} <: AbstractMaintenance_RespirationModel nitrogen_content::T end -PlantSimEngine.inputs_(::ToyMaintenanceRespirationModel) = (carbon_biomass=0.0,) -PlantSimEngine.outputs_(::ToyMaintenanceRespirationModel) = (Rm=-Inf,) +function ToyMaintenanceRespirationModel(Q10, Rm_base, T_ref, P_alive, nitrogen_content) + parameters = promote( + float(Q10), + float(Rm_base), + float(T_ref), + float(P_alive), + float(nitrogen_content), + ) + return ToyMaintenanceRespirationModel{typeof(first(parameters))}(parameters...) +end -function PlantSimEngine.run!(m::ToyMaintenanceRespirationModel, models, status, meteo, constants, extra=nothing) +PlantSimEngine.inputs_(::ToyMaintenanceRespirationModel) = ( + carbon_biomass=Required(Real), +) +PlantSimEngine.outputs_(model::ToyMaintenanceRespirationModel) = ( + Rm=oftype(model.Rm_base, -Inf), +) +PlantSimEngine.environment_inputs_( + model::ToyMaintenanceRespirationModel, +) = (T=zero(model.T_ref),) + +function PlantSimEngine.run!( + model::ToyMaintenanceRespirationModel, + status, + environment, + constants, + context, +) status.Rm = - status.carbon_biomass * m.P_alive * m.nitrogen_content * m.Rm_base * - m.Q10^((meteo.T - m.T_ref) / 10.0) + status.carbon_biomass * + model.P_alive * + model.nitrogen_content * + model.Rm_base * + model.Q10^((environment.T - model.T_ref) / 10) + return nothing end """ @@ -44,7 +72,7 @@ end Total plant maintenance respiration based on the sum of `Rm_organs`, the maintenance respiration of the organs. -# Intputs +# Inputs - `Rm_organs`: a vector of maintenance respiration from all organs in the plant in gC time-step⁻¹ @@ -54,9 +82,18 @@ Total plant maintenance respiration based on the sum of `Rm_organs`, the mainten """ struct ToyPlantRmModel <: AbstractMaintenance_RespirationModel end -PlantSimEngine.inputs_(::ToyPlantRmModel) = (Rm_organs=[-Inf],) +PlantSimEngine.inputs_(::ToyPlantRmModel) = ( + Rm_organs=Required(AbstractVector{<:Real}), +) PlantSimEngine.outputs_(::ToyPlantRmModel) = (Rm=-Inf,) -function PlantSimEngine.run!(::ToyPlantRmModel, models, status, meteo, constants, extra=nothing) +function PlantSimEngine.run!( + ::ToyPlantRmModel, + status, + environment, + constants, + context, +) status.Rm = sum(status.Rm_organs) -end \ No newline at end of file + return nothing +end diff --git a/examples/ToyModelDeveloper.jl b/examples/ToyModelDeveloper.jl new file mode 100644 index 000000000..ca32f9886 --- /dev/null +++ b/examples/ToyModelDeveloper.jl @@ -0,0 +1,82 @@ +PlantSimEngine.@process "toy_development" verbose = false +PlantSimEngine.@process "toy_daily_development" verbose = false + +""" + ToyDevelopmentModel(efficiency) + +Compute one growth increment from required thermal time and an optional stress +factor. + +# Inputs + +- `TT`: required thermal time for the current step. +- `stress`: dimensionless stress factor, defaulting to `1.0`. + +# Outputs + +- `growth`: growth increment for the current step. +""" +struct ToyDevelopmentModel{T} <: AbstractToy_DevelopmentModel + efficiency::T +end + +function ToyDevelopmentModel(efficiency::Real) + parameter = float(efficiency) + return ToyDevelopmentModel{typeof(parameter)}(parameter) +end + +PlantSimEngine.inputs_(::ToyDevelopmentModel) = ( + TT=Required(Real), + stress=Default(1.0), +) +PlantSimEngine.outputs_(model::ToyDevelopmentModel) = ( + growth=zero(model.efficiency), +) + +function PlantSimEngine.run!( + model::ToyDevelopmentModel, + status, + environment, + constants, + context, +) + status.growth = model.efficiency * status.TT * status.stress + return nothing +end + +""" + ToyDailyDevelopmentModel(increment) + +Accumulate one configured growth increment every 24 simulation steps. The model +declares this default cadence and hold-last output semantics. +""" +struct ToyDailyDevelopmentModel{T} <: + AbstractToy_Daily_DevelopmentModel + increment::T +end + +function ToyDailyDevelopmentModel(increment::Real) + parameter = float(increment) + return ToyDailyDevelopmentModel{typeof(parameter)}(parameter) +end + +PlantSimEngine.inputs_(::ToyDailyDevelopmentModel) = NamedTuple() +PlantSimEngine.outputs_(model::ToyDailyDevelopmentModel) = ( + daily_growth=zero(model.increment), +) +PlantSimEngine.timespec(::Type{<:ToyDailyDevelopmentModel}) = + ClockSpec(24.0, 1.0) +PlantSimEngine.output_policy(::Type{<:ToyDailyDevelopmentModel}) = ( + daily_growth=HoldLast(), +) + +function PlantSimEngine.run!( + model::ToyDailyDevelopmentModel, + status, + environment, + constants, + context, +) + status.daily_growth += model.increment + return nothing +end diff --git a/examples/ToyMultiScalePlantTutorial/ToyPlantSimulation1.jl b/examples/ToyMultiScalePlantTutorial/ToyPlantSimulation1.jl deleted file mode 100644 index 120ad9f95..000000000 --- a/examples/ToyMultiScalePlantTutorial/ToyPlantSimulation1.jl +++ /dev/null @@ -1,140 +0,0 @@ - -########################################### -# Toy plant model -# Physiologically meaningless but illustrates organ creation -########################################### - -function get_n_leaves(node::MultiScaleTreeGraph.Node) - root = MultiScaleTreeGraph.get_root(node) - nleaves = length(MultiScaleTreeGraph.traverse(root, x -> 1, symbol=:Leaf)) - return nleaves -end - -PlantSimEngine.@process "organ_emergence" verbose = false - -struct ToyCustomInternodeEmergence{T} <: AbstractOrgan_EmergenceModel - TT_emergence::T - carbon_internode_creation_cost::T - leaf_surface_area::T - leaves_max_surface_area::T -end - -ToyCustomInternodeEmergence(; TT_emergence=300.0, carbon_internode_creation_cost=200.0, leaf_surface_area=3.0, leaves_max_surface_area=100.0) = ToyCustomInternodeEmergence(TT_emergence, carbon_internode_creation_cost, leaf_surface_area, leaves_max_surface_area) - -PlantSimEngine.inputs_(m::ToyCustomInternodeEmergence) = (TT_cu=0.0, carbon_stock=0.0) -PlantSimEngine.outputs_(m::ToyCustomInternodeEmergence) = (TT_cu_emergence=0.0, carbon_organ_creation_consumed=0.0) - -function PlantSimEngine.run!(m::ToyCustomInternodeEmergence, models, status, meteo, constants=nothing, sim_object=nothing) - - leaves_surface_area = m.leaf_surface_area * get_n_leaves(status.node) - status.carbon_organ_creation_consumed = 0.0 - - if leaves_surface_area > m.leaves_max_surface_area - return nothing - end - - # if not enough carbon, no organ creation - if status.carbon_stock < m.carbon_internode_creation_cost - return nothing - end - - if length(MultiScaleTreeGraph.children(status.node)) == 2 && - status.TT_cu - status.TT_cu_emergence >= m.TT_emergence - status_new_internode = add_organ!(status.node, sim_object, "<", :Internode, 2, index=1) - add_organ!(status_new_internode.node, sim_object, "+", :Leaf, 2, index=1) - add_organ!(status_new_internode.node, sim_object, "+", :Leaf, 2, index=1) - - status_new_internode.TT_cu_emergence = m.TT_emergence - status.TT_cu - status.carbon_organ_creation_consumed = m.carbon_internode_creation_cost - end - - return nothing -end - -########################## -### Model accumulating carbon resources -########################## - -PlantSimEngine.@process "resource_stock_computation" verbose = false - -struct ToyStockComputationModel <: AbstractResource_Stock_ComputationModel -end - -PlantSimEngine.inputs_(::ToyStockComputationModel) = - (carbon_captured=0.0, carbon_organ_creation_consumed=0.0) - -PlantSimEngine.outputs_(::ToyStockComputationModel) = (carbon_stock=-Inf,) - -function PlantSimEngine.run!(m::ToyStockComputationModel, models, status, meteo, constants=nothing, extra=nothing) - status.carbon_stock += sum(status.carbon_captured) - sum(status.carbon_organ_creation_consumed) -end - -PlantSimEngine.TimeStepDependencyTrait(::Type{<:ToyStockComputationModel}) = PlantSimEngine.IsTimeStepIndependent() -PlantSimEngine.ObjectDependencyTrait(::Type{<:ToyStockComputationModel}) = PlantSimEngine.IsObjectIndependent() - -######################## -## Leaf model capturing some arbitrary carbon quantity -######################## - -PlantSimEngine.@process "leaf_carbon_capture" verbose = false - -struct ToyLeafCarbonCaptureModel <: AbstractLeaf_Carbon_CaptureModel end - -function PlantSimEngine.inputs_(::ToyLeafCarbonCaptureModel) - NamedTuple()#(TT_cu=-Inf) -end - -function PlantSimEngine.outputs_(::ToyLeafCarbonCaptureModel) - (carbon_captured=0.0,) -end - -function PlantSimEngine.run!(::ToyLeafCarbonCaptureModel, models, status, meteo, constants, extra) - # very crude approximation with LAI of 1 and constant aPPFD - status.carbon_captured = 200.0 * (1.0 - exp(-0.2)) -end - -PlantSimEngine.ObjectDependencyTrait(::Type{<:ToyLeafCarbonCaptureModel}) = PlantSimEngine.IsObjectIndependent() -PlantSimEngine.TimeStepDependencyTrait(::Type{<:ToyLeafCarbonCaptureModel}) = PlantSimEngine.IsTimeStepIndependent() - -mapping = ModelMapping( - :Scene => ToyDegreeDaysCumulModel(), - :Plant => ( - MultiScaleModel( - model=ToyStockComputationModel(), - mapped_variables=[ - :carbon_captured => [:Leaf], - :carbon_organ_creation_consumed => [:Internode] - ], - ), - Status(carbon_stock=0.0) - ), - :Internode => ( - MultiScaleModel( - model=ToyCustomInternodeEmergence(),#TT_emergence=20.0), - mapped_variables=[:TT_cu => (:Scene => :TT_cu), - PreviousTimeStep(:carbon_stock) => (:Plant => :carbon_stock)], - ), - Status(carbon_organ_creation_consumed=0.0), - ), - :Leaf => (ToyLeafCarbonCaptureModel(),), -) - -mtg = MultiScaleTreeGraph.Node(MultiScaleTreeGraph.NodeMTG("/", :Scene, 1, 0)) -#MultiScaleTreeGraph.Node(mtg, MultiScaleTreeGraph.NodeMTG("/", :Soil, 1, 1)) -plant = MultiScaleTreeGraph.Node(mtg, MultiScaleTreeGraph.NodeMTG("+", :Plant, 1, 1)) - -internode1 = MultiScaleTreeGraph.Node(plant, MultiScaleTreeGraph.NodeMTG("/", :Internode, 1, 2)) -MultiScaleTreeGraph.Node(internode1, MultiScaleTreeGraph.NodeMTG("+", :Leaf, 1, 2)) -MultiScaleTreeGraph.Node(internode1, MultiScaleTreeGraph.NodeMTG("+", :Leaf, 1, 2)) - -internode2 = MultiScaleTreeGraph.Node(internode1, MultiScaleTreeGraph.NodeMTG("<", :Internode, 1, 2)) -MultiScaleTreeGraph.Node(internode2, MultiScaleTreeGraph.NodeMTG("+", :Leaf, 1, 2)) -MultiScaleTreeGraph.Node(internode2, MultiScaleTreeGraph.NodeMTG("+", :Leaf, 1, 2)) - - -meteo_day = CSV.read(joinpath(pkgdir(PlantSimEngine), "examples/meteo_day.csv"), DataFrame, header=18) - -outs = run!(mtg, mapping, meteo_day) -mtg - -length(MultiScaleTreeGraph.traverse(mtg, x -> x, symbol=:Leaf)) diff --git a/examples/ToyMultiScalePlantTutorial/ToyPlantSimulation2.jl b/examples/ToyMultiScalePlantTutorial/ToyPlantSimulation2.jl deleted file mode 100644 index 15b3ec356..000000000 --- a/examples/ToyMultiScalePlantTutorial/ToyPlantSimulation2.jl +++ /dev/null @@ -1,235 +0,0 @@ -########################################### -# Toy plant model -# Physiologically and physically completely meaningless -# (no dimension for units, arbitrary values, stores water and carbon in abstract stocks, -# arbitrary max leaf count and root length, constant and non-coupled photosynthesis and water absorption, ...) -# But it should illustrate the basics of simulating a growing multiscale plant with PlantSimEngine's model approach -########################################### - -function get_root_end_node(node::MultiScaleTreeGraph.Node) - root = MultiScaleTreeGraph.get_root(node) - return MultiScaleTreeGraph.traverse(root, x -> x, symbol=:Root, filter_fun=MultiScaleTreeGraph.isleaf) -end - -function get_roots_count(node::MultiScaleTreeGraph.Node) - root = MultiScaleTreeGraph.get_root(node) - return length(MultiScaleTreeGraph.traverse(root, x -> x, symbol=:Root)) -end - -function get_n_leaves(node::MultiScaleTreeGraph.Node) - root = MultiScaleTreeGraph.get_root(node) - nleaves = length(MultiScaleTreeGraph.traverse(root, x -> 1, symbol=:Leaf)) - return nleaves -end - -PlantSimEngine.@process "organ_emergence" verbose = false - -struct ToyCustomInternodeEmergence{T} <: AbstractOrgan_EmergenceModel - TT_emergence::T - carbon_internode_creation_cost::T - leaf_surface_area::T - leaves_max_surface_area::T - water_leaf_threshold::T -end - -ToyCustomInternodeEmergence(; TT_emergence=300.0, carbon_internode_creation_cost=200.0, leaf_surface_area=3.0, leaves_max_surface_area=100.0, - water_leaf_threshold=30.0) = ToyCustomInternodeEmergence(TT_emergence, carbon_internode_creation_cost, leaf_surface_area, leaves_max_surface_area, water_leaf_threshold) - -PlantSimEngine.inputs_(m::ToyCustomInternodeEmergence) = (TT_cu=0.0, water_stock=0.0, carbon_stock=0.0) -PlantSimEngine.outputs_(m::ToyCustomInternodeEmergence) = (TT_cu_emergence=0.0, carbon_organ_creation_consumed=0.0) - -function PlantSimEngine.run!(m::ToyCustomInternodeEmergence, models, status, meteo, constants=nothing, sim_object=nothing) - - leaves_surface_area = m.leaf_surface_area * get_n_leaves(status.node) - status.carbon_organ_creation_consumed = 0.0 - - if leaves_surface_area > m.leaves_max_surface_area - return nothing - end - - # if water levels are low, prioritise roots - if status.water_stock < m.water_leaf_threshold - return nothing - end - - # if not enough carbon, no organ creation - if status.carbon_stock < m.carbon_internode_creation_cost - return nothing - end - - if length(MultiScaleTreeGraph.children(status.node)) == 2 && - status.TT_cu - status.TT_cu_emergence >= m.TT_emergence - status_new_internode = add_organ!(status.node, sim_object, "<", :Internode, 2, index=1) - add_organ!(status_new_internode.node, sim_object, "+", :Leaf, 2, index=1) - add_organ!(status_new_internode.node, sim_object, "+", :Leaf, 2, index=1) - - status_new_internode.TT_cu_emergence = m.TT_emergence - status.TT_cu - status.carbon_organ_creation_consumed = m.carbon_internode_creation_cost - end - - return nothing -end - -############################ -# Naive water absorption model -# Absorbs precipitation water depending on quantity of roots -############################ -PlantSimEngine.@process "water_absorption" verbose = false - -struct ToyWaterAbsorptionModel <: AbstractWater_AbsorptionModel -end - -PlantSimEngine.inputs_(::ToyWaterAbsorptionModel) = (root_water_assimilation=1.0,) -PlantSimEngine.outputs_(::ToyWaterAbsorptionModel) = (water_absorbed=0.0,) - -function PlantSimEngine.run!(m::ToyWaterAbsorptionModel, models, status, meteo, constants=nothing, extra=nothing) - #root_end = get_root_end_node(status.node) - #root_len = root_end[:Root_len] - status.water_absorbed = meteo.Precipitations * status.root_water_assimilation #* root_len -end - -PlantSimEngine.TimeStepDependencyTrait(::Type{<:ToyWaterAbsorptionModel}) = PlantSimEngine.IsTimeStepIndependent() -PlantSimEngine.ObjectDependencyTrait(::Type{<:ToyWaterAbsorptionModel}) = PlantSimEngine.IsObjectIndependent() - - -########################## -### Root growth : when water stocks are low, expand root -########################## - -PlantSimEngine.@process "root_growth" verbose = false - -struct ToyRootGrowthModel{T} <: AbstractRoot_GrowthModel - water_threshold::T - carbon_root_creation_cost::T - root_max_len::Int -end - -PlantSimEngine.inputs_(::ToyRootGrowthModel) = (water_stock=0.0, carbon_stock=0.0,) -PlantSimEngine.outputs_(::ToyRootGrowthModel) = (carbon_root_creation_consumed=0.0,) - -function PlantSimEngine.run!(m::ToyRootGrowthModel, models, status, meteo, constants=nothing, extra=nothing) - if status.water_stock < m.water_threshold && status.carbon_stock > m.carbon_root_creation_cost - - root_end = get_root_end_node(status.node) - - if length(root_end) != 1 - throw(AssertionError("Couldn't find MTG leaf node with symbol \"Root\"")) - end - root_len = get_roots_count(root_end[1]) - if root_len < m.root_max_len - st = add_organ!(root_end[1], extra, "<", :Root, 2, index=1) - status.carbon_root_creation_consumed = m.carbon_root_creation_cost - end - else - status.carbon_root_creation_consumed = 0.0 - end -end - -########################## -### Model accumulating carbon and water resources -########################## - -PlantSimEngine.@process "resource_stock_computation" verbose = false - -struct ToyStockComputationModel <: AbstractResource_Stock_ComputationModel -end -#status.water_stock += meteo.precipitations * root_water_assimilation_ratio - -PlantSimEngine.inputs_(::ToyStockComputationModel) = - (water_absorbed=0.0, carbon_captured=0.0, carbon_organ_creation_consumed=0.0, carbon_root_creation_consumed=0.0) - -PlantSimEngine.outputs_(::ToyStockComputationModel) = (water_stock=-Inf, carbon_stock=-Inf) - -function PlantSimEngine.run!(m::ToyStockComputationModel, models, status, meteo, constants=nothing, extra=nothing) - status.water_stock += sum(status.water_absorbed) #- status.water_transpiration - status.carbon_stock += sum(status.carbon_captured) - sum(status.carbon_organ_creation_consumed) - sum(status.carbon_root_creation_consumed) - - if status.water_stock < 0.0 - status.water_stock = 0.0 - end -end - -PlantSimEngine.TimeStepDependencyTrait(::Type{<:ToyStockComputationModel}) = PlantSimEngine.IsTimeStepIndependent() -PlantSimEngine.ObjectDependencyTrait(::Type{<:ToyStockComputationModel}) = PlantSimEngine.IsObjectIndependent() - -######################## -## Leaf model capturing some arbitrary carbon quantity -######################## - -PlantSimEngine.@process "leaf_carbon_capture" verbose = false - -struct ToyLeafCarbonCaptureModel <: AbstractLeaf_Carbon_CaptureModel end - -function PlantSimEngine.inputs_(::ToyLeafCarbonCaptureModel) - NamedTuple()#(TT_cu=-Inf) -end - -function PlantSimEngine.outputs_(::ToyLeafCarbonCaptureModel) - (carbon_captured=0.0,) -end - -function PlantSimEngine.run!(::ToyLeafCarbonCaptureModel, models, status, meteo, constants, extra) - # very crude approximation with LAI of 1 and constant aPPFD - status.carbon_captured = 200.0 * (1.0 - exp(-0.2)) -end - -PlantSimEngine.ObjectDependencyTrait(::Type{<:ToyLeafCarbonCaptureModel}) = PlantSimEngine.IsObjectIndependent() -PlantSimEngine.TimeStepDependencyTrait(::Type{<:ToyLeafCarbonCaptureModel}) = PlantSimEngine.IsTimeStepIndependent() - -mapping = ModelMapping( - :Scene => ToyDegreeDaysCumulModel(), - :Plant => ( - MultiScaleModel( - model=ToyStockComputationModel(), - mapped_variables=[ - :carbon_captured => [:Leaf], - :water_absorbed => [:Root], - :carbon_root_creation_consumed => [:Root], - :carbon_organ_creation_consumed => [:Internode]], - ), - Status(water_stock=0.0, carbon_stock=0.0) - ), - :Internode => ( - MultiScaleModel( - model=ToyCustomInternodeEmergence(),#TT_emergence=20.0), - mapped_variables=[:TT_cu => (:Scene => :TT_cu), - PreviousTimeStep(:water_stock) => (:Plant => :water_stock), - PreviousTimeStep(:carbon_stock) => (:Plant => :carbon_stock)], - ), - Status(carbon_organ_creation_consumed=0.0), - ), - :Root => (MultiScaleModel( - model=ToyRootGrowthModel(10.0, 50.0, 10), - mapped_variables=[PreviousTimeStep(:carbon_stock) => (:Plant => :carbon_stock), - PreviousTimeStep(:water_stock) => (:Plant => :water_stock)], - ), - ToyWaterAbsorptionModel(), - Status(carbon_root_creation_consumed=0.0, root_water_assimilation=1.0), - ), - :Leaf => (ToyLeafCarbonCaptureModel(),), -) - -mtg = MultiScaleTreeGraph.Node(MultiScaleTreeGraph.NodeMTG("/", :Scene, 1, 0)) - -plant = MultiScaleTreeGraph.Node(mtg, MultiScaleTreeGraph.NodeMTG("+", :Plant, 1, 1)) - -internode1 = MultiScaleTreeGraph.Node(plant, MultiScaleTreeGraph.NodeMTG("/", :Internode, 1, 2)) -MultiScaleTreeGraph.Node(internode1, MultiScaleTreeGraph.NodeMTG("+", :Leaf, 1, 2)) -MultiScaleTreeGraph.Node(internode1, MultiScaleTreeGraph.NodeMTG("+", :Leaf, 1, 2)) - -internode2 = MultiScaleTreeGraph.Node(internode1, MultiScaleTreeGraph.NodeMTG("<", :Internode, 1, 2)) -MultiScaleTreeGraph.Node(internode2, MultiScaleTreeGraph.NodeMTG("+", :Leaf, 1, 2)) -MultiScaleTreeGraph.Node(internode2, MultiScaleTreeGraph.NodeMTG("+", :Leaf, 1, 2)) - -plant_root_start = MultiScaleTreeGraph.Node( - plant, - MultiScaleTreeGraph.NodeMTG("+", :Root, 1, 3), -) - -meteo_day = CSV.read(joinpath(pkgdir(PlantSimEngine), "examples/meteo_day.csv"), DataFrame, header=18) - -outs = run!(mtg, mapping, meteo_day) -mtg - - -length(MultiScaleTreeGraph.traverse(mtg, x -> x, symbol=:Leaf)) diff --git a/examples/ToyMultiScalePlantTutorial/ToyPlantSimulation3.jl b/examples/ToyMultiScalePlantTutorial/ToyPlantSimulation3.jl deleted file mode 100644 index bdd4071b5..000000000 --- a/examples/ToyMultiScalePlantTutorial/ToyPlantSimulation3.jl +++ /dev/null @@ -1,251 +0,0 @@ -########################################### -# Toy plant model with an updated decision model for organ growth -# Physiologically and physically completely meaningless -# (no dimension for units, arbitrary values, stores water and carbon in abstract stocks, -# arbitrary max leaf count and root length, constant and non-coupled photosynthesis and water absorption, ...) -# But it should illustrate the basics of simulating a growing multiscale plant with PlantSimEngine's model approach -########################################### - -function get_root_end_node(node::MultiScaleTreeGraph.Node) - root = MultiScaleTreeGraph.get_root(node) - return MultiScaleTreeGraph.traverse(root, x -> x, symbol=:Root, filter_fun=MultiScaleTreeGraph.isleaf) -end - -function get_roots_count(node::MultiScaleTreeGraph.Node) - root = MultiScaleTreeGraph.get_root(node) - return length(MultiScaleTreeGraph.traverse(root, x -> x, symbol=:Root)) -end - -function get_n_leaves(node::MultiScaleTreeGraph.Node) - root = MultiScaleTreeGraph.get_root(node) - nleaves = length(MultiScaleTreeGraph.traverse(root, x -> 1, symbol=:Leaf)) - return nleaves -end - -PlantSimEngine.@process "organ_emergence" verbose = false - -struct ToyCustomInternodeEmergence{T} <: AbstractOrgan_EmergenceModel - TT_emergence::T - carbon_internode_creation_cost::T - leaf_surface_area::T - leaves_max_surface_area::T - water_leaf_threshold::T -end - -ToyCustomInternodeEmergence(; TT_emergence=300.0, carbon_internode_creation_cost=200.0, leaf_surface_area=3.0, leaves_max_surface_area=100.0, - water_leaf_threshold=30.0) = ToyCustomInternodeEmergence(TT_emergence, carbon_internode_creation_cost, leaf_surface_area, leaves_max_surface_area, water_leaf_threshold) - -PlantSimEngine.inputs_(m::ToyCustomInternodeEmergence) = (TT_cu=0.0, water_stock=0.0, carbon_stock=0.0, carbon_root_creation_consumed=0.0) -PlantSimEngine.outputs_(m::ToyCustomInternodeEmergence) = (TT_cu_emergence=0.0, carbon_organ_creation_consumed=0.0) - -function PlantSimEngine.run!(m::ToyCustomInternodeEmergence, models, status, meteo, constants=nothing, sim_object=nothing) - - leaves_surface_area = m.leaf_surface_area * get_n_leaves(status.node) - status.carbon_organ_creation_consumed = 0.0 - - if leaves_surface_area > m.leaves_max_surface_area - return nothing - end - - # if water levels are low, prioritise roots - if status.water_stock < m.water_leaf_threshold - return nothing - end - - # take into account that the stock may already be depleted - carbon_stock_updated_after_roots = status.carbon_stock - status.carbon_root_creation_consumed - - # if not enough carbon, no organ creation - if carbon_stock_updated_after_roots < m.carbon_internode_creation_cost - return nothing - end - - if length(MultiScaleTreeGraph.children(status.node)) == 2 && - status.TT_cu - status.TT_cu_emergence >= m.TT_emergence - status_new_internode = add_organ!(status.node, sim_object, "<", :Internode, 2, index=1) - add_organ!(status_new_internode.node, sim_object, "+", :Leaf, 2, index=1) - add_organ!(status_new_internode.node, sim_object, "+", :Leaf, 2, index=1) - - status_new_internode.TT_cu_emergence = m.TT_emergence - status.TT_cu - status.carbon_organ_creation_consumed = m.carbon_internode_creation_cost - end - - return nothing -end - -############################ -# Naive water absorption model -# Absorbs precipitation water depending on quantity of roots -############################ -PlantSimEngine.@process "water_absorption" verbose = false - -struct ToyWaterAbsorptionModel <: AbstractWater_AbsorptionModel -end - -PlantSimEngine.inputs_(::ToyWaterAbsorptionModel) = (root_water_assimilation=1.0,) -PlantSimEngine.outputs_(::ToyWaterAbsorptionModel) = (water_absorbed=0.0,) - -function PlantSimEngine.run!(m::ToyWaterAbsorptionModel, models, status, meteo, constants=nothing, extra=nothing) - #root_end = get_root_end_node(status.node) - #root_len = root_end[:Root_len] - status.water_absorbed = meteo.Precipitations * status.root_water_assimilation #* root_len -end - -PlantSimEngine.TimeStepDependencyTrait(::Type{<:ToyWaterAbsorptionModel}) = PlantSimEngine.IsTimeStepIndependent() -PlantSimEngine.ObjectDependencyTrait(::Type{<:ToyWaterAbsorptionModel}) = PlantSimEngine.IsObjectIndependent() - - -########################## -### Root growth : when water stocks are low, expand root -########################## - -PlantSimEngine.@process "root_growth" verbose = false - -struct ToyRootGrowthModel{T} <: AbstractRoot_GrowthModel - carbon_root_creation_cost::T - root_max_len::Int -end - -PlantSimEngine.inputs_(::ToyRootGrowthModel) = NamedTuple() -PlantSimEngine.outputs_(::ToyRootGrowthModel) = (carbon_root_creation_consumed=0.0,) - -function PlantSimEngine.run!(m::ToyRootGrowthModel, models, status, meteo, constants=nothing, extra=nothing) - status.carbon_root_creation_consumed = 0.0 - - root_end = get_root_end_node(status.node) - - if length(root_end) != 1 - throw(AssertionError("Couldn't find MTG leaf node with symbol \"Root\"")) - end - - root_len = get_roots_count(root_end[1]) - if root_len < m.root_max_len - st = add_organ!(root_end[1], extra, "<", :Root, 2, index=1) - status.carbon_root_creation_consumed = m.carbon_root_creation_cost - end -end - -########################## -### Decision model controlling the root growth model -########################## -PlantSimEngine.@process "root_growth_decision" verbose = false - -struct ToyRootGrowthDecisionModel{T} <: AbstractRoot_Growth_DecisionModel - water_threshold::T - carbon_root_creation_cost::T -end - -PlantSimEngine.inputs_(::ToyRootGrowthDecisionModel) = - (water_stock=0.0, carbon_stock=0.0) - -PlantSimEngine.outputs_(::ToyRootGrowthDecisionModel) = NamedTuple() - -PlantSimEngine.dep(::ToyRootGrowthDecisionModel) = (root_growth=AbstractRoot_GrowthModel => [:Root],) - -function PlantSimEngine.run!(m::ToyRootGrowthDecisionModel, models, status, meteo, constants=nothing, extra=nothing) - - if status.water_stock < m.water_threshold && status.carbon_stock > m.carbon_root_creation_cost - status_Root = extra.statuses[:Root][1] - PlantSimEngine.run!(extra.models[:Root].root_growth, models, status_Root, meteo, constants, extra) - end -end - - -########################## -### Model accumulating carbon and water resources -########################## - -PlantSimEngine.@process "resource_stock_computation" verbose = false - -struct ToyStockComputationModel <: AbstractResource_Stock_ComputationModel -end - -PlantSimEngine.inputs_(::ToyStockComputationModel) = - (water_absorbed=0.0, carbon_captured=0.0, carbon_organ_creation_consumed=0.0, carbon_root_creation_consumed=0.0) - -PlantSimEngine.outputs_(::ToyStockComputationModel) = (water_stock=-Inf, carbon_stock=-Inf) - -function PlantSimEngine.run!(m::ToyStockComputationModel, models, status, meteo, constants=nothing, extra=nothing) - status.water_stock += sum(status.water_absorbed) - status.carbon_stock += sum(status.carbon_captured) - sum(status.carbon_organ_creation_consumed) - sum(status.carbon_root_creation_consumed) -end - - -######################## -## Leaf model capturing some arbitrary carbon quantity -######################## - -PlantSimEngine.@process "leaf_carbon_capture" verbose = false - -struct ToyLeafCarbonCaptureModel <: AbstractLeaf_Carbon_CaptureModel end - -function PlantSimEngine.inputs_(::ToyLeafCarbonCaptureModel) - NamedTuple() -end - -function PlantSimEngine.outputs_(::ToyLeafCarbonCaptureModel) - (carbon_captured=0.0,) -end - -function PlantSimEngine.run!(::ToyLeafCarbonCaptureModel, models, status, meteo, constants, extra) - # very crude approximation with LAI of 1 and constant aPPFD - status.carbon_captured = 200.0 * (1.0 - exp(-0.2)) -end - - -mapping = ModelMapping( - :Scene => ToyDegreeDaysCumulModel(), - :Plant => ( - MultiScaleModel( - model=ToyStockComputationModel(), - mapped_variables=[ - :carbon_captured => [:Leaf], - :water_absorbed => [:Root], - PreviousTimeStep(:carbon_root_creation_consumed) => (:Root => :carbon_root_creation_consumed), - PreviousTimeStep(:carbon_organ_creation_consumed) => [:Internode], - ], - ), - ToyRootGrowthDecisionModel(10.0, 50.0), - Status(water_stock=0.0, carbon_stock=0.0) - ), - :Internode => ( - MultiScaleModel( - model=ToyCustomInternodeEmergence(),#TT_emergence=20.0), - mapped_variables=[:TT_cu => (:Scene => :TT_cu), - :water_stock => (:Plant => :water_stock), - :carbon_stock => (:Plant => :carbon_stock), - :carbon_root_creation_consumed => (:Root => :carbon_root_creation_consumed)], - ), - Status(carbon_organ_creation_consumed=0.0), - ), - :Root => (ToyRootGrowthModel(50.0, 10), - ToyWaterAbsorptionModel(), - Status(carbon_root_creation_consumed=0.0, root_water_assimilation=1.0), - ), - :Leaf => (ToyLeafCarbonCaptureModel(),), -) - -mtg = MultiScaleTreeGraph.Node(MultiScaleTreeGraph.NodeMTG("/", :Scene, 1, 0)) - -plant = MultiScaleTreeGraph.Node(mtg, MultiScaleTreeGraph.NodeMTG("+", :Plant, 1, 1)) - -internode1 = MultiScaleTreeGraph.Node(plant, MultiScaleTreeGraph.NodeMTG("/", :Internode, 1, 2)) -MultiScaleTreeGraph.Node(internode1, MultiScaleTreeGraph.NodeMTG("+", :Leaf, 1, 2)) -MultiScaleTreeGraph.Node(internode1, MultiScaleTreeGraph.NodeMTG("+", :Leaf, 1, 2)) - -internode2 = MultiScaleTreeGraph.Node(internode1, MultiScaleTreeGraph.NodeMTG("<", :Internode, 1, 2)) -MultiScaleTreeGraph.Node(internode2, MultiScaleTreeGraph.NodeMTG("+", :Leaf, 1, 2)) -MultiScaleTreeGraph.Node(internode2, MultiScaleTreeGraph.NodeMTG("+", :Leaf, 1, 2)) - -plant_root_start = MultiScaleTreeGraph.Node( - plant, - MultiScaleTreeGraph.NodeMTG("+", :Root, 1, 3), -) - -meteo_day = CSV.read(joinpath(pkgdir(PlantSimEngine), "examples/meteo_day.csv"), DataFrame, header=18) - -outs = run!(mtg, mapping, meteo_day) -mtg - - -length(MultiScaleTreeGraph.traverse(mtg, x -> x, symbol=:Leaf)) diff --git a/examples/ToyMultiScalePlantTutorial/ToyPlantSimulation4.jl b/examples/ToyMultiScalePlantTutorial/ToyPlantSimulation4.jl deleted file mode 100644 index 1684ab44e..000000000 --- a/examples/ToyMultiScalePlantTutorial/ToyPlantSimulation4.jl +++ /dev/null @@ -1,148 +0,0 @@ -########################################### -# Toy plant model MTG visualisation using PlantGeom -########################################### -using PlantSimEngine - -using MultiScaleTreeGraph -using PlantSimEngine.Examples -using Pkg -Pkg.add("CSV") -using CSV -include("ToyPlantSimulation3.jl") - -using Plots -using PlantGeom -# reusing the mtg from part 3: -RecipesBase.plot(mtg) - -#= -using GLMakie -#using CairoMakie -using PlantGeom - -PlantGeom.diagram(mtg)=# - - -using PlantGeom.Meshes - -# Internodes and roots will use a cylinder as a mesh - -cylinder() = Meshes.CylinderSurface(1.0) |> Meshes.discretize |> Meshes.simplexify - -refmesh_internode = PlantGeom.RefMesh("Internode", cylinder()) -refmesh_root = PlantGeom.RefMesh("Root", cylinder()) - -# Leaves and petioles are a single mesh, read from a .ply file - -Pkg.add("PlyIO") -using PlyIO -function read_ply(fname) - ply = PlyIO.load_ply(fname) - x = ply["vertex"]["x"] - y = ply["vertex"]["y"] - z = ply["vertex"]["z"] - points = Meshes.Point.(x, y, z) - connec = [Meshes.connect(Tuple(c .+ 1)) for c in ply["face"]["vertex_indices"]] - Meshes.SimpleMesh(points, connec) -end - -leaf_ply = read_ply("examples/leaf_with_petiole.ply") -refmesh_leaf = PlantGeom.RefMesh("Leaf", leaf_ply) - -Pkg.add("TransformsBase") -Pkg.add("Rotations") -#using PlantGeom.TranformsBase -import TransformsBase: → -import Rotations: RotY, RotZ, RotX -# Add the geometry to the MTG, with transformations -function add_geometry!(mtg, refmesh_internode) - - # incremental offset - internode_height = 0.0 - - # relative scale of the base mesh - internode_width = 0.5 - - # length of the base mesh - internode_length = 1.0 - - traverse!(mtg) do node - if symbol(node) == :Internode - # Set to scale, then translate by the total height - mesh_transformation = Meshes.Scale(internode_width, internode_width, internode_length) → Meshes.Translate(0.0, 0.0, internode_height) - node.geometry = PlantGeom.Geometry(ref_mesh=refmesh_internode, transformation=mesh_transformation) - - internode_height += internode_length - end - end -end - -add_geometry!(mtg, refmesh_internode) - -# Visualize the mesh -using GLMakie -viz(mtg) - -function add_geometry!(mtg, refmesh_internode, refmesh_root, refmesh_leaf) - - # incremental offset - internode_height = 0.0 - root_depth = 0.0 - - # relative scale of the base mesh - internode_width = 0.5 - root_width = 0.2 - - # length of the base mesh - internode_length = 1.0 - root_length = 1.0 - - # ad hoc value to adjust the base mesh to the scene scale - leaf_mesh_scale = 25 - leaf_scale_width = 0.4*leaf_mesh_scale - leaf_scale_height = 0.4*leaf_mesh_scale - - # Helpers to make the leaves opposite decussate - leaf_rotation = MathConstants.pi / 2.0 - i = 0 - - traverse!(mtg) do node - if symbol(node) == :Internode - # Set to scale, then translate by the total height - mesh_transformation = Meshes.Scale(internode_width, internode_width, internode_length) → Meshes.Translate(0.0, 0.0, internode_height) - node.geometry = PlantGeom.Geometry(ref_mesh=refmesh_internode, transformation=mesh_transformation) - - internode_height += node_length - - # Leaves are placed relatively to the parent internode - for chnode in children(node) - if symbol(chnode) == :Leaf - # Leaves are placed halfway along the the parent internode - mesh_transformation = Meshes.Scale(leaf_scale_width, leaf_scale_width, leaf_scale_height) → Meshes.Rotate(RotX(-MathConstants.pi / 6.0)) → Meshes.Translate(0.0, -internode_width, internode_height - internode_length / 2.0) → Meshes.Rotate(RotZ(leaf_rotation)) - chnode.geometry = PlantGeom.Geometry(ref_mesh=refmesh_leaf, transformation=mesh_transformation) - # Set the second leaf in a pair opposite to the first one => add a 180° rotation - leaf_rotation += MathConstants.pi - end - end - - # Opposite decussate => 90° rotation between pairs - i += 1 - if i % 2 == 0 - leaf_rotation = MathConstants.pi / 2.0 - else - leaf_rotation = MathConstants.pi - end - - elseif symbol(node) == :Root - mesh_transformation = Meshes.Scale(root_width, root_width, root_length) → Meshes.Translate(0.0, 0.0, root_depth) → Meshes.Rotate(RotZ(MathConstants.pi)) - node.geometry = PlantGeom.Geometry(ref_mesh=refmesh_root, transformation=mesh_transformation) - root_depth -= root_length - end - end -end - -add_geometry!(mtg, refmesh_internode, refmesh_root, refmesh_leaf) - -# Visualize the mesh -using GLMakie -viz(mtg) \ No newline at end of file diff --git a/examples/ToyRUEGrowthModel.jl b/examples/ToyRUEGrowthModel.jl index c3db5cb6b..a74470b66 100644 --- a/examples/ToyRUEGrowthModel.jl +++ b/examples/ToyRUEGrowthModel.jl @@ -30,24 +30,21 @@ end # Define inputs: function PlantSimEngine.inputs_(::ToyRUEGrowthModel) - (aPPFD=-Inf,) + (aPPFD=Required(Real),) end # Define outputs: -function PlantSimEngine.outputs_(::ToyRUEGrowthModel) - (biomass=0.0, biomass_increment=-Inf) +function PlantSimEngine.outputs_(model::ToyRUEGrowthModel) + (biomass=zero(model.efficiency), biomass_increment=oftype(float(model.efficiency), -Inf)) end # Tells Julia what is the type of elements: Base.eltype(x::ToyRUEGrowthModel{T}) where {T} = T # Implement the growth model: -function PlantSimEngine.run!(::ToyRUEGrowthModel, models, status, meteo, constants, extra) - status.biomass_increment = status.aPPFD * models.growth.efficiency +function PlantSimEngine.run!(model::ToyRUEGrowthModel, status, environment, constants, context) + status.biomass_increment = status.aPPFD * model.efficiency status.biomass += status.biomass_increment end -# And optionally, we can tell PlantSimEngine that we can safely parallelize our model over space (objects): -PlantSimEngine.ObjectDependencyTrait(::Type{<:ToyRUEGrowthModel}) = PlantSimEngine.IsObjectIndependent() - -# Note that this model cannot be parallelized over time because we use the biomass from the previous time-step. \ No newline at end of file +# The model uses biomass from the previous timestep, so time steps are stateful. diff --git a/examples/ToySingleToMultiScale.jl b/examples/ToySingleToMultiScale.jl deleted file mode 100644 index af43b48a9..000000000 --- a/examples/ToySingleToMultiScale.jl +++ /dev/null @@ -1,119 +0,0 @@ -############################## -### Example single- to multi-scale conversion -############################## - -# Environment setup -using CSV -using DataFrames -using PlantSimEngine -using PlantMeteo -using PlantSimEngine.Examples -using MultiScaleTreeGraph - -# Weather data for all simulations -meteo_day = CSV.read(joinpath(pkgdir(PlantSimEngine), "examples/meteo_day.csv"), DataFrame, header=18) - -############################## -### Single-scale simulation -############################## - -models_singlescale = ModelMapping( - ToyLAIModel(), - Beer(0.5), - ToyRUEGrowthModel(0.2), - status=(TT_cu=cumsum(meteo_day.TT),), -) - -outputs_singlescale = run!(models_singlescale, meteo_day) - -############################## -#### Direct translation of the single-scale simulation -############################## -mapping_pseudo_multiscale = ModelMapping( - :Plant => ( - ToyLAIModel(), - Beer(0.5), - ToyRUEGrowthModel(0.2), - Status(TT_cu=cumsum(meteo_day.TT),) - ), -) - -mtg = MultiScaleTreeGraph.Node(MultiScaleTreeGraph.NodeMTG("/", :Plant, 1, 0),) - -# will generate an error as vectors can't be directly passed into a Status in multi-scale simulations -out_pseudo_multiscale = run!(mtg, mapping_pseudo_multiscale, meteo_day) - -############################## -#### Ad Hoc Cumulated Thermal Time Model -############################## - -PlantSimEngine.@process "tt_cu" verbose = false - -struct ToyTt_CuModel <: AbstractTt_CuModel -end - -function PlantSimEngine.run!(::ToyTt_CuModel, models, status, meteo, constants, extra=nothing) - status.TT_cu += meteo.TT -end - -function PlantSimEngine.inputs_(::ToyTt_CuModel) - NamedTuple() -end - -function PlantSimEngine.outputs_(::ToyTt_CuModel) - (TT_cu=-Inf,) -end - -############################## -#### Actual multiscale version of the single-scale simulation -############################## - -mapping_multiscale = ModelMapping( - :Scene => ( - ToyTt_CuModel(), - Status(TT_cu=0.0), - ), - :Plant => ( - MultiScaleModel( - model=ToyLAIModel(), - mapped_variables=[ - :TT_cu => (:Scene => :TT_cu), - ], - ), - Beer(0.5), - ToyRUEGrowthModel(0.2), - ), -) - -# We now need two nodes for our MTG -mtg_multiscale = MultiScaleTreeGraph.Node(MultiScaleTreeGraph.NodeMTG("/", :Scene, 1, 0)) -plant = MultiScaleTreeGraph.Node(mtg_multiscale, MultiScaleTreeGraph.NodeMTG("+", :Plant, 1, 1)) -outputs_multiscale = run!(mtg_multiscale, mapping_multiscale, meteo_day) - -############################## -#### Output comparison -############################## - -computed_TT_cu_multiscale = collect(Base.Iterators.flatten(outputs_multiscale[:Scene][:TT_cu])) - -is_approx_equal_1 = true - -for i in 1:length(computed_TT_cu_multiscale) - if !(computed_TT_cu_multiscale[i] ≈ outputs_singlescale.TT_cu[i]) - is_approx_equal_1 = false - break - end -end - -is_approx_equal_1 - -is_approx_equal_2 = length(unique(computed_TT_cu_multiscale .≈ outputs_singlescale.TT_cu)) == 1 - - -# Note : it is also possible to get the weather data length via PlantSimEngine.get_nsteps(meteo_day) -# instead of checking for array length - -is_perfectly_equal = length(unique(computed_TT_cu_multiscale .== outputs_singlescale.TT_cu)) == 1 - -(computed_TT_cu_multiscale.==outputs_singlescale.TT_cu)[104] -(computed_TT_cu_multiscale.==outputs_singlescale.TT_cu)[105] diff --git a/examples/ToySoilModel.jl b/examples/ToySoilModel.jl index 7d0c20b3a..b3b9b9845 100644 --- a/examples/ToySoilModel.jl +++ b/examples/ToySoilModel.jl @@ -16,23 +16,21 @@ the `values` range using `rand`. - `values`: a range of `soil_water_content` values to sample from. Can be a vector of values `[0.5,0.6]` or a range `0.1:0.1:1.0`. Default is `[0.5]`. """ -struct ToySoilWaterModel{T<:Union{AbstractRange{Float64},AbstractVector{Float64}}} <: AbstractSoil_WaterModel +struct ToySoilWaterModel{T<:Union{AbstractRange,AbstractVector}} <: AbstractSoil_WaterModel values::T end -# Defining a method with keyword arguments and default values: -ToySoilWaterModel(values=[0.5]) = ToySoilWaterModel(values) +# Defining a zero-argument default without shadowing the generated positional +# constructor. +ToySoilWaterModel() = ToySoilWaterModel([0.5]) # Defining the inputs and outputs of the model: PlantSimEngine.inputs_(::ToySoilWaterModel) = NamedTuple() -PlantSimEngine.outputs_(::ToySoilWaterModel) = (soil_water_content=-Inf,) +PlantSimEngine.outputs_(m::ToySoilWaterModel) = ( + soil_water_content=oftype(float(first(m.values)), -Inf), +) # Implementing the actual algorithm by adding a method to the run! function for our model: -function PlantSimEngine.run!(m::ToySoilWaterModel, models, status, meteo, constants=nothing, extra=nothing) +function PlantSimEngine.run!(m::ToySoilWaterModel, status, environment, constants, context) status.soil_water_content = rand(m.values) end - -# The computation of ToySoilWaterModel is independant of previous values and other objects. We can add this information as -# traits to the model to tell PlantSimEngine that it is safe to run the models in parallel: -PlantSimEngine.TimeStepDependencyTrait(::Type{<:ToySoilWaterModel}) = PlantSimEngine.IsTimeStepIndependent() -PlantSimEngine.ObjectDependencyTrait(::Type{<:ToySoilWaterModel}) = PlantSimEngine.IsObjectIndependent() \ No newline at end of file diff --git a/examples/ToySpatialEnvironment.jl b/examples/ToySpatialEnvironment.jl new file mode 100644 index 000000000..9cb7a4b5e --- /dev/null +++ b/examples/ToySpatialEnvironment.jl @@ -0,0 +1,197 @@ +""" + ToySpatialEnvironment(cells; step_seconds=3600.0) + +A minimal spatial environment for examples and tests. + +`cells` maps cell ids to named tuples of environment variables. Objects select +a cell with geometry such as `(cell=:sun,)`. PlantSimEngine compiles that cell +id into a [`ToyEnvironmentHandle`](@ref), so sampling does not resolve geometry +inside the model kernel loop. An application configured with `sink=:cells` may +also commit an accepted named-tuple state to its bound cell. +""" +struct ToySpatialEnvironment{C,T} <: + PlantSimEngine.EnvironmentAPI.AbstractEnvironmentBackend + cells::C + step_seconds::T +end + +ToySpatialEnvironment(cells; step_seconds=3600.0) = + ToySpatialEnvironment(cells, float(step_seconds)) + +""" + ToyEnvironmentHandle + +Opaque compiled handle returned by [`ToySpatialEnvironment`](@ref). +""" +struct ToyEnvironmentHandle + cell::Symbol + sink::Union{Nothing,Symbol} +end + +PlantSimEngine.EnvironmentAPI.base_step_seconds(backend::ToySpatialEnvironment) = + backend.step_seconds +PlantSimEngine.EnvironmentAPI.get_nsteps(::ToySpatialEnvironment) = 1 + +function PlantSimEngine.EnvironmentAPI.environment_variables( + backend::ToySpatialEnvironment, +) + isempty(backend.cells) && return Set{Symbol}() + return Set(Symbol.(propertynames(first(values(backend.cells))))) +end + +function PlantSimEngine.EnvironmentAPI.bind_environment( + backend::ToySpatialEnvironment, + object::PlantSimEngine.Object, + context::PlantSimEngine.EnvironmentAPI.EnvironmentContext, + config, +) + object_geometry = PlantSimEngine.geometry(object) + object_geometry isa NamedTuple && haskey(object_geometry, :cell) || error( + "ToySpatialEnvironment needs `(cell=...,)` geometry for object " * + "`$(object.id.value)`.", + ) + cell = Symbol(object_geometry.cell) + haskey(backend.cells, cell) || error( + "ToySpatialEnvironment has no cell `$(cell)` for object " * + "`$(object.id.value)`.", + ) + sink = + isnothing(config) || !haskey(config, :sink) ? + nothing : Symbol(config.sink) + isnothing(sink) || sink == :cells || error( + "ToySpatialEnvironment only supports `sink=:cells`, got " * + "`$(sink)`.", + ) + return ToyEnvironmentHandle(cell, sink) +end + +function PlantSimEngine.EnvironmentAPI.sample( + backend::ToySpatialEnvironment, + handle::ToyEnvironmentHandle, + variable::Symbol, + time, +) + row = backend.cells[handle.cell] + hasproperty(row, variable) || error( + "ToySpatialEnvironment cell `$(handle.cell)` does not provide " * + "variable `$(variable)`.", + ) + return getproperty(row, variable) +end + +function PlantSimEngine.EnvironmentAPI.sample( + backend::ToySpatialEnvironment, + handle::ToyEnvironmentHandle, + state::NamedTuple, + variable::Symbol, + time, +) + hasproperty(state, variable) || error( + "ToySpatialEnvironment trial state does not provide variable " * + "`$(variable)`.", + ) + return getproperty(state, variable) +end + +function PlantSimEngine.EnvironmentAPI.commit_environment!( + backend::ToySpatialEnvironment, + handle::ToyEnvironmentHandle, + state::NamedTuple, + time, +) + handle.sink == :cells || error( + "ToySpatialEnvironment handle for cell `$(handle.cell)` has no " * + "commit sink.", + ) + backend.cells[handle.cell] = state + return nothing +end + +PlantSimEngine.@process "toy_environment_reader" verbose = false +PlantSimEngine.@process "toy_environment_controller" verbose = false + +""" + ToyEnvironmentReaderModel() + +Read temperature from the model-facing environment. +""" +struct ToyEnvironmentReaderModel <: AbstractToy_Environment_ReaderModel end + +PlantSimEngine.inputs_(::ToyEnvironmentReaderModel) = NamedTuple() +PlantSimEngine.outputs_(::ToyEnvironmentReaderModel) = (temperature_seen=0.0,) +PlantSimEngine.environment_inputs_(::ToyEnvironmentReaderModel) = (T=0.0,) + +function PlantSimEngine.run!( + ::ToyEnvironmentReaderModel, + status, + environment, + constants, + context, +) + status.temperature_seen = environment.T + return nothing +end + +""" + ToyEnvironmentControllerModel(trial_temperature, accepted_temperature) + +Demonstrate a typed trial environment followed by one accepted environment +commit and publication. +""" +struct ToyEnvironmentControllerModel{T} <: + AbstractToy_Environment_ControllerModel + trial_temperature::T + accepted_temperature::T +end + +function ToyEnvironmentControllerModel(trial_temperature, accepted_temperature) + parameters = promote( + float(trial_temperature), + float(accepted_temperature), + ) + return ToyEnvironmentControllerModel(parameters...) +end + +PlantSimEngine.inputs_(::ToyEnvironmentControllerModel) = NamedTuple() +PlantSimEngine.dep(::ToyEnvironmentControllerModel) = ( + reader=Call(One(process=:toy_environment_reader)), +) +function PlantSimEngine.outputs_(model::ToyEnvironmentControllerModel) + initial = zero(model.accepted_temperature) + return ( + trial_temperature_seen=initial, + accepted_temperature_seen=initial, + ) +end +PlantSimEngine.environment_outputs_(model::ToyEnvironmentControllerModel) = ( + T=zero(model.accepted_temperature), +) + +function PlantSimEngine.run!( + model::ToyEnvironmentControllerModel, + status, + environment, + constants, + context, +) + trial_environment = (T=model.trial_temperature,) + trial_target = only(run_call!( + context, + :reader; + environment=trial_environment, + publish=false, + )) + status.trial_temperature_seen = trial_target.status.temperature_seen + + accepted_environment = (T=model.accepted_temperature,) + commit_environment!(context, accepted_environment) + accepted_target = only(run_call!( + context, + :reader; + environment=accepted_environment, + publish=true, + )) + status.accepted_temperature_seen = + accepted_target.status.temperature_seen + return nothing +end diff --git a/examples/benchmark.jl b/examples/benchmark.jl deleted file mode 100644 index a372ad467..000000000 --- a/examples/benchmark.jl +++ /dev/null @@ -1,31 +0,0 @@ -#]add BenchmarkTools - -using BenchmarkTools -using PlantSimEngine, PlantMeteo, DataFrames, CSV, Dates, Statistics -# using PlantSimEngine.Examples - -meteo_day = read_weather(joinpath(pkgdir(PlantSimEngine), "examples/meteo_day.csv"), duration=Day) -models = ModelMapping( - ToyLAIModel(), - status=(TT_cu=cumsum(meteo_day.TT),), -) - -# Match the warning on the executor, the default is ThreadedEx() but ToyRUEGrowthModel can't be run in parallel: -time_run = @benchmark run!($models, $meteo_day) - -median_time_ns = median(time_run.times) / nrow(meteo_day) - -# If we provide a serial executor, it works without a warning: -time_run_seq = @benchmark run!($models, $meteo_day, executor=$(SequentialEx())) -median_time_seq_ns = median(time_run_seq.times) / nrow(meteo_day) - -# Coupled model: -models_coupled = ModelMapping( - ToyLAIModel(), - Beer(0.5), - status=(TT_cu=cumsum(meteo_day.TT),), -) - -# Match the warning on the executor, the default is ThreadedEx() but ToyRUEGrowthModel can't be run in parallel: -time_run_coupled = @benchmark run!($models_coupled, $meteo_day) -median_time_coupled_ns = median(time_run_coupled.times) / nrow(meteo_day) diff --git a/examples/dummy.jl b/examples/dummy.jl index f3a556f1d..eb84eac0d 100644 --- a/examples/dummy.jl +++ b/examples/dummy.jl @@ -13,13 +13,11 @@ A dummy model implementing a "process1" process for testing purposes. struct Process1Model <: AbstractProcess1Model a end -PlantSimEngine.inputs_(::Process1Model) = (var1=-Inf, var2=-Inf) +PlantSimEngine.inputs_(::Process1Model) = (var1=Required(Float64), var2=Required(Float64)) PlantSimEngine.outputs_(::Process1Model) = (var3=-Inf,) -function PlantSimEngine.run!(::Process1Model, models, status, meteo, constants=nothing, extra=nothing) - status.var3 = models.process1.a + status.var1 * status.var2 +function PlantSimEngine.run!(model::Process1Model, status, environment, constants, context) + status.var3 = model.a + status.var1 * status.var2 end -PlantSimEngine.TimeStepDependencyTrait(::Type{<:Process1Model}) = PlantSimEngine.IsTimeStepIndependent() -PlantSimEngine.ObjectDependencyTrait(::Type{<:Process1Model}) = PlantSimEngine.IsObjectIndependent() # Defining a 2nd process called "process2", and a model @@ -32,18 +30,19 @@ PlantSimEngine.@process "process2" verbose = false A dummy model implementing a "process2" process for testing purposes. """ struct Process2Model <: AbstractProcess2Model end -PlantSimEngine.inputs_(::Process2Model) = (var1=-Inf, var3=-Inf) +PlantSimEngine.inputs_(::Process2Model) = (var1=Required(Float64), var3=Required(Float64)) PlantSimEngine.outputs_(::Process2Model) = (var4=-Inf, var5=-Inf) -PlantSimEngine.dep(::Process2Model) = (process1=AbstractProcess1Model,) -function PlantSimEngine.run!(::Process2Model, models, status, meteo, constants=nothing, extra=nothing) +PlantSimEngine.environment_inputs_(::Process2Model) = (T=0.0, Wind=0.0, Rh=0.0) +PlantSimEngine.dep(::Process2Model) = ( + process1=PlantSimEngine.Call(PlantSimEngine.One(process=:process1)), +) +function PlantSimEngine.run!(::Process2Model, status, environment, constants, context) # computing var3 using process1: - PlantSimEngine.run!(models.process1, models, status, meteo, constants) + PlantSimEngine.run_call!(context, :process1; publish=true) # computing var4 and var5: status.var4 = status.var3 * 2.0 - status.var5 = status.var4 + 1.0 * meteo.T + 2.0 * meteo.Wind + 3.0 * meteo.Rh + status.var5 = status.var4 + 1.0 * environment.T + 2.0 * environment.Wind + 3.0 * environment.Rh end -PlantSimEngine.TimeStepDependencyTrait(::Type{<:Process2Model}) = PlantSimEngine.IsTimeStepIndependent() -PlantSimEngine.ObjectDependencyTrait(::Type{<:Process2Model}) = PlantSimEngine.IsObjectIndependent() # Defining a 3d process called "process3", and a model # that implements an algorithm, and that depends on the second one (and @@ -56,20 +55,20 @@ PlantSimEngine.@process "process3" verbose = false A dummy model implementing a "process3" process for testing purposes. """ struct Process3Model <: AbstractProcess3Model end -PlantSimEngine.inputs_(::Process3Model) = (var5=-Inf,) +PlantSimEngine.inputs_(::Process3Model) = (var5=Required(Float64),) PlantSimEngine.outputs_(::Process3Model) = (var4=-Inf, var6=-Inf,) # NB: var4 is computed by process2, so it is not in the inputs, it is also recomputed by this model, # so we need a hard dependency on process2: -PlantSimEngine.dep(::Process3Model) = (process2=Process2Model,) -function PlantSimEngine.run!(::Process3Model, models, status, meteo, constants=nothing, extra=nothing) - # computing var3 using process1: - PlantSimEngine.run!(models.process2, models, status, meteo, constants, extra) +PlantSimEngine.dep(::Process3Model) = ( + process2=PlantSimEngine.Call(PlantSimEngine.One(process=:process2)), +) +function PlantSimEngine.run!(::Process3Model, status, environment, constants, context) + # computing var3, var4 and var5 using process2 (which calls process1): + PlantSimEngine.run_call!(context, :process2; publish=true) # re-computing var4: status.var4 = status.var4 * 2.0 status.var6 = status.var5 + status.var4 end -PlantSimEngine.TimeStepDependencyTrait(::Type{<:Process3Model}) = PlantSimEngine.IsTimeStepIndependent() -PlantSimEngine.ObjectDependencyTrait(::Type{<:Process3Model}) = PlantSimEngine.IsObjectIndependent() # Defining a 4th process called "process4", and a model # that implements an algorithm, and that computes the @@ -83,16 +82,14 @@ A dummy model implementing a "process4" process for testing purposes. It computes the inputs needed for the coupled processes 1-2-3. """ struct Process4Model <: AbstractProcess4Model end -PlantSimEngine.inputs_(::Process4Model) = (var0=-Inf,) +PlantSimEngine.inputs_(::Process4Model) = (var0=Required(Float64),) PlantSimEngine.outputs_(::Process4Model) = (var1=-Inf, var2=-Inf) -function PlantSimEngine.run!(::Process4Model, models, status, meteo, constants=nothing, extra=nothing) +function PlantSimEngine.run!(::Process4Model, status, environment, constants, context) # computing var3 using process1: # re-computing var4: status.var1 = status.var0 + 0.01 status.var2 = status.var1 + 0.02 end -PlantSimEngine.TimeStepDependencyTrait(::Type{<:Process4Model}) = PlantSimEngine.IsTimeStepIndependent() -PlantSimEngine.ObjectDependencyTrait(::Type{<:Process4Model}) = PlantSimEngine.IsObjectIndependent() # Defining a 5th process called "process5", and a model # that implements an algorithm, and that computes other @@ -106,13 +103,11 @@ A dummy model implementing a "process5" process for testing purposes. It needs the outputs from the coupled processes 1-2-3. """ struct Process5Model <: AbstractProcess5Model end -PlantSimEngine.inputs_(::Process5Model) = (var5=-Inf, var6=-Inf) +PlantSimEngine.inputs_(::Process5Model) = (var5=Required(Float64), var6=Required(Float64)) PlantSimEngine.outputs_(::Process5Model) = (var7=-Inf,) -function PlantSimEngine.run!(::Process5Model, models, status, meteo, constants=nothing, extra=nothing) +function PlantSimEngine.run!(::Process5Model, status, environment, constants, context) status.var7 = status.var5 * status.var6 end -PlantSimEngine.TimeStepDependencyTrait(::Type{<:Process5Model}) = PlantSimEngine.IsTimeStepIndependent() -PlantSimEngine.ObjectDependencyTrait(::Type{<:Process5Model}) = PlantSimEngine.IsObjectIndependent() # Defining a 6th process called "process6", and a model @@ -128,13 +123,11 @@ It needs the outputs from the coupled processes 1-2-3, but also from process 7 that is itself independant. """ struct Process6Model <: AbstractProcess6Model end -PlantSimEngine.inputs_(::Process6Model) = (var7=-Inf, var9=-Inf) +PlantSimEngine.inputs_(::Process6Model) = (var7=Required(Float64), var9=Required(Float64)) PlantSimEngine.outputs_(::Process6Model) = (var8=-Inf,) -function PlantSimEngine.run!(::Process6Model, models, status, meteo, constants=nothing, extra=nothing) +function PlantSimEngine.run!(::Process6Model, status, environment, constants, context) status.var8 = status.var7 + 1.0 end -PlantSimEngine.TimeStepDependencyTrait(::Type{<:Process6Model}) = PlantSimEngine.IsTimeStepIndependent() -PlantSimEngine.ObjectDependencyTrait(::Type{<:Process6Model}) = PlantSimEngine.IsObjectIndependent() # Defining a 7th process called "process7", and a model # that depends on nothing but var0 so it is independant. @@ -150,10 +143,8 @@ It is independent (needs :var0 only as for Process4Model), but its outputs are used by Process6Model, so it is a soft-coupling. """ struct Process7Model <: AbstractProcess7Model end -PlantSimEngine.inputs_(::Process7Model) = (var0=-Inf, var3=-Inf) +PlantSimEngine.inputs_(::Process7Model) = (var0=Required(Float64), var3=Required(Float64)) PlantSimEngine.outputs_(::Process7Model) = (var9=-Inf,) -function PlantSimEngine.run!(::Process7Model, models, status, meteo, constants=nothing, extra=nothing) +function PlantSimEngine.run!(::Process7Model, status, environment, constants, context) status.var9 = status.var0 + 1.0 end -PlantSimEngine.TimeStepDependencyTrait(::Type{<:Process7Model}) = PlantSimEngine.IsTimeStepIndependent() -PlantSimEngine.ObjectDependencyTrait(::Type{<:Process7Model}) = PlantSimEngine.IsObjectIndependent() diff --git a/examples/maespa_model_example.jl b/examples/maespa_model_example.jl new file mode 100644 index 000000000..3ff437be8 --- /dev/null +++ b/examples/maespa_model_example.jl @@ -0,0 +1,789 @@ +using Dates +using PlantMeteo +using PlantSimEngine + +include(joinpath(@__DIR__, "plantbiophysics_subsample", "Tuzet.jl")) +include(joinpath(@__DIR__, "plantbiophysics_subsample", "FvCB.jl")) +include(joinpath(@__DIR__, "plantbiophysics_subsample", "Monteith.jl")) + +PlantSimEngine.@process "maespa_soil_water" verbose = false +PlantSimEngine.@process "scene_eb" verbose = false +PlantSimEngine.@process "leaf_state" verbose = false +PlantSimEngine.@process "maespa_lai_dynamic" verbose = false +PlantSimEngine.@process "alloc_a" verbose = false +PlantSimEngine.@process "alloc_b" verbose = false + +duration_seconds(environment) = Dates.value(Dates.Millisecond(environment.duration)) / 1000.0 +mutable struct MaespaSingleLayerEnvironment{F,C} <: + PlantSimEngine.EnvironmentAPI.AbstractEnvironmentBackend + forcing::F # MAESPA forcing data (Meteo data from above the canopy) + canopy::C # Within-canopy computed microclimate +end + +struct MaespaEnvironmentHandle + provider::Symbol + sink::Union{Nothing,Symbol} +end + +function MaespaSingleLayerEnvironment(forcing; canopy=_maespa_meteo_row(forcing, 1)) + canopy = Atmosphere( + T=canopy.T, + Rh=canopy.Rh, + Wind=canopy.Wind, + P=canopy.P, + Cₐ=canopy.Cₐ, + Ri_PAR_f=canopy.Ri_PAR_f, + Ri_SW_f=canopy.Ri_SW_f, + duration=canopy.duration, + ) + return MaespaSingleLayerEnvironment( + forcing, + canopy, + ) +end + +_maespa_meteo_row(environment, time) = + first(Iterators.drop(environment, clamp(Int(round(time)), 1, PlantSimEngine.get_nsteps(environment)) - 1)) + +PlantSimEngine.EnvironmentAPI.base_step_seconds( + backend::MaespaSingleLayerEnvironment, +) = PlantSimEngine.EnvironmentAPI.base_step_seconds( + PlantSimEngine.EnvironmentAPI.environment_backend(backend.forcing), +) +PlantSimEngine.EnvironmentAPI.get_nsteps( + backend::MaespaSingleLayerEnvironment, +) = PlantSimEngine.EnvironmentAPI.get_nsteps(backend.forcing) +PlantSimEngine.EnvironmentAPI.environment_variables( + ::MaespaSingleLayerEnvironment, +) = Set([ + :T, :Rh, :Wind, :P, :Cₐ, :Ri_PAR_f, :Ri_SW_f, :duration, :VPD, :ε, :γ, :Δ, :ρ, :λ, +]) + +function PlantSimEngine.EnvironmentAPI.bind_environment( + backend::MaespaSingleLayerEnvironment, + object::Object, + context::PlantSimEngine.EnvironmentAPI.EnvironmentContext, + config, +) + provider = isnothing(config) ? :canopy : Symbol(config.provider) + sink = isnothing(config) || !haskey(config, :sink) ? nothing : Symbol(config.sink) + provider in (:forcing, :canopy) || error( + "MAESPA single-layer environment provider must be `:forcing` or `:canopy`, got `$(provider)`." + ) + isnothing(sink) || sink == :canopy || error( + "MAESPA single-layer environment sink must be `:canopy`, got `$(sink)`." + ) + return MaespaEnvironmentHandle(provider, sink) +end + +function PlantSimEngine.EnvironmentAPI.sample( + backend::MaespaSingleLayerEnvironment, + handle::MaespaEnvironmentHandle, + variable::Symbol, + time, +) + environment = handle.provider == :forcing ? + _maespa_meteo_row(backend.forcing, time) : + backend.canopy + return getproperty(environment, variable) +end + +function PlantSimEngine.EnvironmentAPI.sample( + backend::MaespaSingleLayerEnvironment{F,C}, + handle::MaespaEnvironmentHandle, + state::C, + variable::Symbol, + time, +) where {F,C} + environment = handle.provider == :forcing ? + _maespa_meteo_row(backend.forcing, time) : + state + return getproperty(environment, variable) +end + +function PlantSimEngine.EnvironmentAPI.commit_environment!( + backend::MaespaSingleLayerEnvironment{F,C}, + handle::MaespaEnvironmentHandle, + state::C, + time, +) where {F,C} + handle.sink == :canopy || error( + "MAESPA environment handle for provider `$(handle.provider)` has no `:canopy` commit sink." + ) + backend.canopy = state + return nothing +end + +struct SoilWater{T} <: AbstractMaespa_Soil_WaterModel + theta_sat::T + psi_e::T + b::T + depth1::T + depth2::T +end + +PlantSimEngine.inputs_(::SoilWater) = (transpiration=Required(Float64), infiltration=Required(Float64)) +PlantSimEngine.outputs_(::SoilWater) = (theta1=0.32, theta2=0.34, psi_soil=-0.1) + +function PlantSimEngine.run!(m::SoilWater, status, environment, constants, context) + withdrawal = max(status.transpiration, 0.0) + recharge = max(status.infiltration, 0.0) + status.theta1 = clamp(status.theta1 + (recharge - 0.7 * withdrawal) / max(m.depth1 * 1000.0, 1.0), 0.04, m.theta_sat) + status.theta2 = clamp(status.theta2 - 0.3 * withdrawal / max(m.depth2 * 1000.0, 1.0), 0.04, m.theta_sat) + rel = clamp(status.theta1 / m.theta_sat, 0.05, 1.0) + status.psi_soil = m.psi_e * rel^(-m.b) + return nothing +end + +struct LeafState <: AbstractLeaf_StateModel end + +PlantSimEngine.inputs_(::LeafState) = NamedTuple() +PlantSimEngine.outputs_(::LeafState) = (leaf_area=0.0, leaf_carbon=0.0) + +PlantSimEngine.run!(::LeafState, status, environment, constants, context) = nothing + +""" + LAIModel(area) + +Compute model leaf area and leaf area index from all selected leaves. +""" +struct LAIModel{T} <: AbstractMaespa_Lai_DynamicModel + area::T + + function LAIModel(area::T) where {T} + area > 0 || throw(ArgumentError("`area` must be strictly positive.")) + new{T}(area) + end +end + +PlantSimEngine.inputs_(::LAIModel) = (leaf_areas=Required(Vector{Float64}),) +PlantSimEngine.outputs_(::LAIModel) = (lai=0.0, leaf_area=(-Inf)) + +function PlantSimEngine.run!(m::LAIModel, status, environment, constants, context) + status.leaf_area = sum(status.leaf_areas) + status.lai = status.leaf_area / m.area + return nothing +end + +struct SceneEB{I,T} <: AbstractScene_EbModel + maxiter::I + tol_t::T + tol_vpd::T + tree_height::T + zht::T + zpd::T + z0ht::T + ground_area::T + qc::T + gbcan_min::T + von_karman::T +end + +function SceneEB( + maxiter, + tol_t, + tol_vpd; + tree_height=2.0, + zht=4.0, + zpd=0.75 * tree_height, + z0ht=0.1 * tree_height, + ground_area=1.0, + qc=0.0, + gbcan_min=0.0123, + von_karman=0.41, +) + ground_area > 0.0 || throw(ArgumentError("`ground_area` must be strictly positive.")) + tree_height > 0.0 || throw(ArgumentError("`tree_height` must be strictly positive.")) + zht > 0.0 || throw(ArgumentError("`zht` must be strictly positive.")) + return SceneEB( + maxiter, + promote(tol_t, + tol_vpd, + tree_height, + zht, + zpd, + z0ht, + ground_area, + qc, + gbcan_min, + von_karman)... + ) +end + +PlantSimEngine.inputs_(::SceneEB) = ( + lai=Required(Float64), + leaf_area=Required(Float64), + leaf_areas=Required(Vector{Float64}), + leaf_carbon=Required(Vector{Float64}), + leaf_Ra_SW_f=Required(Vector{Float64}), + leaf_aPPFD=Required(Vector{Float64}), + Ψₗ=Required(Vector{Float64}), + leaf_rn=Required(Vector{Float64}), + leaf_lambda_e=Required(Vector{Float64}), + leaf_h=Required(Vector{Float64}), + leaf_a=Required(Vector{Float64}), + psi_soil=Required(Float64), +) +PlantSimEngine.environment_inputs_(::SceneEB) = ( + T=0.0, + Rh=0.0, + Wind=0.0, + P=0.0, + Cₐ=0.0, + Ri_PAR_f=0.0, + Ri_SW_f=0.0, + duration=Dates.Hour(1), + VPD=0.0, + λ=0.0, +) +PlantSimEngine.environment_outputs_(::SceneEB) = (T=0.0, Rh=0.0) +PlantSimEngine.outputs_(::SceneEB) = ( + canopy_rn=0.0, + canopy_lambda_e=0.0, + canopy_h=0.0, + canopy_tair=20.0, + canopy_vpd=1.0, + canopy_rh=0.7, + canopy_htot=0.0, + canopy_gcanop=0.0, + scene_transpiration=0.0, + scene_infiltration=0.0, + scene_assimilation=0.0, + iterations=0, +) + +struct SceneEBSolverResult + tair::Float64 + vpd::Float64 + rh::Float64 + psi_soil::Float64 + final_meteo + iterations::Int + htot::Float64 + gcanop::Float64 + lai::Float64 +end + +function _model_leaf_meteo(environment, tair_canopy, vpd_canopy) + return Atmosphere( + T=tair_canopy, + Rh=rh_from_vpd(vpd_canopy, e_sat(tair_canopy)), + Wind=environment.Wind, + P=environment.P, + Cₐ=environment.Cₐ, + Ri_PAR_f=environment.Ri_PAR_f, + Ri_SW_f=environment.Ri_SW_f, + duration=environment.duration, + ) +end + +function _check_leaf_vector_lengths(status, variables) + n = length(status.leaf_areas) + for variable in variables + length(getproperty(status, variable)) == n || + throw(DimensionMismatch("`$(variable)` must have the same length as `leaf_areas`.")) + end + return n +end + +function _aggregate_model_leaf_fluxes(status, ground_area, local_meteo) + n = _check_leaf_vector_lengths(status, (:leaf_rn, :leaf_lambda_e, :leaf_h, :leaf_a)) + total_rn = 0.0 + total_lambda_e = 0.0 + total_h = 0.0 + total_a = 0.0 + for i in 1:n + leaf_area = status.leaf_areas[i] + total_rn += status.leaf_rn[i] * leaf_area + total_lambda_e += status.leaf_lambda_e[i] * leaf_area + total_h += status.leaf_h[i] * leaf_area + total_a += status.leaf_a[i] * leaf_area + end + fluxes = ( + rn=total_rn / ground_area, + lambda_e=total_lambda_e / ground_area, + h=total_h / ground_area, + a=total_a / ground_area, + environment=local_meteo, + ) + status.canopy_rn = fluxes.rn + status.canopy_lambda_e = fluxes.lambda_e + status.canopy_h = fluxes.h + status.scene_assimilation = fluxes.a + return fluxes +end + +function _prepare_model_leaf_inputs!(status, environment, psi_soil) + # Prepare the leaf status for each leaf target, and run the energy balance for each leaf: + status.leaf_Ra_SW_f .= environment.Ri_SW_f + status.leaf_aPPFD .= environment.Ri_PAR_f + status.Ψₗ .= psi_soil + return nothing +end + +function _run_model_leaf_targets!(context, status, local_meteo, meteo_above, psi_soil, ground_area; publish=false) + _prepare_model_leaf_inputs!(status, meteo_above, psi_soil) + run_call!( + context, + :energy_balance; + environment=local_meteo, + publish=publish, + ) + fluxes = _aggregate_model_leaf_fluxes(status, ground_area, local_meteo) + return fluxes +end + +function _run_model_leaf_targets_from_environment!(context, status, local_meteo, meteo_above, psi_soil, ground_area; publish=false) + _prepare_model_leaf_inputs!(status, meteo_above, psi_soil) + run_call!(context, :energy_balance; publish=publish) + fluxes = _aggregate_model_leaf_fluxes(status, ground_area, local_meteo) + return fluxes +end + +function gbcanms(wind, zht, tree_height; gbcan_min=0.0123, von_karman=0.41) + zpd = 0.75 * tree_height + z0 = 0.1 * tree_height + zstar = max(zht, eps(Float64)) + wind2 = max(wind, 1.0e-6) + + if zstar <= tree_height + wind2 *= exp(0.13155 * (tree_height / zstar - 1.0)) + zstar = 2.0 * tree_height + end + + zstar = max(zstar, zpd + z0 + 1.0e-6) + windstar = wind2 * von_karman / log((zstar - zpd) / z0) + alpha1 = 1.5 + zw = zpd + alpha1 * (tree_height - zpd) + gbcanmsini = windstar * von_karman / log((zstar - zpd) / (zw - zpd)) + gbcanmsrou = windstar * von_karman / ((zw - tree_height) / (zw - zpd)) + canopy_air_ms = max(1.0 / (1.0 / gbcanmsini + 1.0 / gbcanmsrou), gbcan_min) + + alpha = 2.0 + z0ht2 = 0.01 + kh = alpha1 * von_karman * windstar * (tree_height - zpd) + soil_denominator = tree_height * exp(alpha) * + (exp(-alpha * z0ht2 / tree_height) - exp(-alpha * (zpd + z0) / tree_height)) + soil_canopy_ms = max(alpha * kh / soil_denominator, 0.0) + return (canopy_air_ms=canopy_air_ms, soil_canopy_ms=soil_canopy_ms) +end + +function canopy_air_update(m::SceneEB, fluxes, meteo_above, canopy_meteo, constants) + gbs = gbcanms( + meteo_above.Wind, + m.zht, + m.tree_height; + gbcan_min=m.gbcan_min, + von_karman=m.von_karman, + ) + gbcan_ms = gbs.canopy_air_ms + tair_above = meteo_above.T + vpd_above = max(0.01, meteo_above.VPD) + qn = fluxes.rn + qe = fluxes.lambda_e + rad_interc = get(fluxes, :rad_interc, 0.0) + rnettot = qn + rad_interc + etot = qe + htot = rnettot - etot - m.qc + heat_conductance = constants.Cₚ * canopy_meteo.ρ * gbcan_ms + + tair_new = tair_above + htot / heat_conductance + tair_new = clamp(tair_new, tair_above - 10.0, tair_above + 10.0) + + vpair_above = PlantMeteo.e_sat(tair_above) - vpd_above + vpair_canopy = vpair_above + etot * canopy_meteo.γ / heat_conductance + vpd_new = max(0.01, PlantMeteo.e_sat(tair_new) - vpair_canopy) + vpd_new = clamp(vpd_new, max(0.01, vpd_above - 1.5), vpd_above + 1.5) + environment = _model_leaf_meteo(meteo_above, tair_new, vpd_new) + return (environment=environment, tair=tair_new, vpd=vpd_new, rh=environment.Rh, htot=htot, gcanop=gbcan_ms) +end + +function _solve_model_energy_balance!( + m::SceneEB, + context, + status, + environment, + constants=PlantMeteo.Constants(), +) + tair_above = environment.T + vpd_above = max(0.01, environment.VPD) + tair_canopy = tair_above + vpd_canopy = vpd_above + psi_soil = status.psi_soil + final_meteo = environment + last_update = (tair=tair_canopy, vpd=vpd_canopy, rh=environment.Rh, htot=0.0, gcanop=0.0) + + for iter in 1:m.maxiter + # Run the energy balance of each leaf, and aggregate the fluxes at the canopy scale: + trial_meteo = _model_leaf_meteo(environment, tair_canopy, vpd_canopy) + fluxes = _run_model_leaf_targets!(context, status, trial_meteo, environment, psi_soil, m.ground_area) + # Update the canopy-scale environment based on the leaf fluxes, and check for convergence: + final_meteo = fluxes.environment + update = canopy_air_update(m, fluxes, environment, trial_meteo, constants) + status.canopy_tair = update.tair + status.canopy_vpd = update.vpd + status.canopy_rh = update.rh + status.canopy_htot = update.htot + status.canopy_gcanop = update.gcanop + last_update = update + if abs(update.tair - tair_canopy) < m.tol_t && abs(update.vpd - vpd_canopy) < m.tol_vpd + tair_canopy = update.tair + vpd_canopy = update.vpd + return SceneEBSolverResult( + tair_canopy, + vpd_canopy, + update.rh, + psi_soil, + update.environment, + iter, + update.htot, + update.gcanop, + status.lai, + ) + end + tair_canopy = 0.5 * (tair_canopy + update.tair) # take the average to help convergence + vpd_canopy = 0.5 * (vpd_canopy + update.vpd) + end + + error( + "SceneEB did not converge after $(m.maxiter) iterations ", + "(tol_t=$(m.tol_t), tol_vpd=$(m.tol_vpd), ", + "last_tair=$(last_update.tair), last_vpd=$(last_update.vpd))." + ) +end + +function _publish_model_leaf_solution!(context, status, solution::SceneEBSolverResult, environment, ground_area) + commit_environment!(context, solution.final_meteo) + fluxes = _run_model_leaf_targets_from_environment!( + context, + status, + solution.final_meteo, + environment, + solution.psi_soil, + ground_area; + publish=true, + ) + n = _check_leaf_vector_lengths(status, (:leaf_carbon, :leaf_a)) + for i in 1:n + status.leaf_carbon[i] += status.leaf_a[i] * status.leaf_areas[i] * duration_seconds(environment) * 12.0e-6 + end + return fluxes +end + +function PlantSimEngine.run!(m::SceneEB, status, environment, constants, context) + solution = _solve_model_energy_balance!(m, context, status, environment, constants) + fluxes = _publish_model_leaf_solution!(context, status, solution, environment, m.ground_area) + transpiration_mm = λE_to_E(fluxes.lambda_e, solution.final_meteo.λ) * duration_seconds(environment) * 18.0e-6 + + status.canopy_tair = solution.tair + status.canopy_vpd = solution.vpd + status.canopy_rh = solution.rh + status.canopy_htot = solution.htot + status.canopy_gcanop = solution.gcanop + status.scene_transpiration = transpiration_mm + status.scene_infiltration = 0.0 + status.scene_assimilation = fluxes.a + status.iterations = solution.iterations + run_call!(context, :soil; publish=true) + return nothing +end + +alloc_inputs() = (leaf_carbon=Required(Vector{Float64}),) +alloc_outputs() = (daily_growth=0.0, leaf_pool=0.0, wood_pool=0.0) + +function allocate!(status, leaf_fraction, wood_fraction) + carbon = sum(status.leaf_carbon) + status.daily_growth = carbon + status.leaf_pool += leaf_fraction * carbon + status.wood_pool += wood_fraction * carbon + return nothing +end + +struct AllocA <: AbstractAlloc_AModel + leaf_fraction::Float64 + wood_fraction::Float64 +end + +struct AllocB <: AbstractAlloc_BModel + leaf_fraction::Float64 + wood_fraction::Float64 +end + +PlantSimEngine.inputs_(::AllocA) = alloc_inputs() +PlantSimEngine.outputs_(::AllocA) = alloc_outputs() +PlantSimEngine.inputs_(::AllocB) = alloc_inputs() +PlantSimEngine.outputs_(::AllocB) = alloc_outputs() + +PlantSimEngine.run!(m::AllocA, status, environment, constants, context) = + allocate!(status, m.leaf_fraction, m.wood_fraction) +PlantSimEngine.run!(m::AllocB, status, environment, constants, context) = + allocate!(status, m.leaf_fraction, m.wood_fraction) + +function _maespa_leaf_status(; leaf_area, sky_fraction, d) + return Status( + Ra_SW_f=0.0, + sky_fraction=sky_fraction, + d=d, + aPPFD=0.0, + Ψₗ=-0.1, + leaf_area=leaf_area, + leaf_carbon=0.0, + Tₗ=20.0, + Rn=0.0, + Ra_LW_f=0.0, + H=0.0, + λE=0.0, + Cₛ=400.0, + Cᵢ=300.0, + A=0.0, + Gₛ=0.0, + Gbₕ=0.0, + Dₗ=0.0, + Gbc=0.0, + iter=0, + ) +end + +_maespa_plant_status() = Status(leaf_carbon=[0.0], daily_growth=0.0, leaf_pool=0.0, wood_pool=0.0) + +function _maespa_model_status() + return Status( + leaf_areas=[0.0], + leaf_carbon=[0.0], + leaf_Ra_SW_f=[0.0], + leaf_aPPFD=[0.0], + Ψₗ=[-0.1], + leaf_rn=[0.0], + leaf_lambda_e=[0.0], + leaf_h=[0.0], + leaf_a=[0.0], + canopy_rn=0.0, + canopy_lambda_e=0.0, + canopy_h=0.0, + leaf_area=0.0, + lai=0.0, + canopy_tair=20.0, + canopy_vpd=1.0, + canopy_rh=0.7, + canopy_htot=0.0, + canopy_gcanop=0.0, + scene_transpiration=0.0, + scene_infiltration=0.0, + scene_assimilation=0.0, + psi_soil=-0.1, + iterations=0, + ) +end + +function _maespa_soil_status() + return Status(theta1=0.33, theta2=0.36, psi_soil=-0.10, transpiration=0.0, infiltration=0.0) +end + +function _maespa_species_template(species; monteith, fvcb, tuzet, allocation) + return CompositeModelTemplate( + ( + ModelSpec(monteith; name=:energy_balance, on=Many(scale=:Leaf), calls=(:photosynthesis => One(scale=:Leaf, application=:photosynthesis)), environment=Environment(provider=:canopy), every=Dates.Hour(1)), + ModelSpec(fvcb; name=:photosynthesis, on=Many(scale=:Leaf), calls=(:stomatal_conductance => One(scale=:Leaf, application=:stomatal_conductance)), every=Dates.Hour(1)), + ModelSpec(tuzet; name=:stomatal_conductance, on=Many(scale=:Leaf), every=Dates.Hour(1)), + ModelSpec(LeafState(); name=:leaf_state, on=Many(scale=:Leaf), every=Dates.Hour(1)), + ModelSpec(allocation; name=:allocation, on=One(scale=:Plant), inputs=(:leaf_carbon => Many(scale=:Leaf, within=Subtree(), var=:leaf_carbon)), every=Dates.Day(1)), + ); + kind=:plant, + species=species, + ) +end + +function _maespa_plant_instance(name, template; nleaves, leaf_area, sky_fraction, d) + plant_id = Symbol(name) + axis_id = Symbol(name, "_axis") + leaves = ntuple(nleaves) do index + Object( + Symbol(name, "_leaf_", index); + scale=:Leaf, + parent=axis_id, + status=_maespa_leaf_status(; leaf_area=leaf_area, sky_fraction=sky_fraction, d=d), + ) + end + return ObjectInstance( + name, + template; + root=Object(plant_id; scale=:Plant, parent=:model, status=_maespa_plant_status()), + objects=( + Object(Symbol(name, "_axis"); scale=:Internode, parent=plant_id), + leaves..., + ), + ) +end + +function build_maespa_model(; scene_model=SceneEB(25, 0.03, 0.005), environment=maespa_meteo()) + environment = environment isa MaespaSingleLayerEnvironment ? environment : MaespaSingleLayerEnvironment(environment) + template_a = _maespa_species_template( + :A; + monteith=Monteith(; ε=0.955, maxiter=20, ΔT=0.02), + fvcb=Fvcb(; VcMaxRef=72.0, JMaxRef=135.0, RdRef=1.1), + tuzet=Tuzet(; g0=0.015, g1=4.8, Ψᵥ=-1.4, sf=3.2, Γ=42.0), + allocation=AllocA(0.35, 0.55), + ) + template_b = _maespa_species_template( + :B; + monteith=Monteith(; ε=0.955, maxiter=20, ΔT=0.02), + fvcb=Fvcb(; VcMaxRef=58.0, JMaxRef=110.0, RdRef=1.3), + tuzet=Tuzet(; g0=0.012, g1=3.5, Ψᵥ=-1.1, sf=3.8, Γ=42.0), + allocation=AllocB(0.55, 0.35), + ) + ground_area = scene_model.ground_area + return CompositeModel( + Object(:model; scale=:Scene, kind=:model, status=_maespa_model_status()), + Object(:soil; scale=:Soil, kind=:soil, parent=:model, status=_maespa_soil_status()), + _maespa_plant_instance( + :plant_A, + template_a; + nleaves=2, + leaf_area=0.018, + sky_fraction=1.0, + d=0.035, + ), + _maespa_plant_instance( + :plant_B, + template_b; + nleaves=3, + leaf_area=0.014, + sky_fraction=0.8, + d=0.028, + ); + applications=( + ModelSpec(LAIModel(ground_area); name=:lai_dynamic, on=One(scale=:Scene), inputs=(:leaf_areas => Many( + kind=:plant, + scale=:Leaf, + within=SceneScope(), + process=:leaf_state, + var=:leaf_area, + ),), every=Dates.Day(1)), + ModelSpec(scene_model; name=:scene_eb, on=One(scale=:Scene), inputs=(:leaf_areas => Many( + kind=:plant, + scale=:Leaf, + within=SceneScope(), + process=:leaf_state, + var=:leaf_area, + ), + :leaf_carbon => Many( + kind=:plant, + scale=:Leaf, + within=SceneScope(), + process=:leaf_state, + var=:leaf_carbon, + ), + :leaf_Ra_SW_f => Many( + kind=:plant, + scale=:Leaf, + within=SceneScope(), + var=:Ra_SW_f, + ), + :leaf_aPPFD => Many( + kind=:plant, + scale=:Leaf, + within=SceneScope(), + var=:aPPFD, + ), + :Ψₗ => Many( + kind=:plant, + scale=:Leaf, + within=SceneScope(), + var=:Ψₗ, + ), + :leaf_rn => Many( + kind=:plant, + scale=:Leaf, + within=SceneScope(), + policy=HoldLast(), + var=:Rn, + ), + :leaf_lambda_e => Many( + kind=:plant, + scale=:Leaf, + within=SceneScope(), + policy=HoldLast(), + var=:λE, + ), + :leaf_h => Many( + kind=:plant, + scale=:Leaf, + within=SceneScope(), + policy=HoldLast(), + var=:H, + ), + :leaf_a => Many( + kind=:plant, + scale=:Leaf, + within=SceneScope(), + policy=HoldLast(), + var=:A, + ), + :psi_soil => One( + kind=:soil, + scale=:Soil, + application=:soil_water, + var=:psi_soil, + ),), calls=(:energy_balance => Many(kind=:plant, scale=:Leaf, process=:energy_balance), + :soil => One(kind=:soil, scale=:Soil, application=:soil_water),), environment=Environment(provider=:forcing, sink=:canopy), every=Dates.Hour(1)), + ModelSpec(SoilWater(0.45, -0.03, 4.4, 0.25, 0.75); name=:soil_water, on=One(kind=:soil, scale=:Soil), inputs=(:transpiration => One( + scale=:Scene, + within=SceneScope(), + application=:scene_eb, + var=:scene_transpiration, + ), + :infiltration => One( + scale=:Scene, + within=SceneScope(), + application=:scene_eb, + var=:scene_infiltration, + ),), every=Dates.Hour(1)), + ), + environment=environment, + ) +end + +function maespa_meteo(; nhours=24) + return Weather([ + Atmosphere( + T=22.0 + 5.0 * sinpi((hour - 7) / 12), + Rh=clamp(0.72 - 0.22 * sinpi((hour - 7) / 12), 0.35, 0.90), + Wind=1.2 + 0.3 * sinpi(hour / 12), + Ri_PAR_f=max(0.0, 900.0 * sinpi((hour - 6) / 12)), + Ri_SW_f=max(0.0, 450.0 * sinpi((hour - 6) / 12)), + duration=Dates.Hour(1), + ) + for hour in 1:nhours + ]) +end + +function run_maespa_example(; nhours=24, check=true) + model = build_maespa_model(; environment=maespa_meteo(; nhours=nhours)) + compiled = Advanced.compile_composite_model(model) + check && Advanced.refresh_environment_bindings!(model, compiled) + simulation = run!( + model; + steps=nhours, + constants=PlantMeteo.Constants(), + outputs=:all, + ) + return ( + model=model, + compiled=simulation.compiled, + environment=simulation.environment_bindings, + simulation=simulation, + ) +end + +if abspath(PROGRAM_FILE) == @__FILE__ + result = run_maespa_example() + model = result.model + println("leaf_count = ", length(model_objects(model; scale=:Leaf))) + println( + "scene_transpiration = ", + only(model_objects(model; scale=:Scene)).status.scene_transpiration, + ) + println("psi_soil = ", only(model_objects(model; kind=:soil)).status.psi_soil) + println("plant_A = ", only(model_objects(model; name=:plant_A)).status.daily_growth) + println("plant_B = ", only(model_objects(model; name=:plant_B)).status.daily_growth) +end diff --git a/examples/plantbiophysics_subsample/FvCB.jl b/examples/plantbiophysics_subsample/FvCB.jl new file mode 100644 index 000000000..7efe0031a --- /dev/null +++ b/examples/plantbiophysics_subsample/FvCB.jl @@ -0,0 +1,196 @@ +# Generate all methods for the photosynthesis process: several environment time-steps, components, +# over an MTG, and the mutating /non-mutating versions +@process "photosynthesis" verbose = false + +# Default policy for assimilation rates when consumed at coarser clocks. +# An explicit `ModelSpec(...; inputs=...)` policy overrides this default. +PlantSimEngine.output_policy(::Type{<:AbstractPhotosynthesisModel}) = (A=PlantSimEngine.Integrate(PlantMeteo.DurationSumReducer()),) + + +""" +Farquhar–von Caemmerer–Berry (FvCB) model for C3 photosynthesis (Farquhar et al., 1980; +von Caemmerer and Farquhar, 1981) coupled with a conductance model. +""" +struct Fvcb{T} <: AbstractPhotosynthesisModel + Tᵣ::T + VcMaxRef::T + JMaxRef::T + RdRef::T + TPURef::T + Eₐᵣ::T + O₂::T + Eₐⱼ::T + Hdⱼ::T + Δₛⱼ::T + Eₐᵥ::T + Hdᵥ::T + Δₛᵥ::T + α::T + θ::T +end + +function Fvcb(; Tᵣ=25.0, VcMaxRef=200.0, JMaxRef=250.0, RdRef=0.6, TPURef=9999.0, Eₐᵣ=46390.0, + O₂=210.0, Eₐⱼ=29680.0, Hdⱼ=200000.0, Δₛⱼ=631.88, Eₐᵥ=58550.0, Hdᵥ=200000.0, + Δₛᵥ=629.26, α=0.425, θ=0.7) + + Fvcb(promote(Tᵣ, VcMaxRef, JMaxRef, RdRef, TPURef, Eₐᵣ, O₂, Eₐⱼ, Hdⱼ, Δₛⱼ, Eₐᵥ, Hdᵥ, Δₛᵥ, α, θ)...) +end + +function PlantSimEngine.inputs_(::Fvcb) + ( + aPPFD=Required(Float64), + Tₗ=Required(Float64), + Cₛ=Required(Float64), + ) +end + +function PlantSimEngine.outputs_(::Fvcb) + (A=-Inf, Gₛ=-Inf, Cᵢ=-Inf) +end + +Base.eltype(x::Fvcb) = typeof(x).parameters[1] + +PlantSimEngine.dep(::Fvcb) = ( + stomatal_conductance=PlantSimEngine.Call( + PlantSimEngine.One(scale=:Leaf, process=:stomatal_conductance), + ), +) +PlantSimEngine.timestep_hint(::Type{<:Fvcb}) = ( + required=(Dates.Minute(1), Dates.Hour(6)), + preferred=Dates.Hour(1) +) + +PlantSimEngine.output_policy(::Type{<:Fvcb}) = ( + A=PlantSimEngine.Integrate(PlantMeteo.DurationSumReducer()), # from μmol m-2 s-1 to μmol m-2 timerstep-1 + Cᵢ=PlantSimEngine.Integrate(PlantMeteo.MeanReducer()), + Gₛ=PlantSimEngine.Integrate(PlantMeteo.DurationSumReducer()), +) + +function arrhenius(kref, Eₐ, Tₖ, Tᵣₖ, R) + kref * exp(Eₐ * (Tₖ - Tᵣₖ) / (R * Tₖ * Tᵣₖ)) +end + +function arrhenius(kref, Eₐ, Tₖ, Tᵣₖ, Hd, Δₛ, R) + activation = arrhenius(kref, Eₐ, Tₖ, Tᵣₖ, R) + deactivation_ref = 1.0 + exp((Tᵣₖ * Δₛ - Hd) / (R * Tᵣₖ)) + deactivation = 1.0 + exp((Tₖ * Δₛ - Hd) / (R * Tₖ)) + return activation * deactivation_ref / deactivation +end + +function Γ_star(Tₖ, Tᵣₖ, R=PlantMeteo.Constants().R) + arrhenius(oftype(Tₖ, 42.75), oftype(Tₖ, 37830.0), Tₖ, Tᵣₖ, R) +end + +function get_km(Tₖ, Tᵣₖ, O₂, R=PlantMeteo.Constants().R) + KC = arrhenius(oftype(Tₖ, 404.9), oftype(Tₖ, 79430.0), Tₖ, Tᵣₖ, R) + KO = arrhenius(oftype(Tₖ, 278.4), oftype(Tₖ, 36380.0), Tₖ, Tᵣₖ, R) + return KC * (1.0 + O₂ / KO) +end + +function PlantSimEngine.run!(m::Fvcb, status, environment, constants, context) + + # Tranform Celsius temperatures in Kelvin: + Tₖ = status.Tₗ - constants.K₀ + Tᵣₖ = m.Tᵣ - constants.K₀ + + # Temperature dependence of the parameters: + Γˢ = Γ_star(Tₖ, Tᵣₖ, constants.R) # Gamma star (CO2 compensation point) in μmol mol-1 + Km = get_km(Tₖ, Tᵣₖ, m.O₂, constants.R) # effective Michaelis–Menten coefficient for CO2 + + # Maximum electron transport rate at the given leaf temperature (μmol m-2 s-1): + JMax = arrhenius(m.JMaxRef, m.Eₐⱼ, Tₖ, Tᵣₖ, m.Hdⱼ, m.Δₛⱼ, constants.R) + # Maximum rate of Rubisco activity at the given models temperature (μmol m-2 s-1): + VcMax = arrhenius(m.VcMaxRef, m.Eₐᵥ, Tₖ, Tᵣₖ, m.Hdᵥ, m.Δₛᵥ, constants.R) + # Rate of mitochondrial respiration at the given leaf temperature (μmol m-2 s-1): + Rd = arrhenius(m.RdRef, m.Eₐᵣ, Tₖ, Tᵣₖ, constants.R) + # Rd is also described as the CO2 release in the light by processes other than the PCO + # cycle, and termed "day" respiration, or "light respiration" (Harley et al., 1986). + + # Actual electron transport rate (considering intercepted PAR and leaf temperature): + J = get_J(status.aPPFD, JMax, m.α, m.θ) # in μmol m-2 s-1 + # RuBP regeneration + Vⱼ = J / 4 + + # Stomatal conductance (mol[CO₂] m-2 s-1), dispatched on type of first argument (gs_closure): + stomatal_model = + PlantSimEngine.call_model(context, :stomatal_conductance) + st_closure = + gs_closure(stomatal_model, status, environment, constants, context) + + Cᵢⱼ = get_Cᵢⱼ(Vⱼ, Γˢ, status.Cₛ, Rd, stomatal_model.g0, st_closure) + + # Electron-transport-limited rate of CO2 assimilation (RuBP regeneration-limited): + Wⱼ = Vⱼ * (Cᵢⱼ - Γˢ) / (Cᵢⱼ + 2.0 * Γˢ) # also called Aⱼ + # See Von Caemmerer, Susanna. 2000. Biochemical models of leaf photosynthesis. + # Csiro publishing, eq. 2.23. + # NB: here the equation is modified because we use Vⱼ instead of J, but it is the same. + + # If Rd is larger than Wⱼ, no assimilation: + if Wⱼ - Rd < 1.0e-6 + Cᵢⱼ = Γˢ + Wⱼ = Vⱼ * (Cᵢⱼ - Γˢ) / (Cᵢⱼ + 2.0 * Γˢ) + end + + Cᵢᵥ = get_Cᵢᵥ(VcMax, Γˢ, status.Cₛ, Rd, stomatal_model.g0, st_closure, Km) + + # Rubisco-carboxylation-limited rate of CO₂ assimilation (RuBP activity-limited): + if Cᵢᵥ <= 0.0 || Cᵢᵥ > status.Cₛ + Wᵥ = 0.0 + else + Wᵥ = VcMax * (Cᵢᵥ - Γˢ) / (Cᵢᵥ + Km) + end + + # Net assimilation (μmol m-2 s-1) + status.A = min(Wᵥ, Wⱼ, 3 * m.TPURef) - Rd + + # Stomatal conductance (mol[CO₂] m-2 s-1) + PlantSimEngine.run_call!( + context, + :stomatal_conductance; + sampled_environment=st_closure, + publish=false, + ) + + # Intercellular CO₂ concentration (Cᵢ, μmol mol) + status.Cᵢ = min(status.Cₛ, status.Cₛ - status.A / status.Gₛ) + nothing +end + +function get_J(aPPFD, JMax, α, θ) + (α * aPPFD + JMax - sqrt((α * aPPFD + JMax)^2 - 4 * α * θ * aPPFD * JMax)) / (2 * θ) +end + +function get_Cᵢⱼ(Vⱼ, Γˢ, Cₛ, Rd, g0, st_closure) + a = g0 + st_closure * (Vⱼ - Rd) + b = (1.0 - Cₛ * st_closure) * (Vⱼ - Rd) + g0 * (2.0 * Γˢ - Cₛ) - + st_closure * (Vⱼ * Γˢ + 2.0 * Γˢ * Rd) + c = -(1.0 - Cₛ * st_closure) * Γˢ * (Vⱼ + 2.0 * Rd) - + g0 * 2.0 * Γˢ * Cₛ + + return positive_root(a, b, c) +end + +function get_Cᵢᵥ(VcMAX, Γˢ, Cₛ, Rd, g0, st_closure, Km) + a = g0 + st_closure * (VcMAX - Rd) + b = (1.0 - Cₛ * st_closure) * (VcMAX - Rd) + g0 * (Km - Cₛ) - st_closure * (VcMAX * Γˢ + Km * Rd) + c = -(1.0 - Cₛ * st_closure) * (VcMAX * Γˢ + Km * Rd) - g0 * Km * Cₛ + + return positive_root(a, b, c) +end + +function max_root(a, b, c) + Δ = b^2.0 - 4.0 * a * c + x1 = (-b + sqrt(Δ)) / (2.0 * a) + x2 = (-b - sqrt(Δ)) / (2.0 * a) + return max(x1, x2) +end + +function positive_root(a, b, c) + Δ = b^2.0 - 4.0 * a * c + return Δ >= 0.0 ? (-b + sqrt(Δ)) / (2.0 * a) : 0.0 +end + +function negative_root(a, b, c) + Δ = b^2.0 - 4.0 * a * c + return Δ >= 0.0 ? (-b - sqrt(Δ)) / (2.0 * a) : 0.0 +end diff --git a/examples/plantbiophysics_subsample/Monteith.jl b/examples/plantbiophysics_subsample/Monteith.jl new file mode 100644 index 000000000..1b278df31 --- /dev/null +++ b/examples/plantbiophysics_subsample/Monteith.jl @@ -0,0 +1,731 @@ +#! Careful: this file is a copy/paste from the original model implementation in PlantBiophysics.jl (v0.16.2). It is only used for testing. +#! If you want to use this model, use the one from PlantBiophysics.jl instead, which is more up to date and maintained. + +@process "energy_balance" verbose = false +""" + black_body(T, K₀, σ) + black_body(T) + +Thermal infrared, *i.e.* longwave radiation emitted from a black body at temperature T. + +- `T`: temperature of the object in Celsius degree +- `K₀`: absolute zero (°C) +- `σ` (``W\\ m^{-2}\\ K^{-4}``) [Stefan-Boltzmann constant](https://en.wikipedia.org/wiki/Stefan%E2%80%93Boltzmann_law) + +# Note + +`K₀` and `σ` are taken from `PlantMeteo.Constants` if not provided. + +""" +function black_body(T, K₀, σ) + Tₖ = T - K₀ + σ * (Tₖ^4.0) +end + +function black_body(T) + constants = PlantMeteo.Constants() + black_body(T, constants.K₀, constants.σ) +end + + +""" +Thermal infrared, *i.e.* longwave radiation emitted from an object at temperature T. + +- `T`: temperature of the object in Celsius degree +- `ε` object [emissivity](https://en.wikipedia.org/wiki/Emissivity) (not to confuse with ε the +ratio of molecular weights from `PlantMeteo.Constants`). A typical value for a leaf is 0.955. +- `K₀`: absolute zero (°C) +- `σ` (``W\\ m^{-2}\\ K^{-4}``) [Stefan-Boltzmann constant](https://en.wikipedia.org/wiki/Stefan%E2%80%93Boltzmann_law) + +# Note + +`K₀` and `σ` are taken from `PlantMeteo.Constants` if not provided. + +# Examples + +```julia +# Thermal infrared radiation of water at 25 °C: +grey_body(25.0, 0.96) +``` +""" +function grey_body(T, ε, K₀, σ) + ε * black_body(T, K₀, σ) +end + +function grey_body(T, ε) + constants = PlantMeteo.Constants() + grey_body(T, ε, constants.K₀, constants.σ) +end + + +""" + net_longwave_radiation(T₁,T₂,ε₁,ε₂,F₁,K₀,σ) + net_longwave_radiation(T₁,T₂,ε₁,ε₂,F₁) + +Net longwave radiation fluxes (*i.e.* thermal radiation, W m-2) between an object and another. +The object of interest is at temperature T₁ and has an emissivity ε₁, and the object with +which it exchanges energy is at temperature T₂ and has an emissivity ε₂. + +If the result is positive, then the object of interest gain energy. + +# Arguments + +- `T₁` (Celsius degree): temperature of the target object (object 1) +- `T₂` (Celsius degree): temperature of the object with which there is potential exchange (object 2) +- `ε₁`: object 1 emissivity +- `ε₂`: object 2 emissivity +- `F₁`: view factor (0-1), *i.e.* visible fraction of object 2 from object 1 (see note) +- `K₀`: absolute zero (°C) +- `σ` (``W\\ m^{-2}\\ K^{-4}``) [Stefan-Boltzmann constant](https://en.wikipedia.org/wiki/Stefan%E2%80%93Boltzmann_law) + +# Note + +`F₁`, the view factor (also called shape factor) is a coefficient applied to the semi-hemisphere +field of view of object 1 that "sees" object 2. E.g. a leaf can be viewed as a plane. If one side +of the leaf sees only object 2 in its field of view (e.g. the sky), then `F₁ = 1`. +Then the net longwave radiation flux for this part of the leaf is multiplied by its actual +surface to get the exchange. Note that we apply reciprocity between the two objects for +the view factor (they have the same value), *i.e.*: A₁F₁₂ = A₂F₂₁. + +Then, if we take a leaf as object 1, and the sky as object 2, the visible fraction of +sky viewed by the leaf would be: + +- `0.5` if the leaf is on top of the canopy, *i.e.* the upper side of the leaf sees the sky, +the side bellow sees other leaves and the soil. +- between 0 and 0.5 if it is within the canopy and partly shaded by other objects. + +Note that `A₁` for a leaf is twice its common used leaf area, because `A₁` is the **total** +leaf area of the object that exchange energy. + +```julia +# Net thermal radiation fluxes between a leaf and the sky considering the leaf at the top of +# the canopy: +Tₗ = 25.0 ; Tₐ = 20.0 +ε₁ = 0.955 ; ε₂ = 1.0 +Ra_LW_f = net_longwave_radiation(Tₗ,Tₐ,ε₁,ε₂,1.0) +Ra_LW_f + +# Ra_LW_f is the net longwave radiation flux between the leaf and the atmosphere per surface area. +# To get the actual net longwave radiation flux we need to multiply by the surface of the +# leaf, e.g. for a leaf of 2cm²: +leaf_area = 2e-4 # in m² +Ra_LW_f * leaf_area + +# The leaf lose ~0.0055 W towards the atmosphere. +``` + +# References + +Cengel, Y, et Transfer Mass Heat. 2003. A practical approach. New York, NY, USA: McGraw-Hill. +""" +function net_longwave_radiation(T₁, T₂, ε₁, ε₂, F₁, K₀, σ) + (black_body(T₂, K₀, σ) - black_body(T₁, K₀, σ)) / (1.0 / ε₁ + 1.0 / ε₂ - 1.0) * F₁ +end + +function net_longwave_radiation(T₁, T₂, ε₁, ε₂, F₁) + constants = PlantMeteo.Constants() + net_longwave_radiation(T₁, T₂, ε₁, ε₂, F₁, constants.K₀, constants.σ) +end + +""" + gbₕ_free(Tₐ,Tₗ,d,Dₕ₀) + gbₕ_free(Tₐ,Tₗ,d) + +Leaf boundary layer conductance for heat under **free** convection (m s-1). + +# Arguments + +- `Tₐ` (°C): air temperature +- `Tₗ` (°C): leaf temperature +- `d` (m): characteristic dimension, *e.g.* leaf width (see eq. 10.9 from Monteith and Unsworth, 2013). +- `Dₕ₀ = 21.5e-6`: molecular diffusivity for heat at base temperature. Use value from +`PlantMeteo.Constants` if not provided. + +# Note + +`R` and `Dₕ₀` can be found using `PlantMeteo.Constants`. To transform in ``mol\\ m^{-2}\\ s^{-1}``, +use [`ms_to_mol`](@ref). + +# References + +Leuning, R., F. M. Kelliher, DGG de Pury, et E.-D. SCHULZE. 1995. « Leaf nitrogen, +photosynthesis, conductance and transpiration: scaling from leaves to canopies ». Plant, +Cell & Environment 18 (10): 1183‑1200. + +Monteith, John, et Mike Unsworth. 2013. Principles of environmental physics: plants, +animals, and the atmosphere. Academic Press. Paragraph 10.1.3, eq. 10.9. +""" +function gbₕ_free(Tₐ, Tₗ, d, Dₕ₀=PlantMeteo.Constants().Dₕ₀) + zeroT = zero(Tₐ) # make it type stable + + if abs(Tₗ - Tₐ) > zeroT + Gr = 1.58e8 * d^3.0 * abs(Tₗ - Tₐ) # Grashof number (Monteith and Unsworth, 2013) + # !Note: Leuning et al. (1995) use 1.6e8 (eq. E4). + # Leuning et al. (1995) eq. E3: + Gbₕ_free = 0.5 * get_Dₕ(Tₐ, Dₕ₀) * (Gr^0.25) / d + else + Gbₕ_free = zeroT + end + + return Gbₕ_free +end + + +""" + gbₕ_forced(Wind,d) + +Boundary layer conductance for heat under **forced** convection (m s-1). See eq. E1 from +Leuning et al. (1995) for more details. + +# Arguments + +- `Wind` (m s-1): wind speed +- `d` (m): characteristic dimension, *e.g.* leaf width (see eq. 10.9 from Monteith and Unsworth, 2013). + +# Notes + +`d` is the minimal dimension of the surface of an object in contact with the air. + +# References + +Leuning, R., F. M. Kelliher, DGG de Pury, et E.-D. SCHULZE. 1995. « Leaf nitrogen, +photosynthesis, conductance and transpiration: scaling from leaves to canopies ». Plant, +Cell & Environment 18 (10): 1183‑1200. +""" +function gbₕ_forced(Wind, d) + 0.003 * sqrt(Wind / d) +end + + +""" + get_Dₕ(T,Dₕ₀) + get_Dₕ(T) + +Dₕ -molecular diffusivity for heat at base temperature- from Dₕ₀ (corrected by temperature). +See Monteith and Unsworth (2013, eq. 3.10). + +# Arguments + +- `Tₐ` (°C): temperature +- `Dₕ₀`: molecular diffusivity for heat at base temperature. Use value from `PlantMeteo.Constants` +if not provided. + +# References + +Monteith, John, et Mike Unsworth. 2013. Principles of environmental physics: plants, +animals, and the atmosphere. Academic Press. Paragraph 10.1.3. +""" +function get_Dₕ(T, Dₕ₀=PlantMeteo.Constants().Dₕ₀) + Dₕ₀ * (1 + 0.007 * T) +end + +""" + ms_to_mol(G,T,P,R,K₀) + ms_to_mol(G,T,P) + +Conversion of a conductance `G` from ``m\\ s^{-1}`` to ``mol\\ m^{-2}\\ s^{-1}``. + +# Arguments + +- `G` (``m\\ s^{-1}``): conductance +- `T` (°C): air temperature +- `P` (kPa): air pressure +- `R` (``J\\ mol^{-1}\\ K^{-1}``): universal gas constant. +- `K₀` (°C): absolute zero + +# See also + +[`mol_to_ms`](@ref) for the inverse process. +""" +function ms_to_mol(G, T, P, R, K₀) + G * f_ms_to_mol(T, P, R, K₀) +end + +function ms_to_mol(G, T, P) + constants = PlantMeteo.Constants() + ms_to_mol(G, T, P, constants.R, constants.K₀) +end + +""" + ms_to_mol(G,T,P,R,K₀) + ms_to_mol(G,T,P) + +Conversion of a conductance `G` from ``mol\\ m^{-2}\\ s^{-1}`` to ``m\\ s^{-1}``. + +# Arguments + +- `G` (``m\\ s^{-1}``): conductance +- `T` (°C): air temperature +- `P` (kPa): air pressure +- `R` (``J\\ mol^{-1}\\ K^{-1}``): universal gas constant. +- `K₀` (°C): absolute zero + +# See also + +[`ms_to_mol`](@ref) for the inverse process. +""" +function mol_to_ms(G, T, P, R, K₀) + G / f_ms_to_mol(T, P, R, K₀) +end + +function mol_to_ms(G, T, P) + constants = PlantMeteo.Constants() + mol_to_ms(G, T, P, constants.R, constants.K₀) +end + +""" +Conversion factor between conductance in ``m\\ s^{-1}`` to ``mol\\ m^{-2}\\ s^{-1}``. + +# Arguments + +- `T` (°C): air temperature +- `P` (kPa): air pressure +- `R` (``J\\ mol^{-1}\\ K^{-1}``): universal gas constant. +- `K₀` (°C): absolute zero +""" +function f_ms_to_mol(T, P, R, K₀) + (P * 1000) / (R * (T - K₀)) +end + +""" + gbh_to_gbw(gbh, Gbₕ_to_Gbₕ₂ₒ = PlantMeteo.Constants().Gbₕ_to_Gbₕ₂ₒ) + gbw_to_gbh(gbh, Gbₕ_to_Gbₕ₂ₒ = PlantMeteo.Constants().Gbₕ_to_Gbₕ₂ₒ) + +Boundary layer conductance for water vapor from boundary layer conductance for heat. + +# Arguments + +- `gbh` (m s-1): boundary layer conductance for heat under mixed convection. +- `Gbₕ_to_Gbₕ₂ₒ`: conversion factor. + +# Note + +Gbₕ is the sum of free and forced convection. See [`gbₕ_free`](@ref) and [`gbₕ_forced`](@ref). +""" +function gbh_to_gbw(gbh, Gbₕ_to_Gbₕ₂ₒ=PlantMeteo.Constants().Gbₕ_to_Gbₕ₂ₒ) + gbh * Gbₕ_to_Gbₕ₂ₒ +end + +function gbw_to_gbh(gbh, Gbₕ_to_Gbₕ₂ₒ=PlantMeteo.Constants().Gbₕ_to_Gbₕ₂ₒ) + gbh / Gbₕ_to_Gbₕ₂ₒ +end + + +""" + gsc_to_gsw(Gₛ, Gsc_to_Gsw = PlantMeteo.Constants().Gsc_to_Gsw) + +Conversion of a stomatal conductance for CO₂ into stomatal conductance for H₂O. +""" +function gsc_to_gsw(Gₛ, Gsc_to_Gsw=PlantMeteo.Constants().Gsc_to_Gsw) + Gₛ * Gsc_to_Gsw +end + +""" + gsw_to_gsc(Gₛ, Gsc_to_Gsw = PlantMeteo.Constants().Gsc_to_Gsw) + +Conversion of a stomatal conductance for H₂O into stomatal conductance for CO₂. +""" +function gsw_to_gsc(Gₛ, Gsc_to_Gsw=PlantMeteo.Constants().Gsc_to_Gsw) + Gₛ / Gsc_to_Gsw +end + +""" +γ_star(γ, a_sh, a_s, rbv, Rsᵥ, Rbₕ) + +γ∗, the apparent value of psychrometer constant (kPa K−1). + +# Arguments + +- `γ` (kPa K−1): psychrometer constant +- `aₛₕ` (1,2): number of faces exchanging heat fluxes (see Schymanski et al., 2017) +- `aₛᵥ` (1,2): number of faces exchanging water fluxes (see Schymanski et al., 2017) +- `Rbᵥ` (s m-1): boundary layer resistance to water vapor +- `Rsᵥ` (s m-1): stomatal resistance to water vapor +- `Rbₕ` (s m-1): boundary layer resistance to heat + +# Note + +Using the corrigendum from Schymanski et al. (2017) in here so the definition of +[`latent_heat`](@ref) remains generic. + +Not to be confused with [`Γ_star`](@ref) the CO₂ compensation point. + +# References + +Monteith, John L., et Mike H. Unsworth. 2013. « Chapter 13 - Steady-State Heat Balance: (i) +Water Surfaces, Soil, and Vegetation ». In Principles of Environmental Physics (Fourth Edition), +edited by John L. Monteith et Mike H. Unsworth, 217‑47. Boston: Academic Press. + +Schymanski, Stanislaus J., et Dani Or. 2017. Leaf-Scale Experiments Reveal an Important +Omission in the Penman–Monteith Equation ». Hydrology and Earth System Sciences 21 (2): 685‑706. +https://doi.org/10.5194/hess-21-685-2017. +""" +function γ_star(γ, aₛₕ, aₛᵥ, Rbᵥ, Rsᵥ, Rbₕ) + γ * aₛₕ / aₛᵥ * (Rbᵥ + Rsᵥ) / Rbₕ # rv + Rsᵥ= Boundary + stomatal conductance to water vapour +end + +""" + λE_to_E(λE, λ, Mₕ₂ₒ=PlantMeteo.Constants().Mₕ₂ₒ) + E_to_λE(E, λ, Mₕ₂ₒ=PlantMeteo.Constants().Mₕ₂ₒ) + +Conversion from latent heat (W m-2) to evaporation (mol[H₂O] m-2 s-1) or the +opposite (`E_to_λE`). + +# Arguments + +- `λE`: latent heat flux (W m-2) +- `E`: water evaporation (mol[H₂O] m-2 s-1) +- `λ` (J kg-1): latent heat of vaporization +- `Mₕ₂ₒ = 18.0e-3` (kg mol-1): Molar mass for water. + +# Note + +`λ` can be computed using: + + λ = latent_heat_vaporization(T, constants.λ₀) + +It is also directly available from the [`Atmosphere`](https://palmstudio.github.io/PlantMeteo.jl/stable/#PlantMeteo.Atmosphere) structure, and by extention in [`Weather`](https://palmstudio.github.io/PlantMeteo.jl/stable/#PlantMeteo.Weather). + +To convert E from mol[H₂O] m-2 s-1 to mm s-1 you can simply do: + + E_mms = E_mol / constants.Mₕ₂ₒ + +mm[H₂O] s-1 is equivalent to kg[H₂O] m-2 s-1, wich is equivalent to l[H₂O] m-2 s-1. + +""" +function λE_to_E(λE, λ, Mₕ₂ₒ=PlantMeteo.Constants().Mₕ₂ₒ) + λE / λ * Mₕ₂ₒ +end + +function E_to_λE(E, λ, Mₕ₂ₒ=PlantMeteo.Constants().Mₕ₂ₒ) + E / Mₕ₂ₒ * λ +end + +""" +Struct to hold parameter and values for the energy model close to the one in +Monteith and Unsworth (2013) + +# Arguments + +- `aₛₕ = 2`: number of faces of the object that exchange sensible heat fluxes +- `aₛᵥ = 1`: number of faces of the object that exchange latent heat fluxes (hypostomatous => 1) +- `ε = 0.955`: emissivity of the object +- `maxiter = 10`: maximal number of iterations allowed to close the energy balance +- `ΔT = 0.01` (°C): maximum difference in object temperature between two iterations to consider convergence + +# Examples + +```julia +energy_model = Monteith() # a leaf in an illuminated chamber +``` +""" +struct Monteith{T,S} <: AbstractEnergy_BalanceModel + aₛₕ::S + aₛᵥ::S + ε::T + maxiter::S + ΔT::T +end + +function Monteith(; aₛₕ=2, aₛᵥ=1, ε=0.955, maxiter=10, ΔT=0.01) + param_int = promote(aₛₕ, aₛᵥ, maxiter) + param_float = promote(ε, ΔT) + Monteith(param_int[1], param_int[2], param_float[1], param_int[3], param_float[2]) +end + +function PlantSimEngine.inputs_(::Monteith) + ( + Ra_SW_f=Required(Float64), + sky_fraction=Required(Float64), + d=Required(Float64), + ) +end + +function PlantSimEngine.environment_inputs_(::Monteith) + ( + T=0.0, + Rh=0.0, + Wind=0.0, + P=0.0, + Cₐ=0.0, + ε=0.0, + VPD=0.0, + γ=0.0, + Δ=0.0, + ρ=0.0, + ) +end + +function PlantSimEngine.outputs_(::Monteith) + ( + Tₗ=-Inf, Rn=-Inf, Ra_LW_f=-Inf, H=-Inf, λE=-Inf, Cₛ=-Inf, Cᵢ=-Inf, + A=-Inf, Gₛ=-Inf, Gbₕ=-Inf, Dₗ=-Inf, Gbc=-Inf, iter=typemin(Int) + ) +end + +Base.eltype(x::Monteith) = typeof(x).parameters[1] +# Multi-rate default for energy balance: keep relatively fine cadence. +PlantSimEngine.timestep_hint(::Type{<:Monteith}) = ( + required=(Dates.Minute(1), Dates.Hour(2)), + preferred=Dates.Hour(1) +) +PlantSimEngine.output_policy(::Type{<:Monteith}) = ( + A=PlantSimEngine.Integrate(PlantMeteo.DurationSumReducer()), + Tₗ=PlantSimEngine.Integrate(PlantMeteo.MeanReducer()), + Rn=PlantSimEngine.Integrate(PlantMeteo.RadiationEnergy()), # W m-2 to MJ m-2 timestep-1 + Ra_LW_f=PlantSimEngine.Integrate(PlantMeteo.RadiationEnergy()), + H=PlantSimEngine.Integrate(PlantMeteo.RadiationEnergy()), + λE=PlantSimEngine.Integrate(PlantMeteo.RadiationEnergy()), + Cₛ=PlantSimEngine.Integrate(PlantMeteo.MeanReducer()), + Cᵢ=PlantSimEngine.Integrate(PlantMeteo.MeanReducer()), + Gₛ=PlantSimEngine.Integrate(PlantMeteo.DurationSumReducer()), + Gbₕ=PlantSimEngine.Integrate(PlantMeteo.DurationSumReducer()), + Dₗ=PlantSimEngine.Integrate(PlantMeteo.MeanReducer()), + Gbc=PlantSimEngine.Integrate(PlantMeteo.DurationSumReducer()), + iter=PlantSimEngine.Integrate(PlantMeteo.MeanReducer()) +) + +PlantSimEngine.dep(::Monteith) = ( + photosynthesis=PlantSimEngine.Call( + PlantSimEngine.One(scale=:Leaf, process=:photosynthesis), + ), +) + +""" + run!(model::Monteith, status, environment, constants, context) + +Leaf energy balance according to Monteith and Unsworth (2013), and corrigendum from +Schymanski et al. (2017). The computation is close to the one from the MAESPA model (Duursma +et al., 2012, Vezy et al., 2018) here. The leaf temperature is computed iteratively to close +the energy balance using the mass flux (~ Rn - λE). + +# Arguments + +- `model`: the current Monteith model instance. +- `status`: the application-local view of the target `Object` state, with + initial values for: + - `Ra_SW_f` (W m-2): net shortwave radiation (PAR + NIR). Often computed from a light interception model + - `sky_fraction` (0-2): view factor between the object and the sky for both faces (see details). + - `d` (m): characteristic dimension, *e.g.* leaf width (see eq. 10.9 from Monteith and Unsworth, 2013). +- `environment`: sampled environment, see [`Atmosphere`](https://palmstudio.github.io/PlantMeteo.jl/stable/#PlantMeteo.Atmosphere). +- `constants`: physical constants supplied by the `CompositeModel` run. +- `context`: compiled runtime context used for the declared photosynthesis + hard call. + +# Details + +The sky_fraction in the variables is equal to 2 if all the leaf is viewing is sky (e.g. in a +controlled chamber), 1 if the leaf is *e.g.* up on the canopy where the upper side of the +leaf sees the sky, and the side bellow sees soil + other leaves that are all considered at +the same temperature than the leaf, or less than 1 if it is partly shaded. + +# Notes + +If you want the algorithm to print a message whenever it does not reach convergence, use the +debugging mode by executing this in the REPL: `ENV["JULIA_DEBUG"] = PlantBiophysics`. + +More information [here](https://docs.julialang.org/en/v1/stdlib/Logging/#Environment-variables). + +# References + +Duursma, R. A., et B. E. Medlyn. 2012. « MAESPA: a model to study interactions between water +limitation, environmental drivers and vegetation function at tree and stand levels, with an +example application to [CO2] × drought interactions ». Geoscientific Model Development 5 (4): +919‑40. https://doi.org/10.5194/gmd-5-919-2012. + +Monteith, John L., et Mike H. Unsworth. 2013. « Chapter 13 - Steady-State Heat Balance: (i) +Water Surfaces, Soil, and Vegetation ». In Principles of Environmental Physics (Fourth Edition), +edited by John L. Monteith et Mike H. Unsworth, 217‑47. Boston: Academic Press. + +Schymanski, Stanislaus J., et Dani Or. 2017. « Leaf-Scale Experiments Reveal an Important +Omission in the Penman–Monteith Equation ». Hydrology and Earth System Sciences 21 (2): 685‑706. +https://doi.org/10.5194/hess-21-685-2017. + +Vezy, Rémi, Mathias Christina, Olivier Roupsard, Yann Nouvellon, Remko Duursma, Belinda Medlyn, +Maxime Soma, et al. 2018. « Measuring and modelling energy partitioning in canopies of varying +complexity using MAESPA model ». Agricultural and Forest Meteorology 253‑254 (printemps): 203‑17. +https://doi.org/10.1016/j.agrformet.2018.02.005. +""" +function PlantSimEngine.run!(model::Monteith, status, environment, constants, context) + + # Initialisations + status.Tₗ = environment.T - 0.2 + Tₗ_new = zero(environment.T) + status.Cₛ = environment.Cₐ + status.Dₗ = PlantMeteo.e_sat(status.Tₗ) - PlantMeteo.e_sat(environment.T) * environment.Rh + γˢ = Rbₕ = Δ = zero(environment.T) + status.Rn = status.Ra_SW_f + iter = 0 + # ?NB: We use iter = 0 and not 1 to get the right number of iterations at the end + # of the for loop, because we use iter += 1 at the end (so it increments once again) + + # Iterative resolution of the energy balance + for i in 1:model.maxiter + + # Update A, Gₛ, Cᵢ through the declared photosynthesis call: + PlantSimEngine.run_call!( + context, + :photosynthesis; + sampled_environment=environment, + publish=false, + ) + + # Stomatal resistance to water vapor + Rsᵥ = 1.0 / (gsc_to_gsw(mol_to_ms(status.Gₛ, environment.T, environment.P, constants.R, constants.K₀), + constants.Gsc_to_Gsw)) + + # Re-computing the net radiation according to simulated leaf temperature: + status.Ra_LW_f = net_longwave_radiation(status.Tₗ, environment.T, model.ε, environment.ε, + status.sky_fraction, constants.K₀, constants.σ) + #= ? NB: we use the sky fraction here (0-2) instead of the view factor (0-1) because: + - we consider both sides of the leaf at the same time (1 -> leaf sees sky on one face) + - we consider all objects in the model have the same temperature as the leaf + of interest except the atmosphere. So the leaf exchange thermal energy_balance only with + the atmosphere. =# + # status.Ra_LW_f = (grey_body(environment.T,1.0) - grey_body(status.Tₗ, 1.0))*status.sky_fraction + + status.Rn = status.Ra_SW_f + status.Ra_LW_f + + # Leaf boundary conductance for heat (m s-1), one sided: + status.Gbₕ = gbₕ_free(environment.T, status.Tₗ, status.d, constants.Dₕ₀) + + gbₕ_forced(environment.Wind, status.d) + # NB, in MAESPA we use Rni so we add the radiation conductance also (not here) + + # Leaf boundary resistance for heat (s m-1): + Rbₕ = 1 / status.Gbₕ + + # Leaf boundary resistance for water vapor (s m-1): + Rbᵥ = 1 / gbh_to_gbw(status.Gbₕ) + + # Leaf boundary conductance for CO₂ (mol[CO₂] m-2 s-1): + status.Gbc = ms_to_mol(status.Gbₕ, environment.T, environment.P, constants.R, constants.K₀) / + constants.Gbc_to_Gbₕ + + # Update Cₛ using boundary layer conductance to CO₂ and assimilation: + status.Cₛ = min(environment.Cₐ, environment.Cₐ - status.A / (status.Gbc * model.aₛᵥ)) + + # Apparent value of psychrometer constant (kPa K−1) + γˢ = γ_star(environment.γ, model.aₛₕ, model.aₛᵥ, Rbᵥ, Rsᵥ, Rbₕ) + + status.λE = latent_heat(status.Rn, environment.VPD, γˢ, Rbₕ, environment.Δ, environment.ρ, + model.aₛₕ, constants.Cₚ) + + # If potential evaporation is needed, here is how to compute it: + # γˢₑ = γ_star(environment.γ, energy_balance.aₛₕ, 1, Rbᵥ, 1.0e-9, Rbₕ) # Rsᵥ is inf. low + # Ev = latent_heat(status.Rn, environment.VPD, γˢₑ, Rbₕ, environment.Δ, environment.ρ, energy_balance.aₛₕ, constants.Cₚ) + + Tₗ_new = environment.T + (status.Rn - status.λE) / + (environment.ρ * constants.Cₚ * (model.aₛₕ / Rbₕ)) + + if abs(Tₗ_new - status.Tₗ) <= model.ΔT + break + end + + status.Tₗ = Tₗ_new + + # Vapour pressure difference between the surface and the saturation vapour pressure: + status.Dₗ = PlantMeteo.e_sat(status.Tₗ) - PlantMeteo.e_sat(environment.T) * environment.Rh + + iter += 1 + end + + status.H = sensible_heat(status.Rn, environment.VPD, γˢ, Rbₕ, environment.Δ, environment.ρ, + model.aₛₕ, constants.Cₚ) + + status.iter = iter + + @debug begin + if iter == model.maxiter + "`run!` algorithm did not converge. Please check the value." + end + end + + # Transpiration (mol[H₂O] m-2 s-1): + # ET = status.λE / environment.λ * constants.Mₕ₂ₒ + # ET / constants.Mₕ₂ₒ to get mm s-1 <=> kg m-2 s-1 <=> l m-2 s-1 + + nothing +end + +""" + latent_heat(Rn, VPD, γˢ, Rbₕ, Δ, ρ, aₛₕ, Cₚ) + latent_heat(Rn, VPD, γˢ, Rbₕ, Δ, ρ, aₛₕ) + +λE -the latent heat flux (W m-2)- using the Monteith and Unsworth (2013) definition corrected by +Schymanski et al. (2017), eq.22. + +- `Rn` (W m-2): net radiation. Carefull: not the isothermal net radiation +- `VPD` (kPa): air vapor pressure deficit +- `γˢ` (kPa K−1): apparent value of psychrometer constant (see `PlantMeteo.γ_star`) +- `Rbₕ` (s m-1): resistance for heat transfer by convection, i.e. resistance to sensible heat +- `Δ` (KPa K-1): rate of change of saturation vapor pressure with temperature (see `PlantMeteo.e_sat_slope`) +- `ρ` (kg m-3): air density of moist air. +- `aₛₕ` (1,2): number of sides that exchange energy for heat (2 for leaves) +- `Cₚ` (J K-1 kg-1): specific heat of air for constant pressure + +# References + +Monteith, J. and Unsworth, M., 2013. Principles of environmental physics: plants, animals, and the atmosphere. Academic Press. See eq. 13.33. + +Schymanski et al. (2017), Leaf-scale experiments reveal an important omission in the Penman–Monteith equation, +Hydrology and Earth System Sciences. DOI: https://doi.org/10.5194/hess-21-685-2017. See equ. 22. + +# Examples + +```julia +Tₐ = 20.0 ; P = 100.0 ; +ρ = air_density(Tₐ, P) # in kg m-3 +Δ = e_sat_slope(Tₐ) + +latent_heat(300.0, 2.0, 0.1461683, 50.0, Δ, ρ, 2.0) +``` +""" +function latent_heat(Rn, VPD, γˢ, Rbₕ, Δ, ρ, aₛₕ, Cₚ) + (Δ * Rn + ρ * Cₚ * VPD * (aₛₕ / Rbₕ)) / (Δ + γˢ) +end + +function latent_heat(Rn, VPD, γˢ, Rbₕ, Δ, ρ, aₛₕ) + latent_heat(Rn, VPD, γˢ, Rbₕ, Δ, ρ, aₛₕ, PlantMeteo.Constants().Cₚ) +end + + +""" + sensible_heat(Rn, VPD, γˢ, Rbₕ, Δ, ρ, aₛₕ, Cₚ) + sensible_heat(Rn, VPD, γˢ, Rbₕ, Δ, ρ, aₛₕ) + +H -the sensible heat flux (W m-2)- using the Monteith and Unsworth (2013) definition corrected by +Schymanski et al. (2017), eq.22. + +- `Rn` (W m-2): net radiation. Carefull: not the isothermal net radiation +- `VPD` (kPa): air vapor pressure deficit +- `γˢ` (kPa K−1): apparent value of psychrometer constant (see `PlantMeteo.γ_star`) +- `Rbₕ` (s m-1): resistance for heat transfer by convection, i.e. resistance to sensible heat +- `Δ` (KPa K-1): rate of change of saturation vapor pressure with temperature (see `PlantMeteo.e_sat_slope`) +- `ρ` (kg m-3): air density of moist air. +- `aₛₕ` (1,2): number of sides that exchange energy for heat (2 for leaves) +- `Cₚ` (J K-1 kg-1): specific heat of air for constant pressure + +# References + +Monteith, J. and Unsworth, M., 2013. Principles of environmental physics: plants, animals, and the atmosphere. Academic Press. See eq. 13.33. + +Schymanski et al. (2017), Leaf-scale experiments reveal an important omission in the Penman–Monteith equation, +Hydrology and Earth System Sciences. DOI: https://doi.org/10.5194/hess-21-685-2017. See equ. 22. + +# Examples + +```julia +Tₐ = 20.0 ; P = 100.0 ; +ρ = air_density(Tₐ, P) # in kg m-3 +Δ = PlantMeteo.e_sat_slope(Tₐ) + +sensible_heat(300.0, 2.0, 0.1461683, 50.0, Δ, ρ, 2.0) +``` +""" +function sensible_heat(Rn, VPD, γˢ, Rbₕ, Δ, ρ, aₛₕ, Cₚ) + (γˢ * Rn - ρ * Cₚ * VPD * (aₛₕ / Rbₕ)) / (Δ + γˢ) +end + +function sensible_heat(Rn, VPD, γˢ, Rbₕ, Δ, ρ, aₛₕ) + sensible_heat(Rn, VPD, γˢ, Rbₕ, Δ, ρ, aₛₕ, PlantMeteo.Constants().Cₚ) +end diff --git a/examples/plantbiophysics_subsample/Tuzet.jl b/examples/plantbiophysics_subsample/Tuzet.jl new file mode 100644 index 000000000..ff6920d3d --- /dev/null +++ b/examples/plantbiophysics_subsample/Tuzet.jl @@ -0,0 +1,107 @@ +#! Careful: this file is more or less a copy/paste from the original model implementation in PlantBiophysics.jl (v0.16.2). It is only used for testing. +#! If you want to use this model, use the one from PlantBiophysics.jl instead, which is more up to date and maintained. + +# Generate all methods for the stomatal conductance process: several environment time-steps, components, +# over an MTG, and the mutating /non-mutating versions +@process "stomatal_conductance" verbose = false + +# Default policy for stomatal conductance when consumed at coarser clocks. +# Conductance is typically summarized over a window rather than accumulated. +PlantSimEngine.output_policy(::Type{<:AbstractStomatal_ConductanceModel}) = (Gₛ=PlantSimEngine.Aggregate(PlantMeteo.DurationSumReducer()),) + +# Gs accepts either an ordinary sampled environment or a closure value passed +# explicitly by the parent photosynthesis call. +function PlantSimEngine.run!(Gs::Gsm, status, environment, constants, context) where {Gsm<:AbstractStomatal_ConductanceModel} + closure = environment isa Number ? + environment : + gs_closure(Gs, status, environment, constants, context) + status.Gₛ = max( + Gs.gs_min, + Gs.g0 + closure * status.A, + ) +end + +""" +Tuzet et al. (2003) stomatal conductance model for CO₂. + +# Arguments + +- `g0`: intercept (μmol m⁻² s⁻¹). +- `g1`: slope. +- `Ψᵥ`: leaf water potential at which stomatal conductance is halved (MPa). +- `sf`: sensitivity factor for stomatal closure. +- `Γ`: CO₂ compensation point (mol mol⁻¹). +- `gs_min`: residual conductance (μmol m⁻² s⁻¹). + +# Variables + +- `Ψₗ`: leaf water potential (MPa). +- `Cₛ`: CO₂ concentration at the leaf surface (μmol mol⁻¹). +- `A`: CO₂ assimilation rate (μmol m⁻² s⁻¹). +- `Gₛ`: stomatal conductance (μmol m⁻² s⁻¹). + +# Note + +The CO₂ compensation point represents the concentration of CO₂ at which photosynthesis and respiration are balanced, +and it is typically a small positive value around 30–50 μmol mol⁻¹ under normal atmospheric conditions. + +This implementation uses Cₛ instead of Cᵢ. + +# References + +Tuzet, A., Perrier, A., & Leuning, R. (2003). A coupled model of stomatal conductance, photosynthesis and transpiration. Plant, Cell & Environment, 26(7), 1097-1116. +""" +struct Tuzet{T} <: AbstractStomatal_ConductanceModel + g0::T + g1::T + Ψᵥ::T + sf::T + Γ::T + gs_min::T +end + +Tuzet(g0, g1, Ψᵥ, sf, Γ, gs_min=oftype(g0, 0.001)) = Tuzet(promote(g0, g1, Ψᵥ, sf, Γ, gs_min)) +Tuzet(; g0, g1, Ψᵥ, sf, Γ, gs_min=0.001) = Tuzet(g0, g1, Ψᵥ, sf, Γ, gs_min) + +function PlantSimEngine.inputs_(::Tuzet) + (Ψₗ=Required(Float64), Cₛ=Required(Float64)) +end + +function PlantSimEngine.outputs_(::Tuzet) + (Gₛ=-Inf,) +end + +Base.eltype(::Tuzet{T}) where T = T + +""" + gs_closure(::Tuzet, status, environment, constants=nothing, context=nothing) + +Stomatal closure for CO₂ according to Tuzet et al. (2003). + +# Arguments + +- `::Tuzet`: an instance of the `Tuzet` model type. +- `status`: A status struct holding the variables for the models. +- `environment`: sampled environment. It is not used in this model. +- `constants`: A constants struct holding the constants for the models. Is not used in this model. +- `context`: The runtime context. It is not used in this model. + +# Details + +The stomatal conductance is calculated as: + + FPSIF = (1 + exp(sf * psiv)) / (1 + exp(sf * (psiv - Ψₗ))) + GSDIVA = g0 + (g1 / (Cₛ - Γ)) * FPSIF + +where `Γ` is the CO₂ compensation point. +""" +function gs_closure(m::Tuzet, status, environment, constants=nothing, context=nothing) + fpsif = (1 + exp(m.sf * m.Ψᵥ)) / + (1 + exp(m.sf * (m.Ψᵥ - status.Ψₗ))) + (m.g1 / (status.Cₛ - m.Γ)) * fpsif +end + +PlantSimEngine.timestep_hint(::Type{<:Tuzet}) = ( + required=(Dates.Minute(1), Dates.Hour(6)), + preferred=Dates.Hour(1) +) diff --git a/ext/PlantSimEngineGraphEditorExt.jl b/ext/PlantSimEngineGraphEditorExt.jl index a9c18ac95..7976690eb 100644 --- a/ext/PlantSimEngineGraphEditorExt.jl +++ b/ext/PlantSimEngineGraphEditorExt.jl @@ -2,908 +2,1319 @@ module PlantSimEngineGraphEditorExt import HTTP import JSON +import Dates import PlantSimEngine -import PlantSimEngine: edit_graph, current_mapping, apply_edit!, undo!, redo! -import Random - -mutable struct GraphEditorSession{M,G,S} <: PlantSimEngine.AbstractGraphEditorSession - mapping::M - mtg::G - history::Vector{M} - future::Vector{M} - server::S +import PlantSimEngine.GraphEditor: edit_graph, current_model, apply_edit!, undo!, redo! + +mutable struct GraphEditorSession <: PlantSimEngine.GraphEditor.AbstractModelGraphEditorSession + model::PlantSimEngine.CompositeModel + templates::Dict{Symbol,Any} + environments::Dict{Symbol,Any} + history::Vector{Any} + future::Vector{Any} + server::Any host::String port::Int token::String url::String - last_saved_path::Union{Nothing,String} - save_target_path::Union{Nothing,String} autosave_path::Union{Nothing,String} - last_autosaved_path::Union{Nothing,String} - recent_file_path::String - recent_mapping_paths::Vector{String} + save_path::Union{Nothing,String} allow_julia_eval::Bool + recent_paths::Vector{String} end -current_mapping(session::GraphEditorSession) = session.mapping +current_model(session::GraphEditorSession) = session.model + +function _normalize_named_catalog(catalog, label) + entries = if catalog isa NamedTuple + collect(pairs(catalog)) + elseif catalog isa AbstractDict + collect(pairs(catalog)) + else + error("$(label) catalog must be a NamedTuple or dictionary.") + end + normalized = Dict{Symbol,Any}() + for (name_, value) in entries + name_ isa Symbol || error("$(label) catalog names must be symbols, got `$(repr(name_))`.") + name = name_ + Base.isidentifier(String(name)) || error( + "$(label) catalog name `$(name)` must be a valid Julia identifier.", + ) + haskey(normalized, name) && error("$(label) catalog contains duplicate name `$(name)`.") + normalized[name] = value + end + return normalized +end + +function _normalize_template_catalog(catalog) + normalized = _normalize_named_catalog(catalog, "Template") + for (name, template) in normalized + template isa PlantSimEngine.CompositeModelTemplate || error( + "Template catalog entry `$(name)` must be a CompositeModelTemplate.", + ) + end + return normalized +end + +_normalize_environment_catalog(catalog) = _normalize_named_catalog(catalog, "Environment") + function Base.close(session::GraphEditorSession) - isopen(session.server) || return nothing - return close(session.server) + try + isopen(session.server) && close(session.server) + catch + close(session.server) + end + return nothing end function Base.show(io::IO, session::GraphEditorSession) - print(io, "GraphEditorSession(url=\"$(session.url)\", host=\"$(session.host)\", port=$(session.port))") + print(io, "GraphEditorSession(url=$(repr(session.url)), applications=$(length(session.model.applications)))") end function Base.show(io::IO, ::MIME"text/plain", session::GraphEditorSession) println(io, "PlantSimEngineGraphEditorExt.GraphEditorSession") println(io, " Open in browser: $(session.url)") - println(io, " Local state JSON: $(_state_url(session))") + println(io, " State JSON: $(_state_url(session))") + println(io, " Current model: GraphEditor.current_model(session)") println(io, " Quit session: close(session)") - println(io, " Current mapping: current_mapping(session)") - isnothing(session.save_target_path) || println(io, " Auto-saving edits to: $(session.save_target_path)") isnothing(session.autosave_path) || println(io, " Recovery autosave: $(session.autosave_path)") - println(io, " Save mapping code: use the \"Mapping code\" panel in the web editor") + isnothing(session.save_path) || println(io, " Saving changes to: $(session.save_path)") end -current_mapping_code(session::GraphEditorSession) = _model_mapping_to_julia(session.mapping) - """ - edit_graph([mapping]; mtg=nothing, host="127.0.0.1", port=8765, open_browser=true, autosave=true, allow_remote=false, allow_julia_eval=nothing) - -Start a local graph editor session. The returned session owns the current -`ModelMapping`; call `current_mapping(session)` to recover the edited mapping. -Call `edit_graph()` without a mapping to start from an empty scratch editor. - -Single-scale mappings are automatically normalized to multiscale form at the :Default scale. -By default, the session URL is opened with the system default browser. Pass -`open_browser=false` to disable this, for example in scripts or tests. -The URL includes a session token and the server is restricted to localhost -unless `allow_remote=true` is passed explicitly. -Raw `julia` parameter values are disabled by default for remote sessions; pass -`allow_julia_eval=true` only for trusted sessions. -When `autosave=true`, a recovery script is written to the temporary directory. -After saving through the web editor, every successful graph edit, undo, redo, -or recent-file load rewrites the saved Julia script. - -This method is provided by the `PlantSimEngineGraphEditorExt` package extension. -Load `HTTP` in the active session to make it available. + edit_graph([model]; templates=NamedTuple(), environments=NamedTuple(), + host="127.0.0.1", port=0, open_browser=true, + autosave=true, allow_remote=false, allow_julia_eval=nothing) + +Start a local Model graph editor. Julia owns the current Composite model and applies all +semantic edits received from the browser. Call `edit_graph()` to start from an +empty Composite model and `close(session)` to stop the server. `templates` is a +named catalog of `CompositeModelTemplate` presets. `environments` is a named +catalog of server-side environment values; these values are referenced by name +and are never serialized to the browser. """ function edit_graph( - mapping::PlantSimEngine.ModelMapping=_empty_editor_mapping(); - mtg=nothing, + model::PlantSimEngine.CompositeModel=PlantSimEngine.CompositeModel(); host::AbstractString="127.0.0.1", - port::Integer=8765, + port::Integer=0, open_browser::Bool=true, autosave::Bool=true, autosave_path::Union{Nothing,AbstractString}=nothing, - recent_file_path::Union{Nothing,AbstractString}=nothing, + save_path::Union{Nothing,AbstractString}=nothing, allow_remote::Bool=false, allow_julia_eval::Union{Nothing,Bool}=nothing, + recover_path::Union{Nothing,AbstractString}=nothing, + recent_paths=nothing, + templates=NamedTuple(), + environments=NamedTuple(), ) - if !_is_loopback_host(host) && !allow_remote - error("Graph editor sessions are limited to localhost by default. Pass `allow_remote=true` only for a trusted network environment.") - end - - # Normalize single-scale to multiscale form for uniform handling downstream - mapping = _normalize_to_multiscale(mapping) - + _is_loopback_host(host) || allow_remote || error( + "Graph editor sessions are limited to localhost by default. Pass `allow_remote=true` only for a trusted network.", + ) + effective_allow_julia_eval = isnothing(allow_julia_eval) ? !allow_remote : allow_julia_eval + template_catalog = _normalize_template_catalog(templates) + environment_catalog = _normalize_environment_catalog(environments) + catalog_values = ( + values(template_catalog)..., + values(environment_catalog)..., + ) + initial_model = isnothing(recover_path) ? PlantSimEngine._model_graph_deepcopy( + model, + catalog_values, + ) : _load_model_file( + _normalized_path(recover_path); + allow_julia_eval=effective_allow_julia_eval, + environments=environment_catalog, + ) session_ref = Ref{Any}() - handler = http -> _handle_http(session_ref[], http) + handler = stream -> _handle_http(session_ref[], stream) server = HTTP.listen!(handler, host, port; listenany=true, verbose=false) actual_port = HTTP.port(server) token = _session_token() - resolved_allow_julia_eval = isnothing(allow_julia_eval) ? !allow_remote : allow_julia_eval + autosave_file = autosave ? _normalized_path( + isnothing(autosave_path) ? _default_autosave_path() : autosave_path, + ) : nothing + remembered_paths = isnothing(recent_paths) ? _load_recent_paths() : String.(recent_paths) session = GraphEditorSession( - mapping, - mtg, - typeof(mapping)[], - typeof(mapping)[], + initial_model, + template_catalog, + environment_catalog, + Any[], + Any[], server, String(host), actual_port, token, "http://$(host):$(actual_port)/?token=$(token)", - nothing, - nothing, - autosave ? _normalized_output_path(isnothing(autosave_path) ? _default_autosave_path() : autosave_path) : nothing, - nothing, - _normalized_output_path(isnothing(recent_file_path) ? _default_recent_file_path() : recent_file_path), - _load_recent_mapping_paths(isnothing(recent_file_path) ? _default_recent_file_path() : recent_file_path), - resolved_allow_julia_eval, + autosave_file, + isnothing(save_path) ? nothing : _normalized_path(save_path), + effective_allow_julia_eval, + String[_normalized_path(path) for path in remembered_paths], ) session_ref[] = session - _persist_session_mapping!(session; write_save_target=false) + isnothing(session.save_path) || _remember_path!(session, session.save_path) + isnothing(recover_path) || _remember_path!(session, _normalized_path(recover_path)) + _persist_model!(session) open_browser && _open_in_default_browser(session.url) return session end -_session_token() = bytes2hex(rand(Random.RandomDevice(), UInt8, 16)) - -function _is_loopback_host(host::AbstractString) - value = lowercase(strip(String(host))) - return value in ("127.0.0.1", "localhost", "::1", "[::1]", "0:0:0:0:0:0:0:1") -end - -_base_url(session::GraphEditorSession) = "http://$(session.host):$(session.port)" -_state_url(session::GraphEditorSession) = "$(_base_url(session))/state?token=$(session.token)" -_websocket_url(session::GraphEditorSession) = "ws://$(session.host):$(session.port)/ws?token=$(session.token)" - -_empty_editor_mapping() = - PlantSimEngine._build_model_mapping(PlantSimEngine.MultiScale, Dict{Symbol,Tuple}(); validated=false) - -function _open_in_default_browser(url::AbstractString) - try - if Sys.isapple() - run(`open $url`) - elseif Sys.iswindows() - run(`cmd /c start "" $url`) - elseif !isnothing(Sys.which("xdg-open")) - run(`xdg-open $url`) - else - @warn "Could not open graph editor automatically because no supported default-browser command was found." url - return false - end - return true - catch err - @warn "Could not open graph editor automatically. Open the session URL manually." url exception = (err, catch_backtrace()) - return false +function apply_edit!(session::GraphEditorSession, edit::PlantSimEngine.GraphEditor.AbstractModelGraphEdit) + candidate = PlantSimEngine.GraphEditor.apply_model_graph_edit( + session.model, + edit; + preserve=(values(session.templates)..., values(session.environments)...), + ) + if edit isa Union{ + PlantSimEngine.GraphEditor.SetCompositeModelEnvironment, + PlantSimEngine.GraphEditor.SetModelApplicationEnvironment, + } + report = PlantSimEngine.GraphEditor.compile_model_report(candidate) + bindings = PlantSimEngine._compile_environment_bindings_for_applications( + candidate, + report.applications, + ) + PlantSimEngine._validate_model_environment_inputs!( + bindings, + Dict(application.id => application for application in report.applications), + ) end -end - -function apply_edit!(session::GraphEditorSession, edit::PlantSimEngine.AbstractGraphEdit) - updated_mapping = PlantSimEngine.apply_graph_edit(session.mapping, edit) - push!(session.history, session.mapping) + push!(session.history, session.model) empty!(session.future) - session.mapping = updated_mapping - return session.mapping + session.model = candidate + _persist_model!(session) + return session.model end function undo!(session::GraphEditorSession) - isempty(session.history) && return session.mapping - push!(session.future, session.mapping) - session.mapping = pop!(session.history) - return session.mapping + isempty(session.history) && return session.model + push!(session.future, session.model) + session.model = pop!(session.history) + _persist_model!(session) + return session.model end function redo!(session::GraphEditorSession) - isempty(session.future) && return session.mapping - push!(session.history, session.mapping) - session.mapping = pop!(session.future) - return session.mapping + isempty(session.future) && return session.model + push!(session.history, session.model) + session.model = pop!(session.future) + _persist_model!(session) + return session.model end -function _handle_http(session::GraphEditorSession, http::HTTP.Stream) - req = http.message - path = HTTP.URI(req.target).path +_session_token() = PlantSimEngine._graph_editor_session_token() - if HTTP.WebSockets.isupgrade(http.message) - _authorized_request(session, req) || return _write_http_response(http, 403, ["Content-Type" => "text/plain; charset=utf-8"], "Forbidden graph editor session token.") - _authorized_origin(session, req) || return _write_http_response(http, 403, ["Content-Type" => "text/plain; charset=utf-8"], "Forbidden graph editor websocket origin.") - return HTTP.WebSockets.upgrade(http) do ws - _handle_websocket(session, ws) - end - end +function _is_loopback_host(host) + return lowercase(strip(String(host))) in ( + "127.0.0.1", + "localhost", + "::1", + "[::1]", + "0:0:0:0:0:0:0:1", + ) +end - response = if path == "/" || path == "/index.html" || path == "/state" - _authorized_request(session, req) || return _write_http_response(http, 403, ["Content-Type" => "text/plain; charset=utf-8"], "Forbidden graph editor session token.") - if path == "/state" - (200, ["Content-Type" => "application/json"], _state_json(session)) - else - (200, ["Content-Type" => "text/html; charset=utf-8"], _editor_html(session)) +_base_url(session) = "http://$(session.host):$(session.port)" +_state_url(session) = "$(_base_url(session))/state?token=$(session.token)" +_websocket_url(session) = "ws://$(session.host):$(session.port)/ws?token=$(session.token)" + +function _handle_http(session::GraphEditorSession, stream::HTTP.Stream) + request = stream.message + path = HTTP.URI(request.target).path + + if HTTP.WebSockets.isupgrade(request) + _authorized_request(session, request) || return _write_response(stream, 403, "text/plain", "Forbidden session token.") + _authorized_origin(session, request) || return _write_response(stream, 403, "text/plain", "Forbidden websocket origin.") + return HTTP.WebSockets.upgrade(stream) do websocket + _handle_websocket(session, websocket) end - else - (404, ["Content-Type" => "text/plain; charset=utf-8"], "Not found") end - status, headers, body = response - return _write_http_response(http, status, headers, body) -end -function _write_http_response(http::HTTP.Stream, status::Integer, headers, body::AbstractString) - HTTP.setstatus(http, status) - for header in headers - HTTP.setheader(http, header) + if path == "/health" + return _write_response(stream, 200, "application/json", JSON.json(Dict("ok" => true))) end - HTTP.setheader(http, "Connection" => "close") - HTTP.setheader(http, "Content-Length" => string(sizeof(body))) - HTTP.startwrite(http) - write(http, body) - return nothing + _authorized_request(session, request) || return _write_response(stream, 403, "text/plain", "Forbidden session token.") + if path == "/" || path == "/index.html" + return _write_response(stream, 200, "text/html; charset=utf-8", _editor_html(session)) + elseif path == "/static" + view = PlantSimEngine.GraphEditor.model_graph_view( + session.model; + templates=session.templates, + environments=session.environments, + ) + return _write_response( + stream, + 200, + "text/html; charset=utf-8", + PlantSimEngine.GraphEditor.model_graph_view_html(view), + ) + elseif path == "/state" + return _write_response(stream, 200, "application/json", _state_json(session)) + end + return _write_response(stream, 404, "text/plain", "Not found") end -function _authorized_request(session::GraphEditorSession, req) - token = _request_token(req) - return !isnothing(token) && token == session.token +function _write_response(stream, status, content_type, body) + HTTP.setstatus(stream, status) + HTTP.setheader(stream, "Content-Type" => content_type) + HTTP.setheader(stream, "Connection" => "close") + HTTP.setheader(stream, "Content-Length" => string(sizeof(body))) + HTTP.startwrite(stream) + write(stream, body) + return nothing end -function _request_token(req) - header = HTTP.header(req, "X-PlantSimEngine-Graph-Token", "") - isempty(header) || return String(header) - return _query_param(String(req.target), "token") +function _authorized_request(session, request) + token = HTTP.header(request, "X-PlantSimEngine-Graph-Token", "") + isempty(token) && (token = something(_query_parameter(request.target, "token"), "")) + return token == session.token end -function _query_param(target::AbstractString, name::AbstractString) +function _query_parameter(target, requested_name) query = String(HTTP.URI(target).query) isempty(query) && return nothing - for part in split(query, '&') - pair = split(part, '='; limit=2) + for component in split(query, '&') + pair = split(component, '='; limit=2) length(pair) == 2 || continue - first(pair) == name && return last(pair) + first(pair) == requested_name && return last(pair) end return nothing end -function _authorized_origin(session::GraphEditorSession, req) - origin = HTTP.header(req, "Origin", "") - isempty(origin) && return true - return String(origin) == _base_url(session) -end - -""" - _normalize_to_multiscale(mapping::PlantSimEngine.ModelMapping{PlantSimEngine.SingleScale}) - -Convert a single-scale ModelMapping to multiscale form at the :Default scale. -This ensures all downstream logic only deals with MultiScale mappings. -""" -function _normalize_to_multiscale(mapping::PlantSimEngine.ModelMapping{PlantSimEngine.SingleScale}) - entry = mapping[:Default] # Returns tuple of (models..., status) - return PlantSimEngine.ModelMapping(:Default => entry; check=true, type_promotion=PlantSimEngine.type_promotion(mapping)) -end - -function _normalize_to_multiscale(mapping::PlantSimEngine.ModelMapping{PlantSimEngine.MultiScale}) - # Already multiscale, return as is - return mapping +function _authorized_origin(session, request) + origin = HTTP.header(request, "Origin", "") + return isempty(origin) || origin == _base_url(session) end -function _handle_websocket(session::GraphEditorSession, ws) - _websocket_send(ws, _state_json(session)) || return nothing +function _handle_websocket(session, websocket) + _send_websocket(websocket, _state_json(session)) || return nothing try - for message in ws - command = JSON.parse(String(message)) + for raw_message in websocket + command = JSON.parse(String(raw_message)) response = _handle_command!(session, command) - _websocket_send(ws, JSON.json(response)) || return nothing + _send_websocket(websocket, JSON.json(response)) || return nothing end catch err - _is_websocket_close_error(err) && return nothing - _websocket_send(ws, JSON.json(_error_payload(err))) + _is_close_error(err) || _send_websocket( + websocket, + JSON.json(Dict("ok" => false, "diagnostics" => [sprint(showerror, err)])), + ) end return nothing end -function _websocket_send(ws, payload::AbstractString) +function _send_websocket(websocket, payload) try - HTTP.WebSockets.send(ws, payload) + HTTP.WebSockets.send(websocket, payload) return true catch err - _is_websocket_close_error(err) && return false + _is_close_error(err) && return false rethrow() end end -function _is_websocket_close_error(err) - err isa EOFError && return true - err isa Base.IOError && return true - return false -end +_is_close_error(err) = err isa EOFError || err isa Base.IOError -function _handle_command!(session::GraphEditorSession, command) - action = get(command, "action", "") +function _handle_command!(session, command) + action = String(get(command, "action", "")) try - persist = false if action == "undo" undo!(session) - persist = true elseif action == "redo" redo!(session) - persist = true elseif action == "edit" - edit = _edit_from_command(session, command) - apply_edit!(session, edit) - persist = true - elseif action == "write_mapping_code" - raw_path = get(command, "path", "") - _write_mapping_code!(session, String(raw_path)) - elseif action == "open_mapping_code" - raw_path = get(command, "path", "") - _open_mapping_code!(session, String(raw_path)) - persist = true + apply_edit!(session, _edit_from_command(session, command)) + elseif action == "save_model_code" + session.save_path = _normalized_path(String(command["path"])) + _remember_path!(session, session.save_path) + _persist_model!(session) + elseif action == "open_model_code" + path = _normalized_path(String(command["path"])) + candidate = _load_model_file( + path; + allow_julia_eval=session.allow_julia_eval, + environments=session.environments, + ) + push!(session.history, session.model) + empty!(session.future) + session.model = candidate + session.save_path = path + _remember_path!(session, path) + _persist_model!(session) + elseif action == "preview_input_binding" + return _preview_input_binding_payload(session, command) + elseif action == "preview_application_targets" + return _preview_application_targets_payload(session, command) + elseif action == "preview_instance" + return _preview_instance_payload(session, command) + elseif action in ("open_add_application", "begin_add_application") + # This command only focuses/prefills frontend state. The Composite model is + # changed by a subsequent add_application edit. else - error("Unsupported graph editor command action `$action`.") + error("Unsupported graph editor command action `$(action)`.") end - diagnostics = persist ? _persist_session_mapping!(session) : String[] - return _state_payload(session; ok=isempty(diagnostics), diagnostics=diagnostics) + return _state_payload(session) catch err return _state_payload(session; ok=false, diagnostics=[sprint(showerror, err)]) end end -function _edit_from_command(session::GraphEditorSession, command) - kind = get(command, "kind", "") - kind == "mark_previous_timestep" && return PlantSimEngine.MarkPreviousTimeStep( - Symbol(command["scale"]), - Symbol(command["process"]), - Symbol(command["variable"]), - ) - kind == "unmark_previous_timestep" && return PlantSimEngine.UnmarkPreviousTimeStep( - Symbol(command["scale"]), - Symbol(command["process"]), - Symbol(command["variable"]), +function _preview_instance_payload(session, command) + candidate = PlantSimEngine.GraphEditor.apply_model_graph_edit( + session.model, + _add_instance_edit(session, command), ) - kind == "remove_model" && return PlantSimEngine.RemoveModel( - Symbol(command["scale"]), - Symbol(command["process"]), - ) - if kind == "update_model" - model_type = _resolve_model_type(command["modelType"]) - parameters = _parameters_from_command(session, get(command, "parameters", Dict())) - timestep = _timestep_from_command(get(command, "timestep", nothing); default_sentinel=true) - return PlantSimEngine.UpdateModel( - Symbol(command["scale"]), - Symbol(command["process"]), - Symbol(get(command, "targetScale", command["scale"])), - model_type, - parameters, - timestep, - ) - end - kind == "set_mapped_variable" && return PlantSimEngine.SetMappedVariable( - Symbol(command["scale"]), - Symbol(command["process"]), - Symbol(command["variable"]), - Symbol(command["sourceScale"]), - Symbol(command["sourceVariable"]), - Symbol(get(command, "mode", "single")), - Symbol.(get(command, "extraSourceScales", [])), + name = Symbol(command["name"]) + instance = only(item for item in candidate.instances if item.name == name) + report = PlantSimEngine.GraphEditor.compile_model_report(candidate) + application_ids = PlantSimEngine._instance_application_ids(candidate, instance) + payload = _state_payload(session) + payload["instancePreview"] = Dict{String,Any}( + "name" => string(name), + "objectIds" => [ + PlantSimEngine._model_graph_json_value(id.value) + for id in PlantSimEngine._instance_object_ids(candidate, instance) + ], + "applications" => [ + Dict( + "applicationId" => string(application.id), + "targetIds" => [ + PlantSimEngine._model_graph_json_value(id.value) + for id in application.target_ids + ], + ) + for application in report.applications if application.id in application_ids + ], + "diagnostics" => [diagnostic.message for diagnostic in report.diagnostics], ) - kind == "set_initialization" && return PlantSimEngine.SetStatusVariable( - Symbol(command["scale"]), - Symbol(command["variable"]), - _parse_parameter_value(session, get(command, "value", Dict("type" => "julia", "value" => "nothing"))), - ) - if kind in ("add_model", "replace_model") - model_type = _resolve_model_type(command["modelType"]) - parameters = _parameters_from_command(session, get(command, "parameters", Dict())) - timestep = _timestep_from_command(get(command, "timestep", nothing)) - if kind == "add_model" - return PlantSimEngine.AddModel(Symbol(command["scale"]), model_type, parameters, timestep) + return payload +end + +function _preview_application_targets_payload(session, command) + selector = _selector_from_payload(command["selector"]) + groups = Dict{String,Any}[] + target_ids = if haskey(command, "applicationRef") + application = _application_ref_from_command(command) + if application.scope == :template + _, selected = PlantSimEngine._model_edit_instance( + session.model, + something(application.instance), + ) + ids = PlantSimEngine.ObjectId[] + for instance in session.model.instances + instance.template === selected.template || continue + scoped = PlantSimEngine._selector_with_scope( + selector, + PlantSimEngine.Scope(instance.name), + ) + selected_ids = PlantSimEngine.resolve_object_ids(session.model, scoped) + append!(ids, selected_ids) + push!(groups, Dict( + "instance" => string(instance.name), + "objectIds" => [id.value for id in selected_ids], + )) + end + unique(ids) + else + PlantSimEngine.resolve_object_ids(session.model, selector) end - return PlantSimEngine.ReplaceModel(Symbol(command["scale"]), Symbol(command["process"]), model_type, parameters, timestep) + else + PlantSimEngine.resolve_object_ids(session.model, selector) end - error("Unsupported graph edit kind `$kind`.") + payload = _state_payload(session) + payload["targetPreview"] = Dict{String,Any}( + "objectIds" => [PlantSimEngine._model_graph_json_value(id.value) for id in target_ids], + "count" => length(target_ids), + "groups" => groups, + ) + return payload end -function _timestep_from_command(timestep; default_sentinel::Bool=false) - isnothing(timestep) && return nothing - timestep isa AbstractDict || error("Unsupported timestep payload `$(timestep)`.") - mode = String(get(timestep, "mode", "default")) - mode == "default" && return (default_sentinel ? :default : nothing) - mode == "clock" || error("Unsupported timestep mode `$mode`. Use `default` or `clock`.") - dt = _parse_real(get(timestep, "dt", "1.0")) - phase = _parse_real(get(timestep, "phase", "0.0")) - return PlantSimEngine.ClockSpec(dt, phase) +function _preview_input_binding_payload(session, command) + application = _application_ref_from_command(command) + application_ids = PlantSimEngine._model_edit_compiled_application_ids( + session.model, + application, + ) + input = Symbol(command["input"]) + candidate = PlantSimEngine.GraphEditor.apply_model_graph_edit( + session.model, + PlantSimEngine.GraphEditor.SetModelInputBinding( + application, + input, + _selector_for_application(session, application, command["selector"]), + ), + ) + report = PlantSimEngine.GraphEditor.compile_model_report(candidate) + bindings = [ + binding for binding in report.input_bindings + if binding.application_id in application_ids && binding.input == input + ] + payload = _state_payload(session) + payload["selectorPreview"] = Dict{String,Any}( + "applicationRef" => _application_ref_payload(application), + "input" => string(input), + "consumerObjectIds" => unique([ + PlantSimEngine._model_graph_json_value(binding.consumer_id.value) + for binding in bindings + ]), + "sourceObjectIds" => unique([ + PlantSimEngine._model_graph_json_value(source_id.value) + for binding in bindings for source_id in binding.source_ids + ]), + "sourceApplicationIds" => unique([ + string(source_id) for binding in bindings + for source_id in binding.source_application_ids + ]), + "bindingCount" => length(bindings), + "diagnostics" => [diagnostic.message for diagnostic in report.diagnostics], + ) + return payload end -_parse_real(value::Real) = Float64(value) -_parse_real(value) = parse(Float64, String(value)) +function _application_ref_payload(application) + return Dict{String,Any}( + "scope" => string(application.scope), + "applicationId" => string(application.application_id), + "instance" => isnothing(application.instance) ? nothing : string(application.instance), + ) +end -function _resolve_model_type(label) - for model_type in PlantSimEngine.available_models() - string(model_type) == label && return model_type - string(nameof(model_type)) == label && return model_type +function _application_ref_from_command(command) + payload = get(command, "applicationRef", nothing) + payload isa AbstractDict || error("Application commands require an `applicationRef` object.") + scope = Symbol(get(payload, "scope", "")) + application_id = Symbol(get(payload, "applicationId", "")) + scope == :global && return PlantSimEngine.GraphEditor.GlobalApplicationRef(application_id) + scope == :template && return PlantSimEngine.GraphEditor.TemplateApplicationRef( + payload["instance"], + application_id, + ) + error("Unsupported application owner scope `$(scope)`.") +end + +function _model_local_templates(session) + templates = Any[] + for instance in session.model.instances + any(template -> template === instance.template, values(session.templates)) && continue + any(template -> template === instance.template, templates) || push!(templates, instance.template) end - error("No loaded PlantSimEngine model type matches `$label`. Load the package that defines it first.") + return templates end -function _parameters_from_command(session::GraphEditorSession, parameters) - pairs = Pair{Symbol,Any}[] - for (key, value) in parameters - push!(pairs, Symbol(key) => _parse_parameter_value(session, value)) +function _template_from_id(session, template_id) + text = String(template_id) + if startswith(text, "catalog:") + name = Symbol(chopprefix(text, "catalog:")) + haskey(session.templates, name) || error("Unknown template catalog entry `$(name)`.") + return session.templates[name] + elseif startswith(text, "model:") + index = parse(Int, chopprefix(text, "model:")) + templates = _model_local_templates(session) + checkbounds(Bool, templates, index) || error("Unknown model-local template `$(text)`.") + return templates[index] end - return (; pairs...) + error("Unsupported template id `$(text)`.") end -function _parse_parameter_value(session::GraphEditorSession, value) - value isa AbstractDict || return value - choice = Symbol(get(value, "type", "julia")) - raw = get(value, "value", nothing) - choice == :float && return parse(Float64, raw) - choice == :integer && return parse(Int, raw) - choice == :boolean && return parse(Bool, raw) - choice == :symbol && return Symbol(raw) - choice == :string && return String(raw) - choice == :nothing && return nothing - choice == :julia && !session.allow_julia_eval && error("Raw Julia parameter values are disabled for this graph editor session.") - choice == :julia && return Core.eval(Main, Meta.parse(String(raw))) - return raw +function _environment_from_id(session, environment_id) + isnothing(environment_id) && return nothing + text = String(environment_id) + text == "none" && return nothing + startswith(text, "environment:") || error("Unsupported environment id `$(text)`.") + name = Symbol(chopprefix(text, "environment:")) + haskey(session.environments, name) || error("Unknown environment catalog entry `$(name)`.") + return session.environments[name] end -function _state_payload(session::GraphEditorSession; ok::Bool=true, diagnostics::Vector{String}=String[]) - graph = JSON.parse(PlantSimEngine.graph_view_json(session.mapping)) - isempty(get(graph, "scales", Any[])) && (graph["scales"] = ["Default"]) - append!(graph["diagnostics"], diagnostics) - return Dict( - "ok" => ok, - "diagnostics" => diagnostics, - "graph" => graph, - "models" => [PlantSimEngine.model_descriptor(T) for T in PlantSimEngine.available_models()], - "canUndo" => !isempty(session.history), - "canRedo" => !isempty(session.future), - "url" => session.url, - "mappingCode" => current_mapping_code(session), - "initializations" => _initialization_payload(session.mapping), - "lastSavedPath" => session.last_saved_path, - "saveTargetPath" => session.save_target_path, - "autosavePath" => session.autosave_path, - "lastAutosavedPath" => session.last_autosaved_path, - "recentMappings" => session.recent_mapping_paths, - ) -end - -_state_json(session::GraphEditorSession) = JSON.json(_state_payload(session)) -_error_payload(err) = Dict("ok" => false, "diagnostics" => [sprint(showerror, err)]) - -function _editor_html(session::GraphEditorSession) - react_html = _react_editor_html(session) - isnothing(react_html) || return react_html - - graph_json = PlantSimEngine.graph_view_json(session.mapping) - config_json = JSON.json(Dict("websocketUrl" => _websocket_url(session))) - return """ - - - - - -PlantSimEngine Graph Editor - - - - -
-

PlantSimEngine Graph Editor

-

This live session is running. The React editor can connect to $(_websocket_url(session)).

-

Current graph state is available at /state.

-

-

-
-
-
-"""
+function _edit_from_command(session, command)
+    kind = String(get(command, "kind", ""))
+    kind == "add_instance" && return _add_instance_edit(session, command)
+    kind == "remove_instance" && return PlantSimEngine.GraphEditor.RemoveModelInstance(command["name"])
+    kind == "set_model_environment" && return PlantSimEngine.GraphEditor.SetCompositeModelEnvironment(
+        _environment_from_id(session, get(command, "environmentId", nothing)),
+    )
+    application = kind in (
+        "remove_application", "mark_previous_timestep", "unmark_previous_timestep",
+        "break_cycle", "set_application_targets", "set_input_binding",
+        "remove_input_binding", "set_call_binding", "remove_call_binding",
+        "set_application_cadence", "set_application_environment", "set_output_routing",
+        "set_update_ordering", "set_instance_override", "remove_instance_override",
+        "set_object_override", "remove_object_override", "update_application",
+        "replace_application_model",
+    ) ? _application_ref_from_command(command) : nothing
+    kind == "remove_application" && return PlantSimEngine.GraphEditor.RemoveModelApplication(application)
+    kind == "mark_previous_timestep" && return PlantSimEngine.GraphEditor.MarkModelPreviousTimeStep(
+        application,
+        Symbol(command["input"]),
+    )
+    kind == "unmark_previous_timestep" && return PlantSimEngine.GraphEditor.UnmarkModelPreviousTimeStep(
+        application,
+        Symbol(command["input"]),
+    )
+    kind == "break_cycle" && return PlantSimEngine.GraphEditor.BreakModelCycle(
+        application,
+        Symbol(command["input"]),
+        Bool(get(command, "initializeMissing", false)),
+        _parameter_value(session, get(command, "initialValue", nothing)),
+    )
+    kind == "set_application_targets" && return PlantSimEngine.GraphEditor.SetModelApplicationTargets(
+        application,
+        _selector_for_application(session, application, command["selector"]),
+    )
+    kind == "set_input_binding" && return PlantSimEngine.GraphEditor.SetModelInputBinding(
+        application,
+        Symbol(command["input"]),
+        _selector_for_application(session, application, command["selector"]),
+    )
+    kind == "remove_input_binding" && return PlantSimEngine.GraphEditor.RemoveModelInputBinding(
+        application,
+        Symbol(command["input"]),
+    )
+    kind == "set_call_binding" && return PlantSimEngine.GraphEditor.SetModelCallBinding(
+        application,
+        Symbol(command["call"]),
+        _selector_for_application(session, application, command["selector"]),
+    )
+    kind == "remove_call_binding" && return PlantSimEngine.GraphEditor.RemoveModelCallBinding(
+        application,
+        Symbol(command["call"]),
+    )
+    kind == "set_application_cadence" && return PlantSimEngine.GraphEditor.SetModelApplicationCadence(
+        application,
+        _period_from_payload(get(command, "cadence", nothing)),
+    )
+    kind == "set_application_environment" && return PlantSimEngine.GraphEditor.SetModelApplicationEnvironment(
+        application,
+        _application_environment_from_payload(session, get(command, "configuration", nothing)),
+    )
+    kind == "set_output_routing" && return PlantSimEngine.GraphEditor.SetModelOutputRouting(
+        application,
+        Symbol(command["output"]),
+        Symbol(command["route"]),
+    )
+    kind == "set_update_ordering" && return PlantSimEngine.GraphEditor.SetModelUpdateOrdering(
+        application,
+        _updates_from_payload(application, get(command, "updates", Any[])),
+    )
+    kind == "set_object_status" && return PlantSimEngine.GraphEditor.SetModelObjectStatus(
+        command["objectId"],
+        Symbol(command["variable"]),
+        _parameter_value(session, command["value"]),
+    )
+    kind == "set_object_statuses" && return PlantSimEngine.GraphEditor.SetModelObjectStatuses(
+        command["objectIds"],
+        Symbol(command["variable"]),
+        _parameter_value(session, command["value"]),
+    )
+    kind == "remove_object_status" && return PlantSimEngine.GraphEditor.RemoveModelObjectStatus(
+        command["objectId"],
+        Symbol(command["variable"]),
+    )
+    kind in ("set_object_metadata", "update_object") && return PlantSimEngine.GraphEditor.SetModelObjectMetadata(
+        PlantSimEngine.ObjectId(command["objectId"]),
+        _metadata_from_payload(get(command, "configuration", Dict())),
+    )
+    kind == "add_object" && return PlantSimEngine.GraphEditor.AddModelObject(
+        _object_from_command(session, command),
+    )
+    kind == "remove_object" && return PlantSimEngine.GraphEditor.RemoveModelObject(
+        command["objectId"];
+        recursive=Bool(get(command, "recursive", true)),
+    )
+    kind == "reparent_object" && return PlantSimEngine.ReparentModelObject(
+        command["objectId"],
+        get(command, "parentId", nothing),
+    )
+    kind == "set_instance_override" && return PlantSimEngine.GraphEditor.SetModelInstanceOverride(
+        command["instance"],
+        application.application_id,
+        _construct_model(session, command["modelType"], get(command, "parameters", Dict())),
+    )
+    kind == "remove_instance_override" && return PlantSimEngine.GraphEditor.RemoveModelInstanceOverride(
+        command["instance"],
+        application.application_id,
+    )
+    kind == "set_object_override" && return PlantSimEngine.GraphEditor.SetModelObjectOverride(
+        command["instance"],
+        command["objectId"],
+        application.application_id,
+        _construct_model(session, command["modelType"], get(command, "parameters", Dict())),
+    )
+    kind == "remove_object_override" && return PlantSimEngine.GraphEditor.RemoveModelObjectOverride(
+        command["instance"],
+        command["objectId"],
+        application.application_id,
+    )
+    kind == "add_application" && return _add_application_edit(session, command)
+    kind == "update_application" && return _update_application_edit(session, command)
+    kind == "replace_application_model" && return PlantSimEngine.GraphEditor.ReplaceModelApplicationModel(
+        application,
+        _construct_model(session, command["modelType"], get(command, "parameters", Dict())),
+    )
+    error("Unsupported Model graph edit kind `$(kind)`.")
+end
+
+function _add_instance_edit(session, command)
+    root_payload = get(command, "rootObject", nothing)
+    root = isnothing(root_payload) ? nothing : _object_from_command(session, root_payload)
+    root_id = isnothing(root) ? command["rootId"] : root.id
+    return PlantSimEngine.GraphEditor.AddModelInstance(
+        command["name"],
+        _template_from_id(session, command["templateId"]),
+        root_id;
+        root_object=root,
+    )
+end
+
+function _selector_for_application(session, application, payload)
+    selector = _selector_from_payload(payload)
+    application.scope == :global && return selector
+    _, instance = PlantSimEngine._model_edit_instance(
+        session.model,
+        something(application.instance),
+    )
+    return PlantSimEngine._model_edit_unmount_selector(selector, instance)
+end
+
+function _application_environment_from_payload(session, payload)
+    isnothing(payload) && return nothing
+    payload isa AbstractDict || error("Application environment configuration must be an object.")
+    values = Pair{Symbol,Any}[]
+    backend_id = get(payload, "backendId", "scene")
+    backend_id in (nothing, "scene") || push!(values, :backend => _environment_from_id(session, backend_id))
+    provider = get(payload, "provider", nothing)
+    isnothing(provider) || isempty(strip(String(provider))) || push!(values, :provider => Symbol(provider))
+    sources = get(payload, "sources", Dict())
+    isempty(sources) || push!(values, :sources => (; (
+        Symbol(key) => Symbol(value) for (key, value) in pairs(sources)
+        if !isempty(strip(String(value)))
+    )...))
+    sink = get(payload, "sink", nothing)
+    isnothing(sink) || isempty(strip(String(sink))) || push!(values, :sink => Symbol(sink))
+    extra = _configuration_from_payload(session, get(payload, "extra", Dict()))
+    append!(values, pairs(extra))
+    return (; values...)
+end
+
+function _symbol_keyed_namedtuple(payload)
+    payload isa AbstractDict || error("Expected an object-valued configuration payload.")
+    return (; (Symbol(key) => value for (key, value) in payload)...)
 end
 
-function _react_editor_html(session::GraphEditorSession)
-    assets_dir = _frontend_dist_dir()
-    manifest_path = joinpath(assets_dir, ".vite", "manifest.json")
-    isfile(manifest_path) || return nothing
+function _metadata_from_payload(payload)
+    payload isa AbstractDict || error("Expected an object metadata payload.")
+    return (; (
+        Symbol(key) => (value isa AbstractString && isempty(strip(value)) ? nothing : value)
+        for (key, value) in payload
+    )...)
+end
 
-    manifest = JSON.parse(read(manifest_path, String))
-    entry = nothing
-    for value in values(manifest)
-        if get(value, "isEntry", false) == true
-            entry = value
-            break
+function _configuration_from_payload(session, payload)
+    isnothing(payload) && return nothing
+    payload isa AbstractDict || return payload
+    values = Pair{Symbol,Any}[]
+    for (key, value) in payload
+        parsed = if value isa AbstractDict && haskey(value, "type") && haskey(value, "value")
+            _parameter_value(session, value)
+        elseif value isa AbstractDict
+            _configuration_from_payload(session, value)
+        elseif value isa AbstractVector
+            [_configuration_from_payload(session, item) for item in value]
+        else
+            value
         end
+        push!(values, Symbol(key) => parsed)
     end
-    isnothing(entry) && (entry = get(manifest, "index.html", nothing))
-    isnothing(entry) && return nothing
-
-    js_file = get(entry, "file", nothing)
-    isnothing(js_file) && return nothing
-    css_files = get(entry, "css", Any[])
-    js = read(joinpath(assets_dir, js_file), String)
-    css = join([read(joinpath(assets_dir, css_file), String) for css_file in css_files], "\n")
-    graph_json = PlantSimEngine.graph_view_json(session.mapping)
-    config_json = replace(JSON.json(Dict("websocketUrl" => _websocket_url(session))), " "<\\/")
-
-    return """
-
-
-
-
-
-PlantSimEngine Graph Editor
-
-
-
-
-
-

-
-
-
-"""
+    return (; values...)
 end
 
-_frontend_dist_dir() = normpath(joinpath(@__DIR__, "..", "frontend", "dist"))
+function _updates_from_payload(application, payload)
+    payload isa AbstractVector || error("Update ordering must be an array.")
+    prefix = application.scope == :template ? string(application.instance, "__") : ""
+    return Tuple(
+        PlantSimEngine.Updates(
+            Symbol.(get(item, "variables", Any[]))...;
+            after=Symbol[
+                Symbol(
+                    !isempty(prefix) && startswith(String(value), prefix) ?
+                    chopprefix(String(value), prefix) : String(value),
+                )
+                for value in get(item, "after", Any[])
+            ],
+        )
+        for item in payload
+    )
+end
 
-function _write_mapping_code!(session::GraphEditorSession, raw_path::AbstractString)
-    path = strip(String(raw_path))
-    isempty(path) && error("The output path is empty. Provide a .jl file path.")
-    full_path = _normalized_output_path(path)
-    _atomic_write(full_path, current_mapping_code(session) * "\n")
-    session.last_saved_path = full_path
-    session.save_target_path = full_path
-    _remember_recent_mapping!(session, full_path)
-    return full_path
+function _object_from_command(session, command)
+    configuration = get(command, "configuration", Dict())
+    status_payload = get(command, "status", Dict())
+    status = if isempty(status_payload)
+        nothing
+    else
+        PlantSimEngine.Status((; (
+            Symbol(name) => _parameter_value(session, value)
+            for (name, value) in status_payload
+        )...))
+    end
+    return PlantSimEngine.Object(
+        command["objectId"];
+        scale=get(configuration, "scale", nothing),
+        kind=get(configuration, "kind", nothing),
+        species=get(configuration, "species", nothing),
+        name=get(configuration, "name", nothing),
+        parent=get(configuration, "parent", nothing),
+        status=status,
+    )
 end
 
-function _open_mapping_code!(session::GraphEditorSession, raw_path::AbstractString)
-    path = strip(String(raw_path))
-    isempty(path) && error("The input path is empty. Provide a .jl file path.")
-    full_path = _normalized_output_path(path)
-    isfile(full_path) || error("No mapping code file exists at `$full_path`.")
-    mapping = _mapping_from_julia_file(full_path)
-    push!(session.history, session.mapping)
-    empty!(session.future)
-    session.mapping = _normalize_to_multiscale(mapping)
-    session.save_target_path = full_path
-    session.last_saved_path = full_path
-    _remember_recent_mapping!(session, full_path)
-    return session.mapping
+function _update_application_edit(session, command)
+    application = _application_ref_from_command(command)
+    model = _construct_model(session, command["modelType"], get(command, "parameters", Dict()))
+    return PlantSimEngine.GraphEditor.UpdateModelApplication(
+        application,
+        model,
+        Symbol(get(command, "name", string(application.application_id))),
+        _selector_for_application(session, application, command["selector"]),
+        _period_from_payload(get(command, "cadence", nothing)),
+    )
 end
 
-function _mapping_from_julia_file(path::AbstractString)
-    module_ = Module(gensym(:PlantSimEngineGraphEditorMapping))
-    Core.eval(module_, :(using Base))
-    Core.eval(module_, :(using PlantSimEngine))
-    result = Core.eval(module_, Meta.parse("begin\n" * read(path, String) * "\nend"))
-    mapping = isdefined(module_, :mapping) ? getfield(module_, :mapping) : result
-    mapping isa PlantSimEngine.ModelMapping || (!isdefined(module_, :mapping) && error("Mapping code `$path` must define a top-level `mapping` variable."))
-    mapping isa PlantSimEngine.ModelMapping || error("`mapping` in `$path` is a $(typeof(mapping)), not a PlantSimEngine.ModelMapping.")
-    return mapping
+function _add_application_edit(session, command)
+    model = _construct_model(session, command["modelType"], get(command, "parameters", Dict()))
+    name = Symbol(command["name"])
+    selector = _selector_from_payload(command["selector"])
+    cadence = _period_from_payload(get(command, "cadence", nothing))
+    spec = PlantSimEngine.ModelSpec(model;
+        name=name,
+        on=selector,
+        every=cadence,)
+    return PlantSimEngine.GraphEditor.AddModelApplication(spec)
 end
 
-function _persist_session_mapping!(session::GraphEditorSession; write_save_target::Bool=true)
-    diagnostics = String[]
-    if write_save_target && !isnothing(session.save_target_path)
-        try
-            _atomic_write(session.save_target_path, current_mapping_code(session) * "\n")
-            session.last_saved_path = session.save_target_path
-        catch err
-            push!(diagnostics, "Could not auto-save mapping code to $(session.save_target_path): $(sprint(showerror, err))")
-        end
+function _resolve_model_type(label)
+    text = String(label)
+    for model_type in PlantSimEngine.GraphEditor.available_models()
+        text in (string(model_type), string(nameof(model_type))) && return model_type
     end
-    if !isnothing(session.autosave_path)
-        try
-            _atomic_write(session.autosave_path, current_mapping_code(session) * "\n")
-            session.last_autosaved_path = session.autosave_path
-        catch err
-            push!(diagnostics, "Could not write recovery autosave to $(session.autosave_path): $(sprint(showerror, err))")
+    error("No loaded model type matches `$(text)`. Load the defining package with `using PackageName` first.")
+end
+
+function _construct_model(session, label, parameters)
+    model_type = _resolve_model_type(label)
+    descriptor = PlantSimEngine.GraphEditor.model_constructor_descriptor(model_type)
+    fields = descriptor["fields"]
+    isempty(fields) && return model_type()
+    default_instance = try
+        model_type()
+    catch
+        nothing
+    end
+    values = Any[]
+    for field in fields
+        name = field["name"]
+        if haskey(parameters, name)
+            push!(values, _parameter_value(session, parameters[name]))
+        elseif !isnothing(default_instance)
+            push!(values, getfield(default_instance, Symbol(name)))
+        else
+            error("Missing constructor parameter `$(name)` for model `$(model_type)`.")
         end
     end
-    return diagnostics
+    return model_type(values...)
 end
 
-function _atomic_write(path::AbstractString, content::AbstractString)
-    full_path = _normalized_output_path(path)
-    mkpath(dirname(full_path))
-    tmp = tempname(dirname(full_path))
-    try
-        write(tmp, content)
-        mv(tmp, full_path; force=true)
-    finally
-        isfile(tmp) && rm(tmp; force=true)
+function _parameter_value(session, payload)
+    payload isa AbstractDict || return payload
+    choice = Symbol(get(payload, "type", "julia"))
+    raw = get(payload, "value", nothing)
+    choice == :float && return parse(Float64, string(raw))
+    choice == :integer && return parse(Int, string(raw))
+    choice == :boolean && return parse(Bool, string(raw))
+    choice == :symbol && return Symbol(raw)
+    choice == :string && return String(raw)
+    choice == :nothing && return nothing
+    choice == :julia && session.allow_julia_eval || choice != :julia || error(
+        "Raw Julia parameter values are disabled for this session.",
+    )
+    choice == :julia && return Core.eval(Main, Meta.parse(String(raw)))
+    return raw
+end
+
+function _selector_from_payload(payload)
+    payload isa AbstractDict || error("A selector payload must be an object.")
+    multiplicity = Symbol(get(payload, "multiplicity", "many"))
+    criteria = get(payload, "criteria", Dict())
+    selectors = PlantSimEngine.AbstractObjectSelector[
+        _selector_atom_from_payload(value)
+        for value in get(criteria, "selectors", Any[])
+    ]
+    keyword_pairs = Pair{Symbol,Any}[]
+    for (key, value) in criteria
+        key == "selectors" && continue
+        value === nothing && continue
+        push!(keyword_pairs, Symbol(key) => _selector_value(Symbol(key), value))
     end
-    return full_path
+    keywords = (; keyword_pairs...)
+    multiplicity == :one && return PlantSimEngine.One(selectors...; keywords...)
+    multiplicity == :optional_one && return PlantSimEngine.OptionalOne(selectors...; keywords...)
+    multiplicity == :many && return PlantSimEngine.Many(selectors...; keywords...)
+    error("Unsupported selector multiplicity `$(multiplicity)`.")
 end
 
-function _normalized_output_path(path::AbstractString)
-    stripped = strip(String(path))
-    return isabspath(stripped) ? normpath(stripped) : normpath(joinpath(pwd(), stripped))
+function _selector_value(key, value)
+    key in (:scale, :kind, :species, :name, :process, :var, :relation, :application) &&
+        return value isa AbstractVector ? Symbol.(value) : Symbol(value)
+    key == :within && return _selector_atom_from_payload(value)
+    key == :policy && return _policy_from_payload(value)
+    key == :window && return _period_from_payload(value)
+    return value
 end
 
-function _default_autosave_path()
-    stamp = string(round(Int, time() * 1000))
-    suffix = string(rand(UInt32); base=16)
-    return joinpath(tempdir(), "PlantSimEngineGraphEditor", "session-$stamp-$suffix", "mapping.autosave.jl")
+function _selector_atom_from_payload(payload)
+    payload isa AbstractDict || error("A structured object selector must be an object.")
+    type = String(get(payload, "type", ""))
+    type == "SceneScope" && return PlantSimEngine.SceneScope()
+    type == "Self" && return PlantSimEngine.Self()
+    type == "Subtree" && return PlantSimEngine.Subtree()
+    type == "SelfPlant" && return PlantSimEngine.SelfPlant()
+    type == "Ancestor" && return PlantSimEngine.Ancestor(; scale=get(payload, "scale", nothing))
+    type == "Scope" && return PlantSimEngine.Scope(payload["name"])
+    type == "Relation" && return PlantSimEngine.Relation(payload["relation"])
+    error("Unsupported structured object selector type `$(type)`.")
+end
+
+function _policy_from_payload(payload)
+    payload isa AbstractDict || error("A temporal policy must be a structured object.")
+    type = String(get(payload, "type", ""))
+    type == "PreviousTimeStep" && return PlantSimEngine.PreviousTimeStep(
+        Symbol(payload["variable"]),
+        Symbol(get(payload, "process", "unknown")),
+    )
+    type == "HoldLast" && return PlantSimEngine.HoldLast()
+    type == "Interpolate" && return PlantSimEngine.Interpolate(
+        ;
+        mode=Symbol(get(payload, "mode", "linear")),
+        extrapolation=Symbol(get(payload, "extrapolation", "linear")),
+    )
+    type == "Integrate" && return PlantSimEngine.Integrate()
+    type == "Aggregate" && return PlantSimEngine.Aggregate()
+    error("Unsupported temporal policy type `$(type)`.")
 end
 
-_default_recent_file_path() = joinpath(DEPOT_PATH[1], "config", "PlantSimEngine", "graph_editor_recent.json")
+function _period_from_payload(payload)
+    isnothing(payload) && return nothing
+    payload isa AbstractDict || error("A cadence or window payload must be an object.")
+    mode = String(get(payload, "mode", "default"))
+    mode == "default" && return nothing
+    mode == "period" || error("Unsupported cadence/window mode `$(mode)`.")
+    value = parse(Int, string(payload["value"]))
+    value > 0 || error("Cadence/window values must be positive.")
+    unit = String(payload["unit"])
+    constructors = Dict(
+        "Second" => Dates.Second,
+        "Minute" => Dates.Minute,
+        "Hour" => Dates.Hour,
+        "Day" => Dates.Day,
+    )
+    haskey(constructors, unit) || error(
+        "Unsupported period unit `$(unit)`. Use Second, Minute, Hour, or Day.",
+    )
+    return constructors[unit](value)
+end
 
-function _load_recent_mapping_paths(path::AbstractString)
-    full_path = _normalized_output_path(path)
-    isfile(full_path) || return String[]
+function _state_payload(session; ok=true, diagnostics=String[])
+    graph = JSON.parse(PlantSimEngine.GraphEditor.model_graph_view_json(
+        session.model;
+        templates=session.templates,
+        environments=session.environments,
+    ))
+    return Dict{String,Any}(
+        "ok" => ok,
+        "diagnostics" => diagnostics,
+        "graph" => graph,
+        "canUndo" => !isempty(session.history),
+        "canRedo" => !isempty(session.future),
+        "url" => session.url,
+        "modelCode" => _model_to_julia(session),
+        "autosavePath" => session.autosave_path,
+        "savePath" => session.save_path,
+        "recentPaths" => session.recent_paths,
+    )
+end
+
+function _remember_path!(session, path)
+    normalized = _normalized_path(path)
+    filter!(!=(normalized), session.recent_paths)
+    pushfirst!(session.recent_paths, normalized)
+    length(session.recent_paths) > 12 && resize!(session.recent_paths, 12)
+    _persist_recent_paths!(session.recent_paths)
+    return normalized
+end
+
+function _recent_paths_file()
+    return joinpath(tempdir(), "PlantSimEngineGraphEditor", "recent-models.json")
+end
+
+function _load_recent_paths()
+    path = _recent_paths_file()
+    isfile(path) || return String[]
     try
-        payload = JSON.parse(read(full_path, String))
-        values = payload isa AbstractDict ? get(payload, "paths", String[]) : payload
-        return [String(item) for item in values if item isa AbstractString && isfile(String(item))]
+        values = JSON.parse(read(path, String))
+        values isa AbstractVector || return String[]
+        return String[_normalized_path(value) for value in values if value isa AbstractString]
     catch
         return String[]
     end
 end
 
-function _remember_recent_mapping!(session::GraphEditorSession, path::AbstractString)
-    full_path = _normalized_output_path(path)
-    filter!(item -> item != full_path, session.recent_mapping_paths)
-    pushfirst!(session.recent_mapping_paths, full_path)
-    length(session.recent_mapping_paths) > 10 && resize!(session.recent_mapping_paths, 10)
-    _write_recent_mapping_paths(session)
-    return session.recent_mapping_paths
+function _persist_recent_paths!(paths)
+    path = _recent_paths_file()
+    mkpath(dirname(path))
+    _atomic_write(path, JSON.json(collect(paths)))
+    return path
 end
 
-function _write_recent_mapping_paths(session::GraphEditorSession)
-    content = JSON.json(Dict("paths" => session.recent_mapping_paths))
-    try
-        _atomic_write(session.recent_file_path, content * "\n")
-    catch err
-        @warn "Could not update graph editor recent mappings." path = session.recent_file_path exception = (err, catch_backtrace())
-    end
-    return session.recent_file_path
-end
-
-function _initialization_payload(mapping::PlantSimEngine.ModelMapping)
-    required_by_scale = _required_status_variables(mapping)
-    payload = Any[]
-    for scale in sort!(collect(keys(required_by_scale)); by=string)
-        status = _scale_status(mapping, scale)
-        for variable in sort!(collect(required_by_scale[scale]); by=string)
-            value_payload = isnothing(status) || !(variable in keys(status)) ?
-                            _status_value_payload(nothing; provided=false) :
-                            _status_value_payload(status[variable]; provided=true)
-            push!(
-                payload,
-                merge(
-                    Dict(
-                        "scale" => string(scale),
-                        "name" => string(variable),
-                    ),
-                    value_payload
-                )
-            )
-        end
+function _load_model_file(path; allow_julia_eval::Bool, environments=Dict{Symbol,Any}())
+    allow_julia_eval || error("Opening Julia Composite model files is disabled for this editor session.")
+    isfile(path) || error("Composite model file `$(path)` does not exist.")
+    source = read(path, String)
+    required_match = match(
+        r"(?m)^# Requires `editor_environments` with named values: ([^.]+)\.$",
+        source,
+    )
+    if !isnothing(required_match)
+        required = Set(Symbol(strip(name)) for name in split(required_match.captures[1], ','))
+        missing = sort!(collect(setdiff(required, Set(keys(environments)))); by=string)
+        isempty(missing) || error(
+            "Composite model file `$(path)` requires environment catalog keys $(missing).",
+        )
     end
-    return payload
+    module_name = Symbol("PlantSimEngineGraphRecovery_", string(time_ns(); base=16))
+    workspace = Module(module_name)
+    Core.eval(workspace, :(using PlantSimEngine))
+    environment_values = (; (
+        name => value for (name, value) in sort!(collect(environments); by=first)
+    )...)
+    Core.eval(workspace, :(editor_environments = $environment_values))
+    included = Base.include(workspace, path)
+    model = isdefined(workspace, :model) ? getfield(workspace, :model) : included
+    model isa PlantSimEngine.CompositeModel || error(
+        "Composite model file `$(path)` must assign its final PlantSimEngine.CompositeModel to `model`.",
+    )
+    return model
 end
 
-function _scale_status(mapping::PlantSimEngine.ModelMapping, scale::Symbol)
-    haskey(mapping, scale) || return nothing
-    for item in _scale_items(mapping[scale])
-        item isa PlantSimEngine.Status && return item
-    end
-    return nothing
-end
+_state_json(session) = JSON.json(_state_payload(session))
 
-function _status_value_payload(value; provided::Bool)
-    choice, label = _status_value_choice(value, provided)
-    return Dict(
-        "value" => label,
-        "type" => choice,
-        "provided" => provided,
+function _editor_html(session)
+    view = PlantSimEngine.GraphEditor.model_graph_view(
+        session.model;
+        templates=session.templates,
+        environments=session.environments,
     )
+    html = PlantSimEngine.GraphEditor.model_graph_view_html(view)
+    config = replace(JSON.json(Dict("websocketUrl" => _websocket_url(session))), " "<\\/")
+    script = ""
+    return replace(html, "" => "$(script)")
 end
 
-_status_value_choice(::Nothing, provided::Bool) = provided ? ("nothing", "") : ("julia", "")
-_status_value_choice(value::Bool, ::Bool) = ("boolean", string(value))
-_status_value_choice(value::Integer, ::Bool) = ("integer", string(value))
-_status_value_choice(value::AbstractFloat, ::Bool) = ("float", string(value))
-_status_value_choice(value::Symbol, ::Bool) = ("symbol", string(value))
-_status_value_choice(value::AbstractString, ::Bool) = ("string", String(value))
-_status_value_choice(value, ::Bool) = ("julia", repr(value))
-
-function _model_mapping_to_julia(mapping::PlantSimEngine.ModelMapping)
+function _model_to_julia(session::GraphEditorSession)
+    model = session.model
     io = IOBuffer()
-    for statement in _using_statements(mapping)
-        println(io, statement)
+    diagnostics = String[]
+    modules = _model_code_modules(model)
+    for module_name in sort!(collect(modules))
+        println(io, "using $(module_name)")
     end
+    println(io, "using Dates")
     println(io)
-    if isempty(keys(mapping))
-        println(io, "# Add at least one model in the graph editor to generate a ModelMapping.")
-        print(io, "# mapping = ModelMapping(...)")
-        return String(take!(io))
-    end
-    required_status_variables = _required_status_variables(mapping)
-    println(io, "mapping = ModelMapping(")
-    for scale in keys(mapping)
-        println(io, "    $(_symbol_code(scale)) => (")
-        items = _scale_items(mapping[scale])
-        required = get(required_status_variables, scale, Set{Symbol}())
-        for item in items
-            code = _mapping_item_to_code(item, required)
-            isnothing(code) && continue
-            println(io, "        $(code),")
-        end
-        println(io, "    ),")
+    if !isnothing(model.source_adapter)
+        push!(diagnostics, "The Composite model source_adapter is runtime-specific and is not reconstructed by generated code.")
     end
-    print(io, ")")
-    return String(take!(io))
-end
+    for model in _model_code_models(model)
+        Base.moduleroot(parentmodule(typeof(model))) === Main || continue
+        push!(
+            diagnostics,
+            "Model $(typeof(model)) is defined in Main. Define or include that model before evaluating this generated Composite model script.",
+        )
+    end
+    for diagnostic in unique(diagnostics)
+        println(io, "# WARNING: ", diagnostic)
+    end
+    required_environments = _required_environment_names(session)
+    if !isempty(required_environments)
+        names = join(sort!(string.(collect(required_environments))), ", ")
+        println(io, "# Requires `editor_environments` with named values: ", names, ".")
+    end
+    isempty(diagnostics) || println(io)
+    println(io, "objects = (")
+    for object in PlantSimEngine.model_objects(model)
+        println(io, "    ", _object_code(session, object), ",")
+    end
+    println(io, ")")
 
-_scale_items(entry) = entry isa Tuple ? entry : (entry,)
+    templates = Any[]
+    for instance in model.instances
+        any(template -> template === instance.template, templates) || push!(templates, instance.template)
+    end
+    for (index, template) in pairs(templates)
+        println(io)
+        println(io, "template_$(index) = ", _template_code(session, template))
+    end
 
-function _using_statements(mapping::PlantSimEngine.ModelMapping)
-    modules = Set{Module}([PlantSimEngine])
-    for scale in keys(mapping)
-        for item in _scale_items(mapping[scale])
-            _collect_mapping_modules!(modules, item)
+    if !isempty(model.instances)
+        println(io)
+        println(io, "instances = (")
+        for instance in model.instances
+            template_index = only(index for (index, template) in pairs(templates) if template === instance.template)
+            println(io, "    ", _instance_code(instance, template_index), ",")
         end
+        println(io, ")")
+    else
+        println(io)
+        println(io, "instances = ()")
     end
-    return ["using $(_module_name(module_))" for module_ in sort!(collect(modules); by=_module_sort_key)]
-end
 
-function _collect_mapping_modules!(modules::Set{Module}, item)
-    item isa PlantSimEngine.Status && return modules
-    if item isa PlantSimEngine.ModelSpec || item isa PlantSimEngine.MultiScaleModel
-        return _collect_spec_modules!(modules, PlantSimEngine.as_model_spec(item))
+    mounted_ids = Set{Symbol}()
+    for instance in model.instances
+        union!(mounted_ids, PlantSimEngine._instance_application_ids(model, instance))
     end
-    item isa PlantSimEngine.AbstractModel && return _collect_model_modules!(modules, item)
-    return modules
-end
-
-function _collect_spec_modules!(modules::Set{Module}, spec::PlantSimEngine.ModelSpec)
-    _collect_model_modules!(modules, PlantSimEngine.model_(spec))
-    _collect_value_modules!(modules, PlantSimEngine.mapped_variables_(spec))
-    _collect_value_modules!(modules, PlantSimEngine.timestep(spec))
-    _collect_value_modules!(modules, spec.input_bindings)
-    _collect_value_modules!(modules, spec.meteo_bindings)
-    _collect_value_modules!(modules, spec.meteo_window)
-    _collect_value_modules!(modules, spec.output_routing)
-    _collect_value_modules!(modules, spec.scope)
-    return modules
-end
-
-function _collect_model_modules!(modules::Set{Module}, model::PlantSimEngine.AbstractModel)
-    module_ = parentmodule(typeof(model))
-    module_ in (Base, Core, Main) || push!(modules, module_)
-    return modules
+    global_applications = [
+        application for application in model.applications
+        if PlantSimEngine._model_edit_application_id(application) ∉ mounted_ids
+    ]
+    println(io, "applications = (")
+    for application in global_applications
+        println(io, "    ", _application_code(session, PlantSimEngine.as_model_spec(application)), ",")
+    end
+    println(io, ")")
+    environment = _environment_value_code(session, model.environment)
+    print(io, "model = CompositeModel(objects...; applications=applications, instances=instances, environment=$(environment))")
+    return String(take!(io))
 end
 
-function _collect_value_modules!(modules::Set{Module}, value)
-    value === nothing && return modules
-    if value isa Type
-        module_ = parentmodule(value)
-        module_ in (Base, Core, Main) || push!(modules, module_)
-        return modules
-    end
-    module_ = parentmodule(typeof(value))
-    module_ in (Base, Core, Main) || push!(modules, module_)
-    if value isa Pair
-        _collect_value_modules!(modules, first(value))
-        _collect_value_modules!(modules, last(value))
-    elseif value isa NamedTuple
-        for item in values(value)
-            _collect_value_modules!(modules, item)
-        end
-    elseif value isa Tuple || value isa AbstractArray
-        for item in value
-            _collect_value_modules!(modules, item)
+function _required_environment_names(session)
+    names = Set{Symbol}()
+    add_value = function (value)
+        for (name, environment) in session.environments
+            environment === value && push!(names, name)
         end
     end
-    return modules
-end
-
-function _module_name(module_::Module)
-    return join(string.(Base.fullname(module_)), ".")
-end
-
-function _module_sort_key(module_::Module)
-    module_ === PlantSimEngine && return ""
-    return _module_name(module_)
+    add_value(session.model.environment)
+    add_spec = function (raw_spec)
+        spec = PlantSimEngine.as_model_spec(raw_spec)
+        environment = PlantSimEngine.environment_config(spec)
+        isnothing(environment) && return
+        payload = environment isa PlantSimEngine.EnvironmentConfig ? environment.config : environment
+        payload isa NamedTuple && haskey(payload, :backend) && add_value(payload.backend)
+    end
+    foreach(add_spec, session.model.applications)
+    for object in PlantSimEngine.model_objects(session.model)
+        isnothing(object.applications) || foreach(add_spec, object.applications)
+    end
+    for instance in session.model.instances
+        foreach(add_spec, instance.template.applications)
+    end
+    return names
 end
 
-function _required_status_variables(mapping::PlantSimEngine.ModelMapping)
-    stripped = Dict{Symbol,Any}()
-    status_only_scales = Set{Symbol}()
-    for scale in keys(mapping)
-        items = [item for item in _scale_items(mapping[scale]) if !(item isa PlantSimEngine.Status)]
-        if isempty(items)
-            push!(status_only_scales, scale)
+function _model_code_models(model)
+    models = Any[]
+    add_application = function (application)
+        process_model = PlantSimEngine.model_(PlantSimEngine.as_model_spec(application))
+        if process_model isa PlantSimEngine.ObjectModelOverrides
+            push!(models, process_model.base)
+            append!(models, values(process_model.overrides))
         else
-            stripped[scale] = tuple(items...)
+            push!(models, process_model)
         end
     end
-
-    required = isempty(stripped) ?
-               Dict{Symbol,Vector{Symbol}}() :
-               PlantSimEngine.to_initialize(PlantSimEngine.ModelMapping(stripped; check=true, type_promotion=PlantSimEngine.type_promotion(mapping)))
-
-    required_by_scale = Dict{Symbol,Set{Symbol}}(
-        scale => Set{Symbol}(variables)
-        for (scale, variables) in pairs(required)
-    )
-    for scale in status_only_scales
-        required_by_scale[scale] = Set{Symbol}()
-        for item in _scale_items(mapping[scale])
-            item isa PlantSimEngine.Status || continue
-            union!(required_by_scale[scale], keys(item))
-        end
+    foreach(add_application, model.applications)
+    for object in PlantSimEngine.model_objects(model)
+        isnothing(object.applications) && continue
+        foreach(add_application, object.applications)
+    end
+    for instance in model.instances
+        foreach(add_application, instance.template.applications)
+        append!(models, values(instance.overrides))
+        append!(models, (override.model for override in instance.object_overrides))
     end
-    return required_by_scale
+    return models
 end
 
-function _mapping_item_to_code(item, required_status_variables=nothing)
-    if item isa PlantSimEngine.Status
-        return _status_to_code(item, required_status_variables)
-    end
-    if item isa PlantSimEngine.ModelSpec || item isa PlantSimEngine.MultiScaleModel
-        return _model_spec_to_code(PlantSimEngine.as_model_spec(item))
+function _model_code_modules(model)
+    modules = Set{String}(["PlantSimEngine"])
+    add_model = function (model)
+        module_ = parentmodule(typeof(model))
+        module_ in (Base, Core, Main) || push!(modules, string(module_))
     end
-    return repr(item)
+    foreach(add_model, _model_code_models(model))
+    return modules
 end
 
-function _status_to_code(status::PlantSimEngine.Status, required_variables)
-    isnothing(required_variables) && (required_variables = Set{Symbol}(keys(status)))
-    kept = Pair{Symbol,Any}[
-        name => status[name]
-        for name in keys(status)
-        if name in required_variables
+function _object_code(session, object)
+    keywords = String[
+        "scale=$(repr(object.scale))",
+        "kind=$(repr(object.kind))",
+        "species=$(repr(object.species))",
+        "name=$(repr(object.name))",
+        "parent=$(isnothing(object.parent) ? "nothing" : repr(object.parent.value))",
     ]
-    isempty(kept) && return nothing
-    names_code = _tuple_code(_symbol_code.(first.(kept)))
-    values_code = _tuple_code([repr(last(item)) for item in kept])
-    return "Status(NamedTuple{$names_code}($values_code))"
+    if object.status isa PlantSimEngine.Status
+        values = join(("$(name)=$(repr(object.status[name]))" for name in propertynames(object.status)), ", ")
+        push!(keywords, "status=Status(; $(values))")
+    end
+    isnothing(object.geometry) || push!(keywords, "geometry=$(repr(object.geometry))")
+    if !isnothing(object.applications) && object.applications != ()
+        applications = join(
+            (_application_code(session, PlantSimEngine.as_model_spec(application)) for application in object.applications),
+            ", ",
+        )
+        push!(keywords, "applications=($(applications),)")
+    end
+    return "Object($(repr(object.id.value)); $(join(keywords, ", ")))"
 end
 
-_symbol_code(symbol::Symbol) = repr(symbol)
-
-function _tuple_code(items)
-    values = collect(items)
-    suffix = length(values) == 1 ? "," : ""
-    return "(" * join(values, ", ") * suffix * ")"
+function _template_code(session, template)
+    applications = join(
+        ("        " * _application_code(session, PlantSimEngine.as_model_spec(application)) * "," for application in template.applications),
+        "\n",
+    )
+    return "CompositeModelTemplate((\n$(applications)\n    ); kind=$(repr(template.kind)), species=$(repr(template.species)), parameters=$(repr(template.parameters)))"
 end
 
-function _model_spec_to_code(spec::PlantSimEngine.ModelSpec)
-    code = "ModelSpec($(repr(PlantSimEngine.model_(spec))))"
-    mapped_variables = PlantSimEngine.mapped_variables_(spec)
-    isempty(mapped_variables) || (code *= " |> MultiScaleModel($(_mapped_variables_to_code(mapped_variables)))")
-    isnothing(PlantSimEngine.timestep(spec)) || (code *= " |> TimeStepModel($(_timestep_to_code(PlantSimEngine.timestep(spec))))")
-    _is_empty_namedtuple(spec.input_bindings) || (code *= " |> InputBindings($(_julia_code(spec.input_bindings)))")
-    _is_empty_namedtuple(spec.meteo_bindings) || (code *= " |> MeteoBindings($(_julia_code(spec.meteo_bindings)))")
-    isnothing(spec.meteo_window) || (code *= " |> MeteoWindow($(_julia_code(spec.meteo_window)))")
-    _is_empty_namedtuple(spec.output_routing) || (code *= " |> OutputRouting($(_julia_code(spec.output_routing)))")
-    _is_default_scope(spec.scope) || (code *= " |> ScopeModel($(_julia_code(spec.scope)))")
-    return code
+function _instance_code(instance, template_index)
+    overrides = if isempty(keys(instance.overrides))
+        "NamedTuple()"
+    else
+        entries = join(("$(key)=$(repr(model))" for (key, model) in pairs(instance.overrides)), ", ")
+        "($(entries),)"
+    end
+    object_overrides = if isempty(instance.object_overrides)
+        "()"
+    else
+        entries = join((_object_override_code(override) for override in instance.object_overrides), ", ")
+        "($(entries),)"
+    end
+    return "ObjectInstance($(repr(instance.name)), template_$(template_index); root=$(repr(PlantSimEngine._instance_root_id(instance).value)), overrides=$(overrides), object_overrides=$(object_overrides))"
 end
 
-_julia_code(value) = repr(value)
-_is_empty_namedtuple(value) = value isa NamedTuple && isempty(keys(value))
-_is_default_scope(scope) = scope == :global
+function _object_override_code(override)
+    options = String["object=$(repr(override.object.value))"]
+    isnothing(override.application) || push!(options, "application=$(repr(override.application))")
+    push!(options, "model=$(repr(override.model))")
+    return "Override(; $(join(options, ", ")))"
+end
 
-function _timestep_to_code(timestep::PlantSimEngine.ClockSpec)
-    return "ClockSpec($(repr(timestep.dt)), $(repr(timestep.phase)))"
+function _environment_value_code(session, value)
+    isnothing(value) && return "nothing"
+    for (name, environment) in session.environments
+        environment === value && return "editor_environments.$(name)"
+    end
+    return repr(value)
 end
 
-_timestep_to_code(timestep) = repr(timestep)
+function _environment_configuration_code(session, payload)
+    payload isa NamedTuple || return repr(payload)
+    entries = String[]
+    for (name, value) in pairs(payload)
+        code = Symbol(name) == :backend ? _environment_value_code(session, value) : repr(value)
+        push!(entries, "$(name)=$(code)")
+    end
+    return isempty(entries) ? "NamedTuple()" : "($(join(entries, ", ")),)"
+end
 
-function _mapped_variables_to_code(mapped_variables)
-    isempty(mapped_variables) && return "[]"
-    return "[" * join((_mapped_variable_to_code(i) for i in mapped_variables), ", ") * "]"
+function _application_code(session, spec)
+    options = String["name=$(repr(PlantSimEngine.application_name(spec)))"]
+    selector = PlantSimEngine.applies_to(spec)
+    isnothing(selector) || push!(options, "on=$(repr(selector))")
+    isempty(keys(PlantSimEngine.value_inputs(spec))) ||
+        push!(options, "inputs=$(repr(PlantSimEngine.value_inputs(spec)))")
+    isempty(keys(PlantSimEngine.model_calls(spec))) ||
+        push!(options, "calls=$(repr(PlantSimEngine.model_calls(spec)))")
+    environment = PlantSimEngine.environment_config(spec)
+    if !isnothing(environment)
+        payload = environment isa PlantSimEngine.EnvironmentConfig ? environment.config : environment
+        push!(options, "environment=Environment($(_environment_configuration_code(session, payload)))")
+    end
+    isnothing(spec.timestep) || push!(options, "every=$(repr(spec.timestep))")
+    if !isempty(keys(PlantSimEngine.environment_bindings(spec)))
+        push!(
+            options,
+            "environment_bindings=$(repr(PlantSimEngine.environment_bindings(spec)))",
+        )
+    end
+    if !isnothing(PlantSimEngine.environment_window(spec))
+        push!(
+            options,
+            "environment_window=$(repr(PlantSimEngine.environment_window(spec)))",
+        )
+    end
+    isempty(keys(PlantSimEngine.output_routing(spec))) ||
+        push!(options, "output_routing=$(repr(PlantSimEngine.output_routing(spec)))")
+    update_codes = String[]
+    for update in PlantSimEngine.updates(spec)
+        variables = join(repr.(collect(update.variables)), ", ")
+        push!(update_codes, "Updates($(variables); after=$(repr(update.after)))")
+    end
+    if length(update_codes) == 1
+        push!(options, "updates=$(only(update_codes))")
+    elseif !isempty(update_codes)
+        push!(options, "updates=($(join(update_codes, ", ")),)")
+    end
+    return "ModelSpec($(repr(PlantSimEngine.model_(spec))); $(join(options, ", ")))"
 end
 
-function _mapped_variable_to_code(mapping)
-    lhs = first(mapping)
-    rhs = last(mapping)
-    lhs_code = _mapped_lhs_to_code(lhs)
-    variable = _mapped_variable_symbol(lhs)
-    rhs_code = _mapped_rhs_to_code(rhs, variable)
-    return "$(lhs_code) => $(rhs_code)"
+function _persist_model!(session)
+    code = _model_to_julia(session) * "\n"
+    isnothing(session.autosave_path) || _atomic_write(session.autosave_path, code)
+    isnothing(session.save_path) || _atomic_write(session.save_path, code)
+    return nothing
 end
 
-_mapped_variable_symbol(variable::Symbol) = variable
-_mapped_variable_symbol(variable::PlantSimEngine.PreviousTimeStep) = variable.variable
+function _atomic_write(path, content)
+    path = _normalized_path(path)
+    mkpath(dirname(path))
+    temporary = tempname(dirname(path))
+    try
+        write(temporary, content)
+        mv(temporary, path; force=true)
+    finally
+        isfile(temporary) && rm(temporary; force=true)
+    end
+    return path
+end
 
-_mapped_lhs_to_code(variable::Symbol) = _symbol_code(variable)
-_mapped_lhs_to_code(variable::PlantSimEngine.PreviousTimeStep) = "PreviousTimeStep($(_symbol_code(variable.variable)))"
+_normalized_path(path) = isabspath(String(path)) ? normpath(String(path)) : normpath(joinpath(pwd(), String(path)))
 
-function _mapped_rhs_to_code(rhs::Pair{Symbol,Symbol}, variable::Symbol)
-    source_scale = first(rhs)
-    source_variable = last(rhs)
-    if source_scale == Symbol("")
-        return "($(_symbol_code(source_scale)) => $(_symbol_code(source_variable)))"
-    end
-    if source_variable == variable
-        return _symbol_code(source_scale)
-    end
-    return "($(_symbol_code(source_scale)) => $(_symbol_code(source_variable)))"
+function _default_autosave_path()
+    return joinpath(
+        tempdir(),
+        "PlantSimEngineGraphEditor",
+        string("session-", time_ns()),
+        "model.autosave.jl",
+    )
 end
 
-function _mapped_rhs_to_code(rhs::AbstractVector{<:Pair{Symbol,Symbol}}, variable::Symbol)
-    compact = all(last(i) == variable for i in rhs)
-    if compact
-        return "[" * join((_symbol_code(first(i)) for i in rhs), ", ") * "]"
+function _open_in_default_browser(url)
+    try
+        if Sys.isapple()
+            run(`open $url`)
+        elseif Sys.iswindows()
+            run(`cmd /c start "" $url`)
+        elseif !isnothing(Sys.which("xdg-open"))
+            run(`xdg-open $url`)
+        else
+            @warn "Could not locate a default-browser command." url
+            return false
+        end
+        return true
+    catch err
+        @warn "Could not open the graph editor automatically." url exception=(err, catch_backtrace())
+        return false
     end
-    return "[" * join(("($(_symbol_code(first(i))) => $(_symbol_code(last(i))))" for i in rhs), ", ") * "]"
 end
 
 end
diff --git a/frontend/.vite/deps/_metadata.json b/frontend/.vite/deps/_metadata.json
deleted file mode 100644
index 76dbdb36e..000000000
--- a/frontend/.vite/deps/_metadata.json
+++ /dev/null
@@ -1,8 +0,0 @@
-{
-  "hash": "9cb674f6",
-  "configHash": "2b83bb6c",
-  "lockfileHash": "dfbd2d0d",
-  "browserHash": "d060dbeb",
-  "optimized": {},
-  "chunks": {}
-}
\ No newline at end of file
diff --git a/frontend/.vite/deps/package.json b/frontend/.vite/deps/package.json
deleted file mode 100644
index 3dbc1ca59..000000000
--- a/frontend/.vite/deps/package.json
+++ /dev/null
@@ -1,3 +0,0 @@
-{
-  "type": "module"
-}
diff --git a/frontend/dist/.vite/manifest.json b/frontend/dist/.vite/manifest.json
index b4fde8484..ebe27b401 100644
--- a/frontend/dist/.vite/manifest.json
+++ b/frontend/dist/.vite/manifest.json
@@ -1,11 +1,11 @@
 {
   "index.html": {
-    "file": "assets/index--4z54nN9.js",
+    "file": "assets/index-CfC2_AOV.js",
     "name": "index",
     "src": "index.html",
     "isEntry": true,
     "css": [
-      "assets/index-DwZ0xeih.css"
+      "assets/index-DH4q_-2-.css"
     ]
   }
 }
\ No newline at end of file
diff --git a/frontend/dist/assets/index--4z54nN9.js b/frontend/dist/assets/index--4z54nN9.js
deleted file mode 100644
index 4ba2bf006..000000000
--- a/frontend/dist/assets/index--4z54nN9.js
+++ /dev/null
@@ -1,38 +0,0 @@
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Su=wi?.selectable??!0;for(const uu of un.current){const Js=ct.get(uu);if(Js)for(const{edgeId:fa}of Js.values()){const bh=on.get(fa);bh&&(bh.selectable??Su)&&An.current.add(fa)}}if(!o1n(Si,un.current)){const uu=d_(Se,un.current,!0);lt(uu)}if(!o1n(Ui,An.current)){const uu=d_(on,An.current);qt(uu)}ee.setState({userSelectionRect:vr,userSelectionActive:!0,nodesSelectionActive:!1})},ke=ln=>{ln.button===0&&(ln.target?.releasePointerCapture?.(ln.pointerId),!Ce&&ln.target===rn.current&&ee.getState().userSelectionRect&&$t?.(ln),ee.setState({userSelectionActive:!1,userSelectionRect:null}),Dn.current&&(H?.(ln),ee.setState({nodesSelectionActive:un.current.size>0})))},Ze=x===!0||Array.isArray(x)&&x.includes(0);return G.jsxs("div",{className:$a(["react-flow__pane",{draggable:Ze,dragging:ze,selection:g}]),onClick:De?void 0:G7e($t,rn),onContextMenu:G7e(In,rn),onWheel:G7e(et,rn),onPointerEnter:De?void 0:Z,onPointerMove:De?en:ne,onPointerUp:De?ke:void 0,onPointerDownCapture:De?He:void 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R0n=()=>Pe.useContext(Cke),Yqn=g=>({connectOnClick:g.connectOnClick,noPanClassName:g.noPanClassName,rfId:g.rfId}),Wqn=(g,E,M)=>x=>{const{connectionClickStartHandle:O,connectionMode:P,connection:k}=x,{fromHandle:H,toHandle:q,isValid:F}=k,W=q?.nodeId===g&&q?.id===E&&q?.type===M;return{connectingFrom:H?.nodeId===g&&H?.id===E&&H?.type===M,connectingTo:W,clickConnecting:O?.nodeId===g&&O?.id===E&&O?.type===M,isPossibleEndHandle:P===m_.Strict?H?.type!==M:g!==H?.nodeId||E!==H?.id,connectionInProcess:!!H,clickConnectionInProcess:!!O,valid:W&&F}};function Zqn({type:g="source",position:E=er.Top,isValidConnection:M,isConnectable:x=!0,isConnectableStart:O=!0,isConnectableEnd:P=!0,id:k,onConnect:H,children:q,className:F,onMouseDown:W,onTouchStart:Z,...ne},le){const se=k||null,ee=g==="target",Ce=Nl(),je=R0n(),{connectOnClick:ze,noPanClassName:be,rfId:De}=Fu(Yqn,Ol),{connectingFrom:rn,connectingTo:an,clickConnecting:un,isPossibleEndHandle:An,connectionInProcess:Dn,clickConnectionInProcess:$t,valid:In}=Fu(Wqn(je,se,g),Ol);je||Ce.getState().onError?.("010",N4.error010());const et=en=>{const{defaultEdgeOptions:ke,onConnect:Ze,hasDefaultEdges:ln}=Ce.getState(),En={...ke,...en};if(ln){const{edges:nt,setEdges:Se}=Ce.getState();Se(vGn(En,nt))}Ze?.(En),H?.(En)},Y=en=>{if(!je)return;const ke=f0n(en.nativeEvent);if(O&&(ke&&en.button===0||!ke)){const 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G.jsxs(G.Fragment,{children:[g?.label,G.jsx(D4,{type:"source",position:M,isConnectable:E})]})}function nUn({data:g,isConnectable:E,targetPosition:M=er.Top,sourcePosition:x=er.Bottom}){return G.jsxs(G.Fragment,{children:[G.jsx(D4,{type:"target",position:M,isConnectable:E}),g?.label,G.jsx(D4,{type:"source",position:x,isConnectable:E})]})}function tUn(){return null}function iUn({data:g,isConnectable:E,targetPosition:M=er.Top}){return G.jsxs(G.Fragment,{children:[G.jsx(D4,{type:"target",position:M,isConnectable:E}),g?.label]})}const Mue={ArrowUp:{x:0,y:-1},ArrowDown:{x:0,y:1},ArrowLeft:{x:-1,y:0},ArrowRight:{x:1,y:0}},$1n={input:eUn,default:nUn,output:iUn,group:tUn};function rUn(g){return g.internals.handleBounds===void 0?{width:g.width??g.initialWidth??g.style?.width,height:g.height??g.initialHeight??g.style?.height}:{width:g.width??g.style?.width,height:g.height??g.style?.height}}const cUn=g=>{const{width:E,height:M,x,y:O}=rq(g.nodeLookup,{filter:P=>!!P.selected});return{width:k3(E)?E:null,height:k3(M)?M:null,userSelectionActive:g.userSelectionActive,transformString:`translate(${g.transform[0]}px,${g.transform[1]}px) scale(${g.transform[2]}) translate(${x}px,${O}px)`}};function uUn({onSelectionContextMenu:g,noPanClassName:E,disableKeyboardA11y:M}){const x=Nl(),{width:O,height:P,transformString:k,userSelectionActive:H}=Fu(cUn,Ol),q=$0n(),F=Pe.useRef(null);Pe.useEffect(()=>{M||F.current?.focus({preventScroll:!0})},[M]);const W=!H&&O!==null&&P!==null;if(P0n({nodeRef:F,disabled:!W}),!W)return null;const Z=g?le=>{const se=x.getState().nodes.filter(ee=>ee.selected);g(le,se)}:void 0,ne=le=>{Object.prototype.hasOwnProperty.call(Mue,le.key)&&(le.preventDefault(),q({direction:Mue[le.key],factor:le.shiftKey?4:1}))};return G.jsx("div",{className:$a(["react-flow__nodesselection","react-flow__container",E]),style:{transform:k},children:G.jsx("div",{ref:F,className:"react-flow__nodesselection-rect",onContextMenu:Z,tabIndex:M?void 0:-1,onKeyDown:M?void 0:ne,style:{width:O,height:P}})})}const R1n=typeof window<"u"?window:void 0,oUn=g=>({nodesSelectionActive:g.nodesSelectionActive,userSelectionActive:g.userSelectionActive});function B0n({children:g,onPaneClick:E,onPaneMouseEnter:M,onPaneMouseMove:x,onPaneMouseLeave:O,onPaneContextMenu:P,onPaneScroll:k,paneClickDistance:H,deleteKeyCode:q,selectionKeyCode:F,selectionOnDrag:W,selectionMode:Z,onSelectionStart:ne,onSelectionEnd:le,multiSelectionKeyCode:se,panActivationKeyCode:ee,zoomActivationKeyCode:Ce,elementsSelectable:je,zoomOnScroll:ze,zoomOnPinch:be,panOnScroll:De,panOnScrollSpeed:rn,panOnScrollMode:an,zoomOnDoubleClick:un,panOnDrag:An,defaultViewport:Dn,translateExtent:$t,minZoom:In,maxZoom:et,preventScrolling:Y,onSelectionContextMenu:He,noWheelClassName:en,noPanClassName:ke,disableKeyboardA11y:Ze,onViewportChange:ln,isControlledViewport:En}){const{nodesSelectionActive:nt,userSelectionActive:Se}=Fu(oUn,Ol),on=WG(F,{target:R1n}),ct=WG(ee,{target:R1n}),lt=ct||An,qt=ct||De,wi=W&<!==!0,li=on||Se||wi;return Fqn({deleteKeyCode:q,multiSelectionKeyCode:se}),G.jsx(Gqn,{onPaneContextMenu:P,elementsSelectable:je,zoomOnScroll:ze,zoomOnPinch:be,panOnScroll:qt,panOnScrollSpeed:rn,panOnScrollMode:an,zoomOnDoubleClick:un,panOnDrag:!on&<,defaultViewport:Dn,translateExtent:$t,minZoom:In,maxZoom:et,zoomActivationKeyCode:Ce,preventScrolling:Y,noWheelClassName:en,noPanClassName:ke,onViewportChange:ln,isControlledViewport:En,paneClickDistance:H,selectionOnDrag:wi,children:G.jsxs(Vqn,{onSelectionStart:ne,onSelectionEnd:le,onPaneClick:E,onPaneMouseEnter:M,onPaneMouseMove:x,onPaneMouseLeave:O,onPaneContextMenu:P,onPaneScroll:k,panOnDrag:lt,isSelecting:!!li,selectionMode:Z,selectionKeyPressed:on,paneClickDistance:H,selectionOnDrag:wi,children:[g,nt&&G.jsx(uUn,{onSelectionContextMenu:He,noPanClassName:ke,disableKeyboardA11y:Ze})]})})}B0n.displayName="FlowRenderer";const sUn=Pe.memo(B0n),lUn=g=>E=>g?yke(E.nodeLookup,{x:0,y:0,width:E.width,height:E.height},E.transform,!0).map(M=>M.id):Array.from(E.nodeLookup.keys());function fUn(g){return Fu(Pe.useCallback(lUn(g),[g]),Ol)}const aUn=g=>g.updateNodeInternals;function hUn(){const g=Fu(aUn),[E]=Pe.useState(()=>typeof ResizeObserver>"u"?null:new ResizeObserver(M=>{const x=new Map;M.forEach(O=>{const P=O.target.getAttribute("data-id");x.set(P,{id:P,nodeElement:O.target,force:!0})}),g(x)}));return Pe.useEffect(()=>()=>{E?.disconnect()},[E]),E}function dUn({node:g,nodeType:E,hasDimensions:M,resizeObserver:x}){const O=Nl(),P=Pe.useRef(null),k=Pe.useRef(null),H=Pe.useRef(g.sourcePosition),q=Pe.useRef(g.targetPosition),F=Pe.useRef(E),W=M&&!!g.internals.handleBounds;return Pe.useEffect(()=>{P.current&&!g.hidden&&(!W||k.current!==P.current)&&(k.current&&x?.unobserve(k.current),x?.observe(P.current),k.current=P.current)},[W,g.hidden]),Pe.useEffect(()=>()=>{k.current&&(x?.unobserve(k.current),k.current=null)},[]),Pe.useEffect(()=>{if(P.current){const Z=F.current!==E,ne=H.current!==g.sourcePosition,le=q.current!==g.targetPosition;(Z||ne||le)&&(F.current=E,H.current=g.sourcePosition,q.current=g.targetPosition,O.getState().updateNodeInternals(new Map([[g.id,{id:g.id,nodeElement:P.current,force:!0}]])))}},[g.id,E,g.sourcePosition,g.targetPosition]),P}function bUn({id:g,onClick:E,onMouseEnter:M,onMouseMove:x,onMouseLeave:O,onContextMenu:P,onDoubleClick:k,nodesDraggable:H,elementsSelectable:q,nodesConnectable:F,nodesFocusable:W,resizeObserver:Z,noDragClassName:ne,noPanClassName:le,disableKeyboardA11y:se,rfId:ee,nodeTypes:Ce,nodeClickDistance:je,onError:ze}){const{node:be,internals:De,isParent:rn}=Fu(Ut=>{const ai=Ut.nodeLookup.get(g),rc=Ut.parentLookup.has(g);return{node:ai,internals:ai.internals,isParent:rc}},Ol);let an=be.type||"default",un=Ce?.[an]||$1n[an];un===void 0&&(ze?.("003",N4.error003(an)),an="default",un=Ce?.default||$1n.default);const An=!!(be.draggable||H&&typeof be.draggable>"u"),Dn=!!(be.selectable||q&&typeof be.selectable>"u"),$t=!!(be.connectable||F&&typeof be.connectable>"u"),In=!!(be.focusable||W&&typeof be.focusable>"u"),et=Nl(),Y=u0n(be),He=dUn({node:be,nodeType:an,hasDimensions:Y,resizeObserver:Z}),en=P0n({nodeRef:He,disabled:be.hidden||!An,noDragClassName:ne,handleSelector:be.dragHandle,nodeId:g,isSelectable:Dn,nodeClickDistance:je}),ke=$0n();if(be.hidden)return null;const Ze=j6(be),ln=rUn(be),En=Dn||An||E||M||x||O,nt=M?Ut=>M(Ut,{...De.userNode}):void 0,Se=x?Ut=>x(Ut,{...De.userNode}):void 0,on=O?Ut=>O(Ut,{...De.userNode}):void 0,ct=P?Ut=>P(Ut,{...De.userNode}):void 0,lt=k?Ut=>k(Ut,{...De.userNode}):void 0,qt=Ut=>{const{selectNodesOnDrag:ai,nodeDragThreshold:rc}=et.getState();Dn&&(!ai||!An||rc>0)&&oke({id:g,store:et,nodeRef:He}),E&&E(Ut,{...De.userNode})},wi=Ut=>{if(!(l0n(Ut.nativeEvent)||se)){if(Ydn.includes(Ut.key)&&Dn){const ai=Ut.key==="Escape";oke({id:g,store:et,unselect:ai,nodeRef:He})}else if(An&&be.selected&&Object.prototype.hasOwnProperty.call(Mue,Ut.key)){Ut.preventDefault();const{ariaLabelConfig:ai}=et.getState();et.setState({ariaLiveMessage:ai["node.a11yDescription.ariaLiveMessage"]({direction:Ut.key.replace("Arrow","").toLowerCase(),x:~~De.positionAbsolute.x,y:~~De.positionAbsolute.y})}),ke({direction:Mue[Ut.key],factor:Ut.shiftKey?4:1})}}},li=()=>{if(se||!He.current?.matches(":focus-visible"))return;const{transform:Ut,width:ai,height:rc,autoPanOnNodeFocus:Qr,setCenter:vr}=et.getState();if(!Qr)return;yke(new Map([[g,be]]),{x:0,y:0,width:ai,height:rc},Ut,!0).length>0||vr(be.position.x+Ze.width/2,be.position.y+Ze.height/2,{zoom:Ut[2]})};return G.jsx("div",{className:$a(["react-flow__node",`react-flow__node-${an}`,{[le]:An},be.className,{selected:be.selected,selectable:Dn,parent:rn,draggable:An,dragging:en}]),ref:He,style:{zIndex:De.z,transform:`translate(${De.positionAbsolute.x}px,${De.positionAbsolute.y}px)`,pointerEvents:En?"all":"none",visibility:Y?"visible":"hidden",...be.style,...ln},"data-id":g,"data-testid":`rf__node-${g}`,onMouseEnter:nt,onMouseMove:Se,onMouseLeave:on,onContextMenu:ct,onClick:qt,onDoubleClick:lt,onKeyDown:In?wi:void 0,tabIndex:In?0:void 0,onFocus:In?li:void 0,role:be.ariaRole??(In?"group":void 0),"aria-roledescription":"node","aria-describedby":se?void 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c,o;(!sc(n)&&n.c.i.c==n.d.i.c||!ABe(mu(z(B($r,1),Ae,8,0,[r.i.n,r.n,r.a])),t))&&!sc(n)&&(n.c==r?R9(n.a,0,new mc(t)):Vt(n.a,new mc(t)),i&&!hf(e.a,t)&&(o=u(T(n,(Oe(),Wc)),78),o||(o=new Os,ae(n,Wc,o)),c=new mc(t),Vi(o,c,o.c.b,o.c),dr(e.a,c)))}function HUe(e,n){var t,i,r,c;for(c=Lt(bc(h1,c1(Lt(bc(n==null?0:Ni(n),d1)),15))),t=c&e.b.length-1,r=null,i=e.b[t];i;r=i,i=i.a)if(i.d==c&&X1(i.i,n))return r?r.a=i.a:e.b[t]=i.a,uAe(u(bf(i.c),593),u(bf(i.f),593)),WT(u(bf(i.b),227),u(bf(i.e),227)),--e.f,++e.e,!0;return!1}function kDn(e){var n,t;for(t=new Gn(Vn(or(e).a.Jc(),new ee));ht(t);)if(n=u(it(t),17),n.c.i.k!=(Bn(),Uu))throw $(new Id(cee+zO(e)+"' has its layer constraint set to FIRST, but has at least one incoming edge that  does not come from a FIRST_SEPARATE node. 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r,c,o,l,f,h,b,p,y,S;if(f=e.c.d,h=e.d.d,f.j!=h.j)for(S=e.b,b=null,l=null,o=Gjn(e),o&&S.i&&(b=e.b.i.i,l=S.i.j),r=f.j,p=null;r!=h.j;)p=n==0?VB(r):U1e(r),c=Sde(r,S.d[r.g],t),y=Sde(p,S.d[p.g],t),o&&b&&l&&(r==b?RFe(c,b,l):p==b&&RFe(y,b,l)),Vt(i,gi(c,y)),r=p}function Cbe(e,n,t){var i,r,c,o,l,f;if(i=vgn(t,e.length),o=e[i],c=aAe(t,o.length),o[c].k==(Bn(),pr))for(f=n.j,r=0;r0&&(t[0]+=e.d,o-=t[0]),t[2]>0&&(t[2]+=e.d,o-=t[2]),c=k.Math.max(0,o),t[1]=k.Math.max(t[1],o),Qae(e,No,r.c+i.b+t[0]-(t[1]-o)/2,t),n==No&&(e.c.b=c,e.c.c=r.c+i.b+(c-o)/2)}function ZUe(){this.c=oe(Gr,Hc,30,(Ne(),z(B(Ac,1),qu,64,0,[Eu,Un,Wn,bt,Xn])).length,15,1),this.b=oe(Gr,Hc,30,z(B(Ac,1),qu,64,0,[Eu,Un,Wn,bt,Xn]).length,15,1),this.a=oe(Gr,Hc,30,z(B(Ac,1),qu,64,0,[Eu,Un,Wn,bt,Xn]).length,15,1),cse(this.c,Ki),cse(this.b,Ir),cse(this.a,Ir)}function LDn(e,n,t,i){var r,c,o,l,f;for(f=n.i,l=t[f.g][e.d[f.g]],r=!1,o=new L(n.d);o.a=r&&(e.c=!1,e.a=!1),e.b[i++]=r,e.b[i]=c,e.c||Nv(e)}}function PDn(e,n,t){var i,r,c,o,l,f,h;for(h=n.d,e.a=new 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99:A=i.q.getDay(),t==5?Xt(e,z(B(Be,1),Ae,2,6,["S","M","T","W","T","F","S"])[A]):t==4?Xt(e,z(B(Be,1),Ae,2,6,[NZ,DZ,_Z,IZ,LZ,PZ,$Z])[A]):t==3?Xt(e,z(B(Be,1),Ae,2,6,["Sun","Mon","Tue","Wed","Thu","Fri","Sat"])[A]):o1(e,A,1);break;case 76:N=i.q.getMonth(),t==5?Xt(e,z(B(Be,1),Ae,2,6,["J","F","M","A","M","J","J","A","S","O","N","D"])[N]):t==4?Xt(e,z(B(Be,1),Ae,2,6,[yZ,kZ,EZ,jZ,Ay,SZ,MZ,AZ,xZ,TZ,CZ,OZ])[N]):t==3?Xt(e,z(B(Be,1),Ae,2,6,["Jan","Feb","Mar","Apr",Ay,"Jun","Jul","Aug","Sep","Oct","Nov","Dec"])[N]):o1(e,N+1,t);break;case 81:_=i.q.getMonth()/3|0,t<4?Xt(e,z(B(Be,1),Ae,2,6,["Q1","Q2","Q3","Q4"])[_]):Xt(e,z(B(Be,1),Ae,2,6,["1st quarter","2nd quarter","3rd quarter","4th quarter"])[_]);break;case 100:R=i.q.getDate(),o1(e,R,t);break;case 109:h=r.q.getMinutes(),o1(e,h,t);break;case 115:o=r.q.getSeconds(),o1(e,o,t);break;case 122:t<4?Xt(e,c.c[0]):Xt(e,c.c[1]);break;case 118:Xt(e,c.b);break;case 90:t<3?Xt(e,jCn(c)):t==3?Xt(e,xCn(c)):Xt(e,TCn(c.a));break;default:return!1}return!0}function Nge(e,n,t,i){var r,c,o,l,f,h,b,p,y,S,A,N,_,R,U,K,ie,de,fe,_e,cn,tn,Mn,Cn,st,Qt;if(NXe(n),f=u(V((!n.b&&(n.b=new Tn(mt,n,4,7)),n.b),0),84),b=u(V((!n.c&&(n.c=new Tn(mt,n,5,8)),n.c),0),84),l=ru(f),h=ru(b),o=(!n.a&&(n.a=new we($i,n,6,6)),n.a).i==0?null:u(V((!n.a&&(n.a=new we($i,n,6,6)),n.a),0),170),_e=u(Rn(e.a,l),9),Cn=u(Rn(e.a,h),9),cn=null,st=null,X(f,193)&&(fe=u(Rn(e.a,f),246),X(fe,12)?cn=u(fe,12):X(fe,9)&&(_e=u(fe,9),cn=u(Le(_e.j,0),12))),X(b,193)&&(Mn=u(Rn(e.a,b),246),X(Mn,12)?st=u(Mn,12):X(Mn,9)&&(Cn=u(Mn,9),st=u(Le(Cn.j,0),12))),!_e||!Cn)throw $(new A5("The source or the target of edge "+n+" could not be found. This usually happens when an edge connects a node laid out by ELK Layered to a node in another level of hierarchy laid out by either another instance of ELK Layered or another layout algorithm alltogether. 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ABn(e,n,t,i){var r,c,o,l,f,h,b,p,y,S,A,N,_,R,U,K,ie,de,fe,_e,cn,tn,Mn,Cn,st,Qt,qi;for(tn=0,Mn=0,_e=new wt,de=u(Ks(Hp(So(new wn(null,new pn(e.b,16)),new MI),new Bk)),15).a+1,cn=oe(It,ei,30,de,15,1),_=oe(It,ei,30,de,15,1),N=0;N1)for(l=st+1;lh.b.e.b*(1-R)+h.c.e.b*R));A++);if(fe.gc()>0&&(Qt=h.a.b==0?vc(h.b.e):u(Bf(h.a),8),K=gi(vc(u(fe.Xb(fe.gc()-1),40).e),u(fe.Xb(fe.gc()-1),40).f),y=gi(vc(u(fe.Xb(0),40).e),u(fe.Xb(0),40).f),A>=fe.gc()-1&&Qt.b>K.b&&h.c.e.b>K.b||A<=0&&Qt.bh.b.e.a*(1-R)+h.c.e.a*R));A++);if(fe.gc()>0&&(Qt=h.a.b==0?vc(h.b.e):u(Bf(h.a),8),K=gi(vc(u(fe.Xb(fe.gc()-1),40).e),u(fe.Xb(fe.gc()-1),40).f),y=gi(vc(u(fe.Xb(0),40).e),u(fe.Xb(0),40).f),A>=fe.gc()-1&&Qt.a>K.a&&h.c.e.a>K.a||A<=0&&Qt.a=te(re(T(e,(Ci(),mye))))&&++Mn):(S.f&&S.d.e.a<=te(re(T(e,(Ci(),mre))))&&++tn,S.g&&S.c.e.a+S.c.f.a>=te(re(T(e,(Ci(),pye))))&&++Mn)}else ie==0?X0e(h):ie<0&&(++cn[st],++_[qi],Cn=yBn(h,n,e,new jc(me(tn),me(Mn)),t,i,new jc(me(_[qi]),me(cn[st]))),tn=u(Cn.a,15).a,Mn=u(Cn.b,15).a)}function xBn(e){e.gb||(e.gb=!0,e.b=xu(e,0),Qi(e.b,18),Ii(e.b,19),e.a=xu(e,1),Qi(e.a,1),Ii(e.a,2),Ii(e.a,3),Ii(e.a,4),Ii(e.a,5),e.o=xu(e,2),Qi(e.o,8),Qi(e.o,9),Ii(e.o,10),Ii(e.o,11),Ii(e.o,12),Ii(e.o,13),Ii(e.o,14),Ii(e.o,15),Ii(e.o,16),Ii(e.o,17),Ii(e.o,18),Ii(e.o,19),Ii(e.o,20),Ii(e.o,21),Ii(e.o,22),Ii(e.o,23),Qc(e.o),Qc(e.o),Qc(e.o),Qc(e.o),Qc(e.o),Qc(e.o),Qc(e.o),Qc(e.o),Qc(e.o),Qc(e.o),e.p=xu(e,3),Qi(e.p,2),Qi(e.p,3),Qi(e.p,4),Qi(e.p,5),Ii(e.p,6),Ii(e.p,7),Qc(e.p),Qc(e.p),e.q=xu(e,4),Qi(e.q,8),e.v=xu(e,5),Ii(e.v,9),Qc(e.v),Qc(e.v),Qc(e.v),e.w=xu(e,6),Qi(e.w,2),Qi(e.w,3),Qi(e.w,4),Ii(e.w,5),e.B=xu(e,7),Ii(e.B,1),Qc(e.B),Qc(e.B),Qc(e.B),e.Q=xu(e,8),Ii(e.Q,0),Qc(e.Q),e.R=xu(e,9),Qi(e.R,1),e.S=xu(e,10),Qc(e.S),Qc(e.S),Qc(e.S),Qc(e.S),Qc(e.S),Qc(e.S),Qc(e.S),Qc(e.S),Qc(e.S),Qc(e.S),Qc(e.S),Qc(e.S),Qc(e.S),Qc(e.S),Qc(e.S),e.T=xu(e,11),Ii(e.T,10),Ii(e.T,11),Ii(e.T,12),Ii(e.T,13),Ii(e.T,14),Qc(e.T),Qc(e.T),e.U=xu(e,12),Qi(e.U,2),Qi(e.U,3),Ii(e.U,4),Ii(e.U,5),Ii(e.U,6),Ii(e.U,7),Qc(e.U),e.V=xu(e,13),Ii(e.V,10),e.W=xu(e,14),Qi(e.W,18),Qi(e.W,19),Qi(e.W,20),Ii(e.W,21),Ii(e.W,22),Ii(e.W,23),e.bb=xu(e,15),Qi(e.bb,10),Qi(e.bb,11),Qi(e.bb,12),Qi(e.bb,13),Qi(e.bb,14),Qi(e.bb,15),Qi(e.bb,16),Ii(e.bb,17),Qc(e.bb),Qc(e.bb),e.eb=xu(e,16),Qi(e.eb,2),Qi(e.eb,3),Qi(e.eb,4),Qi(e.eb,5),Qi(e.eb,6),Qi(e.eb,7),Ii(e.eb,8),Ii(e.eb,9),e.ab=xu(e,17),Qi(e.ab,0),Qi(e.ab,1),e.H=xu(e,18),Ii(e.H,0),Ii(e.H,1),Ii(e.H,2),Ii(e.H,3),Ii(e.H,4),Ii(e.H,5),Qc(e.H),e.db=xu(e,19),Ii(e.db,2),e.c=ri(e,20),e.d=ri(e,21),e.e=ri(e,22),e.f=ri(e,23),e.i=ri(e,24),e.g=ri(e,25),e.j=ri(e,26),e.k=ri(e,27),e.n=ri(e,28),e.r=ri(e,29),e.s=ri(e,30),e.t=ri(e,31),e.u=ri(e,32),e.fb=ri(e,33),e.A=ri(e,34),e.C=ri(e,35),e.D=ri(e,36),e.F=ri(e,37),e.G=ri(e,38),e.I=ri(e,39),e.J=ri(e,40),e.L=ri(e,41),e.M=ri(e,42),e.N=ri(e,43),e.O=ri(e,44),e.P=ri(e,45),e.X=ri(e,46),e.Y=ri(e,47),e.Z=ri(e,48),e.$=ri(e,49),e._=ri(e,50),e.cb=ri(e,51),e.K=ri(e,52))}function TBn(e,n,t,i){var r,c,o,l,f,h,b,p,y,S,A;for(p=jt(e.b,0);p.b!=p.d.c;)if(b=u(kt(p),40),!bn(b.c,$F))for(c=u(ys(new wn(null,new pn(FCn(b,e),16)),_s(new Ui,new Si,new nu,z(B(Zo,1),ye,130,0,[(Kl(),Wo)]))),16),n==(kr(),Zc)||n==cu?c.gd(new NI):c.gd(new DI),A=c.gc(),r=0;r0&&(l=u(Bf(u(c.Xb(r),65).a),8).a,y=b.e.a+b.f.a/2,f=u(Bf(u(c.Xb(r),65).a),8).b,S=b.e.b+b.f.b/2,i>0&&k.Math.abs(f-S)/(k.Math.abs(l-y)/40)>50&&(S>f?pc(u(c.Xb(r),65).a,new Ee(b.e.a+b.f.a+i/5.3,b.e.b+b.f.b*o-i/2)):pc(u(c.Xb(r),65).a,new Ee(b.e.a+b.f.a+i/5.3,b.e.b+b.f.b*o+i/2)))),pc(u(c.Xb(r),65).a,new Ee(b.e.a+b.f.a,b.e.b+b.f.b*o))):n==cu?(h=te(re(T(b,(Ci(),Da)))),b.e.a-i>h?pc(u(c.Xb(r),65).a,new Ee(h-t,b.e.b+b.f.b*o)):u(c.Xb(r),65).a.b>0&&(l=u(Bf(u(c.Xb(r),65).a),8).a,y=b.e.a+b.f.a/2,f=u(Bf(u(c.Xb(r),65).a),8).b,S=b.e.b+b.f.b/2,i>0&&k.Math.abs(f-S)/(k.Math.abs(l-y)/40)>50&&(S>f?pc(u(c.Xb(r),65).a,new Ee(b.e.a-i/5.3,b.e.b+b.f.b*o-i/2)):pc(u(c.Xb(r),65).a,new Ee(b.e.a-i/5.3,b.e.b+b.f.b*o+i/2)))),pc(u(c.Xb(r),65).a,new Ee(b.e.a,b.e.b+b.f.b*o))):n==cf?(h=te(re(T(b,(Ci(),ta)))),b.e.b+b.f.b+i0&&(l=u(Bf(u(c.Xb(r),65).a),8).a,y=b.e.a+b.f.a/2,f=u(Bf(u(c.Xb(r),65).a),8).b,S=b.e.b+b.f.b/2,i>0&&k.Math.abs(l-y)/(k.Math.abs(f-S)/40)>50&&(y>l?pc(u(c.Xb(r),65).a,new Ee(b.e.a+b.f.a*o-i/2,b.e.b+i/5.3+b.f.b)):pc(u(c.Xb(r),65).a,new Ee(b.e.a+b.f.a*o+i/2,b.e.b+i/5.3+b.f.b)))),pc(u(c.Xb(r),65).a,new Ee(b.e.a+b.f.a*o,b.e.b+b.f.b))):(h=te(re(T(b,(Ci(),Da)))),Lze(u(c.Xb(r),65),e)?pc(u(c.Xb(r),65).a,new Ee(b.e.a+b.f.a*o,u(Bf(u(c.Xb(r),65).a),8).b)):b.e.b-i>h?pc(u(c.Xb(r),65).a,new Ee(b.e.a+b.f.a*o,h-t)):u(c.Xb(r),65).a.b>0&&(l=u(Bf(u(c.Xb(r),65).a),8).a,y=b.e.a+b.f.a/2,f=u(Bf(u(c.Xb(r),65).a),8).b,S=b.e.b+b.f.b/2,i>0&&k.Math.abs(l-y)/(k.Math.abs(f-S)/40)>50&&(y>l?pc(u(c.Xb(r),65).a,new Ee(b.e.a+b.f.a*o-i/2,b.e.b-i/5.3)):pc(u(c.Xb(r),65).a,new Ee(b.e.a+b.f.a*o+i/2,b.e.b-i/5.3)))),pc(u(c.Xb(r),65).a,new Ee(b.e.a+b.f.a*o,b.e.b)))}function ZKe(e,n,t){var i,r,c,o,l,f,h,b,p,y,S,A,N,_,R,U,K,ie,de,fe;if(o=n,y=t,so(e.a,o)){if(hf(u(Rn(e.a,o),47),y))return 1}else Zt(e.a,o,new hr);if(so(e.a,y)){if(hf(u(Rn(e.a,y),47),o))return-1}else Zt(e.a,y,new hr);if(so(e.e,o)){if(hf(u(Rn(e.e,o),47),y))return-1}else Zt(e.e,o,new hr);if(so(e.e,y)){if(hf(u(Rn(e.a,y),47),o))return 1}else Zt(e.e,y,new hr);if(o.j!=y.j)return de=pwn(o.j,y.j),de>0?Wl(e,o,y,1):Wl(e,y,o,1),de;if(fe=1,o.e.c.length!=0&&y.e.c.length!=0){if((o.j==(Ne(),Xn)&&y.j==Xn||o.j==Un&&y.j==Un||o.j==bt&&y.j==bt)&&(fe=-fe),b=u(Le(o.e,0),17).c,_=u(Le(y.e,0),17).c,f=b.i,A=_.i,f==A)for(K=new L(f.j);K.a0?(Wl(e,o,y,fe),fe):(Wl(e,y,o,fe),-fe);if(i=pFe(u(ys(yK(e.d),_s(new Ui,new Si,new nu,z(B(Zo,1),ye,130,0,[(Kl(),Wo)]))),20),f,A),i!=0)return i>0?(Wl(e,o,y,fe),fe):(Wl(e,y,o,fe),-fe);if(e.c&&(de=XHe(e,o,y),de!=0))return de>0?(Wl(e,o,y,fe),fe):(Wl(e,y,o,fe),-fe)}return o.g.c.length!=0&&y.g.c.length!=0?((o.j==(Ne(),Xn)&&y.j==Xn||o.j==bt&&y.j==bt)&&(fe=-fe),p=u(T(o,(pe(),yie)),9),R=u(T(y,yie),9),e.f==(ud(),ire)&&p&&R&&bi(p,Oi)&&bi(R,Oi)?(l=w2(p,R,e.b,u(T(e.b,Tb),15).a),S=w2(R,p,e.b,u(T(e.b,Tb),15).a),l>S?(Wl(e,o,y,fe),fe):(Wl(e,y,o,fe),-fe)):e.c&&(de=XHe(e,o,y),de!=0)?de>0?(Wl(e,o,y,fe),fe):(Wl(e,y,o,fe),-fe):(h=0,N=0,bi(u(Le(o.g,0),17),Oi)&&(h=w2(u(Le(o.g,0),246),u(Le(y.g,0),246),e.b,o.g.c.length+o.e.c.length)),bi(u(Le(y.g,0),17),Oi)&&(N=w2(u(Le(y.g,0),246),u(Le(o.g,0),246),e.b,y.g.c.length+y.e.c.length)),p&&p==R||e.g&&(e.g._b(p)&&(h=u(e.g.xc(p),15).a),e.g._b(R)&&(N=u(e.g.xc(R),15).a)),h>N?(Wl(e,o,y,fe),fe):(Wl(e,y,o,fe),-fe))):o.e.c.length!=0&&y.g.c.length!=0?(Wl(e,o,y,fe),1):o.g.c.length!=0&&y.e.c.length!=0?(Wl(e,y,o,fe),-1):bi(o,(pe(),Oi))&&bi(y,Oi)?(c=o.i.j.c.length,l=w2(o,y,e.b,c),S=w2(y,o,e.b,c),(o.j==(Ne(),Xn)&&y.j==Xn||o.j==bt&&y.j==bt)&&(fe=-fe),l>S?(Wl(e,o,y,fe),fe):(Wl(e,y,o,fe),-fe)):(Wl(e,y,o,fe),-fe)}function pe(){pe=Y;var e,n;pi=new yi(uwe),Jve=new yi("coordinateOrigin"),Eie=new yi("processors"),Hve=new Pi("compoundNode",(Ln(),!1)),aD=new Pi("insideConnections",!1),Xve=new yi("originalBendpoints"),Vve=new yi("originalDummyNodePosition"),Kve=new yi("originalLabelEdge"),wM=new yi("representedLabels"),gM=new yi("endLabels"),Xy=new yi("endLabel.origin"),Ky=new Pi("labelSide",(ml(),qD)),i4=new Pi("maxEdgeThickness",0),o0=new Pi("reversed",!1),Qy=new yi(WQe),Na=new Pi("longEdgeSource",null),jf=new Pi("longEdgeTarget",null),Bm=new Pi("longEdgeHasLabelDummies",!1),hD=new Pi("longEdgeBeforeLabelDummy",!1),oJ=new Pi("edgeConstraint",(jg(),rie)),P2=new yi("inLayerLayoutUnit"),Jg=new Pi("inLayerConstraint",(Z1(),lD)),Vy=new Pi("inLayerSuccessorConstraint",new Te),Uve=new Pi("inLayerSuccessorConstraintBetweenNonDummies",!1),Ss=new yi("portDummy"),uJ=new Pi("crossingHint",me(0)),po=new Pi("graphProperties",(n=u(pa(aie),10),new Jl(n,u(zf(n,n.length),10),0))),_u=new Pi("externalPortSide",(Ne(),Eu)),qve=new 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yi("layerConstraints.hiddenNodes"),Qve=new yi("layerConstraints.opposidePort"),jie=new yi("targetNode.modelOrder"),Yy=new Pi("tarjan.lowlink",me(ui)),pM=new Pi("tarjan.id",me(-1)),fJ=new Pi("tarjan.onstack",!1),Xin=new Pi("partOfCycle",!1),o4=new yi("medianHeuristic.weight")}function Gt(){Gt=Y;var e,n;u6=new yi(dWe),i3=new yi(bWe),w9e=(s1(),fce),wfn=new fn(w2e,w9e),Z7=new fn(u7,null),pfn=new yi(Ope),m9e=(Cg(),Ti(dce,z(B(bce,1),ye,299,0,[hce]))),PD=new fn(_F,m9e),$D=new fn(BN,(Ln(),!1)),v9e=(kr(),lh),Wg=new fn(Jee,v9e),E9e=(cd(),xce),k9e=new fn(RN,E9e),kfn=new fn(Tpe,!1),S9e=(rd(),hG),p4=new fn(DF,S9e),L9e=new Hw(12),y1=new fn(Am,L9e),BD=new fn(OS,!1),mce=new fn(LF,!1),zD=new fn(NS,!1),z9e=(Fr(),$b),tA=new fn(eee,z9e),o6=new yi(IF),FD=new yi(TN),Mce=new yi(dF),Ace=new yi(CS),x9e=new Os,m4=new fn(x2e,x9e),vfn=new fn(N2e,!1),Efn=new fn(D2e,!1),new fn(gWe,0),T9e=new SE,ek=new fn(I2e,T9e),oG=new fn(b2e,!1),Tfn=new fn(wWe,1),e3=new yi(pWe),Zm=new yi(mWe),tk=new fn(CN,!1),new fn(vWe,!0),me(0),new fn(yWe,me(100)),new fn(kWe,!1),me(0),new fn(EWe,me(4e3)),me(0),new fn(jWe,me(400)),new fn(SWe,!1),new fn(MWe,!1),new fn(AWe,!0),new fn(xWe,!1),p9e=(ZB(),_ce),mfn=new fn(Cpe,p9e),A9e=(Oj(),VD),Sfn=new fn(TWe,A9e),M9e=(E8(),HD),jfn=new fn(CWe,M9e),Cfn=new fn(t2e,10),Ofn=new fn(i2e,10),Nfn=new fn(r2e,20),Dfn=new fn(c2e,10),G9e=new fn(ZZ,2),q9e=new fn(Hee,10),U9e=new fn(u2e,0),sG=new fn(l2e,5),X9e=new fn(o2e,1),V9e=new fn(s2e,1),d0=new fn(Mm,20),_fn=new fn(f2e,10),Y9e=new fn(a2e,10),s6=new yi(h2e),Q9e=new dCe,K9e=new fn(L2e,Q9e),Afn=new yi(qee),P9e=!1,Mfn=new fn(Gee,P9e),O9e=new Hw(5),C9e=new fn(v2e,O9e),N9e=(gm(),n=u(pa($c),10),new Jl(n,u(zf(n,n.length),10),0)),v4=new fn(s7,N9e),R9e=(Mv(),Pb),$9e=new fn(E2e,R9e),yce=new yi(j2e),kce=new yi(S2e),Ece=new yi(M2e),vce=new yi(A2e),D9e=(e=u(pa(fA),10),new Jl(e,u(zf(e,e.length),10),0)),Zg=new fn(zv,D9e),I9e=nn((Bs(),ok)),Ib=new fn(Dy,I9e),_9e=new Ee(0,0),y4=new fn(_y,_9e),n3=new fn(o7,!1),y9e=(Ua(),ik),wce=new fn(C2e,y9e),gce=new fn(bF,!1),me(1),new fn(OWe,null),B9e=new yi(_2e),jce=new yi(O2e),J9e=(Ne(),Eu),k4=new fn(g2e,J9e),Fs=new yi(d2e),F9e=(Es(),nn(Rb)),t3=new fn(l7,F9e),Sce=new fn(y2e,!1),H9e=new fn(k2e,!0),me(1),Rfn=new fn(bne,me(3)),me(1),zfn=new fn(Npe,me(4)),lG=new fn(ON,1),fG=new fn(gne,null),r3=new fn(NN,150),nk=new fn(DN,1.414),l6=new fn(j2,null),Ifn=new fn(Dpe,1),RD=new fn(p2e,!1),pce=new fn(m2e,!1),yfn=new fn(T2e,1),j9e=(xz(),Cce),new fn(NWe,j9e),xfn=!0,Bfn=(YR(),Dce),Pfn=(fy(),o3),$fn=o3,Lfn=o3}function Vr(){Vr=Y,R3e=new gr("DIRECTION_PREPROCESSOR",0),L3e=new gr("COMMENT_PREPROCESSOR",1),Qv=new gr("EDGE_AND_LAYER_CONSTRAINT_EDGE_REVERSER",2),Lte=new gr("INTERACTIVE_EXTERNAL_PORT_POSITIONER",3),ive=new gr("PARTITION_PREPROCESSOR",4),_H=new gr("LABEL_DUMMY_INSERTER",5),JH=new gr("SELF_LOOP_PREPROCESSOR",6),Lm=new gr("LAYER_CONSTRAINT_PREPROCESSOR",7),nve=new gr("PARTITION_MIDPROCESSOR",8),U3e=new gr("HIGH_DEGREE_NODE_LAYER_PROCESSOR",9),Z3e=new gr("NODE_PROMOTION",10),Im=new gr("LAYER_CONSTRAINT_POSTPROCESSOR",11),tve=new gr("PARTITION_POSTPROCESSOR",12),J3e=new gr("HIERARCHICAL_PORT_CONSTRAINT_PROCESSOR",13),rve=new gr("SEMI_INTERACTIVE_CROSSMIN_PROCESSOR",14),C3e=new gr("BREAKING_POINT_INSERTER",15),$H=new gr("LONG_EDGE_SPLITTER",16),Pte=new gr("PORT_SIDE_PROCESSOR",17),NH=new gr("INVERTED_PORT_PROCESSOR",18),zH=new gr("PORT_LIST_SORTER",19),uve=new gr("SORT_BY_INPUT_ORDER_OF_MODEL",20),BH=new gr("NORTH_SOUTH_PORT_PREPROCESSOR",21),O3e=new gr("BREAKING_POINT_PROCESSOR",22),eve=new gr(wYe,23),ove=new gr(pYe,24),FH=new gr("SELF_LOOP_PORT_RESTORER",25),T3e=new gr("ALTERNATING_LAYER_UNZIPPER",26),cve=new gr("SINGLE_EDGE_GRAPH_WRAPPER",27),DH=new gr("IN_LAYER_CONSTRAINT_PROCESSOR",28),z3e=new gr("END_NODE_PORT_LABEL_MANAGEMENT_PROCESSOR",29),Y3e=new gr("LABEL_AND_NODE_SIZE_PROCESSOR",30),Q3e=new gr("INNERMOST_NODE_MARGIN_CALCULATOR",31),GH=new gr("SELF_LOOP_ROUTER",32),_3e=new gr("COMMENT_NODE_MARGIN_CALCULATOR",33),OH=new gr("END_LABEL_PREPROCESSOR",34),LH=new gr("LABEL_DUMMY_SWITCHER",35),D3e=new gr("CENTER_LABEL_MANAGEMENT_PROCESSOR",36),N7=new gr("LABEL_SIDE_SELECTOR",37),V3e=new gr("HYPEREDGE_DUMMY_MERGER",38),G3e=new gr("HIERARCHICAL_PORT_DUMMY_SIZE_PROCESSOR",39),W3e=new gr("LAYER_SIZE_AND_GRAPH_HEIGHT_CALCULATOR",40),lM=new gr("HIERARCHICAL_PORT_POSITION_PROCESSOR",41),P3e=new gr("CONSTRAINTS_POSTPROCESSOR",42),I3e=new gr("COMMENT_POSTPROCESSOR",43),K3e=new gr("HYPERNODE_PROCESSOR",44),q3e=new gr("HIERARCHICAL_PORT_ORTHOGONAL_EDGE_ROUTER",45),PH=new gr("LONG_EDGE_JOINER",46),HH=new gr("SELF_LOOP_POSTPROCESSOR",47),N3e=new gr("BREAKING_POINT_REMOVER",48),RH=new gr("NORTH_SOUTH_PORT_POSTPROCESSOR",49),X3e=new gr("HORIZONTAL_COMPACTOR",50),IH=new gr("LABEL_DUMMY_REMOVER",51),F3e=new gr("FINAL_SPLINE_BENDPOINTS_CALCULATOR",52),B3e=new gr("END_LABEL_SORTER",53),Jy=new gr("REVERSED_EDGE_RESTORER",54),CH=new gr("END_LABEL_POSTPROCESSOR",55),H3e=new gr("HIERARCHICAL_NODE_RESIZER",56),$3e=new gr("DIRECTION_POSTPROCESSOR",57)}function CBn(e,n,t){var i,r,c,o,l,f,h,b,p,y,S,A,N,_,R,U,K,ie,de,fe,_e,cn,tn,Mn,Cn,st,Qt,qi,Ts,eu,Cl,x4,k0,la,yd,lf,w6,jA,kd,Pa,E0,rw,cw,p6,uw,ow,Ed,g3,A7e,K2,SA,Qce,m6,MA,w3,AA,Yce,Chn;for(A7e=0,Qt=n,eu=0,k0=Qt.length;eu0&&(e.a[Pa.p]=A7e++)}for(MA=0,qi=t,Cl=0,la=qi.length;Cl0;){for(Pa=(at(p6.b>0),u(p6.a.Xb(p6.c=--p6.b),12)),cw=0,l=new L(Pa.e);l.a0&&(Pa.j==(Ne(),Un)?(e.a[Pa.p]=MA,++MA):(e.a[Pa.p]=MA+yd+w6,++w6))}MA+=w6}for(rw=new wt,A=new Zh,st=n,Ts=0,x4=st.length;Tsh.b&&(h.b=uw)):Pa.i.c==g3&&(uwh.c&&(h.c=uw));for(r8(N,0,N.length,null),m6=oe(It,ei,30,N.length,15,1),i=oe(It,ei,30,MA+1,15,1),R=0;R0;)_e%2>0&&(r+=Yce[_e+1]),_e=(_e-1)/2|0,++Yce[_e];for(tn=oe(pon,xn,370,N.length*2,0,1),ie=0;ie0&&XC(Ts.f),ve(R,fG)!=null&&(!R.a&&(R.a=new we(Bt,R,10,11)),!!R.a)&&(!R.a&&(R.a=new we(Bt,R,10,11)),R.a).i>0?(l=u(ve(R,fG),521),cw=l.Sg(R),Fw(R,k.Math.max(R.g,cw.a+yd.b+yd.c),k.Math.max(R.f,cw.b+yd.d+yd.a))):(!R.a&&(R.a=new we(Bt,R,10,11)),R.a).i!=0&&(cw=new Ee(te(re(ve(R,r3))),te(re(ve(R,r3)))/te(re(ve(R,nk)))),Fw(R,k.Math.max(R.g,cw.a+yd.b+yd.c),k.Math.max(R.f,cw.b+yd.d+yd.a)));if(la=u(ve(n,y1),104),S=n.g-(la.b+la.c),y=n.f-(la.d+la.a),ow.ah("Available Child Area: ("+S+"|"+y+")"),Ei(n,Z7,S/y),THe(n,r,i.dh(x4)),u(ve(n,l6),281)==mG&&(lZ(n),Fw(n,la.b+te(re(ve(n,e3)))+la.c,la.d+te(re(ve(n,Zm)))+la.a)),ow.ah("Executed layout algorithm: "+_t(ve(n,u6))+" on node "+n.k),u(ve(n,l6),281)==o3){if(S<0||y<0)throw $(new Id("The size defined by the parent parallel node is too small for the space provided by the paddings of the child hierarchical node. "+n.k));for(Ea(n,e3)||Ea(n,Zm)||lZ(n),N=te(re(ve(n,e3))),A=te(re(ve(n,Zm))),ow.ah("Desired Child Area: ("+N+"|"+A+")"),w6=S/N,jA=y/A,lf=k.Math.min(w6,k.Math.min(jA,te(re(ve(n,Ifn))))),Ei(n,lG,lf),ow.ah(n.k+" -- Local Scale Factor (X|Y): ("+w6+"|"+jA+")"),ie=u(ve(n,PD),22),c=0,o=0,lf'?":bn(fZe,e)?"'(?<' or '(? toIndex: ",Kge=", toIndex: ",Qge="Index: ",Yge=", Size: ",t7="org.eclipse.elk.alg.common",Kt={51:1},CQe="org.eclipse.elk.alg.common.compaction",OQe="Scanline/EventHandler",b1="org.eclipse.elk.alg.common.compaction.oned",NQe="CNode belongs to another CGroup.",DQe="ISpacingsHandler/1",XZ="The ",VZ=" instance has been finished already.",_Qe="The direction ",IQe=" is not supported by the CGraph instance.",LQe="OneDimensionalCompactor",PQe="OneDimensionalCompactor/lambda$0$Type",$Qe="Quadruplet",RQe="ScanlineConstraintCalculator",BQe="ScanlineConstraintCalculator/ConstraintsScanlineHandler",zQe="ScanlineConstraintCalculator/ConstraintsScanlineHandler/lambda$0$Type",FQe="ScanlineConstraintCalculator/Timestamp",HQe="ScanlineConstraintCalculator/lambda$0$Type",_h={178:1,48:1},AS="org.eclipse.elk.alg.common.networksimplex",Aa={171:1,3:1,4:1},JQe="org.eclipse.elk.alg.common.nodespacing",Ig="org.eclipse.elk.alg.common.nodespacing.cellsystem",i7="CENTER",GQe={216:1,337:1},Wge={3:1,4:1,5:1,592:1},Cy="LEFT",Oy="RIGHT",Zge="Vertical alignment cannot be null",ewe="BOTTOM",aF="org.eclipse.elk.alg.common.nodespacing.internal",xS="UNDEFINED",Za=.01,MN="org.eclipse.elk.alg.common.nodespacing.internal.algorithm",qQe="LabelPlacer/lambda$0$Type",UQe="LabelPlacer/lambda$1$Type",XQe="portRatioOrPosition",r7="org.eclipse.elk.alg.common.overlaps",KZ="DOWN",Ny="org.eclipse.elk.alg.common.spore",Sm={3:1,4:1,5:1,198:1},VQe={3:1,6:1,4:1,5:1,90:1,110:1},QZ="org.eclipse.elk.alg.force",nwe="ComponentsProcessor",KQe="ComponentsProcessor/1",twe="ElkGraphImporter/lambda$0$Type",E2={214:1},Bv="org.eclipse.elk.core",AN="org.eclipse.elk.graph.properties",QQe="IPropertyHolder",xN="org.eclipse.elk.alg.force.graph",YQe="Component Layout",iwe="org.eclipse.elk.alg.force.model",yu="org.eclipse.elk.core.data",hF="org.eclipse.elk.force.model",rwe="org.eclipse.elk.force.iterations",cwe="org.eclipse.elk.force.repulsivePower",YZ="org.eclipse.elk.force.temperature",Ih=.001,WZ="org.eclipse.elk.force.repulsion",eh={148:1},TS="org.eclipse.elk.alg.force.options",c7=1.600000023841858,$o="org.eclipse.elk.force",TN="org.eclipse.elk.priority",Mm="org.eclipse.elk.spacing.nodeNode",ZZ="org.eclipse.elk.spacing.edgeLabel",u7="org.eclipse.elk.aspectRatio",dF="org.eclipse.elk.randomSeed",CS="org.eclipse.elk.separateConnectedComponents",Am="org.eclipse.elk.padding",OS="org.eclipse.elk.interactive",eee="org.eclipse.elk.portConstraints",bF="org.eclipse.elk.edgeLabels.inline",NS="org.eclipse.elk.omitNodeMicroLayout",o7="org.eclipse.elk.nodeSize.fixedGraphSize",Dy="org.eclipse.elk.nodeSize.options",zv="org.eclipse.elk.nodeSize.constraints",s7="org.eclipse.elk.nodeLabels.placement",l7="org.eclipse.elk.portLabels.placement",CN="org.eclipse.elk.topdownLayout",ON="org.eclipse.elk.topdown.scaleFactor",NN="org.eclipse.elk.topdown.hierarchicalNodeWidth",DN="org.eclipse.elk.topdown.hierarchicalNodeAspectRatio",j2="org.eclipse.elk.topdown.nodeType",uwe="origin",WQe="random",ZQe="boundingBox.upLeft",eYe="boundingBox.lowRight",owe="org.eclipse.elk.stress.fixed",swe="org.eclipse.elk.stress.desiredEdgeLength",lwe="org.eclipse.elk.stress.dimension",fwe="org.eclipse.elk.stress.epsilon",awe="org.eclipse.elk.stress.iterationLimit",mb="org.eclipse.elk.stress",nYe="ELK Stress",_y="org.eclipse.elk.nodeSize.minimum",gF="org.eclipse.elk.alg.force.stress",tYe="Layered layout",Iy="org.eclipse.elk.alg.layered",_N="org.eclipse.elk.alg.layered.compaction.components",DS="org.eclipse.elk.alg.layered.compaction.oned",wF="org.eclipse.elk.alg.layered.compaction.oned.algs",Lg="org.eclipse.elk.alg.layered.compaction.recthull",nh="org.eclipse.elk.alg.layered.components",xa="NONE",nee="MODEL_ORDER",qu={3:1,6:1,4:1,10:1,5:1,126:1},iYe={3:1,6:1,4:1,5:1,135:1,90:1,110:1},pF="org.eclipse.elk.alg.layered.compound",xi={43:1},Zu="org.eclipse.elk.alg.layered.graph",tee=" -> ",rYe="Not supported by LGraph",hwe="Port side is undefined",f7={3:1,6:1,4:1,5:1,323:1,135:1,90:1,110:1},i0={3:1,6:1,4:1,5:1,135:1,199:1,209:1,90:1,110:1},cYe={3:1,6:1,4:1,5:1,135:1,2004:1,209:1,90:1,110:1},uYe=`([{"' 	\r
-`,oYe=`)]}"' 	\r
-`,sYe="The given string contains parts that cannot be parsed as numbers.",IN="org.eclipse.elk.core.math",lYe={3:1,4:1,140:1,213:1,414:1},fYe={3:1,4:1,104:1,213:1,414:1},r0="org.eclipse.elk.alg.layered.graph.transform",aYe="ElkGraphImporter",hYe="ElkGraphImporter/lambda$1$Type",dYe="ElkGraphImporter/lambda$2$Type",bYe="ElkGraphImporter/lambda$4$Type",Qn="org.eclipse.elk.alg.layered.intermediate",gYe="Node margin calculation",wYe="ONE_SIDED_GREEDY_SWITCH",pYe="TWO_SIDED_GREEDY_SWITCH",iee="No implementation is available for the layout processor ",ree="IntermediateProcessorStrategy",cee="Node '",mYe="FIRST_SEPARATE",vYe="LAST_SEPARATE",yYe="Odd port side processing",fr="org.eclipse.elk.alg.layered.intermediate.compaction",_S="org.eclipse.elk.alg.layered.intermediate.greedyswitch",g1="org.eclipse.elk.alg.layered.p3order.counting",IS={220:1},Ly="org.eclipse.elk.alg.layered.intermediate.loops",El="org.eclipse.elk.alg.layered.intermediate.loops.ordering",vb="org.eclipse.elk.alg.layered.intermediate.loops.routing",mF="org.eclipse.elk.alg.layered.intermediate.preserveorder",Lh="org.eclipse.elk.alg.layered.intermediate.wrapping",Ou="org.eclipse.elk.alg.layered.options",uee="INTERACTIVE",dwe="GREEDY",kYe="DEPTH_FIRST",EYe="EDGE_LENGTH",jYe="SELF_LOOPS",SYe="firstTryWithInitialOrder",bwe="org.eclipse.elk.layered.directionCongruency",gwe="org.eclipse.elk.layered.feedbackEdges",vF="org.eclipse.elk.layered.interactiveReferencePoint",wwe="org.eclipse.elk.layered.mergeEdges",pwe="org.eclipse.elk.layered.mergeHierarchyEdges",mwe="org.eclipse.elk.layered.allowNonFlowPortsToSwitchSides",vwe="org.eclipse.elk.layered.portSortingStrategy",ywe="org.eclipse.elk.layered.thoroughness",kwe="org.eclipse.elk.layered.unnecessaryBendpoints",Ewe="org.eclipse.elk.layered.generatePositionAndLayerIds",LN="org.eclipse.elk.layered.cycleBreaking.strategy",PN="org.eclipse.elk.layered.layering.strategy",jwe="org.eclipse.elk.layered.layering.layerConstraint",Swe="org.eclipse.elk.layered.layering.layerChoiceConstraint",Mwe="org.eclipse.elk.layered.layering.layerId",oee="org.eclipse.elk.layered.layering.minWidth.upperBoundOnWidth",see="org.eclipse.elk.layered.layering.minWidth.upperLayerEstimationScalingFactor",lee="org.eclipse.elk.layered.layering.nodePromotion.strategy",fee="org.eclipse.elk.layered.layering.nodePromotion.maxIterations",aee="org.eclipse.elk.layered.layering.coffmanGraham.layerBound",LS="org.eclipse.elk.layered.crossingMinimization.strategy",Awe="org.eclipse.elk.layered.crossingMinimization.forceNodeModelOrder",hee="org.eclipse.elk.layered.crossingMinimization.hierarchicalSweepiness",dee="org.eclipse.elk.layered.crossingMinimization.semiInteractive",xwe="org.eclipse.elk.layered.crossingMinimization.inLayerPredOf",Twe="org.eclipse.elk.layered.crossingMinimization.inLayerSuccOf",Cwe="org.eclipse.elk.layered.crossingMinimization.positionChoiceConstraint",Owe="org.eclipse.elk.layered.crossingMinimization.positionId",Nwe="org.eclipse.elk.layered.crossingMinimization.greedySwitch.activationThreshold",bee="org.eclipse.elk.layered.crossingMinimization.greedySwitch.type",yF="org.eclipse.elk.layered.crossingMinimization.greedySwitchHierarchical.type",Fv="org.eclipse.elk.layered.nodePlacement.strategy",kF="org.eclipse.elk.layered.nodePlacement.favorStraightEdges",gee="org.eclipse.elk.layered.nodePlacement.bk.edgeStraightening",wee="org.eclipse.elk.layered.nodePlacement.bk.fixedAlignment",pee="org.eclipse.elk.layered.nodePlacement.linearSegments.deflectionDampening",mee="org.eclipse.elk.layered.nodePlacement.networkSimplex.nodeFlexibility",vee="org.eclipse.elk.layered.nodePlacement.networkSimplex.nodeFlexibility.default",Dwe="org.eclipse.elk.layered.edgeRouting.selfLoopDistribution",_we="org.eclipse.elk.layered.edgeRouting.selfLoopOrdering",EF="org.eclipse.elk.layered.edgeRouting.splines.mode",jF="org.eclipse.elk.layered.edgeRouting.splines.sloppy.layerSpacingFactor",yee="org.eclipse.elk.layered.edgeRouting.polyline.slopedEdgeZoneWidth",Iwe="org.eclipse.elk.layered.spacing.baseValue",Lwe="org.eclipse.elk.layered.spacing.edgeNodeBetweenLayers",Pwe="org.eclipse.elk.layered.spacing.edgeEdgeBetweenLayers",$we="org.eclipse.elk.layered.spacing.nodeNodeBetweenLayers",Rwe="org.eclipse.elk.layered.priority.direction",Bwe="org.eclipse.elk.layered.priority.shortness",zwe="org.eclipse.elk.layered.priority.straightness",kee="org.eclipse.elk.layered.compaction.connectedComponents",Fwe="org.eclipse.elk.layered.compaction.postCompaction.strategy",Hwe="org.eclipse.elk.layered.compaction.postCompaction.constraints",SF="org.eclipse.elk.layered.highDegreeNodes.treatment",Eee="org.eclipse.elk.layered.highDegreeNodes.threshold",jee="org.eclipse.elk.layered.highDegreeNodes.treeHeight",fd="org.eclipse.elk.layered.wrapping.strategy",MF="org.eclipse.elk.layered.wrapping.additionalEdgeSpacing",AF="org.eclipse.elk.layered.wrapping.correctionFactor",PS="org.eclipse.elk.layered.wrapping.cutting.strategy",See="org.eclipse.elk.layered.wrapping.cutting.cuts",Mee="org.eclipse.elk.layered.wrapping.cutting.msd.freedom",xF="org.eclipse.elk.layered.wrapping.validify.strategy",TF="org.eclipse.elk.layered.wrapping.validify.forbiddenIndices",CF="org.eclipse.elk.layered.wrapping.multiEdge.improveCuts",OF="org.eclipse.elk.layered.wrapping.multiEdge.distancePenalty",Aee="org.eclipse.elk.layered.wrapping.multiEdge.improveWrappedEdges",xee="org.eclipse.elk.layered.layerUnzipping.strategy",Tee="org.eclipse.elk.layered.layerUnzipping.minimizeEdgeLength",Cee="org.eclipse.elk.layered.layerUnzipping.layerSplit",Oee="org.eclipse.elk.layered.layerUnzipping.resetOnLongEdges",Jwe="org.eclipse.elk.layered.edgeLabels.sideSelection",Gwe="org.eclipse.elk.layered.edgeLabels.centerLabelPlacementStrategy",NF="org.eclipse.elk.layered.considerModelOrder.strategy",qwe="org.eclipse.elk.layered.considerModelOrder.portModelOrder",$N="org.eclipse.elk.layered.considerModelOrder.noModelOrder",Nee="org.eclipse.elk.layered.considerModelOrder.components",Uwe="org.eclipse.elk.layered.considerModelOrder.longEdgeStrategy",Dee="org.eclipse.elk.layered.considerModelOrder.crossingCounterNodeInfluence",_ee="org.eclipse.elk.layered.considerModelOrder.crossingCounterPortInfluence",Iee="org.eclipse.elk.layered.considerModelOrder.groupModelOrder.cycleBreakingId",Lee="org.eclipse.elk.layered.considerModelOrder.groupModelOrder.crossingMinimizationId",Pee="org.eclipse.elk.layered.considerModelOrder.groupModelOrder.componentGroupId",Xwe="org.eclipse.elk.layered.considerModelOrder.groupModelOrder.cbGroupOrderStrategy",$ee="org.eclipse.elk.layered.considerModelOrder.groupModelOrder.cbPreferredSourceId",Ree="org.eclipse.elk.layered.considerModelOrder.groupModelOrder.cbPreferredTargetId",Vwe="org.eclipse.elk.layered.considerModelOrder.groupModelOrder.cmGroupOrderStrategy",Kwe="org.eclipse.elk.layered.considerModelOrder.groupModelOrder.cmEnforcedGroupOrders",Bee="layering",MYe="layering.minWidth",AYe="layering.nodePromotion",a7="crossingMinimization",DF="org.eclipse.elk.hierarchyHandling",xYe="crossingMinimization.greedySwitch",TYe="nodePlacement",CYe="nodePlacement.bk",OYe="edgeRouting",RN="org.eclipse.elk.edgeRouting",th="spacing",Qwe="priority",Ywe="compaction",NYe="compaction.postCompaction",DYe="Specifies whether and how post-process compaction is applied.",Wwe="highDegreeNodes",Zwe="wrapping",_Ye="wrapping.cutting",IYe="wrapping.validify",e2e="wrapping.multiEdge",zee="layerUnzipping",Fee="edgeLabels",$S="considerModelOrder",h7="considerModelOrder.groupModelOrder",n2e="Group ID of the Node Type",t2e="org.eclipse.elk.spacing.commentComment",i2e="org.eclipse.elk.spacing.commentNode",r2e="org.eclipse.elk.spacing.componentComponent",c2e="org.eclipse.elk.spacing.edgeEdge",Hee="org.eclipse.elk.spacing.edgeNode",u2e="org.eclipse.elk.spacing.labelLabel",o2e="org.eclipse.elk.spacing.labelPortHorizontal",s2e="org.eclipse.elk.spacing.labelPortVertical",l2e="org.eclipse.elk.spacing.labelNode",f2e="org.eclipse.elk.spacing.nodeSelfLoop",a2e="org.eclipse.elk.spacing.portPort",h2e="org.eclipse.elk.spacing.individual",d2e="org.eclipse.elk.port.borderOffset",b2e="org.eclipse.elk.noLayout",g2e="org.eclipse.elk.port.side",BN="org.eclipse.elk.debugMode",w2e="org.eclipse.elk.alignment",p2e="org.eclipse.elk.insideSelfLoops.activate",m2e="org.eclipse.elk.insideSelfLoops.yo",Jee="org.eclipse.elk.direction",v2e="org.eclipse.elk.nodeLabels.padding",y2e="org.eclipse.elk.portLabels.nextToPortIfPossible",k2e="org.eclipse.elk.portLabels.treatAsGroup",E2e="org.eclipse.elk.portAlignment.default",j2e="org.eclipse.elk.portAlignment.north",S2e="org.eclipse.elk.portAlignment.south",M2e="org.eclipse.elk.portAlignment.west",A2e="org.eclipse.elk.portAlignment.east",_F="org.eclipse.elk.contentAlignment",x2e="org.eclipse.elk.junctionPoints",T2e="org.eclipse.elk.edge.thickness",C2e="org.eclipse.elk.edgeLabels.placement",O2e="org.eclipse.elk.port.index",N2e="org.eclipse.elk.commentBox",D2e="org.eclipse.elk.hypernode",_2e="org.eclipse.elk.port.anchor",Gee="org.eclipse.elk.partitioning.activate",qee="org.eclipse.elk.partitioning.partition",IF="org.eclipse.elk.position",I2e="org.eclipse.elk.margins",L2e="org.eclipse.elk.spacing.portsSurrounding",LF="org.eclipse.elk.interactiveLayout",Ru="org.eclipse.elk.core.util",P2e={3:1,4:1,5:1,590:1},LYe="NETWORK_SIMPLEX",$2e="SIMPLE",lc={95:1,43:1},S2="org.eclipse.elk.alg.layered.p1cycles",PYe="Depth-first cycle removal",$Ye="Model order cycle breaking",ad="org.eclipse.elk.alg.layered.p2layers",R2e={406:1,220:1},RYe={830:1,3:1,4:1},Ro="org.eclipse.elk.alg.layered.p3order",Hv=17976931348623157e292,Uee=5e-324,Lc="org.eclipse.elk.alg.layered.p4nodes",BYe={3:1,4:1,5:1,838:1},Ph=1e-5,yb="org.eclipse.elk.alg.layered.p4nodes.bk",Xee="org.eclipse.elk.alg.layered.p5edges",Ta="org.eclipse.elk.alg.layered.p5edges.orthogonal",Vee="org.eclipse.elk.alg.layered.p5edges.orthogonal.direction",Kee=1e-6,xm="org.eclipse.elk.alg.layered.p5edges.splines",Qee=.09999999999999998,PF=1e-8,zYe=4.71238898038469,FYe=1.5707963267948966,B2e=3.141592653589793,hd="org.eclipse.elk.alg.mrtree",Yee=.10000000149011612,$F="SUPER_ROOT",RS="org.eclipse.elk.alg.mrtree.graph",z2e=-17976931348623157e292,go="org.eclipse.elk.alg.mrtree.intermediate",HYe="Processor compute fanout",RF={3:1,6:1,4:1,5:1,522:1,90:1,110:1},JYe="Set neighbors in level",zN="org.eclipse.elk.alg.mrtree.options",GYe="DESCENDANTS",F2e="org.eclipse.elk.mrtree.compaction",H2e="org.eclipse.elk.mrtree.edgeEndTextureLength",J2e="org.eclipse.elk.mrtree.treeLevel",G2e="org.eclipse.elk.mrtree.positionConstraint",q2e="org.eclipse.elk.mrtree.weighting",U2e="org.eclipse.elk.mrtree.edgeRoutingMode",X2e="org.eclipse.elk.mrtree.searchOrder",qYe="Position Constraint",Bo="org.eclipse.elk.mrtree",UYe="org.eclipse.elk.tree",XYe="Processor arrange level",d7="org.eclipse.elk.alg.mrtree.p2order",rl="org.eclipse.elk.alg.mrtree.p4route",V2e="org.eclipse.elk.alg.radial",Pg=6.283185307179586,K2e="Before",BF="After",Q2e="org.eclipse.elk.alg.radial.intermediate",VYe="COMPACTION",Wee="org.eclipse.elk.alg.radial.intermediate.compaction",KYe={3:1,4:1,5:1,90:1},Y2e="org.eclipse.elk.alg.radial.intermediate.optimization",Zee="No implementation is available for the layout option ",BS="org.eclipse.elk.alg.radial.options",QYe="CompactionStrategy",W2e="org.eclipse.elk.radial.centerOnRoot",Z2e="org.eclipse.elk.radial.orderId",epe="org.eclipse.elk.radial.radius",zF="org.eclipse.elk.radial.rotate",ene="org.eclipse.elk.radial.compactor",nne="org.eclipse.elk.radial.compactionStepSize",npe="org.eclipse.elk.radial.sorter",tpe="org.eclipse.elk.radial.wedgeCriteria",ipe="org.eclipse.elk.radial.optimizationCriteria",tne="org.eclipse.elk.radial.rotation.targetAngle",ine="org.eclipse.elk.radial.rotation.computeAdditionalWedgeSpace",rpe="org.eclipse.elk.radial.rotation.outgoingEdgeAngles",YYe="Compaction",cpe="rotation",Zl="org.eclipse.elk.radial",WYe="org.eclipse.elk.alg.radial.p1position.wedge",upe="org.eclipse.elk.alg.radial.sorting",ZYe=5.497787143782138,eWe=3.9269908169872414,nWe=2.356194490192345,tWe="org.eclipse.elk.alg.rectpacking",zS="org.eclipse.elk.alg.rectpacking.intermediate",rne="org.eclipse.elk.alg.rectpacking.options",ope="org.eclipse.elk.rectpacking.trybox",spe="org.eclipse.elk.rectpacking.currentPosition",lpe="org.eclipse.elk.rectpacking.desiredPosition",fpe="org.eclipse.elk.rectpacking.inNewRow",ape="org.eclipse.elk.rectpacking.orderBySize",hpe="org.eclipse.elk.rectpacking.widthApproximation.strategy",dpe="org.eclipse.elk.rectpacking.widthApproximation.targetWidth",bpe="org.eclipse.elk.rectpacking.widthApproximation.optimizationGoal",gpe="org.eclipse.elk.rectpacking.widthApproximation.lastPlaceShift",wpe="org.eclipse.elk.rectpacking.packing.strategy",ppe="org.eclipse.elk.rectpacking.packing.compaction.rowHeightReevaluation",mpe="org.eclipse.elk.rectpacking.packing.compaction.iterations",vpe="org.eclipse.elk.rectpacking.whiteSpaceElimination.strategy",cne="widthApproximation",iWe="Compaction Strategy",rWe="packing.compaction",js="org.eclipse.elk.rectpacking",b7="org.eclipse.elk.alg.rectpacking.p1widthapproximation",FF="org.eclipse.elk.alg.rectpacking.p2packing",cWe="No Compaction",ype="org.eclipse.elk.alg.rectpacking.p3whitespaceelimination",FN="org.eclipse.elk.alg.rectpacking.util",HF="No implementation available for ",Tm="org.eclipse.elk.alg.spore",Cm="org.eclipse.elk.alg.spore.options",M2="org.eclipse.elk.sporeCompaction",une="org.eclipse.elk.underlyingLayoutAlgorithm",kpe="org.eclipse.elk.processingOrder.treeConstruction",Epe="org.eclipse.elk.processingOrder.spanningTreeCostFunction",one="org.eclipse.elk.processingOrder.preferredRoot",sne="org.eclipse.elk.processingOrder.rootSelection",lne="org.eclipse.elk.structure.structureExtractionStrategy",jpe="org.eclipse.elk.compaction.compactionStrategy",Spe="org.eclipse.elk.compaction.orthogonal",Mpe="org.eclipse.elk.overlapRemoval.maxIterations",Ape="org.eclipse.elk.overlapRemoval.runScanline",fne="processingOrder",uWe="overlapRemoval",g7="org.eclipse.elk.sporeOverlap",oWe="org.eclipse.elk.alg.spore.p1structure",ane="org.eclipse.elk.alg.spore.p2processingorder",hne="org.eclipse.elk.alg.spore.p3execution",sWe="Topdown Layout",lWe="Invalid index: ",w7="org.eclipse.elk.core.alg",Jv={342:1},Om={296:1},fWe="Make sure its type is registered with the ",xpe=" utility class.",p7="true",dne="false",aWe="Couldn't clone property '",A2=.05,Oo="org.eclipse.elk.core.options",hWe=1.2999999523162842,x2="org.eclipse.elk.box",Tpe="org.eclipse.elk.expandNodes",Cpe="org.eclipse.elk.box.packingMode",dWe="org.eclipse.elk.algorithm",bWe="org.eclipse.elk.resolvedAlgorithm",Ope="org.eclipse.elk.bendPoints",IBn="org.eclipse.elk.labelManager",gWe="org.eclipse.elk.softwrappingFuzziness",wWe="org.eclipse.elk.scaleFactor",pWe="org.eclipse.elk.childAreaWidth",mWe="org.eclipse.elk.childAreaHeight",vWe="org.eclipse.elk.animate",yWe="org.eclipse.elk.animTimeFactor",kWe="org.eclipse.elk.layoutAncestors",EWe="org.eclipse.elk.maxAnimTime",jWe="org.eclipse.elk.minAnimTime",SWe="org.eclipse.elk.progressBar",MWe="org.eclipse.elk.validateGraph",AWe="org.eclipse.elk.validateOptions",xWe="org.eclipse.elk.zoomToFit",TWe="org.eclipse.elk.json.shapeCoords",CWe="org.eclipse.elk.json.edgeCoords",LBn="org.eclipse.elk.font.name",OWe="org.eclipse.elk.font.size",bne="org.eclipse.elk.topdown.sizeCategories",Npe="org.eclipse.elk.topdown.sizeCategoriesHierarchicalNodeWeight",gne="org.eclipse.elk.topdown.sizeApproximator",Dpe="org.eclipse.elk.topdown.scaleCap",NWe="org.eclipse.elk.edge.type",DWe="partitioning",_We="nodeLabels",JF="portAlignment",wne="nodeSize",pne="port",_pe="portLabels",m7="topdown",IWe="insideSelfLoops",Ipe="INHERIT",v7="org.eclipse.elk.fixed",GF="org.eclipse.elk.random",qF={3:1,35:1,23:1,521:1,288:1},LWe="port must have a parent node to calculate the port side",PWe="The edge needs to have exactly one edge section. Found: ",FS="org.eclipse.elk.core.util.adapters",ef="org.eclipse.emf.ecore",Gv="org.eclipse.elk.graph",$We="EMapPropertyHolder",RWe="ElkBendPoint",BWe="ElkGraphElement",zWe="ElkConnectableShape",Lpe="ElkEdge",FWe="ElkEdgeSection",HWe="EModelElement",JWe="ENamedElement",Ppe="ElkLabel",$pe="ElkNode",Rpe="ElkPort",GWe={94:1,93:1},Py="org.eclipse.emf.common.notify.impl",kb="The feature '",HS="' is not a valid changeable feature",qWe="Expecting null",mne="' is not a valid feature",UWe="The feature ID",XWe=" is not a valid feature ID",Bu=32768,VWe={109:1,94:1,93:1,57:1,52:1,100:1},zn="org.eclipse.emf.ecore.impl",$g="org.eclipse.elk.graph.impl",JS="Recursive containment not allowed for ",y7="The datatype '",T2="' is not a valid classifier",vne="The value '",qv={195:1,3:1,4:1},yne="The class '",k7="http://www.eclipse.org/elk/ElkGraph",Bpe="property",GS="value",kne="source",KWe="properties",QWe="identifier",Ene="height",jne="width",Sne="parent",Mne="text",Ane="children",YWe="hierarchical",zpe="sources",xne="targets",Tne="sections",UF="bendPoints",Fpe="outgoingShape",Hpe="incomingShape",Jpe="outgoingSections",Gpe="incomingSections",Ec="org.eclipse.emf.common.util",qpe="Severe implementation error in the Json to ElkGraph importer.",$h="id",ec="org.eclipse.elk.graph.json",E7="Unhandled parameter types: ",WWe="startPoint",ZWe="An edge must have at least one source and one target (edge id: '",j7="').",eZe="Referenced edge section does not exist: ",nZe=" (edge id: '",Upe="target",tZe="sourcePoint",iZe="targetPoint",XF="group",ci="name",rZe="connectableShape cannot be null",cZe="edge cannot be null",uZe="Passed edge is not 'simple'.",VF="org.eclipse.elk.graph.util",HN="The 'no duplicates' constraint is violated",Cne="targetIndex=",Rg=", size=",One="sourceIndex=",Rh={3:1,4:1,20:1,31:1,56:1,18:1,16:1,59:1,71:1,67:1,61:1},Nne={3:1,4:1,20:1,31:1,56:1,18:1,50:1,16:1,59:1,71:1,67:1,61:1,585:1},KF="logging",oZe="measureExecutionTime",sZe="parser.parse.1",lZe="parser.parse.2",QF="parser.next.1",Dne="parser.next.2",fZe="parser.next.3",aZe="parser.next.4",Bg="parser.factor.1",Xpe="parser.factor.2",hZe="parser.factor.3",dZe="parser.factor.4",bZe="parser.factor.5",gZe="parser.factor.6",wZe="parser.atom.1",pZe="parser.atom.2",mZe="parser.atom.3",Vpe="parser.atom.4",_ne="parser.atom.5",Kpe="parser.cc.1",YF="parser.cc.2",vZe="parser.cc.3",yZe="parser.cc.5",Qpe="parser.cc.6",Ype="parser.cc.7",Ine="parser.cc.8",kZe="parser.ope.1",EZe="parser.ope.2",jZe="parser.ope.3",c0="parser.descape.1",SZe="parser.descape.2",MZe="parser.descape.3",AZe="parser.descape.4",xZe="parser.descape.5",nf="parser.process.1",TZe="parser.quantifier.1",CZe="parser.quantifier.2",OZe="parser.quantifier.3",NZe="parser.quantifier.4",Wpe="parser.quantifier.5",DZe="org.eclipse.emf.common.notify",Zpe={415:1,676:1},_Ze={3:1,4:1,20:1,31:1,56:1,18:1,16:1,71:1,61:1},JN={373:1,151:1},qS="index=",Lne={3:1,4:1,5:1,129:1},IZe={3:1,4:1,20:1,31:1,56:1,18:1,16:1,59:1,71:1,61:1},eme={3:1,6:1,4:1,5:1,198:1},LZe={3:1,4:1,5:1,175:1,374:1},Yf=1024,PZe=";/?:@&=+$,",$Ze="invalid authority: ",RZe="EAnnotation",BZe="ETypedElement",zZe="EStructuralFeature",FZe="EAttribute",HZe="EClassifier",JZe="EEnumLiteral",GZe="EGenericType",qZe="EOperation",UZe="EParameter",XZe="EReference",VZe="ETypeParameter",Ri="org.eclipse.emf.ecore.util",Pne={77:1},nme={3:1,20:1,18:1,16:1,61:1,586:1,77:1,72:1,98:1},KZe="org.eclipse.emf.ecore.util.FeatureMap$Entry",gs=8192,US="byte",WF="char",XS="double",VS="float",KS="int",QS="long",YS="short",QZe="java.lang.Object",Uv={3:1,4:1,5:1,255:1},tme={3:1,4:1,5:1,678:1},YZe={3:1,4:1,20:1,31:1,56:1,18:1,16:1,59:1,71:1,67:1,61:1,72:1},au={3:1,4:1,20:1,31:1,56:1,18:1,16:1,59:1,71:1,67:1,61:1,77:1,72:1,98:1},GN="mixed",Jt="http:///org/eclipse/emf/ecore/util/ExtendedMetaData",vf="kind",WZe={3:1,4:1,5:1,679:1},ime={3:1,4:1,20:1,31:1,56:1,18:1,16:1,71:1,61:1,77:1,72:1,98:1},ZF={20:1,31:1,56:1,18:1,16:1,61:1,72:1},eH={50:1,128:1,287:1},nH={75:1,344:1},tH="The value of type '",iH="' must be of type 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A non-flow port is a port on a side that is not part of the currently configured layout flow. For instance, given a left-to-right layout direction, north and south ports would be considered non-flow ports. Further note that the underlying criterium whether to switch sides or not solely relies on the minimization of edge crossings. Hence, edge length and other aesthetics criteria are not addressed."),!1),xr),Yi),nn(h0)),z(B(Be,1),Ae,2,6,["org.eclipse.elk.layered.northOrSouthPort"])))),Ye(n,new Je(Ke(Ve(Qe(hn(Ge(Xe(qe(Ue(new Fe,vwe),""),"Port Sorting Strategy"),"Only relevant for nodes with FIXED_SIDE port constraints. Determines the way a node's ports are distributed on the sides of a node if their order is not prescribed. The option is set on parent nodes."),O4e),Bi),F5e),nn(Sn)))),Ye(n,new Je(Ke(Ve(Qe(hn(Ge(Xe(qe(Ue(new Fe,ywe),""),"Thoroughness"),"How much effort should be spent to produce a nice layout."),me(7)),gc),Mr),nn(Sn)))),Ye(n,new Je(Ke(Ve(Qe(hn(Ge(Xe(qe(Ue(new Fe,kwe),""),"Add Unnecessary Bendpoints"),"Adds bend points even if an edge does not change direction. If true, each long edge dummy will contribute a bend point to its edges and hierarchy-crossing edges will always get a bend point where they cross hierarchy boundaries. By default, bend points are only added where an edge changes direction."),!1),xr),Yi),nn(Sn)))),Ye(n,new Je(Ke(Ve(Qe(hn(Ge(Xe(qe(Ue(new Fe,Ewe),""),"Generate Position and Layer IDs"),"If enabled position id and layer id are generated, which are usually only used internally when setting the interactiveLayout option. This option should be specified on the root node."),!1),xr),Yi),nn(Sn)))),Ye(n,new Je(Ke(Ve(Qe(hn(Ge(Xe(qe(Ue(new Fe,LN),"cycleBreaking"),"Cycle Breaking Strategy"),"Strategy for cycle breaking. Cycle breaking looks for cycles in the graph and determines which edges to reverse to break the cycles. Reversed edges will end up pointing to the opposite direction of regular edges (that is, reversed edges will point left if edges usually point right)."),h4e),Bi),kve),nn(Sn)))),Ye(n,new Je(Ke(Ve(Qe(hn(Ge(Xe(qe(Ue(new Fe,PN),Bee),"Node Layering Strategy"),"Strategy for node layering."),E4e),Bi),C5e),nn(Sn)))),Ye(n,new Je(Ke(Ve(Qe(hn(Ge(Xe(qe(Ue(new Fe,jwe),Bee),"Layer Constraint"),"Determines a constraint on the placement of the node regarding the layering."),y4e),Bi),Zve),nn(ar)))),Ye(n,new Je(Ke(Ve(Qe(hn(Ge(Xe(qe(Ue(new Fe,Swe),Bee),"Layer Choice Constraint"),"Allows to set a constraint regarding the layer placement of a node. Let i be the value of teh constraint. Assumed the drawing has n layers and i < n. If set to i, it expresses that the node should be placed in i-th layer. Should i>=n be true then the node is placed in the last layer of the drawing. Note that this option is not part of any of ELK Layered's default configurations but is only evaluated as part of the `InteractiveLayeredGraphVisitor`, which must be applied manually or used via the `DiagramLayoutEngine."),null),gc),Mr),nn(ar)))),Ye(n,new Je(Ke(Ve(Qe(hn(Ge(Xe(qe(Ue(new Fe,Mwe),Bee),"Layer ID"),"Layer identifier that was calculated by ELK Layered for a node. This is only generated if interactiveLayot or generatePositionAndLayerIds is set."),me(-1)),gc),Mr),nn(ar)))),Ye(n,new Je(Ke(Ve(Qe(hn(Ge(Xe(qe(Ue(new Fe,oee),MYe),"Upper Bound On Width [MinWidth Layerer]"),"Defines a loose upper bound on the width of the MinWidth layerer. If set to '-1' multiple values are tested and the best result is selected."),me(4)),gc),Mr),nn(Sn)))),Gi(n,oee,PN,ucn),Ye(n,new Je(Ke(Ve(Qe(hn(Ge(Xe(qe(Ue(new Fe,see),MYe),"Upper Layer Estimation Scaling Factor [MinWidth Layerer]"),"Multiplied with Upper Bound On Width for defining an upper bound on the width of layers which haven't been determined yet, but whose maximum width had been (roughly) estimated by the MinWidth algorithm. Compensates for too high estimations. If set to '-1' multiple values are tested and the best result is selected."),me(2)),gc),Mr),nn(Sn)))),Gi(n,see,PN,scn),Ye(n,new Je(Ke(Ve(Qe(hn(Ge(Xe(qe(Ue(new Fe,lee),AYe),"Node Promotion Strategy"),"Reduces number of dummy nodes after layering phase (if possible)."),k4e),Bi),R5e),nn(Sn)))),Ye(n,new Je(Ke(Ve(Qe(hn(Ge(Xe(qe(Ue(new Fe,fee),AYe),"Max Node Promotion Iterations"),"Limits the number of iterations for node promotion."),me(0)),gc),Mr),nn(Sn)))),Gi(n,fee,lee,null),Ye(n,new Je(Ke(Ve(Qe(hn(Ge(Xe(qe(Ue(new Fe,aee),"layering.coffmanGraham"),"Layer Bound"),"The maximum number of nodes allowed per layer."),me(ui)),gc),Mr),nn(Sn)))),Gi(n,aee,PN,ncn),Ye(n,new Je(Ke(Ve(Qe(hn(Ge(Xe(qe(Ue(new Fe,LS),a7),"Crossing Minimization Strategy"),"Strategy for crossing minimization."),a4e),Bi),pve),nn(Sn)))),Ye(n,new Je(Ke(Ve(Qe(hn(Ge(Xe(qe(Ue(new Fe,Awe),a7),"Force Node Model Order"),"The node order given by the model does not change to produce a better layout. E.g. if node A is before node B in the model this is not changed during crossing minimization. This assumes that the node model order is already respected before crossing minimization. This can be achieved by setting considerModelOrder.strategy to NODES_AND_EDGES."),!1),xr),Yi),nn(Sn)))),Ye(n,new Je(Ke(Ve(Qe(hn(Ge(Xe(qe(Ue(new Fe,hee),a7),"Hierarchical Sweepiness"),"How likely it is to use cross-hierarchy (1) vs bottom-up (-1)."),.1),tc),wr),nn(Sn)))),Gi(n,hee,DF,Mrn),Ye(n,new Je(Ke(Ve(Qe(hn(Ge(Xe(qe(Ue(new Fe,dee),a7),"Semi-Interactive Crossing Minimization"),"Preserves the order of nodes within a layer but still minimizes crossings between edges connecting long edge dummies. Derives the desired order from positions specified by the 'org.eclipse.elk.position' layout option. Requires a crossing minimization strategy that is able to process 'in-layer' constraints."),!1),xr),Yi),nn(Sn)))),Gi(n,dee,LS,Nrn),Ye(n,new Je(Ke(Ve(Qe(hn(Ge(Xe(qe(Ue(new Fe,xwe),a7),"In Layer Predecessor of"),"Allows to set a constraint which specifies of which node the current node is the predecessor. If set to 's' then the node is the predecessor of 's' and is in the same layer"),null),c6),Be),nn(ar)))),Ye(n,new Je(Ke(Ve(Qe(hn(Ge(Xe(qe(Ue(new Fe,Twe),a7),"In Layer Successor of"),"Allows to set a constraint which specifies of which node the current node is the successor. If set to 's' then the node is the successor of 's' and is in the same layer"),null),c6),Be),nn(ar)))),Ye(n,new Je(Ke(Ve(Qe(hn(Ge(Xe(qe(Ue(new Fe,Cwe),a7),"Position Choice Constraint"),"Allows to set a constraint regarding the position placement of a node in a layer. Assumed the layer in which the node placed includes n other nodes and i < n. If set to i, it expresses that the node should be placed at the i-th position. Should i>=n be true then the node is placed at the last position in the layer. Note that this option is not part of any of ELK Layered's default configurations but is only evaluated as part of the `InteractiveLayeredGraphVisitor`, which must be applied manually or used via the `DiagramLayoutEngine."),null),gc),Mr),nn(ar)))),Ye(n,new Je(Ke(Ve(Qe(hn(Ge(Xe(qe(Ue(new Fe,Owe),a7),"Position ID"),"Position within a layer that was determined by ELK Layered for a node. This is only generated if interactiveLayot or generatePositionAndLayerIds is set."),me(-1)),gc),Mr),nn(ar)))),Ye(n,new Je(Ke(Ve(Qe(hn(Ge(Xe(qe(Ue(new Fe,Nwe),xYe),"Greedy Switch Activation Threshold"),"By default it is decided automatically if the greedy switch is activated or not. The decision is based on whether the size of the input graph (without dummy nodes) is smaller than the value of this option. A '0' enforces the activation."),me(40)),gc),Mr),nn(Sn)))),Ye(n,new Je(Ke(Ve(Qe(hn(Ge(Xe(qe(Ue(new Fe,bee),xYe),"Greedy Switch Crossing Minimization"),"Greedy Switch strategy for crossing minimization. The greedy switch heuristic is executed after the regular crossing minimization as a post-processor. Note that if 'hierarchyHandling' is set to 'INCLUDE_CHILDREN', the 'greedySwitchHierarchical.type' option must be used."),f4e),Bi),bie),nn(Sn)))),Gi(n,bee,LS,jrn),Ye(n,new Je(Ke(Ve(Qe(hn(Ge(Xe(qe(Ue(new Fe,yF),"crossingMinimization.greedySwitchHierarchical"),"Greedy Switch Crossing Minimization (hierarchical)"),"Activates the greedy switch heuristic in case hierarchical layout is used. The differences to the non-hierarchical case (see 'greedySwitch.type') are: 1) greedy switch is inactive by default, 3) only the option value set on the node at which hierarchical layout starts is relevant, and 2) if it's activated by the user, it properly addresses hierarchy-crossing edges."),l4e),Bi),bie),nn(Sn)))),Gi(n,yF,LS,yrn),Gi(n,yF,DF,krn),Ye(n,new Je(Ke(Ve(Qe(hn(Ge(Xe(qe(Ue(new Fe,Fv),TYe),"Node Placement Strategy"),"Strategy for node placement."),C4e),Bi),_5e),nn(Sn)))),Ye(n,new Je(Ke(Ve(Qe(Ge(Xe(qe(Ue(new Fe,kF),TYe),"Favor Straight Edges Over Balancing"),"Favor straight edges over a balanced node placement. The default behavior is determined automatically based on the used 'edgeRouting'. For an orthogonal style it is set to true, for all other styles to false."),xr),Yi),nn(Sn)))),Gi(n,kF,Fv,Mcn),Gi(n,kF,Fv,Acn),Ye(n,new Je(Ke(Ve(Qe(hn(Ge(Xe(qe(Ue(new Fe,gee),CYe),"BK Edge Straightening"),"Specifies whether the Brandes Koepf node placer tries to increase the number of straight edges at the expense of diagram size. There is a subtle difference to the 'favorStraightEdges' option, which decides whether a balanced placement of the nodes is desired, or not. In bk terms this means combining the four alignments into a single balanced one, or not. This option on the other hand tries to straighten additional edges during the creation of each of the four alignments."),A4e),Bi),Ave),nn(Sn)))),Gi(n,gee,Fv,kcn),Ye(n,new Je(Ke(Ve(Qe(hn(Ge(Xe(qe(Ue(new Fe,wee),CYe),"BK Fixed Alignment"),"Tells the BK node placer to use a certain alignment (out of its four) instead of the one producing the smallest height, or the combination of all four."),x4e),Bi),Nve),nn(Sn)))),Gi(n,wee,Fv,jcn),Ye(n,new Je(Ke(Ve(Qe(hn(Ge(Xe(qe(Ue(new Fe,pee),"nodePlacement.linearSegments"),"Linear Segments Deflection Dampening"),"Dampens the movement of nodes to keep the diagram from getting too large."),.3),tc),wr),nn(Sn)))),Gi(n,pee,Fv,Tcn),Ye(n,new Je(Ke(Ve(Qe(Ge(Xe(qe(Ue(new Fe,mee),"nodePlacement.networkSimplex"),"Node Flexibility"),"Aims at shorter and straighter edges. Two configurations are possible: (a) allow ports to move freely on the side they are assigned to (the order is always defined beforehand), (b) additionally allow to enlarge a node wherever it helps. If this option is not configured for a node, the 'nodeFlexibility.default' value is used, which is specified for the node's parent."),Bi),Zie),nn(ar)))),Gi(n,mee,Fv,Dcn),Ye(n,new Je(Ke(Ve(Qe(hn(Ge(Xe(qe(Ue(new Fe,vee),"nodePlacement.networkSimplex.nodeFlexibility"),"Node Flexibility Default"),"Default value of the 'nodeFlexibility' option for the children of a hierarchical node."),T4e),Bi),Zie),nn(Sn)))),Gi(n,vee,Fv,Ncn),Ye(n,new Je(Ke(Ve(Qe(hn(Ge(Xe(qe(Ue(new Fe,Dwe),OYe),"Self-Loop Distribution"),"Alter the distribution of the loops around the node. It only takes effect for PortConstraints.FREE."),w4e),Bi),G5e),nn(ar)))),Ye(n,new Je(Ke(Ve(Qe(hn(Ge(Xe(qe(Ue(new Fe,_we),OYe),"Self-Loop Ordering"),"Alter the ordering of the loops they can either be stacked or sequenced. It only takes effect for PortConstraints.FREE."),p4e),Bi),q5e),nn(ar)))),Ye(n,new Je(Ke(Ve(Qe(hn(Ge(Xe(qe(Ue(new Fe,EF),"edgeRouting.splines"),"Spline Routing Mode"),"Specifies the way control points are assembled for each individual edge. CONSERVATIVE ensures that edges are properly routed around the nodes but feels rather orthogonal at times. SLOPPY uses fewer control points to obtain curvier edge routes but may result in edges overlapping nodes."),m4e),Bi),X5e),nn(Sn)))),Gi(n,EF,RN,Hrn),Ye(n,new Je(Ke(Ve(Qe(hn(Ge(Xe(qe(Ue(new Fe,jF),"edgeRouting.splines.sloppy"),"Sloppy Spline Layer Spacing Factor"),"Spacing factor for routing area between layers when using sloppy spline routing."),.2),tc),wr),nn(Sn)))),Gi(n,jF,RN,Grn),Gi(n,jF,EF,qrn),Ye(n,new Je(Ke(Ve(Qe(hn(Ge(Xe(qe(Ue(new Fe,yee),"edgeRouting.polyline"),"Sloped Edge Zone Width"),"Width of the strip to the left and to the right of each layer where the polyline edge router is allowed to refrain from ensuring that edges are routed horizontally. This prevents awkward bend points for nodes that extent almost to the edge of their layer."),2),tc),wr),nn(Sn)))),Gi(n,yee,RN,Rrn),Ye(n,new Je(Ke(Ve(Qe(Ge(Xe(qe(Ue(new Fe,Iwe),th),"Spacing Base Value"),"An optional base value for all other layout options of the 'spacing' group. It can be used to conveniently alter the overall 'spaciousness' of the drawing. Whenever an explicit value is set for the other layout options, this base value will have no effect. The base value is not inherited, i.e. it must be set for each hierarchical node."),tc),wr),nn(Sn)))),Ye(n,new Je(Ke(Ve(Qe(hn(Ge(Xe(qe(Ue(new Fe,Lwe),th),"Edge Node Between Layers Spacing"),"The spacing to be preserved between nodes and edges that are routed next to the node's layer. For the spacing between nodes and edges that cross the node's layer 'spacing.edgeNode' is used."),10),tc),wr),nn(Sn)))),Ye(n,new Je(Ke(Ve(Qe(hn(Ge(Xe(qe(Ue(new Fe,Pwe),th),"Edge Edge Between Layer Spacing"),"Spacing to be preserved between pairs of edges that are routed between the same pair of layers. Note that 'spacing.edgeEdge' is used for the spacing between pairs of edges crossing the same layer."),10),tc),wr),nn(Sn)))),Ye(n,new Je(Ke(Ve(Qe(hn(Ge(Xe(qe(Ue(new Fe,$we),th),"Node Node Between Layers Spacing"),"The spacing to be preserved between any pair of nodes of two adjacent layers. Note that 'spacing.nodeNode' is used for the spacing between nodes within the layer itself."),20),tc),wr),nn(Sn)))),Ye(n,new Je(Ke(Ve(Qe(hn(Ge(Xe(qe(Ue(new Fe,Rwe),Qwe),"Direction Priority"),"Defines how important it is to have a certain edge point into the direction of the overall layout. This option is evaluated during the cycle breaking phase."),me(0)),gc),Mr),nn(_a)))),Ye(n,new Je(Ke(Ve(Qe(hn(Ge(Xe(qe(Ue(new Fe,Bwe),Qwe),"Shortness Priority"),"Defines how important it is to keep an edge as short as possible. This option is evaluated during the layering phase."),me(0)),gc),Mr),nn(_a)))),Ye(n,new Je(Ke(Ve(Qe(hn(Ge(Xe(qe(Ue(new Fe,zwe),Qwe),"Straightness Priority"),"Defines how important it is to keep an edge straight, i.e. aligned with one of the two axes. This option is evaluated during node placement."),me(0)),gc),Mr),nn(_a)))),Ye(n,new Je(Ke(Ve(Qe(hn(Ge(Xe(qe(Ue(new Fe,kee),Ywe),"Connected Components Compaction"),"Tries to further compact components (disconnected sub-graphs)."),!1),xr),Yi),nn(Sn)))),Gi(n,kee,CS,!0),Ye(n,new Je(Ke(Ve(Qe(hn(Ge(Xe(qe(Ue(new Fe,Fwe),NYe),"Post Compaction Strategy"),DYe),t4e),Bi),$ve),nn(Sn)))),Ye(n,new Je(Ke(Ve(Qe(hn(Ge(Xe(qe(Ue(new Fe,Hwe),NYe),"Post Compaction Constraint Calculation"),DYe),n4e),Bi),bve),nn(Sn)))),Ye(n,new Je(Ke(Ve(Qe(hn(Ge(Xe(qe(Ue(new Fe,SF),Wwe),"High Degree Node Treatment"),"Makes room around high degree nodes to place leafs and trees."),!1),xr),Yi),nn(Sn)))),Ye(n,new Je(Ke(Ve(Qe(hn(Ge(Xe(qe(Ue(new Fe,Eee),Wwe),"High Degree Node Threshold"),"Whether a node is considered to have a high degree."),me(16)),gc),Mr),nn(Sn)))),Gi(n,Eee,SF,!0),Ye(n,new Je(Ke(Ve(Qe(hn(Ge(Xe(qe(Ue(new Fe,jee),Wwe),"High Degree Node Maximum Tree Height"),"Maximum height of a subtree connected to a high degree node to be moved to separate layers."),me(5)),gc),Mr),nn(Sn)))),Gi(n,jee,SF,!0),Ye(n,new Je(Ke(Ve(Qe(hn(Ge(Xe(qe(Ue(new Fe,fd),Zwe),"Graph Wrapping Strategy"),"For certain graphs and certain prescribed drawing areas it may be desirable to split the laid out graph into chunks that are placed side by side. The edges that connect different chunks are 'wrapped' around from the end of one chunk to the start of the other chunk. The points between the chunks are referred to as 'cuts'."),_4e),Bi),Y5e),nn(Sn)))),Ye(n,new Je(Ke(Ve(Qe(hn(Ge(Xe(qe(Ue(new Fe,MF),Zwe),"Additional Wrapped Edges Spacing"),"To visually separate edges that are wrapped from regularly routed edges an additional spacing value can be specified in form of this layout option. The spacing is added to the regular edgeNode spacing."),10),tc),wr),nn(Sn)))),Gi(n,MF,fd,qcn),Gi(n,MF,fd,Ucn),Ye(n,new Je(Ke(Ve(Qe(hn(Ge(Xe(qe(Ue(new Fe,AF),Zwe),"Correction Factor for Wrapping"),"At times and for certain types of graphs the executed wrapping may produce results that are consistently biased in the same fashion: either wrapping to often or to rarely. This factor can be used to correct the bias. Internally, it is simply multiplied with the 'aspect ratio' layout option."),1),tc),wr),nn(Sn)))),Gi(n,AF,fd,Vcn),Gi(n,AF,fd,Kcn),Ye(n,new Je(Ke(Ve(Qe(hn(Ge(Xe(qe(Ue(new Fe,PS),_Ye),"Cutting Strategy"),"The strategy by which the layer indexes are determined at which the layering crumbles into chunks."),D4e),Bi),vve),nn(Sn)))),Gi(n,PS,fd,nun),Gi(n,PS,fd,tun),Ye(n,new Je(Ke(Ve(Qe(Ge(Xe(qe(Ue(new Fe,See),_Ye),"Manually Specified Cuts"),"Allows the user to specify her own cuts for a certain graph."),oh),jl),nn(Sn)))),Gi(n,See,PS,Ycn),Ye(n,new Je(Ke(Ve(Qe(hn(Ge(Xe(qe(Ue(new Fe,Mee),"wrapping.cutting.msd"),"MSD Freedom"),"The MSD cutting strategy starts with an initial guess on the number of chunks the graph should be split into. The freedom specifies how much the strategy may deviate from this guess. E.g. if an initial number of 3 is computed, a freedom of 1 allows 2, 3, and 4 cuts."),N4e),gc),Mr),nn(Sn)))),Gi(n,Mee,PS,Zcn),Ye(n,new Je(Ke(Ve(Qe(hn(Ge(Xe(qe(Ue(new Fe,xF),IYe),"Validification Strategy"),"When wrapping graphs, one can specify indices that are not allowed as split points. The validification strategy makes sure every computed split point is allowed."),I4e),Bi),Q5e),nn(Sn)))),Gi(n,xF,fd,bun),Gi(n,xF,fd,gun),Ye(n,new Je(Ke(Ve(Qe(Ge(Xe(qe(Ue(new Fe,TF),IYe),"Valid Indices for Wrapping"),null),oh),jl),nn(Sn)))),Gi(n,TF,fd,aun),Gi(n,TF,fd,hun),Ye(n,new Je(Ke(Ve(Qe(hn(Ge(Xe(qe(Ue(new Fe,CF),e2e),"Improve Cuts"),"For general graphs it is important that not too many edges wrap backwards. Thus a compromise between evenly-distributed cuts and the total number of cut edges is sought."),!0),xr),Yi),nn(Sn)))),Gi(n,CF,fd,uun),Ye(n,new Je(Ke(Ve(Qe(hn(Ge(Xe(qe(Ue(new Fe,OF),e2e),"Distance Penalty When Improving Cuts"),null),2),tc),wr),nn(Sn)))),Gi(n,OF,fd,run),Gi(n,OF,CF,!0),Ye(n,new Je(Ke(Ve(Qe(hn(Ge(Xe(qe(Ue(new Fe,Aee),e2e),"Improve Wrapped Edges"),"The initial wrapping is performed in a very simple way. As a consequence, edges that wrap from one chunk to another may be unnecessarily long. Activating this option tries to shorten such edges."),!0),xr),Yi),nn(Sn)))),Gi(n,Aee,fd,sun),Ye(n,new Je(Ke(Ve(Qe(hn(Ge(Xe(qe(Ue(new Fe,xee),zee),"Layer Unzipping Strategy"),"The strategy to use for unzipping a layer into multiple sublayers while maintaining the existing ordering of nodes and edges after crossing minimization. The default value is 'NONE'."),M4e),Bi),e4e),nn(Sn)))),Ye(n,new Je(Ke(Ve(Qe(hn(Ge(Xe(qe(Ue(new Fe,Tee),zee),"Minimize Edge Length Heuristic"),"Use a heuristic to decide whether or not to actually perform the layer split with the goal of minimizing the total edge length. This option only works when layerSplit is set to 2. The property can be set to the nodes in a layer, which then applies the property for the layer. If any node sets the value to true, then the value is set to true for the entire layer."),!1),xr),Yi),nn(ar)))),Gi(n,Tee,Cee,bcn),Ye(n,new Je(Ke(Ve(Qe(hn(Ge(Xe(qe(Ue(new Fe,Cee),zee),"Unzipping Layer Split"),"Defines the number of sublayers to split a layer into. The property can be set to the nodes in a layer, which then applies the property for the layer. 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If any node sets the value to false, then the value is set to false for the entire layer."),S4e),xr),Yi),nn(ar)))),Gi(n,Oee,xee,wcn),Ye(n,new Je(Ke(Ve(Qe(hn(Ge(Xe(qe(Ue(new Fe,Jwe),Fee),"Edge Label Side Selection"),"Method to decide on edge label sides."),g4e),Bi),Sve),nn(Sn)))),Ye(n,new Je(Ke(Ve(Qe(hn(Ge(Xe(qe(Ue(new Fe,Gwe),Fee),"Edge Center Label Placement Strategy"),"Determines in which layer center labels of long edges should be placed."),b4e),Bi),P7),Ti(Sn,z(B(uh,1),ye,160,0,[wd]))))),Ye(n,new Je(Ke(Ve(Qe(hn(Ge(Xe(qe(Ue(new Fe,NF),$S),"Consider Model Order"),"Preserves the order of nodes and edges in the model file if this does not lead to additional edge crossings. Depending on the strategy this is not always possible since the node and edge order might be conflicting."),s4e),Bi),z5e),nn(Sn)))),Ye(n,new Je(Ke(Ve(Qe(hn(Ge(Xe(qe(Ue(new Fe,qwe),$S),"Consider Port Order"),"If disabled the port order of output ports is derived from the edge order and input ports are ordered by their incoming connections. If enabled all ports are ordered by the port model order."),!1),xr),Yi),nn(Sn)))),Ye(n,new Je(Ke(Ve(Qe(hn(Ge(Xe(qe(Ue(new Fe,$N),$S),"No Model Order"),"Set on a node to not set a model order for this node even though it is a real node."),!1),xr),Yi),nn(ar)))),Ye(n,new Je(Ke(Ve(Qe(hn(Ge(Xe(qe(Ue(new Fe,Nee),$S),"Consider Model Order for Components"),"If set to NONE the usual ordering strategy (by cumulative node priority and size of nodes) is used. INSIDE_PORT_SIDES orders the components with external ports only inside the groups with the same port side. FORCE_MODEL_ORDER enforces the mode order on components. This option might produce bad alignments and sub optimal drawings in terms of used area since the ordering should be respected."),i4e),Bi),v3e),nn(Sn)))),Gi(n,Nee,CS,null),Ye(n,new Je(Ke(Ve(Qe(hn(Ge(Xe(qe(Ue(new Fe,Uwe),$S),"Long Edge Ordering Strategy"),"Indicates whether long edges are sorted under, over, or equal to nodes that have no connection to a previous layer in a left-to-right or right-to-left layout. Under and over changes to right and left in a vertical layout."),o4e),Bi),N5e),nn(Sn)))),Ye(n,new Je(Ke(Ve(Qe(hn(Ge(Xe(qe(Ue(new Fe,Dee),$S),"Crossing Counter Node Order Influence"),"Indicates with what percentage (1 for 100%) violations of the node model order are weighted against the crossings e.g. a value of 0.5 means two model order violations are as important as on edge crossing. This allows some edge crossings in favor of preserving the model order. 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For instance, ports or labels being placed on the outside of a node's border might introduce such a margin. The margin is used to guarantee non-overlap of other graph elements with those ports or labels."),T9e),oh),y3e),nn(ar)))),Ye(n,new Je(Ke(Ve(Qe(hn(Ge(Xe(qe(Ue(new Fe,b2e),""),"No Layout"),"No layout is done for the associated element. This is used to mark parts of a diagram to avoid their inclusion in the layout graph, or to mark parts of the layout graph to prevent layout engines from processing them. If you wish to exclude the contents of a compound node from automatic layout, while the node itself is still considered on its own layer, use the 'Fixed Layout' algorithm for that node."),!1),xr),Yi),Ti(ar,z(B(uh,1),ye,160,0,[_a,h0,wd]))))),Ye(n,new Je(Ke(Ve(Qe(hn(Ge(Xe(qe(Ue(new Fe,wWe),""),"Scale Factor"),"The scaling factor to be applied to the corresponding node in recursive layout. 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The space left between a node and the comments of another node is controlled by the node-node spacing."),10),tc),wr),nn(Sn)))),Ye(n,new Je(Ke(Ve(Qe(hn(Ge(Xe(qe(Ue(new Fe,r2e),th),"Components Spacing"),"Spacing to be preserved between pairs of connected components. This option is only relevant if 'separateConnectedComponents' is activated."),20),tc),wr),nn(Sn)))),Ye(n,new Je(Ke(Ve(Qe(hn(Ge(Xe(qe(Ue(new Fe,c2e),th),"Edge Spacing"),"Spacing to be preserved between any two edges. Note that while this can somewhat easily be satisfied for the segments of orthogonally drawn edges, it is harder for general polylines or splines."),10),tc),wr),nn(Sn)))),Ye(n,new Je(Ke(Ve(Qe(hn(Ge(Xe(qe(Ue(new Fe,ZZ),th),"Edge Label Spacing"),"The minimal distance to be preserved between a label and the edge it is associated with. 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For each side of a node, this option can reserve additional space before and after the ports on each side. For example, a top spacing of 20 makes sure that the first port on the western and eastern side is 20 units away from the northern border."),Q9e),oh),y3e),nn(Sn)))),Ye(n,new Je(Ke(Ve(Qe(Ge(Xe(qe(Ue(new Fe,qee),DWe),"Layout Partition"),"Partition to which the node belongs. This requires Layout Partitioning to be active. Nodes with lower partition IDs will appear to the left of nodes with higher partition IDs (assuming a left-to-right layout direction)."),gc),Mr),Ti(Sn,z(B(uh,1),ye,160,0,[ar]))))),Gi(n,qee,Gee,xfn),Ye(n,new Je(Ke(Ve(Qe(hn(Ge(Xe(qe(Ue(new Fe,Gee),DWe),"Layout Partitioning"),"Whether to activate partitioned layout. This will allow to group nodes through the Layout Partition option. a pair of nodes with different partition indices is then placed such that the node with lower index is placed to the left of the other node (with left-to-right layout direction). 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If this option is set, it won't do so."),!1),xr),Yi),nn(Sn)))),Ye(n,new Je(Ke(Ve(Qe(hn(Ge(Xe(qe(Ue(new Fe,C2e),Fee),"Edge Label Placement"),"Gives a hint on where to put edge labels."),y9e),Bi),n8e),nn(wd)))),Ye(n,new Je(Ke(Ve(Qe(hn(Ge(Xe(qe(Ue(new Fe,bF),Fee),"Inline Edge Labels"),"If true, an edge label is placed directly on its edge. May only apply to center edge labels. 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t==null?null:Xvn(u(t,164).a);case 27:return Y2n(u(t,195));case 30:return oJe((ji(),u(t,16)));case 31:return oJe(u(t,16));case 40:return Q2n((ji(),t));case 42:return QJe((ji(),t));case 43:return QJe(t);case 59:case 48:return K2n((ji(),t));default:throw $(new Jn(y7+n.ve()+T2))}},s.pi=function(n){var t,i,r,c,o;switch(n.G==-1&&(n.G=(i=gl(n),i?Zd(i.si(),n):-1)),n.G){case 0:return t=new yoe,t;case 1:return r=new mU,r;case 2:return c=new TMe,c;case 3:return o=new CMe,o;default:throw $(new Jn(yne+n.zb+T2))}},s.qi=function(n,t){var i,r,c,o,l,f,h,b,p,y,S,A,N,_,R,U;switch(n.fk()){case 5:case 52:case 4:return t;case 6:return gSn(t);case 8:case 7:return t==null?null:ZAn(t);case 9:return t==null?null:dO(vl((r=bo(t,!0),r.length>0&&(Kn(0,r.length),r.charCodeAt(0)==43)?(Kn(1,r.length+1),r.substr(1)):r),-128,127)<<24>>24);case 10:return t==null?null:dO(vl((c=bo(t,!0),c.length>0&&(Kn(0,c.length),c.charCodeAt(0)==43)?(Kn(1,c.length+1),c.substr(1)):c),-128,127)<<24>>24);case 11:return 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A0n=()=>Be.useContext(Ike),zqn=g=>({connectOnClick:g.connectOnClick,noPanClassName:g.noPanClassName,rfId:g.rfId}),Fqn=(g,E,x)=>M=>{const{connectionClickStartHandle:N,connectionMode:$,connection:k}=M,{fromHandle:H,toHandle:U,isValid:G}=k,ie=U?.nodeId===g&&U?.id===E&&U?.type===x;return{connectingFrom:H?.nodeId===g&&H?.id===E&&H?.type===x,connectingTo:ie,clickConnecting:N?.nodeId===g&&N?.id===E&&N?.type===x,isPossibleEndHandle:$===wD.Strict?H?.type!==x:g!==H?.nodeId||E!==H?.id,connectionInProcess:!!H,clickConnectionInProcess:!!N,valid:ie&&G}};function Jqn({type:g="source",position:E=ur.Top,isValidConnection:x,isConnectable:M=!0,isConnectableStart:N=!0,isConnectableEnd:$=!0,id:k,onConnect:H,children:U,className:G,onMouseDown:ie,onTouchStart:W,...Z},le){const oe=k||null,ee=g==="target",Ce=El(),pe=A0n(),{connectOnClick:$e,noPanClassName:ae,rfId:Ne}=zu(zqn,jl),{connectingFrom:Ue,connectingTo:ln,clickConnecting:un,isPossibleEndHandle:An,connectionInProcess:xn,clickConnectionInProcess:nt,valid:dn}=zu(Fqn(pe,oe,g),jl);pe||Ce.getState().onError?.("010",a5.error010());const bn=pn=>{const{defaultEdgeOptions:Ae,onConnect:ve,hasDefaultEdges:nn}=Ce.getState(),yn={...Ae,...pn};if(nn){const{edges:Pn,setEdges:ye}=Ce.getState();ye(sGn(yn,Pn))}ve?.(yn),H?.(yn)},Y=pn=>{if(!pe)return;const Ae=Wdn(pn.nativeEvent);if(N&&(Ae&&pn.button===0||!Ae)){const 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f,h,b,p,y,S,A,O,D,B;if(A=!1,h=Ebe(t.q,n.f+n.b-t.q.f),S=i.f>n.b&&l,B=r-(t.q.e+h-o),p=(f=aS(i,B,!1),f.a),S&&p>i.f)return!1;if(S){for(y=0,D=new P(n.d);D.a=(kn(c,e.c.length),u(e.c[c],186)).e,!S&&p>n.b&&!b)?!1:((b||S||p<=n.b)&&(b&&p>n.b?(t.d=p,tO(t,$Ge(t,p))):(WHe(t.q,h),t.c=!0),tO(i,r-(t.s+t.r)),LO(i,t.q.e+t.q.d,n.f),kB(n,i),e.c.length>c&&(BO((kn(c,e.c.length),u(e.c[c],186)),i),(kn(c,e.c.length),u(e.c[c],186)).a.c.length==0&&Cd(e,c)),A=!0),A)}function zPn(e,n){var t,i,r,c,o,l,f,h,b,p;for(e.a=new yDe(hkn(Yx)),i=new P(n.a);i.a0&&(Qn(0,t.length),t.charCodeAt(0)!=47)))throw R(new qn("invalid opaquePart: "+t));if(e&&!(n!=null&&xj(SG,n.toLowerCase()))&&!(t==null||!jQ(t,oA,sA)))throw R(new qn(JZe+t));if(e&&n!=null&&xj(SG,n.toLowerCase())&&!BAn(t))throw R(new qn(JZe+t));if(!qjn(i))throw R(new qn("invalid device: "+i));if(!Hkn(r))throw o=r==null?"invalid segments: null":"invalid segment: "+$kn(r),R(new qn(o));if(!(c==null||ah(c,Xo(35))==-1))throw R(new qn("invalid query: "+c))}function 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aBn(e,n,t){var i,r,c,o,l,f,h,b,p,y,S,A,O,D,B,q,V,te,be,fe;switch(t.Tg("Brandes & Koepf node placement",1),e.a=n,e.c=G_n(n),i=u(C(n,(Ie(),Rie)),282),S=Fe(ze(C(n,vx))),e.d=i==(JO(),WJ)&&!S||i==lie,$Pn(e,n),be=null,fe=null,B=null,q=null,D=(sl(4,rm),new xo(4)),u(C(n,Rie),282).g){case 3:B=new b3(n,e.c.d,(Da(),Og),(dh(),Kd)),Gn(D.c,B);break;case 1:q=new b3(n,e.c.d,(Da(),Qa),(dh(),Kd)),Gn(D.c,q);break;case 4:be=new b3(n,e.c.d,(Da(),Og),(dh(),yp)),Gn(D.c,be);break;case 2:fe=new b3(n,e.c.d,(Da(),Qa),(dh(),yp)),Gn(D.c,fe);break;default:B=new b3(n,e.c.d,(Da(),Og),(dh(),Kd)),q=new b3(n,e.c.d,Qa,Kd),be=new b3(n,e.c.d,Og,yp),fe=new b3(n,e.c.d,Qa,yp),Gn(D.c,be),Gn(D.c,fe),Gn(D.c,B),Gn(D.c,q)}for(r=new fCe(n,e.c),l=new P(D);l.aAW(c))&&(p=c);for(!p&&(p=(kn(0,D.c.length),u(D.c[0],185))),O=new P(n.b);O.a0?(Ys(e,t,n),1):(Ys(e,n,t),-1);if(b&&V)return Ys(e,t,n),1;if(p&&q)return Ys(e,n,t),-1;if(p&&V)return 0}else for(cn=new P(h.j);cn.ap&&(In=0,lt+=b+_e,b=0),KXe(be,o,In,lt),n=k.Math.max(n,In+fe.a),b=k.Math.max(b,fe.b),In+=fe.a+_e;for(te=new wt,t=new wt,cn=new P(e);cn.a=-1900?1:0,t>=4?Kt(e,F(z(He,1),Me,2,6,[vYe,yYe])[l]):Kt(e,F(z(He,1),Me,2,6,["BC","AD"])[l]);break;case 121:WEn(e,t,i);break;case 77:XDn(e,t,i);break;case 107:f=r.q.getHours(),f==0?Vh(e,24,t):Vh(e,f,t);break;case 83:lNn(e,t,r);break;case 69:b=i.q.getDay(),t==5?Kt(e,F(z(He,1),Me,2,6,["S","M","T","W","T","F","S"])[b]):t==4?Kt(e,F(z(He,1),Me,2,6,[OZ,NZ,IZ,DZ,_Z,LZ,PZ])[b]):Kt(e,F(z(He,1),Me,2,6,["Sun","Mon","Tue","Wed","Thu","Fri","Sat"])[b]);break;case 97:r.q.getHours()>=12&&r.q.getHours()<24?Kt(e,F(z(He,1),Me,2,6,["AM","PM"])[1]):Kt(e,F(z(He,1),Me,2,6,["AM","PM"])[0]);break;case 104:p=r.q.getHours()%12,p==0?Vh(e,12,t):Vh(e,p,t);break;case 75:y=r.q.getHours()%12,Vh(e,y,t);break;case 72:S=r.q.getHours(),Vh(e,S,t);break;case 99:A=i.q.getDay(),t==5?Kt(e,F(z(He,1),Me,2,6,["S","M","T","W","T","F","S"])[A]):t==4?Kt(e,F(z(He,1),Me,2,6,[OZ,NZ,IZ,DZ,_Z,LZ,PZ])[A]):t==3?Kt(e,F(z(He,1),Me,2,6,["Sun","Mon","Tue","Wed","Thu","Fri","Sat"])[A]):Vh(e,A,1);break;case 76:O=i.q.getMonth(),t==5?Kt(e,F(z(He,1),Me,2,6,["J","F","M","A","M","J","J","A","S","O","N","D"])[O]):t==4?Kt(e,F(z(He,1),Me,2,6,[vZ,yZ,kZ,jZ,ay,EZ,SZ,xZ,AZ,MZ,CZ,TZ])[O]):t==3?Kt(e,F(z(He,1),Me,2,6,["Jan","Feb","Mar","Apr",ay,"Jun","Jul","Aug","Sep","Oct","Nov","Dec"])[O]):Vh(e,O+1,t);break;case 81:D=i.q.getMonth()/3|0,t<4?Kt(e,F(z(He,1),Me,2,6,["Q1","Q2","Q3","Q4"])[D]):Kt(e,F(z(He,1),Me,2,6,["1st quarter","2nd quarter","3rd quarter","4th quarter"])[D]);break;case 100:B=i.q.getDate(),Vh(e,B,t);break;case 109:h=r.q.getMinutes(),Vh(e,h,t);break;case 115:o=r.q.getSeconds(),Vh(e,o,t);break;case 122:t<4?Kt(e,c.c[0]):Kt(e,c.c[1]);break;case 118:Kt(e,c.b);break;case 90:t<3?Kt(e,hTn(c)):t==3?Kt(e,wTn(c)):Kt(e,pTn(c.a));break;default:return!1}return!0}function Ige(e,n,t,i){var r,c,o,l,f,h,b,p,y,S,A,O,D,B,q,V,te,be,fe,_e,on,cn,Tn,In,lt,Qt;if(PXe(n),f=u(K((!n.b&&(n.b=new Nn(mt,n,4,7)),n.b),0),84),b=u(K((!n.c&&(n.c=new Nn(mt,n,5,8)),n.c),0),84),l=iu(f),h=iu(b),o=(!n.a&&(n.a=new we($i,n,6,6)),n.a).i==0?null:u(K((!n.a&&(n.a=new we($i,n,6,6)),n.a),0),170),_e=u(zn(e.a,l),9),In=u(zn(e.a,h),9),on=null,lt=null,X(f,193)&&(fe=u(zn(e.a,f),246),X(fe,12)?on=u(fe,12):X(fe,9)&&(_e=u(fe,9),on=u(Pe(_e.j,0),12))),X(b,193)&&(Tn=u(zn(e.a,b),246),X(Tn,12)?lt=u(Tn,12):X(Tn,9)&&(In=u(Tn,9),lt=u(Pe(In.j,0),12))),!_e||!In)throw R(new a4("The source or the target of edge "+n+" could not be found. 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fn(Ope,k9e),bce=new fn(aF,!1),ke(1),new fn(LWe,null),z9e=new ki(_pe),jce=new ki(Npe),G9e=(De(),ju),t5=new fn(wpe,G9e),Ps=new ki(bpe),J9e=(ps(),rn(mb)),Rm=new fn(V8,J9e),Ece=new fn(kpe,!1),H9e=new fn(jpe,!0),ke(1),Hfn=new fn(dne,ke(3)),ke(1),qfn=new fn(I2e,ke(4)),uG=new fn(MN,1),oG=new fn(bne,null),zm=new fn(CN,150),F7=new fn(TN,1.414),Ky=new fn(np,null),Bfn=new fn(D2e,1),LI=new fn(mpe,!1),wce=new fn(vpe,!1),xfn=new fn(Tpe,1),S9e=(Sz(),Cce),new fn(PWe,S9e),Ifn=!0,Gfn=(KR(),Nce),Ffn=(V4(),Hm),Jfn=Hm,zfn=Hm}function Ur(){Ur=Y,Bve=new br("DIRECTION_PREPROCESSOR",0),Pve=new br("COMMENT_PREPROCESSOR",1),N3=new br("EDGE_AND_LAYER_CONSTRAINT_EDGE_REVERSER",2),_te=new br("INTERACTIVE_EXTERNAL_PORT_POSITIONER",3),r3e=new br("PARTITION_PREPROCESSOR",4),OJ=new br("LABEL_DUMMY_INSERTER",5),zJ=new br("SELF_LOOP_PREPROCESSOR",6),pm=new br("LAYER_CONSTRAINT_PREPROCESSOR",7),t3e=new br("PARTITION_MIDPROCESSOR",8),Xve=new br("HIGH_DEGREE_NODE_LAYER_PROCESSOR",9),e3e=new br("NODE_PROMOTION",10),wm=new br("LAYER_CONSTRAINT_POSTPROCESSOR",11),i3e=new br("PARTITION_POSTPROCESSOR",12),Gve=new br("HIERARCHICAL_PORT_CONSTRAINT_PROCESSOR",13),c3e=new br("SEMI_INTERACTIVE_CROSSMIN_PROCESSOR",14),Ove=new br("BREAKING_POINT_INSERTER",15),_J=new br("LONG_EDGE_SPLITTER",16),Lte=new br("PORT_SIDE_PROCESSOR",17),CJ=new br("INVERTED_PORT_PROCESSOR",18),$J=new br("PORT_LIST_SORTER",19),o3e=new br("SORT_BY_INPUT_ORDER_OF_MODEL",20),PJ=new br("NORTH_SOUTH_PORT_PREPROCESSOR",21),Nve=new br("BREAKING_POINT_PROCESSOR",22),n3e=new br(kQe,23),s3e=new br(jQe,24),RJ=new br("SELF_LOOP_PORT_RESTORER",25),Tve=new br("ALTERNATING_LAYER_UNZIPPER",26),u3e=new br("SINGLE_EDGE_GRAPH_WRAPPER",27),TJ=new br("IN_LAYER_CONSTRAINT_PROCESSOR",28),Fve=new br("END_NODE_PORT_LABEL_MANAGEMENT_PROCESSOR",29),Wve=new br("LABEL_AND_NODE_SIZE_PROCESSOR",30),Qve=new br("INNERMOST_NODE_MARGIN_CALCULATOR",31),FJ=new br("SELF_LOOP_ROUTER",32),_ve=new br("COMMENT_NODE_MARGIN_CALCULATOR",33),MJ=new br("END_LABEL_PREPROCESSOR",34),IJ=new br("LABEL_DUMMY_SWITCHER",35),Dve=new br("CENTER_LABEL_MANAGEMENT_PROCESSOR",36),p7=new br("LABEL_SIDE_SELECTOR",37),Vve=new br("HYPEREDGE_DUMMY_MERGER",38),qve=new br("HIERARCHICAL_PORT_DUMMY_SIZE_PROCESSOR",39),Zve=new br("LAYER_SIZE_AND_GRAPH_HEIGHT_CALCULATOR",40),tx=new br("HIERARCHICAL_PORT_POSITION_PROCESSOR",41),$ve=new br("CONSTRAINTS_POSTPROCESSOR",42),Lve=new br("COMMENT_POSTPROCESSOR",43),Yve=new br("HYPERNODE_PROCESSOR",44),Uve=new br("HIERARCHICAL_PORT_ORTHOGONAL_EDGE_ROUTER",45),DJ=new br("LONG_EDGE_JOINER",46),BJ=new br("SELF_LOOP_POSTPROCESSOR",47),Ive=new br("BREAKING_POINT_REMOVER",48),LJ=new br("NORTH_SOUTH_PORT_POSTPROCESSOR",49),Kve=new br("HORIZONTAL_COMPACTOR",50),NJ=new br("LABEL_DUMMY_REMOVER",51),Jve=new br("FINAL_SPLINE_BENDPOINTS_CALCULATOR",52),zve=new br("END_LABEL_SORTER",53),Cy=new br("REVERSED_EDGE_RESTORER",54),AJ=new br("END_LABEL_POSTPROCESSOR",55),Hve=new br("HIERARCHICAL_NODE_RESIZER",56),Rve=new br("DIRECTION_POSTPROCESSOR",57)}function mBn(e,n,t){var i,r,c,o,l,f,h,b,p,y,S,A,O,D,B,q,V,te,be,fe,_e,on,cn,Tn,In,lt,Qt,Ui,Es,eu,kl,s5,c0,ta,nd,Zl,n6,wA,td,Ca,u0,$g,Rg,t6,Bg,zg,id,Qm,M7e,Mp,pA,Vce,i6,mA,Wm,vA,Yce,_hn;for(M7e=0,Qt=n,eu=0,c0=Qt.length;eu0&&(e.a[Ca.p]=M7e++)}for(mA=0,Ui=t,kl=0,ta=Ui.length;kl0;){for(Ca=(at(t6.b>0),u(t6.a.Xb(t6.c=--t6.b),12)),Rg=0,l=new P(Ca.e);l.a0&&(Ca.j==(De(),Kn)?(e.a[Ca.p]=mA,++mA):(e.a[Ca.p]=mA+nd+n6,++n6))}mA+=n6}for($g=new wt,A=new Fh,lt=n,Es=0,s5=lt.length;Esh.b&&(h.b=Bg)):Ca.i.c==Qm&&(Bgh.c&&(h.c=Bg));for(G9(O,0,O.length,null),i6=se($t,ni,30,O.length,15,1),i=se($t,ni,30,mA+1,15,1),B=0;B0;)_e%2>0&&(r+=Yce[_e+1]),_e=(_e-1)/2|0,++Yce[_e];for(cn=se(jon,On,370,O.length*2,0,1),te=0;te0&>(Es.f),je(B,oG)!=null&&(!B.a&&(B.a=new we(Ft,B,10,11)),!!B.a)&&(!B.a&&(B.a=new we(Ft,B,10,11)),B.a).i>0?(l=u(je(B,oG),521),Rg=l.Sg(B),vw(B,k.Math.max(B.g,Rg.a+nd.b+nd.c),k.Math.max(B.f,Rg.b+nd.d+nd.a))):(!B.a&&(B.a=new we(Ft,B,10,11)),B.a).i!=0&&(Rg=new Se(ne(re(je(B,zm))),ne(re(je(B,zm)))/ne(re(je(B,F7)))),vw(B,k.Math.max(B.g,Rg.a+nd.b+nd.c),k.Math.max(B.f,Rg.b+nd.d+nd.a)));if(ta=u(je(n,s1),104),S=n.g-(ta.b+ta.c),y=n.f-(ta.d+ta.a),zg.ah("Available Child Area: ("+S+"|"+y+")"),Ei(n,B7,S/y),DJe(n,r,i.dh(s5)),u(je(n,Ky),281)==gG&&(sZ(n),vw(n,ta.b+ne(re(je(n,Pm)))+ta.c,ta.d+ne(re(je(n,Lm)))+ta.a)),zg.ah("Executed layout algorithm: "+Pt(je(n,qy))+" on node "+n.k),u(je(n,Ky),281)==Hm){if(S<0||y<0)throw R(new md("The size defined by the parent parallel node is too small for the space provided by the paddings of the child hierarchical node. "+n.k));for(ba(n,Pm)||ba(n,Lm)||sZ(n),O=ne(re(je(n,Pm))),A=ne(re(je(n,Lm))),zg.ah("Desired Child Area: ("+O+"|"+A+")"),n6=S/O,wA=y/A,Zl=k.Math.min(n6,k.Math.min(wA,ne(re(je(n,Bfn))))),Ei(n,uG,Zl),zg.ah(n.k+" -- Local Scale Factor (X|Y): ("+n6+"|"+wA+")"),te=u(je(n,DI),22),c=0,o=0,Zl'?":gn(gZe,e)?"'(?<' or '(? toIndex: ",Yge=", toIndex: ",Qge="Index: ",Wge=", Size: ",J8="org.eclipse.elk.alg.common",Yt={51:1},_Ye="org.eclipse.elk.alg.common.compaction",LYe="Scanline/EventHandler",t1="org.eclipse.elk.alg.common.compaction.oned",PYe="CNode belongs to another CGroup.",$Ye="ISpacingsHandler/1",UZ="The ",XZ=" instance has been finished already.",RYe="The direction ",BYe=" is not supported by the CGraph instance.",zYe="OneDimensionalCompactor",FYe="OneDimensionalCompactor/lambda$0$Type",JYe="Quadruplet",HYe="ScanlineConstraintCalculator",GYe="ScanlineConstraintCalculator/ConstraintsScanlineHandler",qYe="ScanlineConstraintCalculator/ConstraintsScanlineHandler/lambda$0$Type",UYe="ScanlineConstraintCalculator/Timestamp",XYe="ScanlineConstraintCalculator/lambda$0$Type",Sh={178:1,48:1},vS="org.eclipse.elk.alg.common.networksimplex",ma={171:1,3:1,4:1},KYe="org.eclipse.elk.alg.common.nodespacing",dg="org.eclipse.elk.alg.common.nodespacing.cellsystem",H8="CENTER",VYe={216:1,337:1},Zge={3:1,4:1,5:1,592:1},by="LEFT",gy="RIGHT",ewe="Vertical alignment cannot be null",nwe="BOTTOM",sF="org.eclipse.elk.alg.common.nodespacing.internal",yS="UNDEFINED",qa=.01,jN="org.eclipse.elk.alg.common.nodespacing.internal.algorithm",YYe="LabelPlacer/lambda$0$Type",QYe="LabelPlacer/lambda$1$Type",WYe="portRatioOrPosition",G8="org.eclipse.elk.alg.common.overlaps",KZ="DOWN",wy="org.eclipse.elk.alg.common.spore",um={3:1,4:1,5:1,198:1},ZYe={3:1,6:1,4:1,5:1,90:1,110:1},VZ="org.eclipse.elk.alg.force",twe="ComponentsProcessor",eQe="ComponentsProcessor/1",iwe="ElkGraphImporter/lambda$0$Type",ep={214:1},y3="org.eclipse.elk.core",EN="org.eclipse.elk.graph.properties",nQe="IPropertyHolder",SN="org.eclipse.elk.alg.force.graph",tQe="Component Layout",rwe="org.eclipse.elk.alg.force.model",yu="org.eclipse.elk.core.data",lF="org.eclipse.elk.force.model",cwe="org.eclipse.elk.force.iterations",uwe="org.eclipse.elk.force.repulsivePower",YZ="org.eclipse.elk.force.temperature",xh=.001,QZ="org.eclipse.elk.force.repulsion",Ua={148:1},kS="org.eclipse.elk.alg.force.options",q8=1.600000023841858,$o="org.eclipse.elk.force",xN="org.eclipse.elk.priority",om="org.eclipse.elk.spacing.nodeNode",WZ="org.eclipse.elk.spacing.edgeLabel",U8="org.eclipse.elk.aspectRatio",fF="org.eclipse.elk.randomSeed",jS="org.eclipse.elk.separateConnectedComponents",sm="org.eclipse.elk.padding",ES="org.eclipse.elk.interactive",ZZ="org.eclipse.elk.portConstraints",aF="org.eclipse.elk.edgeLabels.inline",SS="org.eclipse.elk.omitNodeMicroLayout",X8="org.eclipse.elk.nodeSize.fixedGraphSize",py="org.eclipse.elk.nodeSize.options",k3="org.eclipse.elk.nodeSize.constraints",K8="org.eclipse.elk.nodeLabels.placement",V8="org.eclipse.elk.portLabels.placement",AN="org.eclipse.elk.topdownLayout",MN="org.eclipse.elk.topdown.scaleFactor",CN="org.eclipse.elk.topdown.hierarchicalNodeWidth",TN="org.eclipse.elk.topdown.hierarchicalNodeAspectRatio",np="org.eclipse.elk.topdown.nodeType",owe="origin",iQe="random",rQe="boundingBox.upLeft",cQe="boundingBox.lowRight",swe="org.eclipse.elk.stress.fixed",lwe="org.eclipse.elk.stress.desiredEdgeLength",fwe="org.eclipse.elk.stress.dimension",awe="org.eclipse.elk.stress.epsilon",hwe="org.eclipse.elk.stress.iterationLimit",W0="org.eclipse.elk.stress",uQe="ELK Stress",my="org.eclipse.elk.nodeSize.minimum",hF="org.eclipse.elk.alg.force.stress",oQe="Layered layout",vy="org.eclipse.elk.alg.layered",ON="org.eclipse.elk.alg.layered.compaction.components",xS="org.eclipse.elk.alg.layered.compaction.oned",dF="org.eclipse.elk.alg.layered.compaction.oned.algs",bg="org.eclipse.elk.alg.layered.compaction.recthull",Xa="org.eclipse.elk.alg.layered.components",va="NONE",eee="MODEL_ORDER",qu={3:1,6:1,4:1,10:1,5:1,126:1},sQe={3:1,6:1,4:1,5:1,135:1,90:1,110:1},bF="org.eclipse.elk.alg.layered.compound",Mi={43:1},Zu="org.eclipse.elk.alg.layered.graph",nee=" -> ",lQe="Not supported by LGraph",dwe="Port side is undefined",Y8={3:1,6:1,4:1,5:1,323:1,135:1,90:1,110:1},Fd={3:1,6:1,4:1,5:1,135:1,199:1,209:1,90:1,110:1},fQe={3:1,6:1,4:1,5:1,135:1,2004:1,209:1,90:1,110:1},aQe=`([{"' 	\r
+`,hQe=`)]}"' 	\r
+`,dQe="The given string contains parts that cannot be parsed as numbers.",NN="org.eclipse.elk.core.math",bQe={3:1,4:1,140:1,213:1,414:1},gQe={3:1,4:1,104:1,213:1,414:1},Jd="org.eclipse.elk.alg.layered.graph.transform",wQe="ElkGraphImporter",pQe="ElkGraphImporter/lambda$1$Type",mQe="ElkGraphImporter/lambda$2$Type",vQe="ElkGraphImporter/lambda$4$Type",Wn="org.eclipse.elk.alg.layered.intermediate",yQe="Node margin calculation",kQe="ONE_SIDED_GREEDY_SWITCH",jQe="TWO_SIDED_GREEDY_SWITCH",tee="No implementation is available for the layout processor ",iee="IntermediateProcessorStrategy",ree="Node '",EQe="FIRST_SEPARATE",SQe="LAST_SEPARATE",xQe="Odd port side processing",lr="org.eclipse.elk.alg.layered.intermediate.compaction",AS="org.eclipse.elk.alg.layered.intermediate.greedyswitch",i1="org.eclipse.elk.alg.layered.p3order.counting",MS={220:1},yy="org.eclipse.elk.alg.layered.intermediate.loops",bl="org.eclipse.elk.alg.layered.intermediate.loops.ordering",Z0="org.eclipse.elk.alg.layered.intermediate.loops.routing",gF="org.eclipse.elk.alg.layered.intermediate.preserveorder",Ah="org.eclipse.elk.alg.layered.intermediate.wrapping",Tu="org.eclipse.elk.alg.layered.options",cee="INTERACTIVE",bwe="GREEDY",AQe="DEPTH_FIRST",MQe="EDGE_LENGTH",CQe="SELF_LOOPS",TQe="firstTryWithInitialOrder",gwe="org.eclipse.elk.layered.directionCongruency",wwe="org.eclipse.elk.layered.feedbackEdges",wF="org.eclipse.elk.layered.interactiveReferencePoint",pwe="org.eclipse.elk.layered.mergeEdges",mwe="org.eclipse.elk.layered.mergeHierarchyEdges",vwe="org.eclipse.elk.layered.allowNonFlowPortsToSwitchSides",ywe="org.eclipse.elk.layered.portSortingStrategy",kwe="org.eclipse.elk.layered.thoroughness",jwe="org.eclipse.elk.layered.unnecessaryBendpoints",Ewe="org.eclipse.elk.layered.generatePositionAndLayerIds",IN="org.eclipse.elk.layered.cycleBreaking.strategy",DN="org.eclipse.elk.layered.layering.strategy",Swe="org.eclipse.elk.layered.layering.layerConstraint",xwe="org.eclipse.elk.layered.layering.layerChoiceConstraint",Awe="org.eclipse.elk.layered.layering.layerId",uee="org.eclipse.elk.layered.layering.minWidth.upperBoundOnWidth",oee="org.eclipse.elk.layered.layering.minWidth.upperLayerEstimationScalingFactor",see="org.eclipse.elk.layered.layering.nodePromotion.strategy",lee="org.eclipse.elk.layered.layering.nodePromotion.maxIterations",fee="org.eclipse.elk.layered.layering.coffmanGraham.layerBound",CS="org.eclipse.elk.layered.crossingMinimization.strategy",Mwe="org.eclipse.elk.layered.crossingMinimization.forceNodeModelOrder",aee="org.eclipse.elk.layered.crossingMinimization.hierarchicalSweepiness",hee="org.eclipse.elk.layered.crossingMinimization.semiInteractive",Cwe="org.eclipse.elk.layered.crossingMinimization.inLayerPredOf",Twe="org.eclipse.elk.layered.crossingMinimization.inLayerSuccOf",Owe="org.eclipse.elk.layered.crossingMinimization.positionChoiceConstraint",Nwe="org.eclipse.elk.layered.crossingMinimization.positionId",Iwe="org.eclipse.elk.layered.crossingMinimization.greedySwitch.activationThreshold",dee="org.eclipse.elk.layered.crossingMinimization.greedySwitch.type",pF="org.eclipse.elk.layered.crossingMinimization.greedySwitchHierarchical.type",j3="org.eclipse.elk.layered.nodePlacement.strategy",mF="org.eclipse.elk.layered.nodePlacement.favorStraightEdges",bee="org.eclipse.elk.layered.nodePlacement.bk.edgeStraightening",gee="org.eclipse.elk.layered.nodePlacement.bk.fixedAlignment",wee="org.eclipse.elk.layered.nodePlacement.linearSegments.deflectionDampening",pee="org.eclipse.elk.layered.nodePlacement.networkSimplex.nodeFlexibility",mee="org.eclipse.elk.layered.nodePlacement.networkSimplex.nodeFlexibility.default",Dwe="org.eclipse.elk.layered.edgeRouting.selfLoopDistribution",_we="org.eclipse.elk.layered.edgeRouting.selfLoopOrdering",vF="org.eclipse.elk.layered.edgeRouting.splines.mode",yF="org.eclipse.elk.layered.edgeRouting.splines.sloppy.layerSpacingFactor",vee="org.eclipse.elk.layered.edgeRouting.polyline.slopedEdgeZoneWidth",Lwe="org.eclipse.elk.layered.spacing.baseValue",Pwe="org.eclipse.elk.layered.spacing.edgeNodeBetweenLayers",$we="org.eclipse.elk.layered.spacing.edgeEdgeBetweenLayers",Rwe="org.eclipse.elk.layered.spacing.nodeNodeBetweenLayers",Bwe="org.eclipse.elk.layered.priority.direction",zwe="org.eclipse.elk.layered.priority.shortness",Fwe="org.eclipse.elk.layered.priority.straightness",yee="org.eclipse.elk.layered.compaction.connectedComponents",Jwe="org.eclipse.elk.layered.compaction.postCompaction.strategy",Hwe="org.eclipse.elk.layered.compaction.postCompaction.constraints",kF="org.eclipse.elk.layered.highDegreeNodes.treatment",kee="org.eclipse.elk.layered.highDegreeNodes.threshold",jee="org.eclipse.elk.layered.highDegreeNodes.treeHeight",q1="org.eclipse.elk.layered.wrapping.strategy",jF="org.eclipse.elk.layered.wrapping.additionalEdgeSpacing",EF="org.eclipse.elk.layered.wrapping.correctionFactor",TS="org.eclipse.elk.layered.wrapping.cutting.strategy",Eee="org.eclipse.elk.layered.wrapping.cutting.cuts",See="org.eclipse.elk.layered.wrapping.cutting.msd.freedom",SF="org.eclipse.elk.layered.wrapping.validify.strategy",xF="org.eclipse.elk.layered.wrapping.validify.forbiddenIndices",AF="org.eclipse.elk.layered.wrapping.multiEdge.improveCuts",MF="org.eclipse.elk.layered.wrapping.multiEdge.distancePenalty",xee="org.eclipse.elk.layered.wrapping.multiEdge.improveWrappedEdges",Aee="org.eclipse.elk.layered.layerUnzipping.strategy",Mee="org.eclipse.elk.layered.layerUnzipping.minimizeEdgeLength",Cee="org.eclipse.elk.layered.layerUnzipping.layerSplit",Tee="org.eclipse.elk.layered.layerUnzipping.resetOnLongEdges",Gwe="org.eclipse.elk.layered.edgeLabels.sideSelection",qwe="org.eclipse.elk.layered.edgeLabels.centerLabelPlacementStrategy",CF="org.eclipse.elk.layered.considerModelOrder.strategy",Uwe="org.eclipse.elk.layered.considerModelOrder.portModelOrder",_N="org.eclipse.elk.layered.considerModelOrder.noModelOrder",Oee="org.eclipse.elk.layered.considerModelOrder.components",Xwe="org.eclipse.elk.layered.considerModelOrder.longEdgeStrategy",Nee="org.eclipse.elk.layered.considerModelOrder.crossingCounterNodeInfluence",Iee="org.eclipse.elk.layered.considerModelOrder.crossingCounterPortInfluence",Dee="org.eclipse.elk.layered.considerModelOrder.groupModelOrder.cycleBreakingId",_ee="org.eclipse.elk.layered.considerModelOrder.groupModelOrder.crossingMinimizationId",Lee="org.eclipse.elk.layered.considerModelOrder.groupModelOrder.componentGroupId",Kwe="org.eclipse.elk.layered.considerModelOrder.groupModelOrder.cbGroupOrderStrategy",Pee="org.eclipse.elk.layered.considerModelOrder.groupModelOrder.cbPreferredSourceId",$ee="org.eclipse.elk.layered.considerModelOrder.groupModelOrder.cbPreferredTargetId",Vwe="org.eclipse.elk.layered.considerModelOrder.groupModelOrder.cmGroupOrderStrategy",Ywe="org.eclipse.elk.layered.considerModelOrder.groupModelOrder.cmEnforcedGroupOrders",Ree="layering",OQe="layering.minWidth",NQe="layering.nodePromotion",Q8="crossingMinimization",TF="org.eclipse.elk.hierarchyHandling",IQe="crossingMinimization.greedySwitch",DQe="nodePlacement",_Qe="nodePlacement.bk",LQe="edgeRouting",LN="org.eclipse.elk.edgeRouting",Ka="spacing",Qwe="priority",Wwe="compaction",PQe="compaction.postCompaction",$Qe="Specifies whether and how post-process compaction is applied.",Zwe="highDegreeNodes",epe="wrapping",RQe="wrapping.cutting",BQe="wrapping.validify",npe="wrapping.multiEdge",Bee="layerUnzipping",zee="edgeLabels",OS="considerModelOrder",W8="considerModelOrder.groupModelOrder",tpe="Group ID of the Node Type",ipe="org.eclipse.elk.spacing.commentComment",rpe="org.eclipse.elk.spacing.commentNode",cpe="org.eclipse.elk.spacing.componentComponent",upe="org.eclipse.elk.spacing.edgeEdge",Fee="org.eclipse.elk.spacing.edgeNode",ope="org.eclipse.elk.spacing.labelLabel",spe="org.eclipse.elk.spacing.labelPortHorizontal",lpe="org.eclipse.elk.spacing.labelPortVertical",fpe="org.eclipse.elk.spacing.labelNode",ape="org.eclipse.elk.spacing.nodeSelfLoop",hpe="org.eclipse.elk.spacing.portPort",dpe="org.eclipse.elk.spacing.individual",bpe="org.eclipse.elk.port.borderOffset",gpe="org.eclipse.elk.noLayout",wpe="org.eclipse.elk.port.side",PN="org.eclipse.elk.debugMode",ppe="org.eclipse.elk.alignment",mpe="org.eclipse.elk.insideSelfLoops.activate",vpe="org.eclipse.elk.insideSelfLoops.yo",Jee="org.eclipse.elk.direction",ype="org.eclipse.elk.nodeLabels.padding",kpe="org.eclipse.elk.portLabels.nextToPortIfPossible",jpe="org.eclipse.elk.portLabels.treatAsGroup",Epe="org.eclipse.elk.portAlignment.default",Spe="org.eclipse.elk.portAlignment.north",xpe="org.eclipse.elk.portAlignment.south",Ape="org.eclipse.elk.portAlignment.west",Mpe="org.eclipse.elk.portAlignment.east",OF="org.eclipse.elk.contentAlignment",Cpe="org.eclipse.elk.junctionPoints",Tpe="org.eclipse.elk.edge.thickness",Ope="org.eclipse.elk.edgeLabels.placement",Npe="org.eclipse.elk.port.index",Ipe="org.eclipse.elk.commentBox",Dpe="org.eclipse.elk.hypernode",_pe="org.eclipse.elk.port.anchor",Hee="org.eclipse.elk.partitioning.activate",Gee="org.eclipse.elk.partitioning.partition",NF="org.eclipse.elk.position",Lpe="org.eclipse.elk.margins",Ppe="org.eclipse.elk.spacing.portsSurrounding",IF="org.eclipse.elk.interactiveLayout",$u="org.eclipse.elk.core.util",$pe={3:1,4:1,5:1,590:1},zQe="NETWORK_SIMPLEX",Rpe="SIMPLE",oc={95:1,43:1},tp="org.eclipse.elk.alg.layered.p1cycles",FQe="Depth-first cycle removal",JQe="Model order cycle breaking",U1="org.eclipse.elk.alg.layered.p2layers",Bpe={406:1,220:1},HQe={830:1,3:1,4:1},Ro="org.eclipse.elk.alg.layered.p3order",E3=17976931348623157e292,qee=5e-324,Lc="org.eclipse.elk.alg.layered.p4nodes",GQe={3:1,4:1,5:1,838:1},Mh=1e-5,eb="org.eclipse.elk.alg.layered.p4nodes.bk",Uee="org.eclipse.elk.alg.layered.p5edges",ya="org.eclipse.elk.alg.layered.p5edges.orthogonal",Xee="org.eclipse.elk.alg.layered.p5edges.orthogonal.direction",Kee=1e-6,lm="org.eclipse.elk.alg.layered.p5edges.splines",Vee=.09999999999999998,DF=1e-8,qQe=4.71238898038469,UQe=1.5707963267948966,zpe=3.141592653589793,X1="org.eclipse.elk.alg.mrtree",Yee=.10000000149011612,_F="SUPER_ROOT",NS="org.eclipse.elk.alg.mrtree.graph",Fpe=-17976931348623157e292,go="org.eclipse.elk.alg.mrtree.intermediate",XQe="Processor compute fanout",LF={3:1,6:1,4:1,5:1,522:1,90:1,110:1},KQe="Set neighbors in level",$N="org.eclipse.elk.alg.mrtree.options",VQe="DESCENDANTS",Jpe="org.eclipse.elk.mrtree.compaction",Hpe="org.eclipse.elk.mrtree.edgeEndTextureLength",Gpe="org.eclipse.elk.mrtree.treeLevel",qpe="org.eclipse.elk.mrtree.positionConstraint",Upe="org.eclipse.elk.mrtree.weighting",Xpe="org.eclipse.elk.mrtree.edgeRoutingMode",Kpe="org.eclipse.elk.mrtree.searchOrder",YQe="Position Constraint",Bo="org.eclipse.elk.mrtree",QQe="org.eclipse.elk.tree",WQe="Processor arrange level",Z8="org.eclipse.elk.alg.mrtree.p2order",Qs="org.eclipse.elk.alg.mrtree.p4route",Vpe="org.eclipse.elk.alg.radial",gg=6.283185307179586,Ype="Before",PF="After",Qpe="org.eclipse.elk.alg.radial.intermediate",ZQe="COMPACTION",Qee="org.eclipse.elk.alg.radial.intermediate.compaction",eWe={3:1,4:1,5:1,90:1},Wpe="org.eclipse.elk.alg.radial.intermediate.optimization",Wee="No implementation is available for the layout option ",IS="org.eclipse.elk.alg.radial.options",nWe="CompactionStrategy",Zpe="org.eclipse.elk.radial.centerOnRoot",e2e="org.eclipse.elk.radial.orderId",n2e="org.eclipse.elk.radial.radius",$F="org.eclipse.elk.radial.rotate",Zee="org.eclipse.elk.radial.compactor",ene="org.eclipse.elk.radial.compactionStepSize",t2e="org.eclipse.elk.radial.sorter",i2e="org.eclipse.elk.radial.wedgeCriteria",r2e="org.eclipse.elk.radial.optimizationCriteria",nne="org.eclipse.elk.radial.rotation.targetAngle",tne="org.eclipse.elk.radial.rotation.computeAdditionalWedgeSpace",c2e="org.eclipse.elk.radial.rotation.outgoingEdgeAngles",tWe="Compaction",u2e="rotation",Gl="org.eclipse.elk.radial",iWe="org.eclipse.elk.alg.radial.p1position.wedge",o2e="org.eclipse.elk.alg.radial.sorting",rWe=5.497787143782138,cWe=3.9269908169872414,uWe=2.356194490192345,oWe="org.eclipse.elk.alg.rectpacking",DS="org.eclipse.elk.alg.rectpacking.intermediate",ine="org.eclipse.elk.alg.rectpacking.options",s2e="org.eclipse.elk.rectpacking.trybox",l2e="org.eclipse.elk.rectpacking.currentPosition",f2e="org.eclipse.elk.rectpacking.desiredPosition",a2e="org.eclipse.elk.rectpacking.inNewRow",h2e="org.eclipse.elk.rectpacking.orderBySize",d2e="org.eclipse.elk.rectpacking.widthApproximation.strategy",b2e="org.eclipse.elk.rectpacking.widthApproximation.targetWidth",g2e="org.eclipse.elk.rectpacking.widthApproximation.optimizationGoal",w2e="org.eclipse.elk.rectpacking.widthApproximation.lastPlaceShift",p2e="org.eclipse.elk.rectpacking.packing.strategy",m2e="org.eclipse.elk.rectpacking.packing.compaction.rowHeightReevaluation",v2e="org.eclipse.elk.rectpacking.packing.compaction.iterations",y2e="org.eclipse.elk.rectpacking.whiteSpaceElimination.strategy",rne="widthApproximation",sWe="Compaction Strategy",lWe="packing.compaction",ms="org.eclipse.elk.rectpacking",e7="org.eclipse.elk.alg.rectpacking.p1widthapproximation",RF="org.eclipse.elk.alg.rectpacking.p2packing",fWe="No Compaction",k2e="org.eclipse.elk.alg.rectpacking.p3whitespaceelimination",RN="org.eclipse.elk.alg.rectpacking.util",BF="No implementation available for ",fm="org.eclipse.elk.alg.spore",am="org.eclipse.elk.alg.spore.options",ip="org.eclipse.elk.sporeCompaction",cne="org.eclipse.elk.underlyingLayoutAlgorithm",j2e="org.eclipse.elk.processingOrder.treeConstruction",E2e="org.eclipse.elk.processingOrder.spanningTreeCostFunction",une="org.eclipse.elk.processingOrder.preferredRoot",one="org.eclipse.elk.processingOrder.rootSelection",sne="org.eclipse.elk.structure.structureExtractionStrategy",S2e="org.eclipse.elk.compaction.compactionStrategy",x2e="org.eclipse.elk.compaction.orthogonal",A2e="org.eclipse.elk.overlapRemoval.maxIterations",M2e="org.eclipse.elk.overlapRemoval.runScanline",lne="processingOrder",aWe="overlapRemoval",n7="org.eclipse.elk.sporeOverlap",hWe="org.eclipse.elk.alg.spore.p1structure",fne="org.eclipse.elk.alg.spore.p2processingorder",ane="org.eclipse.elk.alg.spore.p3execution",dWe="Topdown Layout",bWe="Invalid index: ",t7="org.eclipse.elk.core.alg",S3={342:1},hm={296:1},gWe="Make sure its type is registered with the ",C2e=" utility class.",i7="true",hne="false",wWe="Couldn't clone property '",rp=.05,Oo="org.eclipse.elk.core.options",pWe=1.2999999523162842,cp="org.eclipse.elk.box",T2e="org.eclipse.elk.expandNodes",O2e="org.eclipse.elk.box.packingMode",mWe="org.eclipse.elk.algorithm",vWe="org.eclipse.elk.resolvedAlgorithm",N2e="org.eclipse.elk.bendPoints",EBn="org.eclipse.elk.labelManager",yWe="org.eclipse.elk.softwrappingFuzziness",kWe="org.eclipse.elk.scaleFactor",jWe="org.eclipse.elk.childAreaWidth",EWe="org.eclipse.elk.childAreaHeight",SWe="org.eclipse.elk.animate",xWe="org.eclipse.elk.animTimeFactor",AWe="org.eclipse.elk.layoutAncestors",MWe="org.eclipse.elk.maxAnimTime",CWe="org.eclipse.elk.minAnimTime",TWe="org.eclipse.elk.progressBar",OWe="org.eclipse.elk.validateGraph",NWe="org.eclipse.elk.validateOptions",IWe="org.eclipse.elk.zoomToFit",DWe="org.eclipse.elk.json.shapeCoords",_We="org.eclipse.elk.json.edgeCoords",SBn="org.eclipse.elk.font.name",LWe="org.eclipse.elk.font.size",dne="org.eclipse.elk.topdown.sizeCategories",I2e="org.eclipse.elk.topdown.sizeCategoriesHierarchicalNodeWeight",bne="org.eclipse.elk.topdown.sizeApproximator",D2e="org.eclipse.elk.topdown.scaleCap",PWe="org.eclipse.elk.edge.type",$We="partitioning",RWe="nodeLabels",zF="portAlignment",gne="nodeSize",wne="port",_2e="portLabels",r7="topdown",BWe="insideSelfLoops",L2e="INHERIT",c7="org.eclipse.elk.fixed",FF="org.eclipse.elk.random",JF={3:1,35:1,23:1,521:1,288:1},zWe="port must have a parent node to calculate the port side",FWe="The edge needs to have exactly one edge section. Found: ",_S="org.eclipse.elk.core.util.adapters",ql="org.eclipse.emf.ecore",x3="org.eclipse.elk.graph",JWe="EMapPropertyHolder",HWe="ElkBendPoint",GWe="ElkGraphElement",qWe="ElkConnectableShape",P2e="ElkEdge",UWe="ElkEdgeSection",XWe="EModelElement",KWe="ENamedElement",$2e="ElkLabel",R2e="ElkNode",B2e="ElkPort",VWe={94:1,93:1},ky="org.eclipse.emf.common.notify.impl",nb="The feature '",LS="' is not a valid changeable feature",YWe="Expecting null",pne="' is not a valid feature",QWe="The feature ID",WWe=" is not a valid feature ID",Ru=32768,ZWe={109:1,94:1,93:1,57:1,52:1,100:1},Jn="org.eclipse.emf.ecore.impl",wg="org.eclipse.elk.graph.impl",PS="Recursive containment not allowed for ",u7="The datatype '",up="' is not a valid classifier",mne="The value '",A3={195:1,3:1,4:1},vne="The class '",o7="http://www.eclipse.org/elk/ElkGraph",z2e="property",$S="value",yne="source",eZe="properties",nZe="identifier",kne="height",jne="width",Ene="parent",Sne="text",xne="children",tZe="hierarchical",F2e="sources",Ane="targets",Mne="sections",HF="bendPoints",J2e="outgoingShape",H2e="incomingShape",G2e="outgoingSections",q2e="incomingSections",yc="org.eclipse.emf.common.util",U2e="Severe implementation error in the Json to ElkGraph importer.",Ch="id",Wr="org.eclipse.elk.graph.json",s7="Unhandled parameter types: ",iZe="startPoint",rZe="An edge must have at least one source and one target (edge id: '",l7="').",cZe="Referenced edge section does not exist: ",uZe=" (edge id: '",X2e="target",oZe="sourcePoint",sZe="targetPoint",GF="group",ui="name",lZe="connectableShape cannot be null",fZe="edge cannot be null",aZe="Passed edge is not 'simple'.",qF="org.eclipse.elk.graph.util",BN="The 'no duplicates' constraint is violated",Cne="targetIndex=",pg=", size=",Tne="sourceIndex=",Th={3:1,4:1,20:1,31:1,56:1,18:1,16:1,59:1,71:1,67:1,61:1},One={3:1,4:1,20:1,31:1,56:1,18:1,50:1,16:1,59:1,71:1,67:1,61:1,585:1},UF="logging",hZe="measureExecutionTime",dZe="parser.parse.1",bZe="parser.parse.2",XF="parser.next.1",Nne="parser.next.2",gZe="parser.next.3",wZe="parser.next.4",mg="parser.factor.1",K2e="parser.factor.2",pZe="parser.factor.3",mZe="parser.factor.4",vZe="parser.factor.5",yZe="parser.factor.6",kZe="parser.atom.1",jZe="parser.atom.2",EZe="parser.atom.3",V2e="parser.atom.4",Ine="parser.atom.5",Y2e="parser.cc.1",KF="parser.cc.2",SZe="parser.cc.3",xZe="parser.cc.5",Q2e="parser.cc.6",W2e="parser.cc.7",Dne="parser.cc.8",AZe="parser.ope.1",MZe="parser.ope.2",CZe="parser.ope.3",Hd="parser.descape.1",TZe="parser.descape.2",OZe="parser.descape.3",NZe="parser.descape.4",IZe="parser.descape.5",Ul="parser.process.1",DZe="parser.quantifier.1",_Ze="parser.quantifier.2",LZe="parser.quantifier.3",PZe="parser.quantifier.4",Z2e="parser.quantifier.5",$Ze="org.eclipse.emf.common.notify",eme={415:1,676:1},RZe={3:1,4:1,20:1,31:1,56:1,18:1,16:1,71:1,61:1},zN={373:1,151:1},RS="index=",_ne={3:1,4:1,5:1,129:1},BZe={3:1,4:1,20:1,31:1,56:1,18:1,16:1,59:1,71:1,61:1},nme={3:1,6:1,4:1,5:1,198:1},zZe={3:1,4:1,5:1,175:1,374:1},Gf=1024,FZe=";/?:@&=+$,",JZe="invalid authority: ",HZe="EAnnotation",GZe="ETypedElement",qZe="EStructuralFeature",UZe="EAttribute",XZe="EClassifier",KZe="EEnumLiteral",VZe="EGenericType",YZe="EOperation",QZe="EParameter",WZe="EReference",ZZe="ETypeParameter",Ri="org.eclipse.emf.ecore.util",Lne={77:1},tme={3:1,20:1,18:1,16:1,61:1,586:1,77:1,72:1,98:1},een="org.eclipse.emf.ecore.util.FeatureMap$Entry",as=8192,BS="byte",VF="char",zS="double",FS="float",JS="int",HS="long",GS="short",nen="java.lang.Object",M3={3:1,4:1,5:1,255:1},ime={3:1,4:1,5:1,678:1},ten={3:1,4:1,20:1,31:1,56:1,18:1,16:1,59:1,71:1,67:1,61:1,72:1},au={3:1,4:1,20:1,31:1,56:1,18:1,16:1,59:1,71:1,67:1,61:1,77:1,72:1,98:1},FN="mixed",Ut="http:///org/eclipse/emf/ecore/util/ExtendedMetaData",af="kind",ien={3:1,4:1,5:1,679:1},rme={3:1,4:1,20:1,31:1,56:1,18:1,16:1,71:1,61:1,77:1,72:1,98:1},YF={20:1,31:1,56:1,18:1,16:1,61:1,72:1},QF={50:1,128:1,287:1},WF={75:1,344:1},ZF="The value of type '",eJ="' must be of type '",C3=1306,hf="http://www.eclipse.org/emf/2002/Ecore",nJ=-32768,op="constraints",sc="baseType",ren="getEStructuralFeature",cen="getFeatureID",qS="feature",uen="getOperationID",cme="operation",oen="defaultValue",sen="eTypeParameters",len="isInstance",fen="getEEnumLiteral",aen="eContainingClass",ii={58:1},hen={3:1,4:1,5:1,122:1},den="org.eclipse.emf.ecore.resource",ben={94:1,93:1,588:1,1996:1},Pne="org.eclipse.emf.ecore.resource.impl",ume="unspecified",JN="simple",tJ="attribute",gen="attributeWildcard",iJ="element",$ne="elementWildcard",ka="collapse",Rne="itemType",rJ="namespace",HN="##targetNamespace",df="whiteSpace",ome="wildcards",vg="http://www.eclipse.org/emf/2003/XMLType",Bne="##any",f7="uninitialized",GN="The multiplicity constraint is 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gie,z3e,F3e=yt(Tu,"InteractiveReferencePoint",420,Tt,e4n,umn),Qin,J3e,Oy,dp,oI,tH,H3e,G3e,iH,q3e,Ny,rH,sx,Iy,K1,wie,cH,Iu,U3e,ob,po,pie,mie,sI,jg,bp,Dy,X3e,Win,_y,lI,km,Ea,gf,vie,R3,sb,Oi,mi,K3e,V3e,Y3e,Q3e,W3e,yie,uH,vs,gp,kie,Ly,lx,qd,B3,wp,z3,F3,M7,Eg,Z3e,jie,Eie,fx,Py,oH,$y,J3;m(165,23,{3:1,35:1,23:1,165:1},fT);var ax,V1,hx,Sg,fI,e5e=yt(Tu,"LayerConstraint",165,Tt,Z6n,omn),Zin;m(423,23,{3:1,35:1,23:1,423:1},pse);var Sie,xie,n5e=yt(Tu,"LayerUnzippingStrategy",423,Tt,n4n,smn),ern;m(843,1,Ua,xC),s.tf=function(n){en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,gwe),""),"Direction Congruency"),"Specifies how drawings of the same graph with different layout directions compare to each other: either a natural reading direction is preserved or the drawings are rotated versions of each other."),b5e),(lg(),Bi)),S3e),rn((vh(),Cn))))),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,wwe),""),"Feedback Edges"),"Whether feedback edges should be highlighted by routing around the nodes."),($n(),!1)),xr),Qi),rn(Cn)))),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,wF),""),"Interactive Reference Point"),"Determines which point of a node is considered by interactive layout phases."),y5e),Bi),F3e),rn(Cn)))),qi(n,wF,IN,rcn),qi(n,wF,CS,icn),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,pwe),""),"Merge Edges"),"Edges that have no ports are merged so they touch the connected nodes at the same points. When this option is disabled, one port is created for each edge directly connected to a node. When it is enabled, all such incoming edges share an input port, and all outgoing edges share an output port."),!1),xr),Qi),rn(Cn)))),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,mwe),""),"Merge Hierarchy-Crossing Edges"),"If hierarchical layout is active, hierarchy-crossing edges use as few hierarchical ports as possible. They are broken by the algorithm, with hierarchical ports inserted as required. Usually, one such port is created for each edge at each hierarchy crossing point. With this option set to true, we try to create as few hierarchical ports as possible in the process. In particular, all edges that form a hyperedge can share a port."),!0),xr),Qi),rn(Cn)))),en(n,new qe(tgn(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,vwe),""),"Allow Non-Flow Ports To Switch Sides"),"Specifies whether non-flow ports may switch sides if their node's port constraints are either FIXED_SIDE or FIXED_ORDER. A non-flow port is a port on a side that is not part of the currently configured layout flow. For instance, given a left-to-right layout direction, north and south ports would be considered non-flow ports. Further note that the underlying criterium whether to switch sides or not solely relies on the minimization of edge crossings. Hence, edge length and other aesthetics criteria are not addressed."),!1),xr),Qi),rn(Yd)),F(z(He,1),Me,2,6,["org.eclipse.elk.layered.northOrSouthPort"])))),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,ywe),""),"Port Sorting Strategy"),"Only relevant for nodes with FIXED_SIDE port constraints. Determines the way a node's ports are distributed on the sides of a node if their order is not prescribed. The option is set on parent nodes."),N5e),Bi),J4e),rn(Cn)))),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,kwe),""),"Thoroughness"),"How much effort should be spent to produce a nice layout."),ke(7)),dc),jr),rn(Cn)))),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,jwe),""),"Add Unnecessary Bendpoints"),"Adds bend points even if an edge does not change direction. If true, each long edge dummy will contribute a bend point to its edges and hierarchy-crossing edges will always get a bend point where they cross hierarchy boundaries. By default, bend points are only added where an edge changes direction."),!1),xr),Qi),rn(Cn)))),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,Ewe),""),"Generate Position and Layer IDs"),"If enabled position id and layer id are generated, which are usually only used internally when setting the interactiveLayout option. This option should be specified on the root node."),!1),xr),Qi),rn(Cn)))),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,IN),"cycleBreaking"),"Cycle Breaking Strategy"),"Strategy for cycle breaking. Cycle breaking looks for cycles in the graph and determines which edges to reverse to break the cycles. Reversed edges will end up pointing to the opposite direction of regular edges (that is, reversed edges will point left if edges usually point right)."),d5e),Bi),j3e),rn(Cn)))),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,DN),Ree),"Node Layering Strategy"),"Strategy for node layering."),E5e),Bi),O4e),rn(Cn)))),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,Swe),Ree),"Layer Constraint"),"Determines a constraint on the placement of the node regarding the layering."),k5e),Bi),e5e),rn(fr)))),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,xwe),Ree),"Layer Choice Constraint"),"Allows to set a constraint regarding the layer placement of a node. Let i be the value of teh constraint. Assumed the drawing has n layers and i < n. If set to i, it expresses that the node should be placed in i-th layer. Should i>=n be true then the node is placed in the last layer of the drawing. Note that this option is not part of any of ELK Layered's default configurations but is only evaluated as part of the `InteractiveLayeredGraphVisitor`, which must be applied manually or used via the `DiagramLayoutEngine."),null),dc),jr),rn(fr)))),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,Awe),Ree),"Layer ID"),"Layer identifier that was calculated by ELK Layered for a node. This is only generated if interactiveLayot or generatePositionAndLayerIds is set."),ke(-1)),dc),jr),rn(fr)))),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,uee),OQe),"Upper Bound On Width [MinWidth Layerer]"),"Defines a loose upper bound on the width of the MinWidth layerer. If set to '-1' multiple values are tested and the best result is selected."),ke(4)),dc),jr),rn(Cn)))),qi(n,uee,DN,acn),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,oee),OQe),"Upper Layer Estimation Scaling Factor [MinWidth Layerer]"),"Multiplied with Upper Bound On Width for defining an upper bound on the width of layers which haven't been determined yet, but whose maximum width had been (roughly) estimated by the MinWidth algorithm. Compensates for too high estimations. If set to '-1' multiple values are tested and the best result is selected."),ke(2)),dc),jr),rn(Cn)))),qi(n,oee,DN,dcn),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,see),NQe),"Node Promotion Strategy"),"Reduces number of dummy nodes after layering phase (if possible)."),j5e),Bi),B4e),rn(Cn)))),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,lee),NQe),"Max Node Promotion Iterations"),"Limits the number of iterations for node promotion."),ke(0)),dc),jr),rn(Cn)))),qi(n,lee,see,null),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,fee),"layering.coffmanGraham"),"Layer Bound"),"The maximum number of nodes allowed per layer."),ke(oi)),dc),jr),rn(Cn)))),qi(n,fee,DN,ucn),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,CS),Q8),"Crossing Minimization Strategy"),"Strategy for crossing minimization."),h5e),Bi),m3e),rn(Cn)))),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,Mwe),Q8),"Force Node Model Order"),"The node order given by the model does not change to produce a better layout. E.g. if node A is before node B in the model this is not changed during crossing minimization. This assumes that the node model order is already respected before crossing minimization. This can be achieved by setting considerModelOrder.strategy to NODES_AND_EDGES."),!1),xr),Qi),rn(Cn)))),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,aee),Q8),"Hierarchical Sweepiness"),"How likely it is to use cross-hierarchy (1) vs bottom-up (-1)."),.1),ec),gr),rn(Cn)))),qi(n,aee,TF,Orn),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,hee),Q8),"Semi-Interactive Crossing Minimization"),"Preserves the order of nodes within a layer but still minimizes crossings between edges connecting long edge dummies. Derives the desired order from positions specified by the 'org.eclipse.elk.position' layout option. Requires a crossing minimization strategy that is able to process 'in-layer' constraints."),!1),xr),Qi),rn(Cn)))),qi(n,hee,CS,Prn),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,Cwe),Q8),"In Layer Predecessor of"),"Allows to set a constraint which specifies of which node the current node is the predecessor. If set to 's' then the node is the predecessor of 's' and is in the same layer"),null),Gy),He),rn(fr)))),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,Twe),Q8),"In Layer Successor of"),"Allows to set a constraint which specifies of which node the current node is the successor. If set to 's' then the node is the successor of 's' and is in the same layer"),null),Gy),He),rn(fr)))),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,Owe),Q8),"Position Choice Constraint"),"Allows to set a constraint regarding the position placement of a node in a layer. Assumed the layer in which the node placed includes n other nodes and i < n. If set to i, it expresses that the node should be placed at the i-th position. Should i>=n be true then the node is placed at the last position in the layer. Note that this option is not part of any of ELK Layered's default configurations but is only evaluated as part of the `InteractiveLayeredGraphVisitor`, which must be applied manually or used via the `DiagramLayoutEngine."),null),dc),jr),rn(fr)))),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,Nwe),Q8),"Position ID"),"Position within a layer that was determined by ELK Layered for a node. This is only generated if interactiveLayot or generatePositionAndLayerIds is set."),ke(-1)),dc),jr),rn(fr)))),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,Iwe),IQe),"Greedy Switch Activation Threshold"),"By default it is decided automatically if the greedy switch is activated or not. The decision is based on whether the size of the input graph (without dummy nodes) is smaller than the value of this option. A '0' enforces the activation."),ke(40)),dc),jr),rn(Cn)))),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,dee),IQe),"Greedy Switch Crossing Minimization"),"Greedy Switch strategy for crossing minimization. The greedy switch heuristic is executed after the regular crossing minimization as a post-processor. Note that if 'hierarchyHandling' is set to 'INCLUDE_CHILDREN', the 'greedySwitchHierarchical.type' option must be used."),a5e),Bi),die),rn(Cn)))),qi(n,dee,CS,Crn),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,pF),"crossingMinimization.greedySwitchHierarchical"),"Greedy Switch Crossing Minimization (hierarchical)"),"Activates the greedy switch heuristic in case hierarchical layout is used. The differences to the non-hierarchical case (see 'greedySwitch.type') are: 1) greedy switch is inactive by default, 3) only the option value set on the node at which hierarchical layout starts is relevant, and 2) if it's activated by the user, it properly addresses hierarchy-crossing edges."),f5e),Bi),die),rn(Cn)))),qi(n,pF,CS,xrn),qi(n,pF,TF,Arn),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,j3),DQe),"Node Placement Strategy"),"Strategy for node placement."),O5e),Bi),_4e),rn(Cn)))),en(n,new qe(We(Qe(Ze(Xe(Ye(Ke(Ve(new Ge,mF),DQe),"Favor Straight Edges Over Balancing"),"Favor straight edges over a balanced node placement. The default behavior is determined automatically based on the used 'edgeRouting'. For an orthogonal style it is set to true, for all other styles to false."),xr),Qi),rn(Cn)))),qi(n,mF,j3,Ocn),qi(n,mF,j3,Ncn),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,bee),_Qe),"BK Edge Straightening"),"Specifies whether the Brandes Koepf node placer tries to increase the number of straight edges at the expense of diagram size. There is a subtle difference to the 'favorStraightEdges' option, which decides whether a balanced placement of the nodes is desired, or not. In bk terms this means combining the four alignments into a single balanced one, or not. This option on the other hand tries to straighten additional edges during the creation of each of the four alignments."),M5e),Bi),M3e),rn(Cn)))),qi(n,bee,j3,Acn),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,gee),_Qe),"BK Fixed Alignment"),"Tells the BK node placer to use a certain alignment (out of its four) instead of the one producing the smallest height, or the combination of all four."),C5e),Bi),I3e),rn(Cn)))),qi(n,gee,j3,Ccn),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,wee),"nodePlacement.linearSegments"),"Linear Segments Deflection Dampening"),"Dampens the movement of nodes to keep the diagram from getting too large."),.3),ec),gr),rn(Cn)))),qi(n,wee,j3,Dcn),en(n,new qe(We(Qe(Ze(Xe(Ye(Ke(Ve(new Ge,pee),"nodePlacement.networkSimplex"),"Node Flexibility"),"Aims at shorter and straighter edges. Two configurations are possible: (a) allow ports to move freely on the side they are assigned to (the order is always defined beforehand), (b) additionally allow to enlarge a node wherever it helps. If this option is not configured for a node, the 'nodeFlexibility.default' value is used, which is specified for the node's parent."),Bi),Wie),rn(fr)))),qi(n,pee,j3,$cn),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,mee),"nodePlacement.networkSimplex.nodeFlexibility"),"Node Flexibility Default"),"Default value of the 'nodeFlexibility' option for the children of a hierarchical node."),T5e),Bi),Wie),rn(Cn)))),qi(n,mee,j3,Pcn),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,Dwe),LQe),"Self-Loop Distribution"),"Alter the distribution of the loops around the node. It only takes effect for PortConstraints.FREE."),p5e),Bi),q4e),rn(fr)))),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,_we),LQe),"Self-Loop Ordering"),"Alter the ordering of the loops they can either be stacked or sequenced. It only takes effect for PortConstraints.FREE."),m5e),Bi),U4e),rn(fr)))),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,vF),"edgeRouting.splines"),"Spline Routing Mode"),"Specifies the way control points are assembled for each individual edge. CONSERVATIVE ensures that edges are properly routed around the nodes but feels rather orthogonal at times. SLOPPY uses fewer control points to obtain curvier edge routes but may result in edges overlapping nodes."),v5e),Bi),K4e),rn(Cn)))),qi(n,vF,LN,Xrn),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,yF),"edgeRouting.splines.sloppy"),"Sloppy Spline Layer Spacing Factor"),"Spacing factor for routing area between layers when using sloppy spline routing."),.2),ec),gr),rn(Cn)))),qi(n,yF,LN,Vrn),qi(n,yF,vF,Yrn),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,vee),"edgeRouting.polyline"),"Sloped Edge Zone Width"),"Width of the strip to the left and to the right of each layer where the polyline edge router is allowed to refrain from ensuring that edges are routed horizontally. This prevents awkward bend points for nodes that extent almost to the edge of their layer."),2),ec),gr),rn(Cn)))),qi(n,vee,LN,Hrn),en(n,new qe(We(Qe(Ze(Xe(Ye(Ke(Ve(new Ge,Lwe),Ka),"Spacing Base Value"),"An optional base value for all other layout options of the 'spacing' group. It can be used to conveniently alter the overall 'spaciousness' of the drawing. Whenever an explicit value is set for the other layout options, this base value will have no effect. The base value is not inherited, i.e. it must be set for each hierarchical node."),ec),gr),rn(Cn)))),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,Pwe),Ka),"Edge Node Between Layers Spacing"),"The spacing to be preserved between nodes and edges that are routed next to the node's layer. For the spacing between nodes and edges that cross the node's layer 'spacing.edgeNode' is used."),10),ec),gr),rn(Cn)))),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,$we),Ka),"Edge Edge Between Layer Spacing"),"Spacing to be preserved between pairs of edges that are routed between the same pair of layers. Note that 'spacing.edgeEdge' is used for the spacing between pairs of edges crossing the same layer."),10),ec),gr),rn(Cn)))),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,Rwe),Ka),"Node Node Between Layers Spacing"),"The spacing to be preserved between any pair of nodes of two adjacent layers. Note that 'spacing.nodeNode' is used for the spacing between nodes within the layer itself."),20),ec),gr),rn(Cn)))),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,Bwe),Qwe),"Direction Priority"),"Defines how important it is to have a certain edge point into the direction of the overall layout. This option is evaluated during the cycle breaking phase."),ke(0)),dc),jr),rn(xa)))),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,zwe),Qwe),"Shortness Priority"),"Defines how important it is to keep an edge as short as possible. This option is evaluated during the layering phase."),ke(0)),dc),jr),rn(xa)))),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,Fwe),Qwe),"Straightness Priority"),"Defines how important it is to keep an edge straight, i.e. aligned with one of the two axes. 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Internally, it is simply multiplied with the 'aspect ratio' layout option."),1),ec),gr),rn(Cn)))),qi(n,EF,q1,Zcn),qi(n,EF,q1,eun),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,TS),RQe),"Cutting Strategy"),"The strategy by which the layer indexes are determined at which the layering crumbles into chunks."),D5e),Bi),y3e),rn(Cn)))),qi(n,TS,q1,uun),qi(n,TS,q1,oun),en(n,new qe(We(Qe(Ze(Xe(Ye(Ke(Ve(new Ge,Eee),RQe),"Manually Specified Cuts"),"Allows the user to specify her own cuts for a certain graph."),Za),gl),rn(Cn)))),qi(n,Eee,TS,tun),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,See),"wrapping.cutting.msd"),"MSD Freedom"),"The MSD cutting strategy starts with an initial guess on the number of chunks the graph should be split into. The freedom specifies how much the strategy may deviate from this guess. E.g. if an initial number of 3 is computed, a freedom of 1 allows 2, 3, and 4 cuts."),I5e),dc),jr),rn(Cn)))),qi(n,See,TS,run),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,SF),BQe),"Validification Strategy"),"When wrapping graphs, one can specify indices that are not allowed as split points. The validification strategy makes sure every computed split point is allowed."),L5e),Bi),Q4e),rn(Cn)))),qi(n,SF,q1,vun),qi(n,SF,q1,yun),en(n,new qe(We(Qe(Ze(Xe(Ye(Ke(Ve(new Ge,xF),BQe),"Valid Indices for Wrapping"),null),Za),gl),rn(Cn)))),qi(n,xF,q1,wun),qi(n,xF,q1,pun),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,AF),npe),"Improve Cuts"),"For general graphs it is important that not too many edges wrap backwards. 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For instance, ports or labels being placed on the outside of a node's border might introduce such a margin. The margin is used to guarantee non-overlap of other graph elements with those ports or labels."),T9e),Za),kve),rn(fr)))),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,gpe),""),"No Layout"),"No layout is done for the associated element. This is used to mark parts of a diagram to avoid their inclusion in the layout graph, or to mark parts of the layout graph to prevent layout engines from processing them. If you wish to exclude the contents of a compound node from automatic layout, while the node itself is still considered on its own layer, use the 'Fixed Layout' algorithm for that node."),!1),xr),Qi),Ci(fr,F(z(Wa,1),Ee,160,0,[xa,Yd,Q1]))))),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,kWe),""),"Scale Factor"),"The scaling factor to be applied to the corresponding node in recursive layout. 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Layouts are then scaled down to fit the area provided by their parents. Graphs must follow a certain structure for topdown layout to work properly. {@link TopdownNodeTypes.PARALLEL_NODE} nodes must have children of type {@link TopdownNodeTypes.HIERARCHICAL_NODE} and must define {@link topdown.hierarchicalNodeWidth} and {@link topdown.hierarchicalNodeAspectRatio} for their children. Furthermore they need to be laid out using an algorithm that is a {@link TopdownLayoutProvider}. Hierarchical nodes can also be parents of other hierarchical nodes and can optionally use a {@link TopdownSizeApproximator} to dynamically set sizes during topdown layout. In this case {@link topdown.hierarchicalNodeWidth} and {@link topdown.hierarchicalNodeAspectRatio} should be set on the node itself rather than the parent. The values are then used by the size approximator as base values. Hierarchical nodes require the layout option {@link nodeSize.fixedGraphSize} to be true to prevent the algorithm used there from resizing the hierarchical node. This option is not supported if 'Hierarchy Handling' is set to 'INCLUDE_CHILDREN'"),!1),xr),Qi),rn(Cn)))),qi(n,AN,np,null),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,SWe),""),"Animate"),"Whether the shift from the old layout to the new computed layout shall be animated."),!0),xr),Qi),rn(Cn)))),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,xWe),""),"Animation Time Factor"),"Factor for computation of animation time. The higher the value, the longer the animation time. If the value is 0, the resulting time is always equal to the minimum defined by 'Minimal Animation Time'."),ke(100)),dc),jr),rn(Cn)))),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,AWe),""),"Layout Ancestors"),"Whether the hierarchy levels on the path from the selected element to the root of the diagram shall be included in the layout process."),!1),xr),Qi),rn(Cn)))),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,MWe),""),"Maximal Animation Time"),"The maximal time for animations, in milliseconds."),ke(4e3)),dc),jr),rn(Cn)))),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,CWe),""),"Minimal Animation Time"),"The minimal time for animations, in milliseconds."),ke(400)),dc),jr),rn(Cn)))),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,TWe),""),"Progress Bar"),"Whether a progress bar shall be displayed during layout computations."),!1),xr),Qi),rn(Cn)))),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,OWe),""),"Validate Graph"),"Whether the graph shall be validated before any layout algorithm is applied. If this option is enabled and at least one error is found, the layout process is aborted and a message is shown to the user."),!1),xr),Qi),rn(Cn)))),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,NWe),""),"Validate Options"),"Whether layout options shall be validated before any layout algorithm is applied. If this option is enabled and at least one error is found, the layout process is aborted and a message is shown to the user."),!0),xr),Qi),rn(Cn)))),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,IWe),""),"Zoom to Fit"),"Whether the zoom level shall be set to view the whole diagram after layout."),!1),xr),Qi),rn(Cn)))),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,O2e),"box"),"Box Layout Mode"),"Configures the packing mode used by the {@link BoxLayoutProvider}. If SIMPLE is not required (neither priorities are used nor the interactive mode), GROUP_DEC can improve the packing and decrease the area. GROUP_MIXED and GROUP_INC may, in very specific scenarios, work better."),m9e),Bi),O8e),rn(Cn)))),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,DWe),"json"),"Shape Coords"),"For layouts transferred into JSON graphs, specify the coordinate system to be used for nodes, ports, and labels of nodes and ports."),M9e),Bi),y8e),rn(Cn)))),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,_We),"json"),"Edge Coords"),"For layouts transferred into JSON graphs, specify the coordinate system to be used for edge route points and edge labels."),A9e),Bi),n8e),rn(Cn)))),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,ipe),Ka),"Comment Comment Spacing"),"Spacing to be preserved between a comment box and other comment boxes connected to the same node. The space left between comment boxes of different nodes is controlled by the node-node spacing."),10),ec),gr),rn(Cn)))),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,rpe),Ka),"Comment Node Spacing"),"Spacing to be preserved between a node and its connected comment boxes. The space left between a node and the comments of another node is controlled by the node-node spacing."),10),ec),gr),rn(Cn)))),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,cpe),Ka),"Components Spacing"),"Spacing to be preserved between pairs of connected components. This option is only relevant if 'separateConnectedComponents' is activated."),20),ec),gr),rn(Cn)))),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,upe),Ka),"Edge Spacing"),"Spacing to be preserved between any two edges. Note that while this can somewhat easily be satisfied for the segments of orthogonally drawn edges, it is harder for general polylines or splines."),10),ec),gr),rn(Cn)))),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,WZ),Ka),"Edge Label Spacing"),"The minimal distance to be preserved between a label and the edge it is associated with. Note that the placement of a label is influenced by the 'edgelabels.placement' option."),2),ec),gr),rn(Cn)))),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,Fee),Ka),"Edge Node Spacing"),"Spacing to be preserved between nodes and edges."),10),ec),gr),rn(Cn)))),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,ope),Ka),"Label Spacing"),"Determines the amount of space to be left between two labels of the same graph element."),0),ec),gr),rn(Cn)))),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,fpe),Ka),"Label Node Spacing"),"Spacing to be preserved between labels and the border of node they are associated with. Note that the placement of a label is influenced by the 'nodelabels.placement' option."),5),ec),gr),rn(Cn)))),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,spe),Ka),"Horizontal spacing between Label and Port"),"Horizontal spacing to be preserved between labels and the ports they are associated with. Note that the placement of a label is influenced by the 'portlabels.placement' option."),1),ec),gr),rn(Cn)))),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,lpe),Ka),"Vertical spacing between Label and Port"),"Vertical spacing to be preserved between labels and the ports they are associated with. Note that the placement of a label is influenced by the 'portlabels.placement' option."),1),ec),gr),rn(Cn)))),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,om),Ka),"Node Spacing"),"The minimal distance to be preserved between each two nodes."),20),ec),gr),rn(Cn)))),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,ape),Ka),"Node Self Loop Spacing"),"Spacing to be preserved between a node and its self loops."),10),ec),gr),rn(Cn)))),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,hpe),Ka),"Port Spacing"),"Spacing between pairs of ports of the same node."),10),ec),gr),Ci(Cn,F(z(Wa,1),Ee,160,0,[fr]))))),en(n,new qe(We(Qe(Ze(Xe(Ye(Ke(Ve(new Ge,dpe),Ka),"Individual Spacing"),"Allows to specify individual spacing values for graph elements that shall be different from the value specified for the element's parent."),Za),wan),Ci(fr,F(z(Wa,1),Ee,160,0,[xa,Yd,Q1]))))),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,Ppe),Ka),"Additional Port Space"),"Additional space around the sets of ports on each node side. For each side of a node, this option can reserve additional space before and after the ports on each side. For example, a top spacing of 20 makes sure that the first port on the western and eastern side is 20 units away from the northern border."),Q9e),Za),kve),rn(Cn)))),en(n,new qe(We(Qe(Ze(Xe(Ye(Ke(Ve(new Ge,Gee),$We),"Layout Partition"),"Partition to which the node belongs. This requires Layout Partitioning to be active. Nodes with lower partition IDs will appear to the left of nodes with higher partition IDs (assuming a left-to-right layout direction)."),dc),jr),Ci(Cn,F(z(Wa,1),Ee,160,0,[fr]))))),qi(n,Gee,Hee,Ifn),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,Hee),$We),"Layout Partitioning"),"Whether to activate partitioned layout. This will allow to group nodes through the Layout Partition option. a pair of nodes with different partition indices is then placed such that the node with lower index is placed to the left of the other node (with left-to-right layout direction). Depending on the layout algorithm, this may only be guaranteed to work if all nodes have a layout partition configured, or at least if edges that cross partitions are not part of a partition-crossing cycle."),$9e),xr),Qi),rn(Cn)))),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,ype),RWe),"Node Label Padding"),"Define padding for node labels that are placed inside of a node."),N9e),Za),jve),rn(Cn)))),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,K8),RWe),"Node Label Placement"),"Hints for where node labels are to be placed; if empty, the node label's position is not modified."),I9e),Hy),$c),Ci(fr,F(z(Wa,1),Ee,160,0,[Q1]))))),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,Epe),zF),"Port Alignment"),"Defines the default port distribution for a node. May be overridden for each side individually."),B9e),Bi),eA),rn(fr)))),en(n,new qe(We(Qe(Ze(Xe(Ye(Ke(Ve(new Ge,Spe),zF),"Port Alignment (North)"),"Defines how ports on the northern side are placed, overriding the node's general port alignment."),Bi),eA),rn(fr)))),en(n,new qe(We(Qe(Ze(Xe(Ye(Ke(Ve(new Ge,xpe),zF),"Port Alignment (South)"),"Defines how ports on the southern side are placed, overriding the node's general port alignment."),Bi),eA),rn(fr)))),en(n,new qe(We(Qe(Ze(Xe(Ye(Ke(Ve(new Ge,Ape),zF),"Port Alignment (West)"),"Defines how ports on the western side are placed, overriding the node's general port alignment."),Bi),eA),rn(fr)))),en(n,new qe(We(Qe(Ze(Xe(Ye(Ke(Ve(new Ge,Mpe),zF),"Port Alignment (East)"),"Defines how ports on the eastern side are placed, overriding the node's general port alignment."),Bi),eA),rn(fr)))),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,k3),gne),"Node Size Constraints"),"What should be taken into account when calculating a node's size. Empty size constraints specify that a node's size is already fixed and should not be changed."),D9e),Hy),iA),rn(fr)))),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,py),gne),"Node Size Options"),"Options modifying the behavior of the size constraints set on a node. Each member of the set specifies something that should be taken into account when calculating node sizes. The empty set corresponds to no further modifications."),L9e),Hy),k8e),rn(fr)))),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,my),gne),"Node Size Minimum"),"The minimal size to which a node can be reduced."),_9e),Za),Lr),rn(fr)))),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,X8),gne),"Fixed Graph Size"),"By default, the fixed layout provider will enlarge a graph until it is large enough to contain its children. If this option is set, it won't do so."),!1),xr),Qi),rn(Cn)))),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,Ope),zee),"Edge Label Placement"),"Gives a hint on where to put edge labels."),k9e),Bi),t8e),rn(Q1)))),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,aF),zee),"Inline Edge Labels"),"If true, an edge label is placed directly on its edge. May only apply to center edge labels. This kind of label placement is only advisable if the label's rendering is such that it is not crossed by its edge and thus stays legible."),!1),xr),Qi),rn(Q1)))),en(n,new qe(We(Qe(Ze(Xe(Ye(Ke(Ve(new Ge,SBn),"font"),"Font Name"),"Font name used for a label."),Gy),He),rn(Q1)))),en(n,new qe(We(Qe(Ze(Xe(Ye(Ke(Ve(new Ge,LWe),"font"),"Font Size"),"Font size used for a label."),dc),jr),rn(Q1)))),en(n,new qe(We(Qe(Ze(Xe(Ye(Ke(Ve(new Ge,_pe),wne),"Port Anchor Offset"),"The offset to the port position where connections shall be attached."),Za),Lr),rn(Yd)))),en(n,new qe(We(Qe(Ze(Xe(Ye(Ke(Ve(new Ge,Npe),wne),"Port Index"),"The index of a port in the fixed order around a node. The order is assumed as clockwise, starting with the leftmost port on the top side. This option must be set if 'Port Constraints' is set to FIXED_ORDER and no specific positions are given for the ports. Additionally, the option 'Port Side' must be defined in this case."),dc),jr),rn(Yd)))),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,wpe),wne),"Port Side"),"The side of a node on which a port is situated. This option must be set if 'Port Constraints' is set to FIXED_SIDE or FIXED_ORDER and no specific positions are given for the ports."),G9e),Bi),xc),rn(Yd)))),en(n,new qe(We(Qe(Ze(Xe(Ye(Ke(Ve(new Ge,bpe),wne),"Port Border Offset"),"The offset of ports on the node border. With a positive offset the port is moved outside of the node, while with a negative offset the port is moved towards the inside. An offset of 0 means that the port is placed directly on the node border, i.e. if the port side is north, the port's south border touches the nodes's north border; if the port side is east, the port's west border touches the nodes's east border; if the port side is south, the port's north border touches the node's south border; if the port side is west, the port's east border touches the node's west border."),ec),gr),rn(Yd)))),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,V8),_2e),"Port Label Placement"),"Decides on a placement method for port labels; if empty, the node label's position is not modified."),J9e),Hy),fG),rn(fr)))),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,kpe),_2e),"Port Labels Next to Port"),"Use 'portLabels.placement': NEXT_TO_PORT_OF_POSSIBLE."),!1),xr),Qi),rn(fr)))),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,jpe),_2e),"Treat Port Labels as Group"),"If this option is true (default), the labels of a port will be treated as a group when it comes to centering them next to their port. If this option is false, only the first label will be centered next to the port, with the others being placed below. This only applies to labels of eastern and western ports and will have no effect if labels are not placed next to their port."),!0),xr),Qi),rn(fr)))),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,dne),r7),"Number of size categories"),"Defines the number of categories to use for the FIXED_INTEGER_RATIO_BOXES size approximator."),ke(3)),dc),jr),rn(Cn)))),qi(n,dne,bne,Gfn),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,I2e),r7),"Weight of a node containing children for determining the graph size"),"When determining the graph size for the size categorisation, this value determines how many times a node containing children is weighted more than a simple node. For example setting this value to four would result in a graph containing a simple node and a hierarchical node to be counted as having a size of five."),ke(4)),dc),jr),rn(Cn)))),qi(n,I2e,dne,null),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,MN),r7),"Topdown Scale Factor"),"The scaling factor to be applied to the nodes laid out within the node in recursive topdown layout. The difference to 'Scale Factor' is that the node itself is not scaled. This value has to be set on hierarchical nodes."),1),ec),gr),rn(Cn)))),qi(n,MN,np,Ffn),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,bne),r7),"Topdown Size Approximator"),"The size approximator to be used to set sizes of hierarchical nodes during topdown layout. The default value is null, which results in nodes keeping whatever size is defined for them e.g. through parent parallel node or by manually setting the size."),null),Za),QBn),rn(fr)))),qi(n,bne,np,Jfn),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,CN),r7),"Topdown Hierarchical Node Width"),"The fixed size of a hierarchical node when using topdown layout. If this value is set on a parallel node it applies to its children, when set on a hierarchical node it applies to the node itself."),150),ec),gr),Ci(Cn,F(z(Wa,1),Ee,160,0,[fr]))))),qi(n,CN,np,null),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,TN),r7),"Topdown Hierarchical Node Aspect Ratio"),"The fixed aspect ratio of a hierarchical node when using topdown layout. Default is 1/sqrt(2). If this value is set on a parallel node it applies to its children, when set on a hierarchical node it applies to the node itself."),1.414),ec),gr),Ci(Cn,F(z(Wa,1),Ee,160,0,[fr]))))),qi(n,TN,np,null),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,np),r7),"Topdown Node Type"),"The different node types used for topdown layout. If the node type is set to {@link TopdownNodeTypes.PARALLEL_NODE} the algorithm must be set to a {@link TopdownLayoutProvider} such as {@link TopdownPacking}. The {@link nodeSize.fixedGraphSize} option is technically only required for hierarchical nodes."),null),Bi),E8e),rn(fr)))),qi(n,np,X8,null),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,D2e),r7),"Topdown Scale Cap"),"Determines the upper limit for the topdown scale factor. The default value is 1.0 which ensures that nested children never end up appearing larger than their parents in terms of unit sizes such as the font size. If the limit is larger, nodes will fully utilize the available space, but it is counteriniuitive for inner nodes to have a larger scale than outer nodes."),1),ec),gr),rn(Cn)))),qi(n,D2e,np,zfn),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,mpe),BWe),"Activate Inside Self Loops"),"Whether this node allows to route self loops inside of it instead of around it. If set to true, this will make the node a compound node if it isn't already, and will require the layout algorithm to support compound nodes with hierarchical ports."),!1),xr),Qi),rn(fr)))),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,vpe),BWe),"Inside Self Loop"),"Whether a self loop should be routed inside a node instead of around that node."),!1),xr),Qi),rn(xa)))),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,Tpe),"edge"),"Edge Thickness"),"The thickness of an edge. This is a hint on the line width used to draw an edge, possibly requiring more space to be reserved for it."),1),ec),gr),rn(xa)))),en(n,new qe(We(Qe(Ze(an(Xe(Ye(Ke(Ve(new Ge,PWe),"edge"),"Edge Type"),"The type of an edge. This is usually used for UML class diagrams, where associations must be handled differently from generalizations."),S9e),Bi),s8e),rn(xa)))),Oj(n,new P4(Sj(b9(d9(new d0,Rn),"Layered"),'The layer-based method was introduced by Sugiyama, Tagawa and Toda in 1981. It emphasizes the direction of edges by pointing as many edges as possible into the same direction. The nodes are arranged in layers, which are sometimes called "hierarchies", and then reordered such that the number of edge crossings is minimized. Afterwards, concrete coordinates are computed for the nodes and edge bend points.'))),Oj(n,new P4(Sj(b9(d9(new d0,"org.eclipse.elk.orthogonal"),"Orthogonal"),`Orthogonal methods that follow the "topology-shape-metrics" approach by Batini, Nardelli and Tamassia '86. The first phase determines the topology of the drawing by applying a planarization technique, which results in a planar representation of the graph. The orthogonal shape is computed in the second phase, which aims at minimizing the number of edge bends, and is called orthogonalization. The third phase leads to concrete coordinates for nodes and edge bend points by applying a compaction method, thus defining the metrics.`))),Oj(n,new P4(Sj(b9(d9(new d0,$o),"Force"),"Layout algorithms that follow physical analogies by simulating a system of attractive and repulsive forces. The first successful method of this kind was proposed by Eades in 1984."))),Oj(n,new P4(Sj(b9(d9(new d0,"org.eclipse.elk.circle"),"Circle"),"Circular layout algorithms emphasize cycles or biconnected components of a graph by arranging them in circles. 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uoe(this)},s.Wb=function(n){NB(this,n)},s.Ek=function(){u(this.c,77).Ek()},v(Ri,"EcoreEMap",142),m(169,142,tme,Hs),s.Zj=function(){var n,t,i,r,c,o;if(this.d==null){for(o=se(z8e,nme,67,2*this.f+1,0,1),i=this.c.Jc();i.e!=i.i.gc();)t=u(i.Wj(),136),r=t.yi(),c=(r&oi)%o.length,n=o[c],!n&&(n=o[c]=new uoe(this)),n.Ec(t);this.d=o}},v(Jn,"EAnnotationImpl/1",169),m(293,439,{109:1,94:1,93:1,158:1,197:1,57:1,114:1,470:1,52:1,100:1,161:1,293:1,117:1,118:1}),s.Ih=function(n,t,i){var r,c;switch(n){case 0:return!this.Ab&&(this.Ab=new we(Zt,this,0,3)),this.Ab;case 1:return this.zb;case 2:return $n(),(this.Bb&256)!=0;case 3:return $n(),(this.Bb&512)!=0;case 4:return ke(this.s);case 5:return ke(this.t);case 6:return $n(),!!this.Hk();case 7:return $n(),c=this.s,c>=1;case 8:return t?ff(this):this.r;case 9:return this.q}return Pl(this,n-dt(this.fi()),Mn((r=u(Xn(this,16),29),r||this.fi()),n),t,i)},s.Rh=function(n,t,i){var r,c;switch(t){case 0:return!this.Ab&&(this.Ab=new we(Zt,this,0,3)),vc(this.Ab,n,i);case 9:return SV(this,i)}return c=u(Mn((r=u(Xn(this,16),29),r||this.fi()),t),69),c.uk().yk(this,Lo(this),t-dt(this.fi()),n,i)},s.Th=function(n){var t,i;switch(n){case 0:return!!this.Ab&&this.Ab.i!=0;case 1:return this.zb!=null;case 2:return(this.Bb&256)==0;case 3:return(this.Bb&512)==0;case 4:return this.s!=0;case 5:return this.t!=1;case 6:return this.Hk();case 7:return i=this.s,i>=1;case 8:return!!this.r&&!this.q.e&&Mw(this.q).i==0;case 9:return!!this.q&&!(this.r&&!this.q.e&&Mw(this.q).i==0)}return Ll(this,n-dt(this.fi()),Mn((t=u(Xn(this,16),29),t||this.fi()),n))},s.$h=function(n,t){var i,r;switch(n){case 0:!this.Ab&&(this.Ab=new we(Zt,this,0,3)),kt(this.Ab),!this.Ab&&(this.Ab=new we(Zt,this,0,3)),nr(this.Ab,u(t,18));return;case 1:this.ri(Pt(t));return;case 2:Ld(this,Fe(ze(t)));return;case 3:Pd(this,Fe(ze(t)));return;case 4:Nd(this,u(t,15).a);return;case 5:this.Xk(u(t,15).a);return;case 8:cg(this,u(t,143));return;case 9:r=Fa(this,u(t,87),null),r&&r.mj();return}Jl(this,n-dt(this.fi()),Mn((i=u(Xn(this,16),29),i||this.fi()),n),t)},s.fi=function(){return jn(),Van},s.hi=function(n){var t,i;switch(n){case 0:!this.Ab&&(this.Ab=new we(Zt,this,0,3)),kt(this.Ab);return;case 1:this.ri(null);return;case 2:Ld(this,!0);return;case 3:Pd(this,!0);return;case 4:Nd(this,0);return;case 5:this.Xk(1);return;case 8:cg(this,null);return;case 9:i=Fa(this,null,null),i&&i.mj();return}Fl(this,n-dt(this.fi()),Mn((t=u(Xn(this,16),29),t||this.fi()),n))},s.mi=function(){ff(this),this.Bb|=1},s.Fk=function(){return ff(this)},s.Gk=function(){return this.t},s.Hk=function(){var n;return n=this.t,n>1||n==-1},s.Qi=function(){return(this.Bb&512)!=0},s.Wk=function(n,t){return z1e(this,n,t)},s.Xk=function(n){$2(this,n)},s.Ib=function(){return tbe(this)},s.s=0,s.t=1,v(Jn,"ETypedElementImpl",293),m(451,293,{109:1,94:1,93:1,158:1,197:1,57:1,179:1,69:1,114:1,470:1,52:1,100:1,161:1,451:1,293:1,117:1,118:1,682:1}),s.xh=function(n){return EHe(this,n)},s.Ih=function(n,t,i){var r,c;switch(n){case 0:return!this.Ab&&(this.Ab=new we(Zt,this,0,3)),this.Ab;case 1:return this.zb;case 2:return $n(),(this.Bb&256)!=0;case 3:return $n(),(this.Bb&512)!=0;case 4:return ke(this.s);case 5:return ke(this.t);case 6:return $n(),!!this.Hk();case 7:return $n(),c=this.s,c>=1;case 8:return t?ff(this):this.r;case 9:return this.q;case 10:return $n(),(this.Bb&Gf)!=0;case 11:return $n(),(this.Bb&V0)!=0;case 12:return $n(),(this.Bb&cm)!=0;case 13:return this.j;case 14:return A8(this);case 15:return $n(),(this.Bb&as)!=0;case 16:return $n(),(this.Bb&jh)!=0;case 17:return O2(this)}return Pl(this,n-dt(this.fi()),Mn((r=u(Xn(this,16),29),r||this.fi()),n),t,i)},s.Ph=function(n,t,i){var r,c,o;switch(t){case 0:return!this.Ab&&(this.Ab=new we(Zt,this,0,3)),Co(this.Ab,n,i);case 17:return this.Cb&&(i=(c=this.Db>>16,c>=0?EHe(this,i):this.Cb.Qh(this,-1-c,null,i))),hl(this,n,17,i)}return o=u(Mn((r=u(Xn(this,16),29),r||this.fi()),t),69),o.uk().xk(this,Lo(this),t-dt(this.fi()),n,i)},s.Rh=function(n,t,i){var r,c;switch(t){case 0:return!this.Ab&&(this.Ab=new we(Zt,this,0,3)),vc(this.Ab,n,i);case 9:return SV(this,i);case 17:return hl(this,null,17,i)}return c=u(Mn((r=u(Xn(this,16),29),r||this.fi()),t),69),c.uk().yk(this,Lo(this),t-dt(this.fi()),n,i)},s.Th=function(n){var t,i;switch(n){case 0:return!!this.Ab&&this.Ab.i!=0;case 1:return this.zb!=null;case 2:return(this.Bb&256)==0;case 3:return(this.Bb&512)==0;case 4:return this.s!=0;case 5:return this.t!=1;case 6:return this.Hk();case 7:return i=this.s,i>=1;case 8:return!!this.r&&!this.q.e&&Mw(this.q).i==0;case 9:return!!this.q&&!(this.r&&!this.q.e&&Mw(this.q).i==0);case 10:return(this.Bb&Gf)==0;case 11:return(this.Bb&V0)!=0;case 12:return(this.Bb&cm)!=0;case 13:return this.j!=null;case 14:return A8(this)!=null;case 15:return(this.Bb&as)!=0;case 16:return(this.Bb&jh)!=0;case 17:return!!O2(this)}return Ll(this,n-dt(this.fi()),Mn((t=u(Xn(this,16),29),t||this.fi()),n))},s.$h=function(n,t){var i,r;switch(n){case 0:!this.Ab&&(this.Ab=new we(Zt,this,0,3)),kt(this.Ab),!this.Ab&&(this.Ab=new we(Zt,this,0,3)),nr(this.Ab,u(t,18));return;case 1:XV(this,Pt(t));return;case 2:Ld(this,Fe(ze(t)));return;case 3:Pd(this,Fe(ze(t)));return;case 4:Nd(this,u(t,15).a);return;case 5:this.Xk(u(t,15).a);return;case 8:cg(this,u(t,143));return;case 9:r=Fa(this,u(t,87),null),r&&r.mj();return;case 10:l8(this,Fe(ze(t)));return;case 11:h8(this,Fe(ze(t)));return;case 12:a8(this,Fe(ze(t)));return;case 13:Dse(this,Pt(t));return;case 15:f8(this,Fe(ze(t)));return;case 16:d8(this,Fe(ze(t)));return}Jl(this,n-dt(this.fi()),Mn((i=u(Xn(this,16),29),i||this.fi()),n),t)},s.fi=function(){return jn(),Kan},s.hi=function(n){var t,i;switch(n){case 0:!this.Ab&&(this.Ab=new we(Zt,this,0,3)),kt(this.Ab);return;case 1:X(this.Cb,88)&&Y2(Ms(u(this.Cb,88)),4),Mo(this,null);return;case 2:Ld(this,!0);return;case 3:Pd(this,!0);return;case 4:Nd(this,0);return;case 5:this.Xk(1);return;case 8:cg(this,null);return;case 9:i=Fa(this,null,null),i&&i.mj();return;case 10:l8(this,!0);return;case 11:h8(this,!1);return;case 12:a8(this,!1);return;case 13:this.i=null,xB(this,null);return;case 15:f8(this,!1);return;case 16:d8(this,!1);return}Fl(this,n-dt(this.fi()),Mn((t=u(Xn(this,16),29),t||this.fi()),n))},s.mi=function(){$9(Vc((ls(),nc),this)),ff(this),this.Bb|=1},s.nk=function(){return this.f},s.gk=function(){return A8(this)},s.ok=function(){return O2(this)},s.sk=function(){return null},s.Yk=function(){return this.k},s.Jj=function(){return this.n},s.tk=function(){return mz(this)},s.uk=function(){var n,t,i,r,c,o,l,f,h;return this.p||(i=O2(this),(i.i==null&&kh(i),i.i).length,r=this.sk(),r&&dt(O2(r)),c=ff(this),l=c.ik(),n=l?(l.i&1)!=0?l==ts?Qi:l==$t?jr:l==Ym?b7:l==Jr?gr:l==Ap?sp:l==o5?lp:l==ds?jy:KS:l:null,t=A8(this),f=c.gk(),Ljn(this),(this.Bb&jh)!=0&&((o=Wde((ls(),nc),i))&&o!=this||(o=$4(Vc(nc,this))))?this.p=new QCe(this,o):this.Hk()?this.$k()?r?(this.Bb&as)!=0?n?this._k()?this.p=new Ub(47,n,this,r):this.p=new Ub(5,n,this,r):this._k()?this.p=new Wb(46,this,r):this.p=new Wb(4,this,r):n?this._k()?this.p=new Ub(49,n,this,r):this.p=new Ub(7,n,this,r):this._k()?this.p=new Wb(48,this,r):this.p=new Wb(6,this,r):(this.Bb&as)!=0?n?n==yg?this.p=new xd(50,Oan,this):this._k()?this.p=new xd(43,n,this):this.p=new xd(1,n,this):this._k()?this.p=new Md(42,this):this.p=new Md(0,this):n?n==yg?this.p=new xd(41,Oan,this):this._k()?this.p=new xd(45,n,this):this.p=new xd(3,n,this):this._k()?this.p=new Md(44,this):this.p=new Md(2,this):X(c,159)?n==AG?this.p=new Md(40,this):(this.Bb&512)!=0?(this.Bb&as)!=0?n?this.p=new xd(9,n,this):this.p=new Md(8,this):n?this.p=new xd(11,n,this):this.p=new Md(10,this):(this.Bb&as)!=0?n?this.p=new xd(13,n,this):this.p=new Md(12,this):n?this.p=new xd(15,n,this):this.p=new Md(14,this):r?(h=r.t,h>1||h==-1?this._k()?(this.Bb&as)!=0?n?this.p=new Ub(25,n,this,r):this.p=new Wb(24,this,r):n?this.p=new Ub(27,n,this,r):this.p=new Wb(26,this,r):(this.Bb&as)!=0?n?this.p=new Ub(29,n,this,r):this.p=new Wb(28,this,r):n?this.p=new Ub(31,n,this,r):this.p=new Wb(30,this,r):this._k()?(this.Bb&as)!=0?n?this.p=new Ub(33,n,this,r):this.p=new Wb(32,this,r):n?this.p=new Ub(35,n,this,r):this.p=new Wb(34,this,r):(this.Bb&as)!=0?n?this.p=new Ub(37,n,this,r):this.p=new Wb(36,this,r):n?this.p=new Ub(39,n,this,r):this.p=new Wb(38,this,r)):this._k()?(this.Bb&as)!=0?n?this.p=new xd(17,n,this):this.p=new Md(16,this):n?this.p=new xd(19,n,this):this.p=new Md(18,this):(this.Bb&as)!=0?n?this.p=new xd(21,n,this):this.p=new Md(20,this):n?this.p=new xd(23,n,this):this.p=new Md(22,this):this.Zk()?this._k()?this.p=new zNe(u(c,29),this,r):this.p=new bae(u(c,29),this,r):X(c,159)?n==AG?this.p=new Md(40,this):(this.Bb&as)!=0?n?this.p=new $Ie(t,f,this,(MQ(),l==$t?i7e:l==ts?W8e:l==Ap?r7e:l==Ym?t7e:l==Jr?n7e:l==o5?c7e:l==ds?Z8e:l==Wl?e7e:Hce)):this.p=new ZDe(u(c,159),t,f,this):n?this.p=new PIe(t,f,this,(MQ(),l==$t?i7e:l==ts?W8e:l==Ap?r7e:l==Ym?t7e:l==Jr?n7e:l==o5?c7e:l==ds?Z8e:l==Wl?e7e:Hce)):this.p=new WDe(u(c,159),t,f,this):this.$k()?r?(this.Bb&as)!=0?this._k()?this.p=new JNe(u(c,29),this,r):this.p=new Zle(u(c,29),this,r):this._k()?this.p=new FNe(u(c,29),this,r):this.p=new ZK(u(c,29),this,r):(this.Bb&as)!=0?this._k()?this.p=new ROe(u(c,29),this):this.p=new mle(u(c,29),this):this._k()?this.p=new $Oe(u(c,29),this):this.p=new BK(u(c,29),this):this._k()?r?(this.Bb&as)!=0?this.p=new HNe(u(c,29),this,r):this.p=new efe(u(c,29),this,r):(this.Bb&as)!=0?this.p=new BOe(u(c,29),this):this.p=new vle(u(c,29),this):r?(this.Bb&as)!=0?this.p=new GNe(u(c,29),this,r):this.p=new nfe(u(c,29),this,r):(this.Bb&as)!=0?this.p=new zOe(u(c,29),this):this.p=new fR(u(c,29),this)),this.p},s.pk=function(){return(this.Bb&Gf)!=0},s.Zk=function(){return!1},s.$k=function(){return!1},s.qk=function(){return(this.Bb&jh)!=0},s.vk=function(){return AY(this)},s._k=function(){return!1},s.rk=function(){return(this.Bb&as)!=0},s.al=function(n){this.k=n},s.ri=function(n){XV(this,n)},s.Ib=function(){return Jz(this)},s.e=!1,s.n=0,v(Jn,"EStructuralFeatureImpl",451),m(335,451,{109:1,94:1,93:1,38:1,158:1,197:1,57:1,179:1,69:1,114:1,470:1,52:1,100:1,335:1,161:1,451:1,293:1,117:1,118:1,682:1},vX),s.Ih=function(n,t,i){var r,c;switch(n){case 0:return!this.Ab&&(this.Ab=new we(Zt,this,0,3)),this.Ab;case 1:return this.zb;case 2:return $n(),(this.Bb&256)!=0;case 3:return $n(),(this.Bb&512)!=0;case 4:return ke(this.s);case 5:return ke(this.t);case 6:return $n(),!!Y0e(this);case 7:return $n(),c=this.s,c>=1;case 8:return t?ff(this):this.r;case 9:return this.q;case 10:return $n(),(this.Bb&Gf)!=0;case 11:return $n(),(this.Bb&V0)!=0;case 12:return $n(),(this.Bb&cm)!=0;case 13:return this.j;case 14:return A8(this);case 15:return $n(),(this.Bb&as)!=0;case 16:return $n(),(this.Bb&jh)!=0;case 17:return O2(this);case 18:return $n(),(this.Bb&Ru)!=0;case 19:return t?XY(this):n$e(this)}return Pl(this,n-dt((jn(),Xm)),Mn((r=u(Xn(this,16),29),r||Xm),n),t,i)},s.Th=function(n){var t,i;switch(n){case 0:return!!this.Ab&&this.Ab.i!=0;case 1:return this.zb!=null;case 2:return(this.Bb&256)==0;case 3:return(this.Bb&512)==0;case 4:return this.s!=0;case 5:return this.t!=1;case 6:return Y0e(this);case 7:return i=this.s,i>=1;case 8:return!!this.r&&!this.q.e&&Mw(this.q).i==0;case 9:return!!this.q&&!(this.r&&!this.q.e&&Mw(this.q).i==0);case 10:return(this.Bb&Gf)==0;case 11:return(this.Bb&V0)!=0;case 12:return(this.Bb&cm)!=0;case 13:return this.j!=null;case 14:return A8(this)!=null;case 15:return(this.Bb&as)!=0;case 16:return(this.Bb&jh)!=0;case 17:return!!O2(this);case 18:return(this.Bb&Ru)!=0;case 19:return!!n$e(this)}return Ll(this,n-dt((jn(),Xm)),Mn((t=u(Xn(this,16),29),t||Xm),n))},s.$h=function(n,t){var i,r;switch(n){case 0:!this.Ab&&(this.Ab=new we(Zt,this,0,3)),kt(this.Ab),!this.Ab&&(this.Ab=new we(Zt,this,0,3)),nr(this.Ab,u(t,18));return;case 1:XV(this,Pt(t));return;case 2:Ld(this,Fe(ze(t)));return;case 3:Pd(this,Fe(ze(t)));return;case 4:Nd(this,u(t,15).a);return;case 5:xAe(this,u(t,15).a);return;case 8:cg(this,u(t,143));return;case 9:r=Fa(this,u(t,87),null),r&&r.mj();return;case 10:l8(this,Fe(ze(t)));return;case 11:h8(this,Fe(ze(t)));return;case 12:a8(this,Fe(ze(t)));return;case 13:Dse(this,Pt(t));return;case 15:f8(this,Fe(ze(t)));return;case 16:d8(this,Fe(ze(t)));return;case 18:mQ(this,Fe(ze(t)));return}Jl(this,n-dt((jn(),Xm)),Mn((i=u(Xn(this,16),29),i||Xm),n),t)},s.fi=function(){return jn(),Xm},s.hi=function(n){var t,i;switch(n){case 0:!this.Ab&&(this.Ab=new we(Zt,this,0,3)),kt(this.Ab);return;case 1:X(this.Cb,88)&&Y2(Ms(u(this.Cb,88)),4),Mo(this,null);return;case 2:Ld(this,!0);return;case 3:Pd(this,!0);return;case 4:Nd(this,0);return;case 5:this.b=0,$2(this,1);return;case 8:cg(this,null);return;case 9:i=Fa(this,null,null),i&&i.mj();return;case 10:l8(this,!0);return;case 11:h8(this,!1);return;case 12:a8(this,!1);return;case 13:this.i=null,xB(this,null);return;case 15:f8(this,!1);return;case 16:d8(this,!1);return;case 18:mQ(this,!1);return}Fl(this,n-dt((jn(),Xm)),Mn((t=u(Xn(this,16),29),t||Xm),n))},s.mi=function(){XY(this),$9(Vc((ls(),nc),this)),ff(this),this.Bb|=1},s.Hk=function(){return Y0e(this)},s.Wk=function(n,t){return this.b=0,this.a=null,z1e(this,n,t)},s.Xk=function(n){xAe(this,n)},s.Ib=function(){var n;return(this.Db&64)!=0?Jz(this):(n=new cf(Jz(this)),n.a+=" (iD: ",yd(n,(this.Bb&Ru)!=0),n.a+=")",n.a)},s.b=0,v(Jn,"EAttributeImpl",335),m(360,439,{109:1,94:1,93:1,143:1,158:1,197:1,57:1,114:1,52:1,100:1,360:1,161:1,117:1,118:1,681:1}),s.bl=function(n){return n.Ah()==this},s.xh=function(n){return WQ(this,n)},s.yh=function(n,t){this.w=null,this.Db=t<<16|this.Db&255,this.Cb=n},s.Ih=function(n,t,i){var r;switch(n){case 0:return!this.Ab&&(this.Ab=new we(Zt,this,0,3)),this.Ab;case 1:return this.zb;case 2:return this.D!=null?this.D:this.B;case 3:return Gw(this);case 4:return 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r;switch(t){case 0:return!this.c&&(this.c=new tr(this,0)),tN(this.c,n,i);case 1:return(!this.c&&(this.c=new tr(this,0)),u(u(fo(this.c,(Si(),Pg)),163),72)).Vk(n,i);case 2:return!this.b&&(this.b=new tr(this,2)),tN(this.b,n,i)}return r=u(Mn((this.j&2)==0?this.fi():(!this.k&&(this.k=new nl),this.k).Lk(),t),69),r.uk().yk(this,khe(this),t-dt(this.fi()),n,i)},s.Th=function(n){switch(n){case 0:return!!this.c&&this.c.i!=0;case 1:return!(!this.c&&(this.c=new tr(this,0)),u(fo(this.c,(Si(),Pg)),163)).dc();case 2:return!!this.b&&this.b.i!=0}return Ll(this,n-dt(this.fi()),Mn((this.j&2)==0?this.fi():(!this.k&&(this.k=new nl),this.k).Lk(),n))},s.$h=function(n,t){switch(n){case 0:!this.c&&(this.c=new tr(this,0)),BT(this.c,t);return;case 1:(!this.c&&(this.c=new tr(this,0)),u(u(fo(this.c,(Si(),Pg)),163),219)).Wb(t);return;case 2:!this.b&&(this.b=new tr(this,2)),BT(this.b,t);return}Jl(this,n-dt(this.fi()),Mn((this.j&2)==0?this.fi():(!this.k&&(this.k=new nl),this.k).Lk(),n),t)},s.fi=function(){return 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3:return!this.c&&(this.c=new tr(this,0)),Pt(cN(this.c,(Si(),fA),!0));case 4:return Jle(this.a,(!this.c&&(this.c=new tr(this,0)),Pt(cN(this.c,(Si(),fA),!0))));case 5:return this.a}return Pl(this,n-dt((Si(),c5)),Mn((this.j&2)==0?c5:(!this.k&&(this.k=new nl),this.k).Lk(),n),t,i)},s.Th=function(n){switch(n){case 0:return!!this.c&&this.c.i!=0;case 1:return!(!this.c&&(this.c=new tr(this,0)),u(fo(this.c,(Si(),Pg)),163)).dc();case 2:return!!this.b&&this.b.i!=0;case 3:return!this.c&&(this.c=new tr(this,0)),Pt(cN(this.c,(Si(),fA),!0))!=null;case 4:return Jle(this.a,(!this.c&&(this.c=new tr(this,0)),Pt(cN(this.c,(Si(),fA),!0))))!=null;case 5:return!!this.a}return Ll(this,n-dt((Si(),c5)),Mn((this.j&2)==0?c5:(!this.k&&(this.k=new nl),this.k).Lk(),n))},s.$h=function(n,t){switch(n){case 0:!this.c&&(this.c=new tr(this,0)),BT(this.c,t);return;case 1:(!this.c&&(this.c=new tr(this,0)),u(u(fo(this.c,(Si(),Pg)),163),219)).Wb(t);return;case 2:!this.b&&(this.b=new tr(this,2)),BT(this.b,t);return;case 3:Tae(this,Pt(t));return;case 4:Tae(this,Fle(this.a,t));return;case 5:I(this,u(t,159));return}Jl(this,n-dt((Si(),c5)),Mn((this.j&2)==0?c5:(!this.k&&(this.k=new nl),this.k).Lk(),n),t)},s.fi=function(){return Si(),c5},s.hi=function(n){switch(n){case 0:!this.c&&(this.c=new tr(this,0)),kt(this.c);return;case 1:(!this.c&&(this.c=new tr(this,0)),u(fo(this.c,(Si(),Pg)),163)).$b();return;case 2:!this.b&&(this.b=new tr(this,2)),kt(this.b);return;case 3:!this.c&&(this.c=new tr(this,0)),Vz(this.c,(Si(),fA),null);return;case 4:Tae(this,Fle(this.a,null));return;case 5:this.a=null;return}Fl(this,n-dt((Si(),c5)),Mn((this.j&2)==0?c5:(!this.k&&(this.k=new nl),this.k).Lk(),n))},v(kr,"SimpleAnyTypeImpl",672),m(673,501,{109:1,94:1,93:1,57:1,52:1,100:1,2083:1,673:1},_xe),s.Ih=function(n,t,i){switch(n){case 0:return i?(!this.a&&(this.a=new tr(this,0)),this.a):(!this.a&&(this.a=new tr(this,0)),this.a.b);case 1:return i?(!this.b&&(this.b=new os((jn(),Ac),Du,this,1)),this.b):(!this.b&&(this.b=new os((jn(),Ac),Du,this,1)),nO(this.b));case 2:return i?(!this.c&&(this.c=new os((jn(),Ac),Du,this,2)),this.c):(!this.c&&(this.c=new os((jn(),Ac),Du,this,2)),nO(this.c));case 3:return!this.a&&(this.a=new tr(this,0)),fo(this.a,(Si(),uD));case 4:return!this.a&&(this.a=new tr(this,0)),fo(this.a,(Si(),oD));case 5:return!this.a&&(this.a=new tr(this,0)),fo(this.a,(Si(),aA));case 6:return!this.a&&(this.a=new tr(this,0)),fo(this.a,(Si(),hA))}return Pl(this,n-dt((Si(),xp)),Mn((this.j&2)==0?xp:(!this.k&&(this.k=new nl),this.k).Lk(),n),t,i)},s.Rh=function(n,t,i){var r;switch(t){case 0:return!this.a&&(this.a=new tr(this,0)),tN(this.a,n,i);case 1:return!this.b&&(this.b=new os((jn(),Ac),Du,this,1)),K$(this.b,n,i);case 2:return!this.c&&(this.c=new os((jn(),Ac),Du,this,2)),K$(this.c,n,i);case 5:return!this.a&&(this.a=new tr(this,0)),QOe(fo(this.a,(Si(),aA)),n,i)}return r=u(Mn((this.j&2)==0?(Si(),xp):(!this.k&&(this.k=new nl),this.k).Lk(),t),69),r.uk().yk(this,khe(this),t-dt((Si(),xp)),n,i)},s.Th=function(n){switch(n){case 0:return!!this.a&&this.a.i!=0;case 1:return!!this.b&&this.b.f!=0;case 2:return!!this.c&&this.c.f!=0;case 3:return!this.a&&(this.a=new tr(this,0)),!T$(fo(this.a,(Si(),uD)));case 4:return!this.a&&(this.a=new tr(this,0)),!T$(fo(this.a,(Si(),oD)));case 5:return!this.a&&(this.a=new tr(this,0)),!T$(fo(this.a,(Si(),aA)));case 6:return!this.a&&(this.a=new tr(this,0)),!T$(fo(this.a,(Si(),hA)))}return Ll(this,n-dt((Si(),xp)),Mn((this.j&2)==0?xp:(!this.k&&(this.k=new nl),this.k).Lk(),n))},s.$h=function(n,t){switch(n){case 0:!this.a&&(this.a=new tr(this,0)),BT(this.a,t);return;case 1:!this.b&&(this.b=new os((jn(),Ac),Du,this,1)),NB(this.b,t);return;case 2:!this.c&&(this.c=new os((jn(),Ac),Du,this,2)),NB(this.c,t);return;case 3:!this.a&&(this.a=new tr(this,0)),u4(fo(this.a,(Si(),uD))),!this.a&&(this.a=new tr(this,0)),Yj(fo(this.a,uD),u(t,18));return;case 4:!this.a&&(this.a=new tr(this,0)),u4(fo(this.a,(Si(),oD))),!this.a&&(this.a=new tr(this,0)),Yj(fo(this.a,oD),u(t,18));return;case 5:!this.a&&(this.a=new tr(this,0)),u4(fo(this.a,(Si(),aA))),!this.a&&(this.a=new tr(this,0)),Yj(fo(this.a,aA),u(t,18));return;case 6:!this.a&&(this.a=new tr(this,0)),u4(fo(this.a,(Si(),hA))),!this.a&&(this.a=new tr(this,0)),Yj(fo(this.a,hA),u(t,18));return}Jl(this,n-dt((Si(),xp)),Mn((this.j&2)==0?xp:(!this.k&&(this.k=new nl),this.k).Lk(),n),t)},s.fi=function(){return Si(),xp},s.hi=function(n){switch(n){case 0:!this.a&&(this.a=new tr(this,0)),kt(this.a);return;case 1:!this.b&&(this.b=new os((jn(),Ac),Du,this,1)),this.b.c.$b();return;case 2:!this.c&&(this.c=new os((jn(),Ac),Du,this,2)),this.c.c.$b();return;case 3:!this.a&&(this.a=new tr(this,0)),u4(fo(this.a,(Si(),uD)));return;case 4:!this.a&&(this.a=new tr(this,0)),u4(fo(this.a,(Si(),oD)));return;case 5:!this.a&&(this.a=new tr(this,0)),u4(fo(this.a,(Si(),aA)));return;case 6:!this.a&&(this.a=new tr(this,0)),u4(fo(this.a,(Si(),hA)));return}Fl(this,n-dt((Si(),xp)),Mn((this.j&2)==0?xp:(!this.k&&(this.k=new nl),this.k).Lk(),n))},s.Ib=function(){var n;return(this.j&4)!=0?Ff(this):(n=new cf(Ff(this)),n.a+=" (mixed: ",Uj(n,this.a),n.a+=")",n.a)},v(kr,"XMLTypeDocumentRootImpl",673),m(1990,710,{109:1,94:1,93:1,469:1,158:1,57:1,114:1,52:1,100:1,161:1,117:1,118:1,2084:1},lC),s.oi=function(n,t){switch(n.fk()){case 7:case 8:case 9:case 10:case 16:case 22:case 23:case 24:case 25:case 26:case 32:case 33:case 34:case 36:case 37:case 44:case 45:case 50:case 51:case 53:case 55:case 56:case 57:case 58:case 60:case 61:case 4:return t==null?null:fu(t);case 19:case 28:case 29:case 35:case 38:case 39:case 41:case 46:case 52:case 54:case 5:return Pt(t);case 6:return Fpn(u(t,195));case 12:case 47:case 49:case 11:return fVe(this,n,t);case 13:return t==null?null:zLn(u(t,247));case 15:case 14:return t==null?null:L3n(ne(re(t)));case 17:return eGe((Si(),t));case 18:return eGe(t);case 21:case 20:return t==null?null:P3n(u(t,164).a);case 27:return zpn(u(t,195));case 30:return hHe((Si(),u(t,16)));case 31:return hHe(u(t,16));case 40:return Bpn((Si(),t));case 42:return nGe((Si(),t));case 43:return nGe(t);case 59:case 48:return Rpn((Si(),t));default:throw R(new qn(u7+n.ve()+up))}},s.pi=function(n){var t,i,r,c,o;switch(n.G==-1&&(n.G=(i=ol(n),i?$d(i.si(),n):-1)),n.G){case 0:return t=new koe,t;case 1:return r=new pU,r;case 2:return c=new Dxe,c;case 3:return o=new _xe,o;default:throw R(new qn(vne+n.zb+up))}},s.qi=function(n,t){var i,r,c,o,l,f,h,b,p,y,S,A,O,D,B,q;switch(n.fk()){case 5:case 52:case 4:return t;case 6:return rSn(t);case 8:case 7:return t==null?null:JAn(t);case 9:return t==null?null:fO(al((r=bo(t,!0),r.length>0&&(Qn(0,r.length),r.charCodeAt(0)==43)?(Qn(1,r.length+1),r.substr(1)):r),-128,127)<<24>>24);case 10:return t==null?null:fO(al((c=bo(t,!0),c.length>0&&(Qn(0,c.length),c.charCodeAt(0)==43)?(Qn(1,c.length+1),c.substr(1)):c),-128,127)<<24>>24);case 11:return 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span,.provenance-edge span,.provenance-edge small{color:var(--muted);font-size:11px;line-height:1.25}.provenance-block{margin-top:10px}.empty-state.compact{padding:7px 8px;font-size:11px}.live-session{border-left:1px solid rgba(183,166,150,.36);padding-left:10px}.live-pill{display:inline-flex;align-items:center;height:28px;padding:0 9px;border:1px solid rgba(191,106,84,.38);border-radius:999px;color:var(--clay);background:#bf6a5414;font-size:11px;font-weight:800;text-transform:uppercase}.live-pill.connected{border-color:#1f7a5357;color:var(--accent);background:#1f7a5317}.metric-button:disabled{cursor:not-allowed;opacity:.42}.model-browser{display:grid;gap:7px}.model-browser-control{display:grid;gap:4px}.model-browser-control span,.parameter-row label{color:var(--muted);font-size:11px;font-weight:700}.model-browser-control select,.model-browser-control input,.parameter-row input,.parameter-row select{min-width:0;border:1px solid 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h4{margin:0;color:var(--muted);font-size:11px;font-family:ui-monospace,SFMono-Regular,Menlo,monospace;font-weight:700}.initialization-editor{display:grid;gap:12px}.initialization-editor-group{display:grid;gap:8px}.initialization-editor-group h3{margin:0}.initialization-editor-row{display:grid;grid-template-columns:minmax(0,.85fr) minmax(0,1fr) minmax(82px,.72fr) auto;gap:7px;align-items:center;padding:9px;border:1px solid rgba(191,106,84,.26);border-left:4px solid var(--clay);border-radius:8px;background:#fffaf2c7}.initialization-editor-row.provided{border-color:#1f7a533d;border-left-color:var(--accent)}.initialization-editor-row label{overflow-wrap:anywhere;font-weight:700}.initialization-editor-row input,.initialization-editor-row select{min-width:0;height:30px;border:1px solid rgba(183,166,150,.44);border-radius:8px;background:#ffffffc7;color:var(--ink);font:inherit}.initialization-editor-row input{padding:0 8px}.initialization-editor-row small{grid-column:1 / -1;color:var(--muted);font-size:10px;text-transform:uppercase;letter-spacing:.05em}.parameter-row{display:grid;grid-template-columns:minmax(0,.75fr) minmax(0,1fr) minmax(78px,.8fr);gap:6px;align-items:center}.parameter-row input,.parameter-row select{height:28px;padding:0 7px;font-size:12px}.rate-editor{display:grid;gap:6px;padding:7px;border:1px solid rgba(183,166,150,.28);border-radius:8px;background:#fcf9f4b8}.add-model-footer{position:sticky;bottom:-18px;display:flex;justify-content:flex-end;margin:2px -9px 0;padding:10px 9px;border-top:1px solid rgba(183,166,150,.34);border-radius:0 0 10px 10px;background:#fffaf2f0;-webkit-backdrop-filter:blur(8px);backdrop-filter:blur(8px)}.rate-summary{color:var(--muted);font-size:11px;line-height:1.35}.rate-clock-row{display:grid;grid-template-columns:1fr 1fr;gap:6px}.rate-clock-row label{display:grid;gap:4px;color:var(--muted);font-size:11px;font-weight:700}.rate-clock-row input{min-width:0;height:28px;border:1px solid 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10px}.topbar:before{display:none}.brand-block{min-width:128px}.search-box{flex-basis:100%;max-width:none;min-width:0}.metrics{margin-left:0}.relationship-legend,.scale-controls,.floating-panel{top:132px;left:10px;right:10px;width:auto}.scale-controls{top:326px}.react-flow__minimap{display:none}}.mapping-dialog-overlay{position:fixed;inset:0;z-index:1000;background:#31272161;display:flex;align-items:center;justify-content:center}.mapping-dialog{background:var(--paper);border:1px solid var(--line-strong);border-radius:10px;box-shadow:0 8px 32px var(--shadow);width:360px;max-width:calc(100vw - 32px);display:flex;flex-direction:column;gap:0;overflow:hidden}.mapping-dialog-header{display:flex;align-items:center;justify-content:space-between;padding:14px 16px 10px;border-bottom:1px solid var(--line)}.mapping-dialog-header .eyebrow{font-size:11px;font-weight:600;text-transform:uppercase;letter-spacing:.07em;color:var(--muted)}.mapping-dialog-body{padding:14px 16px;display:flex;flex-direction:column;gap:14px}.mapping-port-summary{display:flex;align-items:center;gap:8px;background:var(--paper-strong);border:1px solid var(--line);border-radius:6px;padding:10px 12px}.mapping-port{display:flex;flex-direction:column;gap:1px;flex:1;min-width:0}.mapping-port small{font-size:10px;text-transform:uppercase;letter-spacing:.06em;color:var(--muted)}.mapping-port strong{font-size:12px;font-weight:700;color:var(--accent);overflow:hidden;text-overflow:ellipsis;white-space:nowrap}.mapping-port span{font-size:11px;color:var(--ink);overflow:hidden;text-overflow:ellipsis;white-space:nowrap}.mapping-port.target strong{color:var(--clay)}.mapping-arrow{font-size:18px;color:var(--muted);flex-shrink:0}.mapping-mode-section{display:flex;flex-direction:column;gap:6px}.mapping-mode-label{font-size:11px;font-weight:600;text-transform:uppercase;letter-spacing:.06em;color:var(--muted);margin-bottom:2px}.mapping-radio{display:flex;align-items:center;gap:8px;font-size:13px;cursor:pointer;padding:4px 0}.mapping-radio input[type=radio]{accent-color:var(--accent);width:14px;height:14px;flex-shrink:0}.mapping-scale-picker{display:flex;flex-direction:column;gap:4px}.mapping-checkbox{display:flex;align-items:center;gap:8px;font-size:13px;cursor:pointer;padding:2px 0}.mapping-checkbox input[type=checkbox]{accent-color:var(--accent);width:14px;height:14px;flex-shrink:0}.mapping-dialog-footer{display:flex;justify-content:flex-end;gap:8px;padding:10px 16px 14px;border-top:1px solid var(--line)}.accent-button{background:var(--accent);color:#fff;border-color:transparent}.accent-button:hover:not(:disabled){background:var(--sage-dark);border-color:transparent}
diff --git a/frontend/dist/index.html b/frontend/dist/index.html
index 559aa6705..cd68b8a4a 100644
--- a/frontend/dist/index.html
+++ b/frontend/dist/index.html
@@ -4,8 +4,8 @@
     
     
     PlantSimEngine Dependency Graph
-    
-    
+    
+    
   
   
     

diff --git a/frontend/e2e/graph-editor.spec.ts b/frontend/e2e/graph-editor.spec.ts
index 5077a896c..5991ee8ec 100644
--- a/frontend/e2e/graph-editor.spec.ts
+++ b/frontend/e2e/graph-editor.spec.ts
@@ -1,8 +1,9 @@
 import { expect, test, type APIRequestContext, type Locator, type Page } from "@playwright/test";
-import type { GraphEditorState, GraphNodeData } from "../src/types";
+import { copyFile } from "node:fs/promises";
+import type { ApplicationGraphNode, EditorState } from "../src/types";
 import { startGraphEditorServer, type GraphEditorServer } from "./graphEditorServer";
 
-test.describe.serial("PlantSimEngine graph editor", () => {
+test.describe.serial("PlantSimEngine model graph editor", () => {
   let server: GraphEditorServer;
 
   test.beforeAll(async () => {
@@ -13,99 +14,230 @@ test.describe.serial("PlantSimEngine graph editor", () => {
     await server?.stop();
   });
 
-  test("starts a real Julia editor session", async ({ page, request }) => {
+  test("starts empty and adds an object", async ({ page, request }) => {
     await page.goto(server.url);
+    await expect(page.getByText("Model Graph")).toBeVisible();
 
-    await expect(page.getByText("Dependency Graph")).toBeVisible();
-
-    const state = await getState(request, server.url);
+    let state = await getState(request, server.url);
     expect(state.ok).toBe(true);
-    expect(state.graph.cyclic).toBe(false);
-    expect(state.graph.nodes.some((node) => node.modelType.includes("ToyLAIModel"))).toBe(true);
-    expect(state.graph.nodes.some((node) => node.modelType.includes("Beer"))).toBe(true);
+    expect(state.graph.metadata.objectCount).toBe(0);
+    expect(state.graph.metadata.applicationCount).toBe(0);
+
+    await page.getByTestId("add-object").click();
+    await page.getByTestId("object-id").fill("leaf");
+    await page.locator(".object-form label", { hasText: "Scale" }).getByRole("textbox").fill("Leaf");
+    await page.locator(".object-form label", { hasText: "Kind" }).getByRole("textbox").fill("organ");
+    await page.locator(".object-form label", { hasText: "Name" }).getByRole("textbox").fill("leaf");
+    await page.getByTestId("object-submit").click();
+
+    state = await waitForState(request, server.url, (value) => value.graph.metadata.objectCount === 1);
+    expect(state.graph.objects[0].scale).toBe("Leaf");
+  });
+
+  test("adds and updates an application", async ({ page, request }) => {
+    await page.goto(server.url);
+    await openAddApplication(page, "Beer");
+    await page.getByTestId("application-name").fill("light");
+    await page.getByTestId("application-param-k").fill("0.5");
+    await page.getByTestId("application-target-preview").click();
+    await expect(page.getByTestId("application-target-preview-result")).toContainText("1 target object");
+    await page.getByTestId("application-submit").click();
+
+    let state = await waitForState(request, server.url, (value) => value.graph.metadata.applicationCount === 1);
+    let light = findApplication(state, "light");
+    expect(light.modelName).toContain("Beer");
+
+    await page.getByTestId("application-node-light").click();
+    await page.getByRole("button", { name: "Edit application" }).click();
+    await page.getByTestId("application-param-k").fill("0.8");
+    await page.getByTestId("application-cadence-mode").selectOption("period");
+    await page.getByTestId("application-cadence-value").fill("2");
+    await page.getByTestId("application-cadence-unit").selectOption("Hour");
+    await page.getByTestId("application-submit").click();
+
+    state = await waitForState(request, server.url, (value) => findApplication(value, "light").modelParameters.k?.value === 0.8);
+    light = findApplication(state, "light");
+    expect(light.targetIds).toEqual(["leaf"]);
+    expect(light.cadence).toMatchObject({ mode: "period", value: 2, unit: "Hour" });
   });
 
-  test("updates, adds, maps, removes, creates a cycle, and breaks it", async ({ page, request }) => {
+  test("static viewer opens the inspector without an editor connection", async ({ page }) => {
+    const url = new URL(server.url);
+    url.pathname = "/static";
+    await page.goto(url.toString());
+    await expect(page.getByTestId("application-node-light")).toBeVisible();
+    await page.getByTestId("application-node-light").click();
+    await expect(page.locator(".model-inspector")).toContainText("light");
+    await expect(page.getByText("Edit application")).toHaveCount(0);
+  });
+
+  test("creates and breaks a cycle directly in the graph", async ({ page, request }) => {
     await page.goto(server.url);
+    await page.getByTestId("port-input-LAI").getByRole("button").click();
+    await page.locator(".candidate-card", { hasText: "ReebE2E" }).click();
+    await expect(page.getByTestId("application-form")).toBeVisible();
+    await page.getByTestId("application-name").fill("reeb");
+    await page.getByTestId("application-submit").click();
+
+    let state = await waitForState(request, server.url, (value) => value.graph.metadata.cyclic === true);
+    expect(state.graph.edges.filter((edge) => edge.cycle && edge.projection === "applications")).toHaveLength(2);
+    await expect(page.getByTestId("cycle-callout")).toBeVisible();
 
-    const beer = await findNode(request, server.url, (node) => node.modelType.includes("Beer"));
-    await openInspectorPanel(page);
-    await page.getByTestId(`model-node-${beer.scale}-${beer.process}`).click();
-    await expect(page.getByTestId("existing-model-editor")).toBeVisible();
-    await page.getByTestId("edit-param-k").fill("0.8");
-    await page.getByTestId("update-model-submit").click();
-    await waitForState(request, server.url, (state) => {
-      const updated = state.graph.nodes.find((node) => node.process === beer.process && node.scale === beer.scale);
-      return updated?.modelParameters?.k?.value === "0.8";
-    });
-
-    await openAddModelPanel(page);
-    await page.getByTestId("add-model-scale").selectOption("Default");
-    await selectOptionContaining(page.getByTestId("add-model-type"), "ToyDegreeDaysCumulModel");
-    await page.getByTestId("add-model-submit").click();
-    const degreeDays = await waitForNode(request, server.url, (node) => node.modelType.includes("ToyDegreeDaysCumulModel"));
-
-    await openInspectorPanel(page);
-    await page.getByTestId(`model-node-${degreeDays.scale}-${degreeDays.process}`).click();
-    await page.getByTestId("remove-model-submit").click();
-    await waitForState(request, server.url, (state) =>
-      !state.graph.nodes.some((node) => node.modelType.includes("ToyDegreeDaysCumulModel"))
-    );
-
-    await openAddModelPanel(page);
-    await page.getByTestId("add-model-scale").selectOption("Default");
-    await selectOptionContaining(page.getByTestId("add-model-type"), "ToyDegreeDaysCumulModel");
-    await page.getByTestId("add-model-submit").click();
-    const mappedDegreeDays = await waitForNode(request, server.url, (node) => node.modelType.includes("ToyDegreeDaysCumulModel"));
-
-    const lai = await findNode(request, server.url, (node) => node.modelType.includes("ToyLAIModel"));
-    await openInspectorPanel(page);
-    await page.getByTestId(`port-input-${lai.scale}-${lai.process}-TT_cu`).click();
-    await expect(page.getByTestId("mapping-source-output")).toBeVisible();
-    await selectOptionContaining(page.getByTestId("mapping-source-output"), `${mappedDegreeDays.scale}.${mappedDegreeDays.process}.TT_cu`);
-    await page.getByTestId("mapping-apply").click();
-    await waitForState(request, server.url, (state) => state.ok && !state.graph.cyclic);
-
-    await openAddModelPanel(page);
-    await page.getByTestId("add-model-scale").selectOption("Default");
-    await selectOptionContaining(page.getByTestId("add-model-type"), "ReebE2E");
-    await page.getByTestId("add-param-k").fill("0.6");
-    await page.getByTestId("add-model-submit").click();
-
-    await waitForState(request, server.url, (state) => state.graph.cyclic === true);
-    await expect(page.getByTestId("cycle-break-prompt")).toBeVisible();
-    await expect(page.locator(".react-flow__edge.cycle_edge")).toHaveCount(2);
-
-    await page.getByTestId("cycle-break-choose").click();
-    await expect(page.locator(".port-cycle-break-button")).not.toHaveCount(0);
-    await page.locator(".port-cycle-break-button").first().click();
-
-    await waitForState(request, server.url, (state) =>
-      state.graph.cyclic === false && state.mappingCode.includes("PreviousTimeStep(:")
-    );
-    await expect(page.getByTestId("cycle-break-prompt")).toHaveCount(0);
-
-    await page.getByTestId("toolbar-mapping-code").click();
-    await expect(page.getByTestId("mapping-code")).toHaveValue(/PreviousTimeStep\(:/);
+    await page.getByTestId("choose-cycle-break").click();
+    const scissors = page.locator("[data-testid^='cycle-break-']").first();
+    await expect(scissors).toBeVisible();
+    await scissors.click();
+    await expect(page.getByTestId("cycle-break-dialog")).toBeVisible();
+    const initialization = page.getByTestId("cycle-break-dialog").getByRole("textbox");
+    if (await initialization.count()) await initialization.fill("0.0");
+    await page.getByTestId("confirm-cycle-break").click();
+
+    state = await waitForState(request, server.url, (value) => value.graph.metadata.cyclic === false);
+    expect(state.graph.edges.some((edge) => edge.kind === "previous_timestep")).toBe(true);
+    expect(state.modelCode).toContain("PreviousTimeStep");
+  });
+
+  test("connects another consumer and supports undo, redo, remove, and save", async ({ page, request }, testInfo) => {
+    await page.goto(server.url);
+    await page.getByTestId("configure-environment").click();
+    await page.getByTestId("scene-environment").selectOption("environment:weather");
+    await page.getByTestId("environment-submit").click();
+    await waitForState(request, server.url, (value) => value.graph.metadata.sceneEnvironmentId === "environment:weather");
+    await openAddApplication(page, "E2EConsumer");
+    await page.getByTestId("application-name").fill("consumer");
+    await page.getByTestId("application-submit").click();
+    await waitForState(request, server.url, (value) => value.graph.applications.some((application) => application.applicationId === "consumer"));
+
+    await page.getByTestId("application-node-light").click();
+    await page.getByTestId("configure-application").click();
+    await page.getByTestId("call-name").fill("consumer_call");
+    await page.getByTestId("call-target").selectOption("consumer");
+    await page.getByTestId("add-call-binding").click();
+    await waitForState(request, server.url, (value) => value.graph.metadata.callCount === 1);
+    await page.getByTestId("environment-backend").selectOption("scene");
+    await page.getByTestId("environment-provider").fill("model");
+    await page.getByTestId("apply-environment").click();
+    let state = await waitForState(request, server.url, (value) => findApplication(value, "light").environment?.provider === "model");
+    expect(state.graph.edges.some((edge) => edge.kind === "manual_call" && edge.call === "consumer_call")).toBe(true);
+    await page.getByRole("button", { name: "Done" }).click();
+
+    await page.getByTestId("port-output-aPPFD").first().getByRole("button").click();
+    await page.locator(".candidate-card.existing", { hasText: "consumer" }).click();
+    await expect(page.getByTestId("binding-form")).toBeVisible();
+    await page.getByTestId("binding-preview-button").click();
+    await expect(page.getByTestId("binding-preview")).toContainText("resolved binding");
+    await page.getByTestId("binding-submit").click();
+    state = await waitForState(request, server.url, (value) => value.graph.edges.some((edge) => edge.targetApplicationId === "consumer" && edge.targetVariable === "aPPFD"));
+    expect(state.graph.metadata.applicationCount).toBe(3);
+
+    await page.getByTestId("application-node-light").click();
+    await page.getByTestId("configure-application").click();
+    await page.getByTitle("Remove consumer_call call").click();
+    await waitForState(request, server.url, (value) => value.graph.metadata.callCount === 0);
+    await page.getByRole("button", { name: "Done" }).click();
+
+    await page.getByTestId("application-node-consumer").click();
+    await page.getByRole("button", { name: "Remove application" }).click();
+    await waitForState(request, server.url, (value) => !value.graph.applications.some((application) => application.applicationId === "consumer"));
+    await page.getByRole("button", { name: "Undo" }).click();
+    await waitForState(request, server.url, (value) => value.graph.applications.some((application) => application.applicationId === "consumer"));
+    await page.getByRole("button", { name: "Redo" }).click();
+    await waitForState(request, server.url, (value) => !value.graph.applications.some((application) => application.applicationId === "consumer"));
+
+    const savePath = testInfo.outputPath("model.jl");
+    await page.getByTestId("save-model").click();
+    await page.getByPlaceholder("/absolute/path/to/model.jl").fill(savePath);
+    await page.locator(".model-file-dialog").getByRole("button", { name: "Save", exact: true }).click();
+    state = await waitForState(request, server.url, (value) => value.savePath === savePath);
+    expect(state.recentPaths).toContain(savePath);
+  });
+
+  test("mounts one template twice, configures an override and environment, then reopens with undo and redo", async ({ page, request }, testInfo) => {
+    await page.goto(server.url);
+    await addObject(page, "plant_a", "Plant", "plant", "plant_a");
+    await addObject(page, "plant_b", "Plant", "plant", "plant_b");
+    await waitForState(request, server.url, (value) => value.graph.objects.some((object) => object.objectId === "plant_b"));
+
+    for (const plant of ["plant_a", "plant_b"]) {
+      await page.getByTestId("add-instance").click();
+      await page.getByTestId("instance-template").selectOption("catalog:plant");
+      await page.getByTestId("instance-name").fill(plant);
+      await page.getByTestId("instance-root").selectOption(plant);
+      await page.getByTestId("instance-preview-button").click();
+      await expect(page.getByTestId("instance-preview")).toContainText("1 claimed object");
+      await page.getByTestId("instance-submit").click();
+      await waitForState(request, server.url, (value) => value.graph.instances.some((instance) => instance.name === plant));
+    }
+
+    let state = await getState(request, server.url);
+    expect(findApplication(state, "plant_a__template_source").targetIds).toEqual(["plant_a"]);
+    expect(findApplication(state, "plant_b__template_source").targetIds).toEqual(["plant_b"]);
+
+    await page.getByTestId("application-node-plant_b__template_source").click();
+    await page.getByRole("button", { name: "Create override" }).click();
+    await page.getByTestId("application-param-coefficient").fill("2.0");
+    await page.getByRole("button", { name: "Apply override" }).click();
+    state = await waitForState(request, server.url, (value) => findApplication(value, "plant_b__template_source").modelParameters.coefficient?.value === 2);
+    expect(findApplication(state, "plant_a__template_source").modelParameters.coefficient?.value).toBe(1);
+
+    await page.getByTestId("configure-environment").click();
+    await page.getByTestId("scene-environment").selectOption("environment:weather");
+    await page.getByTestId("environment-submit").click();
+    await waitForState(request, server.url, (value) => value.graph.metadata.sceneEnvironmentId === "environment:weather");
+
+    await page.getByTestId("application-node-plant_a__template_source").click();
+    await page.getByTestId("configure-application").click();
+    await page.getByTestId("environment-backend").selectOption("environment:canopy");
+    await page.getByTestId("environment-provider").fill("canopy_cells");
+    await page.getByTestId("environment-source-T").fill("air_temperature");
+    await page.getByTestId("environment-sink").fill("canopy_state");
+    await page.getByTestId("apply-environment").click();
+    state = await waitForState(request, server.url, (value) => findApplication(value, "plant_a__template_source").environment?.sources.T === "air_temperature");
+    expect(findApplication(state, "plant_b__template_source").environment?.backendId).toBe("environment:canopy");
+    await page.getByRole("button", { name: "Done" }).click();
+
+    const savePath = testInfo.outputPath("multi-plant-model.jl");
+    await page.getByTestId("save-model").click();
+    await page.getByPlaceholder("/absolute/path/to/model.jl").fill(savePath);
+    await page.locator(".model-file-dialog").getByRole("button", { name: "Save", exact: true }).click();
+    await waitForState(request, server.url, (value) => value.savePath === savePath);
+    const reopenPath = testInfo.outputPath("multi-plant-reopen-model.jl");
+    await copyFile(savePath, reopenPath);
+
+    await page.getByRole("button", { name: "Objects" }).click();
+    await page.locator(".entity-node.instance", { hasText: "plant_b" }).click();
+    await page.getByRole("button", { name: "Unmount instance" }).click();
+    await waitForState(request, server.url, (value) => value.graph.instances.length === 1);
+
+    await page.getByTestId("open-model").click();
+    await page.getByPlaceholder("/absolute/path/to/model.jl").fill(reopenPath);
+    await page.locator(".model-file-dialog").getByRole("button", { name: "Open", exact: true }).click();
+    await waitForState(request, server.url, (value) => value.graph.instances.length === 2);
+    await page.getByRole("button", { name: "Undo" }).click();
+    await waitForState(request, server.url, (value) => value.graph.instances.length === 1);
+    await page.getByRole("button", { name: "Redo" }).click();
+    await waitForState(request, server.url, (value) => value.graph.instances.length === 2);
   });
 });
 
-async function openInspectorPanel(page: Page) {
-  await page.getByTestId("toolbar-add-model").click();
-  await page.getByTestId("toolbar-inspector").click();
+async function openAddApplication(page: Page, modelName: string) {
+  await page.getByTestId("add-application").click();
+  await selectOptionContaining(page.getByTestId("application-model-select"), modelName);
 }
 
-async function openAddModelPanel(page: Page) {
-  await page.getByTestId("toolbar-add-model").click();
-  await expect(page.getByTestId("add-model-panel")).toBeVisible();
+async function addObject(page: Page, id: string, scale: string, kind: string, name: string) {
+  await page.getByTestId("add-object").click();
+  await page.getByTestId("object-id").fill(id);
+  await page.locator(".object-form label", { hasText: "Scale" }).getByRole("textbox").fill(scale);
+  await page.locator(".object-form label", { hasText: "Kind" }).getByRole("textbox").fill(kind);
+  await page.locator(".object-form label", { hasText: "Name" }).getByRole("textbox").fill(name);
+  await page.getByTestId("object-submit").click();
 }
 
-async function getState(request: APIRequestContext, baseURL: string): Promise {
+async function getState(request: APIRequestContext, baseURL: string): Promise {
   const response = await request.get(stateURL(baseURL));
-  if (!response.ok()) {
-    throw new Error(`Expected /state to return 2xx, got ${response.status()}:\n${await response.text()}`);
-  }
-  return await response.json() as GraphEditorState;
+  expect(response.ok()).toBe(true);
+  return await response.json() as EditorState;
 }
 
 function stateURL(baseURL: string): string {
@@ -117,48 +249,28 @@ function stateURL(baseURL: string): string {
   return url.toString();
 }
 
-async function waitForState(
-  request: APIRequestContext,
-  baseURL: string,
-  predicate: (state: GraphEditorState) => boolean,
-  timeoutMs = 15_000,
-): Promise {
+async function waitForState(request: APIRequestContext, baseURL: string, predicate: (state: EditorState) => boolean, timeoutMs = 20_000): Promise {
   const deadline = Date.now() + timeoutMs;
   let latest = await getState(request, baseURL);
   while (Date.now() < deadline) {
     if (predicate(latest)) return latest;
-    await new Promise((resolve) => setTimeout(resolve, 250));
+    await new Promise((resolve) => setTimeout(resolve, 200));
     latest = await getState(request, baseURL);
   }
-  throw new Error(`Timed out waiting for editor state. Latest state:\n${JSON.stringify(latest, null, 2)}`);
-}
-
-async function findNode(
-  request: APIRequestContext,
-  baseURL: string,
-  predicate: (node: GraphNodeData) => boolean,
-): Promise {
-  const state = await getState(request, baseURL);
-  const node = state.graph.nodes.find(predicate);
-  expect(node, `Expected graph node in ${state.graph.nodes.map((item) => item.modelType).join(", ")}`).toBeTruthy();
-  return node!;
+  throw new Error(`Timed out waiting for editor state:\n${JSON.stringify(latest, null, 2)}`);
 }
 
-async function waitForNode(
-  request: APIRequestContext,
-  baseURL: string,
-  predicate: (node: GraphNodeData) => boolean,
-): Promise {
-  const state = await waitForState(request, baseURL, (candidate) => candidate.graph.nodes.some(predicate));
-  return state.graph.nodes.find(predicate)!;
+function findApplication(state: EditorState, id: string): ApplicationGraphNode {
+  const application = state.graph.applications.find((item) => item.applicationId === id);
+  expect(application, `Expected application ${id}`).toBeTruthy();
+  return application!;
 }
 
 async function selectOptionContaining(select: Locator, text: string) {
   const value = await select.evaluate((element, needle) => {
     const selectElement = element as HTMLSelectElement;
-    const option = [...selectElement.options].find((item) => item.textContent?.includes(needle));
-    return option?.value ?? null;
+    return [...selectElement.options].find((option) => option.textContent?.includes(needle))?.value ?? null;
   }, text);
-  expect(value, `Expected select option containing ${text}`).toBeTruthy();
+  expect(value, `Expected option containing ${text}`).toBeTruthy();
   await select.selectOption(value!);
 }
diff --git a/frontend/src/App.test.ts b/frontend/src/App.test.ts
new file mode 100644
index 000000000..9a32749a9
--- /dev/null
+++ b/frontend/src/App.test.ts
@@ -0,0 +1,77 @@
+import { describe, expect, it } from "vitest";
+import { applicationPortId, applicationsForPort, deriveCandidatePortIds, endpointsForCandidate, modelsForPort, objectSubtreeIds, selectorSuggestion } from "./App";
+import type { ApplicationGraphNode, GraphPort, ModelDescriptor, ObjectGraphNode, ModelGraphView } from "./types";
+
+const output: GraphPort = { id: applicationPortId("source", "output", "signal"), name: "signal", role: "output", default: 0, defaultJulia: "0", expectedType: "Int" };
+const input: GraphPort = { id: applicationPortId("consumer", "input", "signal"), name: "signal", role: "input", default: 0, defaultJulia: "0", expectedType: "Int" };
+
+const source = application("source", [], [output], ["leaf"]);
+const consumer = application("consumer", [input], [], ["leaf"]);
+
+describe("candidate composition", () => {
+  it("keeps plus controls for exact existing-application matches", () => {
+    const graph = graphView([source, consumer], []);
+    const ids = deriveCandidatePortIds(graph);
+    expect(ids.has(output.id)).toBe(true);
+    expect(ids.has(input.id)).toBe(true);
+  });
+
+  it("matches model descriptors by exact declared variable name", () => {
+    const exact = model("Exact", { signal: 0 }, {});
+    const near = model("Near", { Signal: 0 }, {});
+    expect(modelsForPort([near, exact], output).map((item) => item.name)).toEqual(["Exact"]);
+  });
+
+  it("separates existing applications and produces directed binding endpoints", () => {
+    const candidate = { application: source, port: output, x: 0, y: 0 };
+    expect(applicationsForPort([source, consumer], candidate)).toEqual([consumer]);
+    const endpoints = endpointsForCandidate(candidate, consumer);
+    expect(endpoints.sourceApplication.applicationId).toBe("source");
+    expect(endpoints.targetApplication.applicationId).toBe("consumer");
+    expect(endpoints.targetPort.name).toBe("signal");
+  });
+});
+
+describe("selector suggestions", () => {
+  it("suggests a conservative target selector from one application", () => {
+    const suggestion = selectorSuggestion(source);
+    expect(suggestion.multiplicity).toBe("one");
+    expect(suggestion.criteria.scale).toBe("Leaf");
+  });
+});
+
+describe("object topology scoping", () => {
+  it("includes the selected object and all descendants", () => {
+    const objects: ObjectGraphNode[] = [
+      object("plant", null),
+      object("leaf", "object:plant"),
+      object("cell", "object:leaf"),
+      object("soil", null),
+    ];
+    expect(new Set(objectSubtreeIds(objects, "plant"))).toEqual(new Set(["plant", "leaf", "cell"]));
+  });
+});
+
+function application(id: string, inputs: GraphPort[], outputs: GraphPort[], targetIds: unknown[]): ApplicationGraphNode {
+  return {
+    id: `application:${id}`, applicationId: id, owner: { scope: "global", applicationId: id, instance: null, templateId: null }, name: id, process: id, modelType: id, modelName: id, module: "Main", package: null,
+    modelParameters: {}, selector: { type: "One", multiplicity: "one", criteria: { selectors: [], scale: "Leaf" }, julia: "" },
+    targetIds, targetCount: targetIds.length, targetScales: ["Leaf"], targetKinds: [], targetSpecies: [], targetInstances: [], cadence: { mode: "default", value: null, unit: null, julia: "nothing" }, clock: null,
+    inputs, outputs, environmentInputs: [], environmentOutputs: [], inputBindings: {}, callBindings: {}, environment: null, environmentBindings: {}, environmentWindow: { mode: "default", value: null, unit: null, julia: "nothing" }, outputRouting: {}, updates: [], modelStorage: "shared_application", objectOverrides: [],
+  };
+}
+
+function model(name: string, inputs: Record, outputs: Record): ModelDescriptor {
+  return { type: name, name, module: "Main", package: null, process: name, processType: name, inputs, outputs, environmentInputs: {}, environmentOutputs: {}, constructor: { fields: [], parameterGroups: {}, hasZeroArgConstructor: true, constructible: true } };
+}
+
+function object(id: string, parent: string | null): ObjectGraphNode {
+  return { id: `object:${id}`, objectId: id, scale: null, kind: null, species: null, name: id, instance: null, parent, children: [], hasGeometry: false, hasStatus: false };
+}
+
+function graphView(applications: ApplicationGraphNode[], modelLibrary: ModelDescriptor[]): ModelGraphView {
+  return {
+    schemaVersion: 2, level: "applications", metadata: { title: "", modelRevision: 0, objectCount: 1, instanceCount: 0, applicationCount: applications.length, executionCount: applications.length, bindingCount: 0, callCount: 0, unresolvedInitializationCount: 0, cyclic: false, strictlyCompiled: true, sceneEnvironmentId: null },
+    objects: [], templates: [], instances: [], applications, executions: [], edges: [], modelLibrary, environments: [], initialization: [], diagnostics: [], cycles: [], availableActions: [],
+  };
+}
diff --git a/frontend/src/App.tsx b/frontend/src/App.tsx
index e954a2a86..4f1c646e4 100644
--- a/frontend/src/App.tsx
+++ b/frontend/src/App.tsx
@@ -1,2711 +1,1057 @@
-import { useCallback, useEffect, useMemo, useRef, useState, type ReactNode } from "react";
+import { useCallback, useEffect, useMemo, useState } from "react";
 import {
   Background,
   Controls,
+  MarkerType,
   MiniMap,
   ReactFlow,
-  MarkerType,
   useEdgesState,
   useNodesState,
   type Connection,
   type Edge,
   type Node,
-  type ReactFlowInstance,
 } from "@xyflow/react";
 import "@xyflow/react/dist/style.css";
 import {
   AlertTriangle,
+  Boxes,
   CircleAlert,
-  Filter,
+  Code2,
+  GitBranch,
   FolderOpen,
-  GitPullRequestArrow,
+  Layers3,
   Network,
-  RotateCcw,
-  Route,
-  ScissorsLineDashed,
+  Plus,
+  Scissors,
   Search,
+  Save,
+  Undo2,
+  Redo2,
   X,
 } from "lucide-react";
+import { ApplicationForm, type ApplicationFormValue } from "./ApplicationForm";
+import { ApplicationConfigurationForm } from "./ApplicationConfigurationForm";
+import { BindingForm, type BindingEndpoints, type BindingFormValue } from "./BindingForm";
+import { EnvironmentForm } from "./EnvironmentForm";
+import { InstanceForm, type InstanceFormValue } from "./InstanceForm";
+import { ObjectForm, type ObjectFormValue } from "./ObjectForm";
+import { OverrideForm, type OverrideFormValue } from "./OverrideForm";
+import { ApplicationNode, EntityNode } from "./ModelNode";
 import { DependencyEdge } from "./DependencyEdge";
-import { ModelNode } from "./ModelNode";
 import { layoutGraph, type LayoutMode } from "./layout";
-import { sampleGraph } from "./sampleGraph";
-import type { DependencyGraphView, GraphEdgeData, GraphEditorState, GraphNodeData, GraphPort, InitializationDescriptor, ModelDescriptor, RuntimeGraphNodeData } from "./types";
+import { sampleModelGraph } from "./sampleModelGraph";
+import type {
+  ApplicationGraphNode,
+  DetailMode,
+  EditorState,
+  EnvironmentDescriptor,
+  EnvironmentGraphNode,
+  ExecutionGraphNode,
+  GraphPort,
+  GraphViewMode,
+  InstanceDescriptor,
+  InstancePreview,
+  ModelDescriptor,
+  ObjectGraphNode,
+  RuntimeApplicationNode,
+  RuntimeEntityNode,
+  ModelGraphEdge,
+  ModelGraphView,
+  ModelRootDescriptor,
+  SelectorPreview,
+  TemplateDescriptor,
+  TargetPreview,
+} from "./types";
 import "./styles.css";
 
-type EdgeFilterKey = "dataFlow" | "mapped" | "callStack";
-type EdgeFilters = Record;
-type FocusMode = "none" | "upstream" | "downstream" | "neighborhood";
-type SidePanel = "inspector" | "add_model" | "initializations" | "mapping_code" | null;
-type GraphViewMode = "overview" | "detail";
-
-type PendingMappingConnection = {
-  sourceNode: GraphNodeData;
-  sourcePort: GraphPort;
-  targetNode: GraphNodeData;
-  targetPort: GraphPort;
-};
-
-type CandidatePopover = {
-  portId: string;
-  anchor: { x: number; y: number };
-};
-
-type AddModelSelection = {
-  modelType: string;
-  scale: string;
-  requestId: number;
-};
-
-type SearchResult = {
-  id: string;
-  kind: "model" | "input" | "output";
-  node: GraphNodeData;
-  port?: GraphPort;
-  label: string;
-  detail: string;
-};
-
-type RequiredInput = {
-  node: GraphNodeData;
-  port: GraphPort;
-  reason: "previous_time_step" | "mapped_unresolved" | "user_initialization";
-};
-
-type CycleBreakOption = {
-  edge: GraphEdgeData;
-  node: GraphNodeData;
-  port: GraphPort;
-};
-
-type ValidationWarning = {
-  id: string;
-  severity: "error" | "warning" | "info";
-  category: "init" | "mapping" | "ownership" | "hard_dependency" | "cross_scale";
-  title: string;
-  detail: string;
-  nodeId?: string;
-  nodeIds?: string[];
-  portId?: string;
-  portIds?: string[];
-  edgeId?: string;
-};
-
-type FocusState = {
-  active: boolean;
-  edges: Set;
-  nodes: Set;
-  ports: Set;
-};
-
-const nodeTypes = { model: ModelNode };
-const edgeTypes = { dependency: DependencyEdge };
-const edgeColors = {
-  base: "#a99a8c",
-  accent: "#1f7a53",
-  mapped: "#4f8d69",
-  hard: "#bf6a54",
-};
-
-const defaultEdgeFilters: EdgeFilters = {
-  dataFlow: true,
-  mapped: true,
-  callStack: true,
-};
-
-const focusLabels: Record = {
-  none: "No focus",
-  upstream: "Upstream",
-  downstream: "Downstream",
-  neighborhood: "Both",
-};
-
-const layoutLabels: Record = {
-  data_flow: "Data-flow",
-  compact: "Compact",
-  scale_grouped: "Scale grouped",
-  call_stack: "Call stack",
-  overview: "Overview",
+type FlowNode = Node;
+type FlowEdge = Edge;
+type CandidatePopover = { port: GraphPort; application: ApplicationGraphNode; x: number; y: number };
+type CycleBreakSelection = { application: ApplicationGraphNode; port: GraphPort };
+type InspectorSelection = ApplicationGraphNode | TemplateDescriptor | InstanceDescriptor | ObjectGraphNode | ExecutionGraphNode | EnvironmentDescriptor | EnvironmentGraphNode | ModelRootDescriptor | ModelGraphEdge | null;
+type GraphScopeFilter = { label: string; objectIds: unknown[] };
+type ApplicationFormState = {
+  mode: "add" | "update";
+  application?: ApplicationGraphNode;
+  initialModelType?: string;
+  suggestedSelector?: ApplicationGraphNode["selector"];
 };
+type ObjectFormState = { mode: "add" | "update"; object?: ObjectGraphNode };
 
-const valueTypeChoices = ["float", "integer", "boolean", "symbol", "string", "nothing", "julia"];
+const nodeTypes = { application: ApplicationNode, entity: EntityNode };
+const edgeTypes = { modelEdge: DependencyEdge };
 
 export default function App() {
-  const [graph, setGraph] = useState(loadInitialGraph());
-  const [editorModels, setEditorModels] = useState([]);
-  const [editorSocket, setEditorSocket] = useState(null);
-  const [editorConnected, setEditorConnected] = useState(false);
+  const [graph, setGraph] = useState(loadInitialGraph);
+  const [view, setView] = useState(() => loadInitialGraph().level);
+  const [detailMode, setDetailMode] = useState(() => loadInitialGraph().metadata.applicationCount > 24 ? "overview" : "detail");
+  const [query, setQuery] = useState("");
+  const [selected, setSelected] = useState(null);
+  const [scopeFilter, setScopeFilter] = useState(null);
+  const [selectedPort, setSelectedPort] = useState(null);
+  const [candidate, setCandidate] = useState(null);
+  const [showDiagnostics, setShowDiagnostics] = useState(false);
+  const [showInitialization, setShowInitialization] = useState(false);
+  const [showModelCode, setShowModelCode] = useState(false);
+  const [showOpen, setShowOpen] = useState(false);
+  const [showSave, setShowSave] = useState(false);
+  const [modelCode, setSceneCode] = useState("");
+  const [autosavePath, setAutosavePath] = useState(null);
+  const [savePath, setSavePath] = useState(null);
+  const [recentPaths, setRecentPaths] = useState([]);
+  const [socket, setSocket] = useState(null);
+  const [connected, setConnected] = useState(false);
   const [canUndo, setCanUndo] = useState(false);
   const [canRedo, setCanRedo] = useState(false);
-  const [activePanel, setActivePanel] = useState(() => loadEditorConfig()?.websocketUrl ? "inspector" : null);
-  const [mappingCode, setMappingCode] = useState("");
-  const [initializations, setInitializations] = useState([]);
-  const [lastSavedPath, setLastSavedPath] = useState(null);
-  const [saveTargetPath, setSaveTargetPath] = useState(null);
-  const [autosavePath, setAutosavePath] = useState(null);
-  const [lastAutosavedPath, setLastAutosavedPath] = useState(null);
-  const [recentMappings, setRecentMappings] = useState([]);
-  const [editorFeedback, setEditorFeedback] = useState<{ kind: "error" | "info"; text: string } | null>(null);
-  const [savePath, setSavePath] = useState("mapping.generated.jl");
-  const [customScales, setCustomScales] = useState([]);
-  const [selected, setSelected] = useState(null);
-  const [activePort, setActivePort] = useState(null);
-  const [pendingConnection, setPendingConnection] = useState(null);
-  const [showRequiredPanel, setShowRequiredPanel] = useState(false);
-  const [showWarningsPanel, setShowWarningsPanel] = useState(false);
-  const [showOpenPanel, setShowOpenPanel] = useState(false);
-  const [showRelationshipsPanel, setShowRelationshipsPanel] = useState(false);
-  const [showScalesPanel, setShowScalesPanel] = useState(false);
-  const [showSearchResults, setShowSearchResults] = useState(false);
-  const [searchQuery, setSearchQuery] = useState("");
-  const [layoutMode, setLayoutMode] = useState("data_flow");
-  const [focusMode, setFocusMode] = useState("neighborhood");
-  const [viewMode, setViewMode] = useState(() => defaultGraphViewMode(loadInitialGraph()));
-  const [viewModeTouched, setViewModeTouched] = useState(false);
-  const [edgeFilters, setEdgeFilters] = useState(defaultEdgeFilters);
-  const [collapsedScales, setCollapsedScales] = useState>(() => new Set());
-  const [pinnedFocus, setPinnedFocus] = useState(null);
-  const [selectedEdge, setSelectedEdge] = useState(null);
+  const [feedback, setFeedback] = useState(null);
+  const [applicationForm, setApplicationForm] = useState(null);
+  const [targetPreview, setTargetPreview] = useState(null);
+  const [showInstanceForm, setShowInstanceForm] = useState(false);
+  const [instancePreview, setInstancePreview] = useState(null);
+  const [showEnvironmentForm, setShowEnvironmentForm] = useState(false);
+  const [objectForm, setObjectForm] = useState(null);
+  const [overrideApplication, setOverrideApplication] = useState(null);
+  const [configurationApplicationId, setConfigurationApplicationId] = useState(null);
+  const [bindingForm, setBindingForm] = useState(null);
+  const [bindingPreview, setBindingPreview] = useState(null);
   const [cycleBreakMode, setCycleBreakMode] = useState(false);
-  const [candidatePopover, setCandidatePopover] = useState(null);
-  const [addModelSelection, setAddModelSelection] = useState(null);
-  const [addModelFocusRequest, setAddModelFocusRequest] = useState(0);
-  const [highlightAddModelPanel, setHighlightAddModelPanel] = useState(false);
-  const [flowInstance, setFlowInstance] = useState, Edge> | null>(null);
-  const [nodes, setNodes, onNodesChange] = useNodesState>([]);
-  const [edges, setEdges, onEdgesChange] = useEdgesState>([]);
-  const sidePanelRef = useRef(null);
-
-  const nodeById = useMemo(() => new Map(graph.nodes.map((node) => [node.id, node])), [graph]);
-  const portById = useMemo(() => buildPortIndex(graph), [graph]);
-  const incomingByPort = useMemo(() => groupEdgesByPort(graph.edges, "targetPort"), [graph.edges]);
-  const outgoingByPort = useMemo(() => groupEdgesByPort(graph.edges, "sourcePort"), [graph.edges]);
-  const requiredInputPortIds = useMemo(() => deriveRequiredInputPorts(graph), [graph]);
-  const candidatePortIds = useMemo(() => deriveCandidatePortIds(graph, editorModels, incomingByPort), [editorModels, graph, incomingByPort]);
-  const requiredInputs = useMemo(() => deriveRequiredInputs(graph, requiredInputPortIds, incomingByPort), [graph, incomingByPort, requiredInputPortIds]);
-  const warningItems = useMemo(() => deriveValidationWarnings(graph, requiredInputPortIds, incomingByPort), [graph, incomingByPort, requiredInputPortIds]);
-  const actionableWarningItems = useMemo(() => warningItems.filter((item) => item.severity !== "info"), [warningItems]);
-  const searchResults = useMemo(() => deriveSearchResults(graph, searchQuery), [graph, searchQuery]);
-  const visibleNodeData = useMemo(() => graph.nodes.filter((node) => !collapsedScales.has(node.scale)), [collapsedScales, graph.nodes]);
-  const editorScales = useMemo(() => {
-    const graphScales = graph.scales.length > 0 ? graph.scales : ["Default"];
-    const merged = [...graphScales, ...customScales];
-    return [...new Set(merged)];
-  }, [customScales, graph.scales]);
-  const visibleNodeIds = useMemo(() => new Set(visibleNodeData.map((node) => node.id)), [visibleNodeData]);
-  const visibleEdgeData = useMemo(() => graph.edges.filter((edge) => (
-    edgeMatchesFilters(edge, edgeFilters) &&
-    visibleNodeIds.has(edge.source) &&
-    visibleNodeIds.has(edge.target)
-  )), [edgeFilters, graph.edges, visibleNodeIds]);
-  const cycleBreakOptions = useMemo(() => deriveCycleBreakOptions(graph, nodeById, portById), [graph, nodeById, portById]);
-  const cycleBreakPortIds = useMemo(() => new Set(cycleBreakOptions.map((option) => option.port.id)), [cycleBreakOptions]);
-  const hoverHighlight = useMemo(() => deriveHighlight(graph, activePort), [activePort, graph]);
-  const traversalFocus = useMemo(
-    () => deriveFocus(graph, selected?.id ?? null, activePort, focusMode),
-    [activePort, focusMode, graph, selected?.id],
+  const [cycleBreakSelection, setCycleBreakSelection] = useState(null);
+  const [nodes, setNodes, onNodesChange] = useNodesState([]);
+  const [edges, setEdges, onEdgesChange] = useEdgesState([]);
+
+  const editorConfig = useMemo(loadEditorConfig, []);
+  const applicationById = useMemo(() => new Map(graph.applications.map((application) => [application.applicationId, application])), [graph.applications]);
+  const unresolvedPortIds = useMemo(() => new Set(
+    graph.initialization
+      .filter((row) => row.role === "input" && row.disposition === "unresolved")
+      .map((row) => applicationPortId(row.applicationId, "input", row.variable)),
+  ), [graph.initialization]);
+  const previousPortIds = useMemo(() => new Set(
+    graph.initialization
+      .filter((row) => row.role === "input" && row.previousTimeStep)
+      .map((row) => applicationPortId(row.applicationId, "input", row.variable)),
+  ), [graph.initialization]);
+  const cyclicApplications = useMemo(() => new Set(graph.cycles.flatMap((cycle) => cycle.applicationIds)), [graph.cycles]);
+  const cycleBreakPortIds = useMemo(() => new Set(
+    graph.cycles.flatMap((cycle) => cycle.breakCandidates.map((candidate) => applicationPortId(candidate.applicationId, "input", candidate.input))),
+  ), [graph.cycles]);
+  const candidatePortIds = useMemo(() => deriveCandidatePortIds(graph), [graph]);
+  const candidateModels = useMemo(() => candidate ? modelsForPort(graph.modelLibrary, candidate.port) : [], [candidate, graph.modelLibrary]);
+  const candidateApplications = useMemo(() => candidate ? applicationsForPort(graph.applications, candidate) : [], [candidate, graph.applications]);
+  const portIndex = useMemo(() => {
+    const index = new Map();
+    for (const application of graph.applications) {
+      for (const port of [...application.inputs, ...application.outputs]) index.set(port.id, { application, port });
+    }
+    return index;
+  }, [graph.applications]);
+  const scopedObjectIds = useMemo(
+    () => scopeFilter ? new Set(scopeFilter.objectIds.map(objectKey)) : null,
+    [scopeFilter],
   );
-  const focus = useMemo(() => pinnedFocus?.active ? pinnedFocus : traversalFocus, [pinnedFocus, traversalFocus]);
-  const activeCandidatePortId = candidatePopover?.portId ?? null;
-  const candidatePopoverInfo = useMemo(() => {
-    if (!candidatePopover) return null;
-    const portInfo = portById.get(candidatePopover.portId);
-    if (!portInfo || !candidatePortIds.has(candidatePopover.portId)) return null;
-    const { port } = portInfo;
-    const field = port.role === "input" ? "outputs" : "inputs";
-    const models = editorModels
-      .filter((model) => Object.prototype.hasOwnProperty.call(modelVariableDeclarations(model, field), port.name))
-      .sort((left, right) => left.name.localeCompare(right.name));
-    if (models.length === 0) return null;
-    return {
-      anchor: candidatePopover.anchor,
-      node: portInfo.node,
-      port,
-      title: port.role === "input" ? "Models That Compute" : "Models That Consume",
-      models,
-    };
-  }, [candidatePopover, candidatePortIds, editorModels, portById]);
-
-  const toggleCandidatePopover = useCallback((port: GraphPort, anchor: { x: number; y: number }) => {
-    setActivePort(port);
-    setCandidatePopover((current) => current?.portId === port.id ? null : { portId: port.id, anchor });
-  }, []);
 
   useEffect(() => {
-    const config = loadEditorConfig();
-    if (!config?.websocketUrl) return;
-
-    const socket = new WebSocket(config.websocketUrl);
-    setEditorSocket(socket);
-    socket.addEventListener("open", () => {
-      setEditorConnected(true);
-      setEditorFeedback(null);
-    });
-    socket.addEventListener("close", () => {
-      setEditorConnected(false);
-      setEditorFeedback({ kind: "error", text: "Graph editor connection closed. Refresh the page or restart the Julia session." });
-    });
-    socket.addEventListener("message", (event) => {
-      const payload = JSON.parse(event.data) as GraphEditorState;
+    if (!editorConfig?.websocketUrl) return;
+    const nextSocket = new WebSocket(editorConfig.websocketUrl);
+    setSocket(nextSocket);
+    nextSocket.addEventListener("open", () => { setConnected(true); setFeedback(null); });
+    nextSocket.addEventListener("close", () => { setConnected(false); setFeedback("Editor connection closed."); });
+    nextSocket.addEventListener("message", (event) => {
+      const payload = JSON.parse(event.data) as EditorState;
       if (payload.graph) setGraph(payload.graph);
-      if (payload.models) setEditorModels(payload.models);
-      if (typeof payload.mappingCode === "string") setMappingCode(payload.mappingCode);
-      if (Array.isArray(payload.initializations)) setInitializations(payload.initializations);
-      setLastSavedPath(typeof payload.lastSavedPath === "string" ? payload.lastSavedPath : null);
-      setSaveTargetPath(typeof payload.saveTargetPath === "string" ? payload.saveTargetPath : null);
-      if (typeof payload.saveTargetPath === "string") setSavePath(payload.saveTargetPath);
-      setAutosavePath(typeof payload.autosavePath === "string" ? payload.autosavePath : null);
-      setLastAutosavedPath(typeof payload.lastAutosavedPath === "string" ? payload.lastAutosavedPath : null);
-      if (Array.isArray(payload.recentMappings)) setRecentMappings(payload.recentMappings);
-      setCanUndo(Boolean(payload.canUndo));
-      setCanRedo(Boolean(payload.canRedo));
+      if (typeof payload.modelCode === "string") setSceneCode(payload.modelCode);
+      setAutosavePath(payload.autosavePath ?? null);
+      setSavePath(payload.savePath ?? null);
+      setRecentPaths(payload.recentPaths ?? []);
+      if (payload.selectorPreview) setBindingPreview(payload.selectorPreview);
+      if (payload.targetPreview) setTargetPreview(payload.targetPreview);
+      if (payload.instancePreview) setInstancePreview(payload.instancePreview);
       if (payload.ok === false) {
-        const message = payload.diagnostics?.[0] ?? "Graph editor command failed.";
-        setEditorFeedback({ kind: "error", text: message });
-      } else if (payload.diagnostics?.length) {
-        setEditorFeedback({ kind: "info", text: payload.diagnostics[0] });
-      } else {
-        setEditorFeedback(null);
+        setBindingPreview(null);
+        setTargetPreview(null);
+        setInstancePreview(null);
       }
+      setCanUndo(Boolean(payload.canUndo));
+      setCanRedo(Boolean(payload.canRedo));
+      setFeedback(payload.ok === false ? payload.diagnostics?.[0] || "The edit failed." : null);
     });
-    return () => socket.close();
-  }, []);
+    return () => nextSocket.close();
+  }, [editorConfig?.websocketUrl]);
 
-  const sendEditorCommand = useCallback((command: Record) => {
-    if (!editorSocket || editorSocket.readyState !== WebSocket.OPEN) {
-      setEditorFeedback({ kind: "error", text: "Graph editor is offline; command was not sent." });
-      return;
+  useEffect(() => {
+    if (!graph.metadata.cyclic) {
+      setCycleBreakMode(false);
+      setCycleBreakSelection(null);
     }
-    editorSocket.send(JSON.stringify(command));
-  }, [editorSocket]);
-
-  const breakCycleAtPort = useCallback((port: GraphPort) => {
-    const target = portById.get(port.id);
-    if (!target || port.role !== "input") return;
-    sendEditorCommand({
-      action: "edit",
-      kind: "mark_previous_timestep",
-      scale: target.node.scale,
-      process: target.node.process,
-      variable: port.name,
-    });
-    setCycleBreakMode(false);
-    setPinnedFocus(null);
-    setSelectedEdge(null);
-    setSelected(target.node);
-    setActivePort(port);
-  }, [portById, sendEditorCommand]);
+  }, [graph.metadata.cyclic]);
 
-  const removeGraphModel = useCallback((node: GraphNodeData) => {
-    const target = removableMappingNode(node, nodeById);
-    if (!target) {
-      setEditorFeedback({ kind: "error", text: `Cannot remove ${node.process}: no owning ModelMapping model was found.` });
+  const sendCommand = useCallback((command: Record) => {
+    if (!socket || socket.readyState !== WebSocket.OPEN) {
+      setFeedback("This action requires an interactive Julia editor session.");
       return;
     }
-    sendEditorCommand({
-      action: "edit",
-      kind: "remove_model",
-      scale: target.scale,
-      process: target.process,
-    });
-    setSelected((current) => current?.id === node.id || current?.id === target.id ? null : current);
-    setActivePort(null);
-    setSelectedEdge(null);
-  }, [nodeById, sendEditorCommand]);
+    socket.send(JSON.stringify(command));
+  }, [socket]);
 
-  const togglePanel = useCallback((panel: Exclude) => {
-    setActivePanel((current) => current === panel ? null : panel);
+  const openCandidates = useCallback((application: ApplicationGraphNode, port: GraphPort, anchor: { x: number; y: number }) => {
+    setSelected(application);
+    setSelectedPort(port);
+    setCandidate({ application, port, x: anchor.x, y: anchor.y });
   }, []);
 
-  const openAddModelPanel = useCallback(() => {
-    setActivePanel("add_model");
-    setHighlightAddModelPanel(true);
-    setAddModelFocusRequest(Date.now());
-  }, []);
-
-  const addCustomScale = useCallback((rawScale: string) => {
-    const scale = rawScale.trim();
-    if (!scale) return;
-    setCustomScales((current) => current.includes(scale) || graph.scales.includes(scale) ? current : [...current, scale]);
-  }, [graph.scales]);
-
-  useEffect(() => {
-    if (activePanel !== "add_model" || !highlightAddModelPanel) return;
-    sidePanelRef.current?.scrollIntoView({ block: "nearest", inline: "nearest" });
-    sidePanelRef.current?.focus({ preventScroll: true });
-    const timeout = window.setTimeout(() => setHighlightAddModelPanel(false), 1800);
-    return () => window.clearTimeout(timeout);
-  }, [activePanel, highlightAddModelPanel, addModelFocusRequest]);
-
-  useEffect(() => {
-    if (!viewModeTouched) setViewMode(defaultGraphViewMode(graph));
-  }, [graph, viewModeTouched]);
-
-  useEffect(() => {
-    const nextNodes = visibleNodeData.map((node) => ({
-      id: node.id,
-      type: "model",
-      position: { x: 0, y: 0 },
-      data: runtimeNodeData(node, {
-        activePort: null,
-        highlightedPortIds: new Set(),
-        focusedPortIds: new Set(),
-        requiredInputPortIds,
-        candidatePortIds,
-        cycleNodeIds: new Set(graph.cycleNodes),
-        cycleBreakPortIds,
-        cycleBreakMode,
-        focusedNodeIds: new Set(),
-        hasActiveFocus: false,
-        activeCandidatePortId,
-        setActivePort,
-        setCandidatePopover: toggleCandidatePopover,
-        breakCycleAtPort,
-        removeGraphModel,
-        viewMode,
-      }),
-    }));
-    const nextEdges = visibleEdgeData.map((edge) => flowEdge(edge, new Set(), new Set(), false, false));
-    layoutGraph(nextNodes, nextEdges, effectiveLayoutMode(viewMode, layoutMode)).then((layouted) => {
-      setNodes(layouted);
-      setEdges(nextEdges);
-    });
-  }, [activeCandidatePortId, breakCycleAtPort, candidatePortIds, cycleBreakMode, cycleBreakPortIds, graph.cycleNodes, layoutMode, removeGraphModel, requiredInputPortIds, setEdges, setNodes, toggleCandidatePopover, viewMode, visibleEdgeData, visibleNodeData]);
-
   useEffect(() => {
-    const focusEdges = focus.active ? focus.edges : new Set();
-    setNodes((current) => current.map((node) => ({
-      ...node,
-      data: runtimeNodeData(node.data, {
-        activePort,
-        highlightedPortIds: hoverHighlight.ports,
-        focusedPortIds: focus.ports,
-        requiredInputPortIds,
-        candidatePortIds,
-        cycleNodeIds: new Set(graph.cycleNodes),
-        cycleBreakPortIds,
-        cycleBreakMode,
-        focusedNodeIds: focus.nodes,
-        hasActiveFocus: focus.active,
-        activeCandidatePortId,
-        setActivePort,
-        setCandidatePopover: toggleCandidatePopover,
-        breakCycleAtPort,
-        removeGraphModel,
-        viewMode,
-      }),
-    })));
-    setEdges((current) => current.map((edge) => edge.data ? flowEdge(edge.data, hoverHighlight.edges, focusEdges, Boolean(activePort), focus.active) : edge));
-  }, [activeCandidatePortId, activePort, breakCycleAtPort, candidatePortIds, cycleBreakMode, cycleBreakPortIds, focus, graph.cycleNodes, hoverHighlight.edges, hoverHighlight.ports, removeGraphModel, requiredInputPortIds, setEdges, setNodes, toggleCandidatePopover, viewMode]);
-
-  useEffect(() => {
-    if (candidatePopover && !candidatePortIds.has(candidatePopover.portId)) setCandidatePopover(null);
-  }, [candidatePopover, candidatePortIds]);
-
-  const onConnect = useCallback((connection: Connection) => {
-    if (!editorConnected) return;
-    const sourcePortId = connection.sourceHandle;
-    const targetPortId = connection.targetHandle;
-    if (!sourcePortId || !targetPortId) return;
-    const sourceInfo = portById.get(sourcePortId);
-    const targetInfo = portById.get(targetPortId);
-    if (!sourceInfo || !targetInfo) return;
-    // Only handle output-to-input connections.
-    if (sourceInfo.port.role !== "output" || targetInfo.port.role !== "input") return;
-    setPendingConnection({
-      sourceNode: sourceInfo.node,
-      sourcePort: sourceInfo.port,
-      targetNode: targetInfo.node,
-      targetPort: targetInfo.port,
+    const nextNodes = buildNodes({
+      graph,
+      view,
+      detailMode,
+      query,
+      scopedObjectIds,
+      unresolvedPortIds,
+      previousPortIds,
+      candidatePortIds,
+      cyclicApplications,
+      cycleBreakPortIds,
+      cycleBreakMode,
+      openCandidates,
+      onPortClick: setSelectedPort,
+      onCycleBreak: (application, port) => setCycleBreakSelection({ application, port }),
     });
-  }, [editorConnected, portById]);
-
-  const relayout = useCallback(() => {
-    layoutGraph(nodes, edges, effectiveLayoutMode(viewMode, layoutMode)).then(setNodes);
-  }, [edges, layoutMode, nodes, setNodes, viewMode]);
-
-  const focusNode = useCallback((node: GraphNodeData, port?: GraphPort | null) => {
-    setPinnedFocus(null);
-    setSelectedEdge(null);
-    setSelected(node);
-    setActivePort(port ?? null);
-    setActivePanel("inspector");
-    setCollapsedScales((current) => {
-      if (!current.has(node.scale)) return current;
-      const next = new Set(current);
-      next.delete(node.scale);
-      return next;
+    const nodeIds = new Set(nextNodes.map((node) => node.id));
+    const nextEdges = buildEdges(graph, view).filter((edge) => nodeIds.has(edge.source) && nodeIds.has(edge.target));
+    const layoutMode: LayoutMode = view === "topology" ? "topology" : detailMode === "overview" ? "overview" : "data_flow";
+    layoutGraph(nextNodes, nextEdges, layoutMode).then(setNodes);
+    setEdges(nextEdges);
+  }, [candidatePortIds, cycleBreakMode, cycleBreakPortIds, cyclicApplications, detailMode, graph, openCandidates, previousPortIds, query, scopedObjectIds, setEdges, setNodes, unresolvedPortIds, view]);
+
+  const inspectSelection = useCallback((_: unknown, node: FlowNode) => {
+    if (node.data.nodeKind === "application") {
+      setSelected(applicationById.get(node.data.applicationId) ?? null);
+    } else {
+      setSelected(node.data.detail);
+      if (node.data.nodeKind === "object") {
+        const object = node.data.detail as ObjectGraphNode;
+        setScopeFilter({
+          label: `subtree ${object.name || String(object.objectId)}`,
+          objectIds: objectSubtreeIds(graph.objects, object.objectId),
+        });
+      } else if (node.data.nodeKind === "instance") {
+        const instance = node.data.detail as InstanceDescriptor;
+        setScopeFilter({ label: `instance ${instance.name}`, objectIds: instance.objectIds });
+      } else if (node.data.nodeKind === "model") {
+        setScopeFilter(null);
+      }
+    }
+    setSelectedPort(null);
+  }, [applicationById, graph.objects]);
+
+  const selectCandidateModel = useCallback((model: ModelDescriptor) => {
+    if (!candidate) return;
+    setTargetPreview(null);
+    setApplicationForm({
+      mode: "add",
+      initialModelType: model.type,
+      suggestedSelector: selectorSuggestion(candidate.application),
     });
-    const renderedNode = nodes.find((item) => item.id === node.id);
-    if (renderedNode && flowInstance) {
-      flowInstance.setCenter(renderedNode.position.x + 156, renderedNode.position.y + 90, { zoom: 0.85, duration: 520 });
+    if (!connected) setFeedback(`${model.name} matches ${candidate.port.name}. Start an interactive Julia editor session to add it to the composite model.`);
+    setCandidate(null);
+  }, [candidate, connected]);
+
+  const submitApplication = useCallback((value: ApplicationFormValue) => {
+    if (!connected) {
+      setFeedback("Adding or updating an application requires an interactive Julia editor session.");
+      setApplicationForm(null);
+      return;
     }
-  }, [flowInstance, nodes]);
-
-  const focusEdge = useCallback((edge: GraphEdgeData) => {
-    const port = edge.targetPort ? portById.get(edge.targetPort)?.port : edge.sourcePort ? portById.get(edge.sourcePort)?.port : null;
-    const node = port?.id === edge.targetPort ? nodeById.get(edge.target) : nodeById.get(edge.source);
-    if (node) focusNode(node, port ?? null);
-  }, [focusNode, nodeById, portById]);
-
-  const chooseCycleBreakPoint = useCallback(() => {
-    setCycleBreakMode(true);
-    setViewModeTouched(true);
-    setViewMode("detail");
-    setActivePanel("inspector");
-    setSelected(null);
-    setSelectedEdge(null);
-    setCandidatePopover(null);
-    setActivePort(null);
+    sendCommand({
+      action: "edit",
+      kind: value.applicationRef ? "update_application" : "add_application",
+      ...value,
+    });
+    setApplicationForm(null);
+  }, [connected, sendCommand]);
 
-    const nextFocus = emptyFocusState();
-    nextFocus.active = true;
-    for (const option of cycleBreakOptions) {
-      nextFocus.edges.add(option.edge.id);
-      nextFocus.nodes.add(option.edge.source);
-      nextFocus.nodes.add(option.edge.target);
-      if (option.edge.sourcePort) nextFocus.ports.add(option.edge.sourcePort);
-      nextFocus.ports.add(option.port.id);
+  const submitInstance = useCallback((value: InstanceFormValue) => {
+    if (!connected) {
+      setFeedback("Adding a template instance requires an interactive Julia editor session.");
+      return;
     }
-    setPinnedFocus(nextFocus);
-
-    if (flowInstance && cycleBreakOptions.length > 0) {
-      const nodeIds = [...new Set(cycleBreakOptions.flatMap((option) => [option.edge.source, option.edge.target]))];
-      flowInstance.fitView({
-        nodes: nodeIds.map((id) => ({ id })),
-        padding: 0.36,
-        duration: 520,
-        maxZoom: 1.05,
-      });
+    sendCommand({ action: "edit", kind: "add_instance", ...value });
+    setShowInstanceForm(false);
+    setInstancePreview(null);
+  }, [connected, sendCommand]);
+
+  const submitBinding = useCallback((value: BindingFormValue) => {
+    if (!connected) {
+      setFeedback("Creating a binding requires an interactive Julia editor session.");
+      setBindingForm(null);
+      return;
     }
-  }, [cycleBreakOptions, flowInstance]);
-
-  useEffect(() => {
-    if (!graph.cyclic) setCycleBreakMode(false);
-  }, [graph.cyclic]);
-
-  const toggleEdgeFilter = useCallback((key: EdgeFilterKey) => {
-    setEdgeFilters((current) => ({ ...current, [key]: !current[key] }));
-  }, []);
-
-  const toggleScale = useCallback((scale: string) => {
-    setSelected(null);
-    setSelectedEdge(null);
-    setActivePort(null);
-    setPinnedFocus(null);
-    setCollapsedScales((current) => {
-      const next = new Set(current);
-      if (next.has(scale)) next.delete(scale);
-      else next.add(scale);
-      return next;
+    sendCommand({ action: "edit", kind: "set_input_binding", ...value });
+    setBindingForm(null);
+  }, [connected, sendCommand]);
+
+  const submitObject = useCallback((value: ObjectFormValue) => {
+    if (!connected) {
+      setFeedback("Adding or updating an object requires an interactive Julia editor session.");
+      setObjectForm(null);
+      return;
+    }
+    sendCommand({
+      action: "edit",
+      kind: objectForm?.mode === "update" ? "update_object" : "add_object",
+      objectId: value.objectId,
+      configuration: value.configuration,
     });
-  }, []);
+    setObjectForm(null);
+  }, [connected, objectForm?.mode, sendCommand]);
 
-  const expandAllScales = useCallback(() => setCollapsedScales(new Set()), []);
-
-  const focusWarning = useCallback((warning: ValidationWarning) => {
-    if (warning.portIds?.length) {
-      const nextFocus = emptyFocusState();
-      nextFocus.active = true;
-      for (const portId of warning.portIds) {
-        const target = portById.get(portId);
-        if (!target) continue;
-        nextFocus.ports.add(portId);
-        nextFocus.nodes.add(target.node.id);
-      }
-      setPinnedFocus(nextFocus);
-      const first = portById.get(warning.portIds[0]);
-      if (first) {
-        setSelected(null);
-        setSelectedEdge(null);
-        setActivePort(null);
-        if (flowInstance && warning.nodeIds && warning.nodeIds.length > 1) {
-          flowInstance.fitView({
-            nodes: warning.nodeIds.map((id) => ({ id })),
-            padding: 0.28,
-            duration: 520,
-            maxZoom: 0.95,
-          });
-        } else {
-          const renderedNode = nodes.find((item) => item.id === first.node.id);
-          if (renderedNode && flowInstance) {
-            flowInstance.setCenter(renderedNode.position.x + 156, renderedNode.position.y + 90, { zoom: 0.9, duration: 520 });
-          }
-        }
-      }
+  const submitOverride = useCallback((value: OverrideFormValue) => {
+    if (!connected) {
+      setFeedback("Creating an override requires an interactive Julia editor session.");
+      setOverrideApplication(null);
       return;
     }
+    sendCommand({
+      action: "edit",
+      kind: value.scope === "instance" ? "set_instance_override" : "set_object_override",
+      ...value,
+    });
+    setOverrideApplication(null);
+  }, [connected, sendCommand]);
 
-    setPinnedFocus(null);
-    setSelectedEdge(null);
-    if (warning.edgeId) {
-      const edge = graph.edges.find((item) => item.id === warning.edgeId);
-      if (edge) focusEdge(edge);
+  const removeOverride = useCallback((value: OverrideFormValue) => {
+    if (!connected) {
+      setFeedback("Removing an override requires an interactive Julia editor session.");
       return;
     }
-    if (warning.portId) {
-      const target = portById.get(warning.portId);
-      if (target) focusNode(target.node, target.port);
+    sendCommand({
+      action: "edit",
+      kind: value.scope === "instance" ? "remove_instance_override" : "remove_object_override",
+      ...value,
+    });
+    setOverrideApplication(null);
+  }, [connected, sendCommand]);
+
+  const connectPorts = useCallback((connection: Connection) => {
+    if (!connection.sourceHandle || !connection.targetHandle) return;
+    const source = portIndex.get(connection.sourceHandle);
+    const target = portIndex.get(connection.targetHandle);
+    if (!source || !target || source.port.role !== "output" || target.port.role !== "input") {
+      setFeedback("Connect an application output to an application input.");
       return;
     }
-    if (warning.nodeId) {
-      const node = nodeById.get(warning.nodeId);
-      if (node) focusNode(node);
+    setBindingForm({
+      sourceApplication: source.application,
+      sourcePort: source.port,
+      targetApplication: target.application,
+      targetPort: target.port,
+    });
+    setBindingPreview(null);
+  }, [portIndex]);
+
+  const activeInitialization = useMemo(() => {
+    if (!selected) return graph.initialization;
+    if ("applicationId" in selected) return graph.initialization.filter((row) => row.applicationId === selected.applicationId);
+    if ("objectId" in selected) return graph.initialization.filter((row) => String(row.objectId) === String(selected.objectId));
+    if ("objectIds" in selected) {
+      const ids = new Set(selected.objectIds.map(objectKey));
+      return graph.initialization.filter((row) => ids.has(objectKey(row.objectId)));
     }
-  }, [flowInstance, focusEdge, focusNode, graph.edges, nodeById, nodes, portById]);
+    return graph.initialization;
+  }, [graph.initialization, selected]);
 
   return (
-    

-      

-        

-          
-
-          

-            
PlantSimEngine

-            
Dependency Graph

-          

-
-          

-            
-             {
-                setSearchQuery(event.target.value);
-                setShowSearchResults(true);
-              }}
-              onFocus={() => setShowSearchResults(true)}
-            />
-            {searchQuery && (
-              
-            )}
-            {showSearchResults && searchQuery.trim().length > 0 && (
-              

-                {searchResults.length > 0 ? searchResults.map((result) => (
-                  
-                )) : 
No match.
}
-              

-            )}
-          

-
-          

-            {visibleNodeData.length}/{graph.nodes.length} models
-            {visibleEdgeData.length}/{graph.edges.length} links
-            {requiredInputs.length > 0 && (
-              
-            )}
-            {actionableWarningItems.length > 0 && (
-              
-            )}
-            {graph.cyclic &&  cycle}
-          

-
-          

-            
-            
-            
-            
-          

-
-          

-            
-            }
+        

+        

+          {graph.metadata.applicationCount} applications
+          {graph.metadata.objectCount} objects
+          {graph.metadata.unresolvedInitializationCount > 0 && (
+            
+          )}
+          {graph.diagnostics.length > 0 && (
+            
+          )}
+        

+        
+        

+          {editorConfig && }
+          {editorConfig && }
+          {view !== "topology" && (
+            
-          

-
-          

-            
-            {editorSocket && (
-              <>
-                
-                
-                
-              
-            )}
-          

-
-          {editorSocket && (
-            

-              {editorConnected ? "live" : "offline"}
-              
-              
-            

           )}
+          {editorConfig && }
+          {editorConfig && }
+          {editorConfig && graph.templates.length > 0 && }
+          {editorConfig && }
+          {editorConfig && }
+          {editorConfig && }
+          
         

+      
 
-        {editorFeedback && (
-          

-            {editorFeedback.text}
-          

-        )}
-
-        {graph.cyclic && (
-          
-        )}
-
-        {showRelationshipsPanel && }
-        {showScalesPanel && }
-
-        {showRequiredPanel && (
-           setShowRequiredPanel(false)}>
-            
-          
-        )}
-
-        {showWarningsPanel && (
-           setShowWarningsPanel(false)}>
-            
-          
-        )}
-
-        {showOpenPanel && (
-           {
-              sendEditorCommand({ action: "open_mapping_code", path });
-              setShowOpenPanel(false);
+      {graph.metadata.cyclic && (
+        

+          
+          
Current-step dependency cycleSelect a cycle input to read its previous accepted timestep value.

+          
+        

+      )}
+      {feedback && 
{feedback}
}
+      {scopeFilter && (
+        

+          Showing {view === "resolved" ? "executions" : view === "applications" ? "applications" : "topology"} for {scopeFilter.label} ({scopeFilter.objectIds.length} objects)
+          {view === "topology" && }
+          
+        

+      )}
 
-         {
-            setShowSearchResults(false);
-            setCandidatePopover(null);
-            setShowOpenPanel(false);
-            setShowRelationshipsPanel(false);
-            setShowScalesPanel(false);
-          }}
-          onEdgeClick={(_, edge) => {
-            if (edge.data) {
-              setCandidatePopover(null);
-              setSelectedEdge(edge.data);
-              setSelected(null);
-              setActivePort(null);
-              setPinnedFocus(null);
-              setActivePanel("inspector");
-            }
-          }}
-          onNodeClick={(_, node) => {
-            setCandidatePopover(null);
-            setSelectedEdge(null);
-            setSelected(node.data);
-            setActivePanel("inspector");
+      

+        

+           setSelected(edge.data ?? null)}
+            fitView
+            minZoom={0.05}
+            maxZoom={2}
+          >
+            
+            
+            
+          
+        

+         {
+            setTargetPreview(null);
+            setApplicationForm({
+              mode: "update",
+              application,
+            });
           }}
-          fitView
-          fitViewOptions={{ padding: viewMode === "overview" ? 0.14 : 0.08, minZoom: 0.03, maxZoom: viewMode === "overview" ? 1.25 : 1 }}
-          minZoom={0.03}
-          maxZoom={2}
-        >
-          
-          
-          
-        
-
-        {candidatePopoverInfo && (
-           {
-              const requestId = Date.now();
-              setAddModelSelection({
-                modelType: model.type,
-                scale: candidatePopoverInfo.node.scale,
-                requestId,
-              });
-              setAddModelFocusRequest(requestId);
-              setHighlightAddModelPanel(true);
-              setActivePanel("add_model");
-              setCandidatePopover(null);
-            }}
-            onClose={() => setCandidatePopover(null)}
-          />
-        )}
+          onRemoveApplication={(application) => sendCommand({
+            action: "edit",
+            kind: "remove_application",
+            applicationRef: application.owner,
+          })}
+          onConfigureApplication={(application) => setConfigurationApplicationId(application.applicationId)}
+          onOverrideApplication={setOverrideApplication}
+          onRemoveInstance={(instance) => sendCommand({ action: "edit", kind: "remove_instance", name: instance.name })}
+          onEditObject={(object) => setObjectForm({ mode: "update", object })}
+          onRemoveObject={(object) => sendCommand({ action: "edit", kind: "remove_object", objectId: object.objectId, recursive: true })}
+        />
       

 
-      {activePanel && (
-        
+      {candidate && (candidateModels.length > 0 || candidateApplications.length > 0) && (
+         {
+            setBindingForm(endpointsForCandidate(candidate, application));
+            setBindingPreview(null);
+            setCandidate(null);
+          }}
+          onClose={() => setCandidate(null)}
+        />
       )}
-
-      {pendingConnection && (
-         {
-            sendEditorCommand(command);
-            setPendingConnection(null);
+      {showDiagnostics &&  setShowDiagnostics(false)} sendCommand={sendCommand} interactive={connected} />}
+      {showInitialization &&  setShowInitialization(false)} sendCommand={sendCommand} interactive={connected} />}
+      {showModelCode &&  setShowModelCode(false)} />}
+      {showOpen &&  { sendCommand({ action: "open_model_code", path }); setShowOpen(false); }} onClose={() => setShowOpen(false)} />}
+      {showSave &&  { sendCommand({ action: "save_model_code", path }); setShowSave(false); }} onClose={() => setShowSave(false)} />}
+      {applicationForm && (
+         { setTargetPreview(null); sendCommand({ action: "preview_application_targets", selector, applicationRef: applicationForm.application?.owner }); }}
+          onSubmit={submitApplication}
+          onClose={() => { setApplicationForm(null); setTargetPreview(null); }}
+        />
+      )}
+      {bindingForm && (
+         { setBindingPreview(null); sendCommand({ action: "preview_input_binding", ...value }); }}
+          onSubmit={submitBinding}
+          onClose={() => { setBindingForm(null); setBindingPreview(null); }}
+        />
+      )}
+      {objectForm && (
+         setObjectForm(null)} />
+      )}
+      {showInstanceForm && (
+         { setInstancePreview(null); sendCommand({ action: "preview_instance", ...value }); }} onSubmit={submitInstance} onClose={() => { setShowInstanceForm(false); setInstancePreview(null); }} />
+      )}
+      {showEnvironmentForm && (
+         { sendCommand({ action: "edit", kind: "set_model_environment", environmentId }); setShowEnvironmentForm(false); }} onClose={() => setShowEnvironmentForm(false)} />
+      )}
+      {overrideApplication && (
+         setOverrideApplication(null)} />
+      )}
+      {configurationApplicationId && applicationById.get(configurationApplicationId) && (
+         setConfigurationApplicationId(null)} />
+      )}
+      {cycleBreakSelection && (
+         {
+            sendCommand({
+              action: "edit",
+              kind: "break_cycle",
+              applicationRef: cycleBreakSelection.application.owner,
+              input: cycleBreakSelection.port.name,
+              initializeMissing,
+              initialValue,
+            });
+            setCycleBreakSelection(null);
           }}
-          onCancel={() => setPendingConnection(null)}
+          onClose={() => setCycleBreakSelection(null)}
         />
       )}
     

   );
 }
 
-function MappingDialog({
-  connection,
-  scales,
-  onConfirm,
-  onCancel,
+function buildNodes({
+  graph,
+  view,
+  detailMode,
+  query,
+  scopedObjectIds,
+  unresolvedPortIds,
+  previousPortIds,
+  candidatePortIds,
+  cyclicApplications,
+  cycleBreakPortIds,
+  cycleBreakMode,
+  openCandidates,
+  onPortClick,
+  onCycleBreak,
 }: {
-  connection: PendingMappingConnection;
-  scales: string[];
-  onConfirm: (command: Record) => void;
-  onCancel: () => void;
-}) {
-  const [mode, setMode] = useState<"single" | "multi">("single");
-  const [selectedScales, setSelectedScales] = useState([connection.sourceNode.scale]);
+  graph: ModelGraphView;
+  view: GraphViewMode;
+  detailMode: DetailMode;
+  query: string;
+  scopedObjectIds: Set | null;
+  unresolvedPortIds: Set;
+  previousPortIds: Set;
+  candidatePortIds: Set;
+  cyclicApplications: Set;
+  cycleBreakPortIds: Set;
+  cycleBreakMode: boolean;
+  openCandidates: (application: ApplicationGraphNode, port: GraphPort, anchor: { x: number; y: number }) => void;
+  onPortClick: (port: GraphPort) => void;
+  onCycleBreak: (application: ApplicationGraphNode, port: GraphPort) => void;
+}): FlowNode[] {
+  const matches = (value: unknown) => !query || JSON.stringify(value).toLowerCase().includes(query.toLowerCase());
+  if (view === "topology") {
+    const modelDetail: ModelRootDescriptor = {
+      entity: "model",
+      objectCount: graph.metadata.objectCount,
+      instanceCount: graph.metadata.instanceCount,
+      applicationCount: graph.metadata.applicationCount,
+    };
+    const modelNode: FlowNode = {
+      id: "model:root",
+      type: "entity",
+      position: { x: 0, y: 0 },
+      data: {
+        nodeKind: "model",
+        title: graph.metadata.title || "Composite model",
+        subtitle: "model root",
+        badges: [`${graph.metadata.instanceCount} instances`, `${graph.metadata.objectCount} objects`],
+        detail: modelDetail,
+      },
+    };
+    const templateNodes: FlowNode[] = graph.templates.filter(matches).map((template) => ({
+      id: `template:${template.id}`,
+      type: "entity",
+      position: { x: 0, y: 0 },
+      data: {
+        nodeKind: "template",
+        title: template.name,
+        subtitle: template.source === "catalog" ? "template preset" : "model-local template",
+        badges: [`${template.applications.length} applications`, `${template.mountedInstances.length} mounts`],
+        detail: template,
+      },
+    }));
+    const instanceNodes: FlowNode[] = graph.instances.filter(matches).map((instance) => ({
+      id: instance.id,
+      type: "entity",
+      position: { x: 0, y: 0 },
+      data: {
+        nodeKind: "instance",
+        title: instance.name,
+        subtitle: [instance.kind, instance.species].filter(Boolean).join(" · ") || "object instance",
+        badges: [`${instance.objectIds.length} objects`, `${instance.applicationIds.length} applications`, `${instance.instanceOverrides.length + instance.objectOverrides.length} overrides`],
+        detail: instance,
+      },
+    }));
+    const objectNodes: FlowNode[] = graph.objects.filter(matches).map((object) => ({
+      id: object.id,
+      type: "entity",
+      position: { x: 0, y: 0 },
+      data: {
+        nodeKind: "object",
+        title: object.name || String(object.objectId),
+        subtitle: [object.kind, object.scale, object.instance].filter(Boolean).join(" · "),
+        badges: [object.species, object.hasStatus ? "status" : null, object.hasGeometry ? "geometry" : null].filter(Boolean) as string[],
+        detail: object,
+      },
+    }));
+    return [modelNode, ...templateNodes, ...instanceNodes, ...objectNodes];
+  }
+  if (view === "resolved") {
+    const applications = new Map(graph.applications.map((application) => [application.applicationId, application]));
+    const executionNodes: FlowNode[] = graph.executions
+      .filter((execution) => !scopedObjectIds || scopedObjectIds.has(objectKey(execution.objectId)))
+      .filter(matches).map((execution) => {
+      const application = applications.get(execution.applicationId);
+      return {
+        id: execution.id,
+        type: "entity",
+        position: { x: 0, y: 0 },
+        data: {
+          nodeKind: "execution",
+          title: execution.applicationId,
+          subtitle: `object ${String(execution.objectId)}`,
+          badges: [shortType(execution.modelType), execution.overridden ? "override" : "shared"],
+          inputPortIds: [...(application?.inputs ?? []), ...(application?.environmentInputs ?? [])].map((port) => port.id),
+          outputPortIds: [...(application?.outputs ?? []), ...(application?.environmentOutputs ?? [])].map((port) => port.id),
+          detail: execution,
+        },
+      };
+    });
+    return [...executionNodes, ...environmentNodes(graph, "resolved")];
+  }
+  const applicationNodes: FlowNode[] = graph.applications
+    .filter((application) => !scopedObjectIds || application.targetIds.some((id) => scopedObjectIds.has(objectKey(id))))
+    .filter(matches).map((application) => ({
+    id: application.id,
+    type: "application",
+    position: { x: 0, y: 0 },
+    data: {
+      ...application,
+      nodeKind: "application",
+      detailMode,
+      cyclic: cyclicApplications.has(application.applicationId),
+      requiredInputPortIds: application.inputs.filter((port) => unresolvedPortIds.has(port.id)).map((port) => port.id),
+      candidatePortIds: [...application.inputs, ...application.outputs].filter((port) => candidatePortIds.has(port.id)).map((port) => port.id),
+      previousTimeStepPortIds: application.inputs.filter((port) => previousPortIds.has(port.id)).map((port) => port.id),
+      cycleBreakInputPortIds: application.inputs.filter((port) => cycleBreakPortIds.has(port.id)).map((port) => port.id),
+      cycleBreakMode,
+      onCandidateClick: (port, anchor) => openCandidates(application, port, anchor),
+      onPortClick,
+      onCycleBreak,
+    },
+  }));
+  return [...applicationNodes, ...environmentNodes(graph, "applications")];
+}
+
+function environmentNodes(graph: ModelGraphView, projection: "applications" | "resolved"): FlowNode[] {
+  const relevant = graph.edges.filter((edge) => edge.kind === "environment_binding" && edge.projection === projection);
+  const ids = new Set(relevant.flatMap((edge) => [edge.source, edge.target]).filter((id) => id.startsWith("environment:")));
+  return [...ids].map((id) => {
+    const provider = id.slice("environment:".length);
+    const descriptor = graph.environments.find((environment) => environment.id === id);
+    const inputs = uniqueStrings(relevant.filter((edge) => edge.target === id).map((edge) => edge.targetPort).filter(Boolean) as string[]);
+    const outputs = uniqueStrings(relevant.filter((edge) => edge.source === id).map((edge) => edge.sourcePort).filter(Boolean) as string[]);
+    return {
+      id,
+      type: "entity",
+      position: { x: 0, y: 0 },
+      data: {
+        nodeKind: "environment",
+        title: descriptor?.name || provider,
+        subtitle: descriptor?.active ? "active scene environment" : "environment backend",
+        badges: [`${outputs.length} inputs`, `${inputs.length} outputs`],
+        inputPortIds: inputs,
+        outputPortIds: outputs,
+        detail: descriptor || { provider },
+      },
+    };
+  });
+}
 
-  const toggleScale = (scale: string) => {
-    setSelectedScales((current) =>
-      current.includes(scale) ? current.filter((s) => s !== scale) : [...current, scale]
-    );
-  };
+function uniqueStrings(values: string[]) { return [...new Set(values)]; }
+
+function buildEdges(graph: ModelGraphView, view: GraphViewMode): FlowEdge[] {
+  const sourceEdges = view === "topology" ? [...graph.edges, ...topologyContainerEdges(graph)] : graph.edges;
+  return sourceEdges
+    .filter((edge) => edgeProjectionMatches(edge, view))
+    .map((edge) => ({
+      id: edge.id,
+      source: edge.source,
+      target: edge.target,
+      sourceHandle: edge.sourcePort || undefined,
+      targetHandle: edge.targetPort || undefined,
+      type: "modelEdge",
+      data: edge,
+      markerEnd: { type: MarkerType.ArrowClosed, color: edgeColor(edge), width: 16, height: 16 },
+      style: {
+        stroke: edgeColor(edge),
+        strokeWidth: edge.cycle ? 4 : edge.kind === "manual_call" ? 2.5 : 1.8,
+        strokeDasharray: edge.kind === "previous_timestep" ? "7 5" : edge.kind === "manual_call" ? "3 4" : undefined,
+      },
+    }));
+}
 
-  const handleConfirm = () => {
-    const command: Record = {
-      action: "edit",
-      kind: "set_mapped_variable",
-      scale: connection.targetNode.scale,
-      process: connection.targetNode.process,
-      variable: connection.targetPort.name,
-      sourceScale: connection.sourceNode.scale,
-      sourceVariable: connection.sourcePort.name,
-      mode: mode === "single" && connection.sourceNode.scale === connection.targetNode.scale ? "same_scale" : mode,
-    };
-    if (mode === "multi") {
-      const extras = selectedScales.filter((s) => s !== connection.sourceNode.scale);
-      if (extras.length > 0) command.extraSourceScales = extras;
+function topologyContainerEdges(graph: ModelGraphView): ModelGraphEdge[] {
+  const edges: ModelGraphEdge[] = [];
+  const instanceObjectIds = new Set(graph.instances.flatMap((instance) => instance.objectIds.map(objectKey)));
+  for (const template of graph.templates) {
+    edges.push({
+      id: `topology:model:template:${template.id}`,
+      source: "model:root",
+      target: `template:${template.id}`,
+      kind: "object_topology",
+      projection: "topology",
+      cycle: false,
+    });
+  }
+  for (const instance of graph.instances) {
+    edges.push({
+      id: `topology:${instance.id}:object:${String(instance.rootId)}`,
+      source: instance.id,
+      target: `object:${String(instance.rootId)}`,
+      kind: "object_topology",
+      projection: "topology",
+      cycle: false,
+    });
+  }
+  for (const object of graph.objects) {
+    if (object.parent === null && !instanceObjectIds.has(objectKey(object.objectId))) {
+      edges.push({
+        id: `topology:model:${object.id}`,
+        source: "model:root",
+        target: object.id,
+        kind: "object_topology",
+        projection: "topology",
+        cycle: false,
+      });
     }
-    onConfirm(command);
-  };
+  }
+  return edges;
+}
 
-  return (
-    

-      
 e.stopPropagation()}>
-        

-          
Variable Mapping

-          
-        

+export function objectSubtreeIds(objects: ObjectGraphNode[], rootId: unknown): unknown[] {
+  const children = new Map();
+  for (const object of objects) {
+    if (object.parent === null) continue;
+    const key = objectKey(object.parent);
+    children.set(key, [...(children.get(key) ?? []), object.objectId]);
+  }
+  const result: unknown[] = [];
+  const pending: unknown[] = [rootId];
+  const visited = new Set();
+  while (pending.length > 0) {
+    const id = pending.pop()!;
+    const key = objectKey(id);
+    if (visited.has(key)) continue;
+    visited.add(key);
+    result.push(id);
+    pending.push(...(children.get(key) ?? []));
+  }
+  return result;
+}
 
-        

-          

-            

-              Source
-              {connection.sourceNode.scale}
-              {connection.sourceNode.process}.{connection.sourcePort.name}
-            

-            
->

-            

-              Target
-              {connection.targetNode.scale}
-              {connection.targetNode.process}.{connection.targetPort.name}
-            

-          

+function objectKey(value: unknown) {
+  const text = String(value);
+  return text.startsWith("object:") ? text.slice("object:".length) : text;
+}
 
-          

-            
Mapping mode

-            
-            
-          

+function edgeProjectionMatches(edge: ModelGraphEdge, view: GraphViewMode) {
+  const projection = (edge as ModelGraphEdge & { projection?: string }).projection;
+  if (view === "topology") return edge.kind === "object_topology" || edge.kind === "template_mount";
+  if (view === "resolved") return projection === "resolved";
+  return projection === "applications" || (!projection && !["object_topology", "application_target"].includes(edge.kind));
+}
 
-          {mode === "multi" && (
-            

-              
Source scales

-              {scales.map((scale) => (
-                
-              ))}
-            

-          )}
-        

+function edgeColor(edge: ModelGraphEdge) {
+  if (edge.cycle) return "#cf4937";
+  if (edge.kind === "previous_timestep") return "#317b62";
+  if (edge.kind === "manual_call") return "#be6a54";
+  if (edge.kind === "object_topology") return "#7b7167";
+  if (edge.kind === "environment_binding") return "#367b8b";
+  return "#a59687";
+}
 
-        

-          
-          
-        

-      

-    

-  );
+export function deriveCandidatePortIds(graph: ModelGraphView) {
+  const result = new Set();
+  for (const application of graph.applications) {
+    for (const input of application.inputs) {
+      const existing = graph.applications.some((other) =>
+        other.applicationId !== application.applicationId && other.outputs.some((output) => output.name === input.name)
+      );
+      if (existing || graph.modelLibrary.some((model) => Object.prototype.hasOwnProperty.call(model.outputs, input.name))) result.add(input.id);
+    }
+    for (const output of application.outputs) {
+      const existing = graph.applications.some((other) =>
+        other.applicationId !== application.applicationId && other.inputs.some((input) => input.name === output.name)
+      );
+      if (existing || graph.modelLibrary.some((model) => Object.prototype.hasOwnProperty.call(model.inputs, output.name))) result.add(output.id);
+    }
+  }
+  return result;
 }
 
-function RelationshipLegend({ filters, onToggle }: { filters: EdgeFilters; onToggle: (key: EdgeFilterKey) => void }) {
-  return (
-    

-      
 Relationships

-      
-      
-      
-      
 red inputs need initialization

-    

-  );
+export function modelsForPort(library: ModelDescriptor[], port: GraphPort) {
+  const field = port.role === "input" ? "outputs" : "inputs";
+  return library
+    .filter((model) => Object.prototype.hasOwnProperty.call(model[field], port.name))
+    .sort((left, right) => `${left.package}.${left.name}`.localeCompare(`${right.package}.${right.name}`));
 }
 
-function ScaleControls({
-  scales,
-  collapsedScales,
-  onToggle,
-  onExpandAll,
+function CandidatePopover({
+  candidate,
+  models,
+  applications,
+  onSelectModel,
+  onSelectApplication,
+  onClose,
 }: {
-  scales: string[];
-  collapsedScales: Set;
-  onToggle: (scale: string) => void;
-  onExpandAll: () => void;
+  candidate: CandidatePopover;
+  models: ModelDescriptor[];
+  applications: ApplicationGraphNode[];
+  onSelectModel: (model: ModelDescriptor) => void;
+  onSelectApplication: (application: ApplicationGraphNode) => void;
+  onClose: () => void;
 }) {
+  const title = candidate.port.role === "input" ? `Models that compute ${candidate.port.name}` : `Models that consume ${candidate.port.name}`;
   return (
-    

-      
 Scales

-      

-        {scales.map((scale) => {
-          const collapsed = collapsedScales.has(scale);
-          return (
-            
-          );
-        })}
+    

+      
{title}Exact declared variable-name matches

+      

+        {applications.length > 0 && 
Existing applications
}
+        {applications.map((application) => (
+          
+        ))}
+        {models.length > 0 && 
Available models
}
+        {models.map((model) => (
+          
+        ))}
       

-      {collapsedScales.size > 0 && }
-    

+    
   );
 }
 
-function FloatingPanel({ className, title, subtitle, onClose, children }: { className: string; title: string; subtitle: string; onClose: () => void; children: ReactNode }) {
-  return (
-    

-      

-        

-          
{title}

-          
{subtitle}

-        

-        
-      

-      {children}
-    

-  );
+export function applicationsForPort(applications: ApplicationGraphNode[], candidate: CandidatePopover) {
+  return applications
+    .filter((application) => application.applicationId !== candidate.application.applicationId)
+    .filter((application) => {
+      const ports = candidate.port.role === "input" ? application.outputs : application.inputs;
+      return ports.some((port) => port.name === candidate.port.name);
+    })
+    .sort((left, right) => left.applicationId.localeCompare(right.applicationId));
+}
+
+export function endpointsForCandidate(candidate: CandidatePopover, application: ApplicationGraphNode): BindingEndpoints {
+  if (candidate.port.role === "input") {
+    const sourcePort = application.outputs.find((port) => port.name === candidate.port.name);
+    if (!sourcePort) throw new Error(`Application ${application.applicationId} does not output ${candidate.port.name}.`);
+    return { sourceApplication: application, sourcePort, targetApplication: candidate.application, targetPort: candidate.port };
+  }
+  const targetPort = application.inputs.find((port) => port.name === candidate.port.name);
+  if (!targetPort) throw new Error(`Application ${application.applicationId} does not input ${candidate.port.name}.`);
+  return { sourceApplication: candidate.application, sourcePort: candidate.port, targetApplication: application, targetPort };
 }
 
-function RequiredInputList({ groups, onSelect, compact = false }: { groups: Map; onSelect: (node: GraphNodeData, port?: GraphPort | null) => void; compact?: boolean }) {
-  if (groups.size === 0) return 
Every input is computed by another model.
;
+function Inspector({ selection, port, initialization, interactive, onEditApplication, onConfigureApplication, onRemoveApplication, onOverrideApplication, onRemoveInstance, onEditObject, onRemoveObject }: { selection: InspectorSelection; port: GraphPort | null; initialization: ModelGraphView["initialization"]; interactive: boolean; onEditApplication: (application: ApplicationGraphNode) => void; onConfigureApplication: (application: ApplicationGraphNode) => void; onRemoveApplication: (application: ApplicationGraphNode) => void; onOverrideApplication: (application: ApplicationGraphNode) => void; onRemoveInstance: (instance: InstanceDescriptor) => void; onEditObject: (object: ObjectGraphNode) => void; onRemoveObject: (object: ObjectGraphNode) => void }) {
+  const application = selection && "applicationId" in selection && "selector" in selection ? selection as ApplicationGraphNode : null;
+  const object = selection && "objectId" in selection && !("applicationId" in selection) ? selection as ObjectGraphNode : null;
+  const instance = selection && "templateId" in selection && "objectIds" in selection ? selection as InstanceDescriptor : null;
   return (
-    

-      {[...groups.entries()].map(([group, items]) => (
-        

-          
{group}

-          {items.map(({ node, port, reason }) => (
-            
-          ))}
-        

-      ))}
-    

+    
   );
 }
 
-function WarningList({
-  warnings,
-  onFocusWarning,
-}: {
-  warnings: ValidationWarning[];
-  onFocusWarning: (warning: ValidationWarning) => void;
-}) {
-  if (warnings.length === 0) return 
No validation warnings.
;
-  const grouped = groupValidationWarnings(warnings);
-  return (
-    

-      {(["error", "warning", "info"] as const).map((severity) => {
-        const items = grouped.get(severity) ?? [];
-        if (items.length === 0) return null;
-        return (
-          

-            
{validationSeverityLabel(severity)} ({items.length})

-            {items.map((warning) => (
-              
-            ))}
-          

-        );
-      })}
+function DiagnosticsPanel({ graph, onClose, sendCommand, interactive }: { graph: ModelGraphView; onClose: () => void; sendCommand: (command: Record) => void; interactive: boolean }) {
+  return 
+    {graph.diagnostics.map((diagnostic) => 
{diagnostic.code}
{diagnostic.message}
{diagnostic.suggestions.map((suggestion) => {suggestion})}
)}
+    {graph.cycles.map((cycle) => 
{cycle.applicationIds.join(" → ")}
Choose an input to read from the previous timestep.
{cycle.breakCandidates.map((candidate) => { const owner = graph.applications.find((application) => application.applicationId === candidate.applicationId)?.owner; return ; })}
)}
+    {graph.diagnostics.length === 0 && graph.cycles.length === 0 && 
No diagnostics.
}
+  ;
+}
+
+function InitializationPanel({ graph, onClose, sendCommand, interactive }: { graph: ModelGraphView; onClose: () => void; sendCommand: (command: Record) => void; interactive: boolean }) {
+  const unresolved = graph.initialization.filter((row) => row.disposition === "unresolved");
+  const groups = new Map();
+  for (const row of unresolved) {
+    const key = `${row.applicationId}:${row.variable}`;
+    groups.set(key, [...(groups.get(key) || []), row]);
+  }
+  return 
+    {[...groups.entries()].map(([key, rows]) => )}
+    {unresolved.length === 0 && 
No unresolved initial values.
}
+  ;
+}
+
+function InitializationGroup({ rows, interactive, sendCommand }: { rows: ModelGraphView["initialization"]; interactive: boolean; sendCommand: (command: Record) => void }) {
+  const [valueType, setValueType] = useState("float");
+  const [value, setValue] = useState("");
+  const first = rows[0];
+  const typedValue = { type: valueType, value };
+  return 

+    
{first.variable}{first.applicationId}
{rows.length} object{rows.length === 1 ? "" : "s"} · expected {first.expectedType}

+    
Required because the input has no producer, environment source, status value, or usable temporal initialization.

+    {interactive && 
}
+    
{rows.map((row) => 
Object {String(row.objectId)}{row.origin}{interactive && }
)}

+  
;
+}
+
+function SceneCodePanel({ code, onClose }: { code: string; onClose: () => void }) {
+  return 
{code || "Model code is available from an interactive editor session."}
;
+}
+
+function SceneFileDialog({ mode, recentPaths, currentPath, autosavePath, onSubmit, onClose }: { mode: "open" | "save"; recentPaths: string[]; currentPath: string | null; autosavePath: string | null; onSubmit: (path: string) => void; onClose: () => void }) {
+  const [path, setPath] = useState(currentPath || "");
+  return 
+    

+      
{mode === "open" ? "Open a Julia script whose final binding is `model = CompositeModel(...)`. Future edits will be saved back to that file." : "After the first save, every successful graph edit automatically rewrites this Julia script."}

+      
+      {mode === "open" && recentPaths.length > 0 && 
Recent models
{recentPaths.map((recent) => )}
}
+      {mode === "open" && autosavePath && 
Recovery autosave
}
+      Use Git to version saved composite-model scripts and review scientific configuration changes.
     

-  );
+  ;
 }
 
-function OpenMappingPanel({
-  recentMappings,
-  disabled,
-  onOpen,
+function CycleBreakDialog({
+  selection,
+  initialization,
+  onSubmit,
   onClose,
 }: {
-  recentMappings: string[];
-  disabled: boolean;
-  onOpen: (path: string) => void;
+  selection: CycleBreakSelection;
+  initialization: ModelGraphView["initialization"];
+  onSubmit: (initializeMissing: boolean, initialValue: { type: string; value: string } | null) => void;
   onClose: () => void;
 }) {
-  const [path, setPath] = useState("");
-
-  const openPath = () => {
-    const trimmed = path.trim();
-    if (!trimmed) return;
-    onOpen(trimmed);
-  };
-
-  return (
-    
-      

-        
-        

-          

-            Recent mappings
-          

-          {recentMappings.length > 0 ? (
-            

-              {recentMappings.map((item) => (
-                
-              ))}
-            

-          ) : 
No recent mapping.
}
-        

-      

-    
+  const missing = initialization.filter((row) =>
+    row.applicationId === selection.application.applicationId &&
+    row.variable === selection.port.name &&
+    row.disposition !== "supplied"
   );
-}
-
-function CycleBreakPrompt({
-  active,
-  optionCount,
-  editorConnected,
-  onChoose,
-}: {
-  active: boolean;
-  optionCount: number;
-  editorConnected: boolean;
-  onChoose: () => void;
-}) {
-  return (
-    

-      

-        Cycle detected
-        
-          Choose which variable to decouple. The selected input will be wrapped in PreviousTimeStep, so that model uses the value from the previous timestep and is disconnected from this current-step variable within a run.
-        
+  const [valueType, setValueType] = useState("float");
+  const [value, setValue] = useState("");
+  return 

+    
 event.stopPropagation()} data-testid="cycle-break-dialog">
+      
Break the current-step cycle{selection.application.applicationId}.{selection.port.name}

+      

+        
This changes the application input to read its value from the previous accepted timestep. The model is disconnected from the current value during each run step.

+        
Application-wide changeIt affects all {selection.application.targetCount} targets selected by this application.

+        {missing.length > 0 && 
Required initial value
{missing.length} target{missing.length === 1 ? "" : "s"} need a value before the first timestep.
}
       

-      
-    

-  );
+      

+    
+  
;
 }
 
-function InspectorDetails({
-  selected,
-  selectedEdge,
-  activePort,
-  requiredInputPortIds,
-  incomingEdges,
-  outgoingEdges,
-  nodeById,
-  portById,
-  graphNodes,
-  onFocusEdge,
-  models,
-  scales,
-  onAddScale,
-  onCommand,
-  editorConnected,
-}: {
-  selected: GraphNodeData | null;
-  selectedEdge: GraphEdgeData | null;
-  activePort: GraphPort | null;
-  requiredInputPortIds: Set;
-  incomingEdges: GraphEdgeData[];
-  outgoingEdges: GraphEdgeData[];
-  nodeById: Map;
-  portById: Map;
-  graphNodes: GraphNodeData[];
-  onFocusEdge: (edge: GraphEdgeData) => void;
-  models: ModelDescriptor[];
-  scales: string[];
-  onAddScale: (scale: string) => void;
-  onCommand: (command: Record) => void;
-  editorConnected: boolean;
-}) {
-  return (
-    <>
-      {selectedEdge && (
-        
-      )}
-      {selected ? (
-        

-          
-          
-          
-          
-           port.name).join(", ") || "none"} />
-           port.name).join(", ") || "none"} />
-          {selected.inputs.filter((port) => requiredInputPortIds.has(port.id)).map((port) => (
-            
 {port.name} must be initialized

-          ))}
-          {selected.inputs.filter((port) => port.previousTimeStep).map((port) => (
-            
 {port.name} uses previous timestep

-          ))}
-          {selected.role === "model" && (
-            
-          )}
-        

-      ) : !selectedEdge ? (
-        
Select a model node.

-      ) : null}
-
-      
Variable Provenance

-      {activePort ? (
-        

-          

-            {activePort.name}
-            {activePort.role}
-          

-          
-          {activePort.mappingMode && }
-          {activePort.sourceScale && }
-          {requiredInputPortIds.has(activePort.id) && 
 required initialization
}
-          {activePort.previousTimeStep && 
 uses previous timestep
}
-          
-          
-          {activePort.role === "input" && (
-            
-          )}
-        

-      ) : (
-        
Hover, click, or search a variable to see where it comes from and where it goes.

-      )}
-    
-  );
-}
-
-function EdgeDetails({
-  edge,
-  nodeById,
-  portById,
-  onCommand,
-  editorConnected,
-}: {
-  edge: GraphEdgeData;
-  nodeById: Map;
-  portById: Map;
-  onCommand: (command: Record) => void;
-  editorConnected: boolean;
-}) {
-  const source = nodeById.get(edge.source);
-  const target = nodeById.get(edge.target);
-  const sourcePort = edge.sourcePort ? portById.get(edge.sourcePort)?.port : null;
-  const targetPort = edge.targetPort ? portById.get(edge.targetPort)?.port : null;
-  const breakable = isCycleEdge(edge) && target && targetPort && targetPort.role === "input";
-  return (
-    

-      

-        {edgeKindLabel(edge)}
-        {edge.scaleRelation}
-      

-      
-      
-      
-      
-      
-      
-      {breakable && (
-        
-      )}
-      {edge.diagnostics.length > 0 ? edge.diagnostics.map((item) => (
-        
{item}

-      )) : 
No edge diagnostics.
}
-    

-  );
-}
-
-function EdgeList({
-  title,
-  edges,
-  direction,
-  nodeById,
-  portById,
-  onFocusEdge,
-}: {
-  title: string;
-  edges: GraphEdgeData[];
-  direction: "incoming" | "outgoing";
-  nodeById: Map;
-  portById: Map;
-  onFocusEdge: (edge: GraphEdgeData) => void;
-}) {
-  return (
-    

-      
{title}

-      {edges.length > 0 ? edges.map((edge) => {
-        const source = nodeById.get(edge.source);
-        const target = nodeById.get(edge.target);
-        const sourcePort = edge.sourcePort ? portById.get(edge.sourcePort)?.port : null;
-        const targetPort = edge.targetPort ? portById.get(edge.targetPort)?.port : null;
-        const main = direction === "incoming"
-          ? `${source?.scale ?? "?"}.${source?.process ?? "?"}.${sourcePort?.name ?? edge.sourceVariable ?? "model"}`
-          : `${target?.scale ?? "?"}.${target?.process ?? "?"}.${targetPort?.name ?? edge.targetVariable ?? "model"}`;
-        return (
-          
-        );
-      }) : 
No {title.toLowerCase()} edge.
}
-    

-  );
-}
-
-function ModelCandidatePopover({
-  anchor,
-  title,
-  variable,
-  role,
-  models,
-  onSelectModel,
-  onClose,
-}: {
-  anchor: { x: number; y: number };
-  title: string;
-  variable: string;
-  role: "input" | "output";
-  models: ModelDescriptor[];
-  onSelectModel: (model: ModelDescriptor) => void;
-  onClose: () => void;
-}) {
-  const field = role === "input" ? "outputs" : "inputs";
-  const fieldLabel = role === "input" ? "Outputs" : "Inputs";
-  return (
-    
 event.stopPropagation()}>
-      

-        

-          
{title}

-          
{variable}

-        

-        
-      

-      

-        {models.map((model) => {
-          const declarations = modelVariableDeclarations(model, field);
-          return (
-            
-          );
-        })}
-      

-    

-  );
-}
-
-function candidatePopoverStyle(anchor: { x: number; y: number }) {
-  if (typeof window === "undefined") return { left: anchor.x, top: anchor.y };
-  const margin = 12;
-  const width = Math.min(360, window.innerWidth - margin * 2);
-  const maxHeight = Math.min(420, window.innerHeight - margin * 2);
-  const opensLeft = anchor.x + width + margin > window.innerWidth;
-  const left = Math.min(
-    Math.max(opensLeft ? anchor.x - width - 10 : anchor.x + 10, margin),
-    Math.max(margin, window.innerWidth - width - margin),
-  );
-  const top = Math.min(
-    Math.max(anchor.y - 28, margin),
-    Math.max(margin, window.innerHeight - maxHeight - margin),
-  );
-  return { left, top, width, maxHeight };
-}
-
-function modelVariableDeclarations(model: ModelDescriptor, field: "inputs" | "outputs"): Record {
-  const declarations = model[field];
-  if (!declarations || typeof declarations !== "object" || Array.isArray(declarations)) return {};
-  return declarations;
-}
-
-function Row({ label, value }: { label: string; value: string }) {
-  return 
{label}{value}
;
-}
-
-function RateEditor({
-  mode,
-  dt,
-  phase,
-  defaultLabel,
-  onModeChange,
-  onDtChange,
-  onPhaseChange,
-}: {
-  mode: "default" | "clock";
-  dt: string;
-  phase: string;
-  defaultLabel: string;
-  onModeChange: (mode: "default" | "clock") => void;
-  onDtChange: (value: string) => void;
-  onPhaseChange: (value: string) => void;
-}) {
-  return (
-    

-      
-      {mode === "default" ? (
-        
Uses model default: {defaultLabel}

-      ) : (
-        

-          
-          
-        

-      )}
-    

-  );
-}
-
-function ExistingModelEditor({
-  node,
-  models,
-  scales,
-  onAddScale,
-  onCommand,
-  disabled,
-}: {
-  node: GraphNodeData;
-  models: ModelDescriptor[];
-  scales: string[];
-  onAddScale: (scale: string) => void;
-  onCommand: (command: Record) => void;
-  disabled: boolean;
-}) {
-  const matchingModels = useMemo(() => {
-    const sameProcess = models.filter((model) => model.process === node.process);
-    return sameProcess.length > 0 ? sameProcess : models;
-  }, [models, node.process]);
-  const initialModel = matchingModels.find((model) => model.name === node.modelType || model.type === node.modelType) ?? matchingModels[0];
-  const [modelType, setModelType] = useState(initialModel?.type ?? node.modelType);
-  const selectedModel = matchingModels.find((model) => model.type === modelType) ?? initialModel;
-  const [targetScale, setTargetScale] = useState(node.scale);
-  const [newScale, setNewScale] = useState("");
-  const initialValues = useMemo(() => {
-    if (!selectedModel) return {};
-    return Object.fromEntries(selectedModel.constructor.fields.map((field) => [
-      field.name,
-      node.modelParameters?.[field.name]?.value ?? parameterDefaultValue(field.default),
-    ]));
-  }, [node.modelParameters, selectedModel]);
-  const initialTypes = useMemo(() => {
-    if (!selectedModel) return {};
-    return Object.fromEntries(selectedModel.constructor.fields.map((field) => [
-      field.name,
-      node.modelParameters?.[field.name]?.type ?? field.inferredChoice,
-    ]));
-  }, [node.modelParameters, selectedModel]);
-  const [values, setValues] = useState>(initialValues);
-  const [types, setTypes] = useState>(initialTypes);
-  const initialTimestep = node.timestep ?? { mode: "default" as const, dt: "1.0", phase: "0.0" };
-  const [rateMode, setRateMode] = useState<"default" | "clock">(initialTimestep.mode === "clock" ? "clock" : "default");
-  const [rateDt, setRateDt] = useState(initialTimestep.dt ?? "1.0");
-  const [ratePhase, setRatePhase] = useState(initialTimestep.phase ?? "0.0");
-
-  useEffect(() => {
-    setValues(initialValues);
-    setTypes(initialTypes);
-  }, [initialTypes, initialValues]);
-
-  const setSharedType = useCallback((fieldName: string, nextType: string) => {
-    if (!selectedModel) return;
-    const field = selectedModel.constructor.fields.find((item) => item.name === fieldName);
-    const group = field?.typeParameter ? selectedModel.constructor.parameterGroups[field.typeParameter] ?? [fieldName] : [fieldName];
-    setTypes((current) => ({ ...current, ...Object.fromEntries(group.map((name) => [name, nextType])) }));
-  }, [selectedModel]);
-
-  const parameters = useCallback(() => {
-    if (!selectedModel) return {};
-    return Object.fromEntries(selectedModel.constructor.fields.map((field) => [
-      field.name,
-      { type: types[field.name] ?? field.inferredChoice, value: values[field.name] ?? "" },
-    ]));
-  }, [selectedModel, types, values]);
-
-  if (!selectedModel) return null;
-  const timestep = rateMode === "clock" ? { mode: "clock", dt: rateDt, phase: ratePhase } : { mode: "default" };
-
-  return (
-    

-      
Edit Model

-      
-      
-      
-      
-      {selectedModel.constructor.fields.map((field) => (
-        

-          
-           setValues((current) => ({ ...current, [field.name]: event.target.value }))} />
-          
-        

-      ))}
-      

-        
-        
-      

-    

-  );
-}
-
-function VariableMappingEditor({
-  target,
-  graphNodes,
-  disabled,
-  onCommand,
-}: {
-  target: { node: GraphNodeData; port: GraphPort } | null;
-  graphNodes: GraphNodeData[];
-  disabled: boolean;
-  onCommand: (command: Record) => void;
-}) {
-  const sourceOptions = useMemo(() => {
-    if (!target) return [];
-    return graphNodes
-      .flatMap((node) => node.outputs.map((port) => ({ node, port })))
-      .filter(({ node, port }) => node.id !== target.node.id || port.name !== target.port.name)
-      .sort((left, right) => `${left.node.scale}.${left.node.process}.${left.port.name}`.localeCompare(`${right.node.scale}.${right.node.process}.${right.port.name}`));
-  }, [graphNodes, target]);
-  const [sourceId, setSourceId] = useState("");
-  const [mode, setMode] = useState<"single" | "multi">("single");
-  const [extraScales, setExtraScales] = useState([]);
-
-  useEffect(() => {
-    setSourceId(sourceOptions[0]?.port.id ?? "");
-    setMode("single");
-    setExtraScales([]);
-  }, [sourceOptions]);
-
-  if (!target) return null;
-  const selected = sourceOptions.find((item) => item.port.id === sourceId) ?? sourceOptions[0] ?? null;
-  const candidateExtraScales = selected
-    ? [...new Set(sourceOptions
-      .filter((item) => item.port.name === selected.port.name && item.node.scale !== selected.node.scale)
-      .map((item) => item.node.scale))]
-    : [];
-
-  const toggleExtraScale = (scale: string) => {
-    setExtraScales((current) =>
-      current.includes(scale) ? current.filter((item) => item !== scale) : [...current, scale]
-    );
-  };
-
-  const apply = () => {
-    if (!selected) return;
-    const command: Record = {
-      action: "edit",
-      kind: "set_mapped_variable",
-      scale: target.node.scale,
-      process: target.node.process,
-      variable: target.port.name,
-      sourceScale: selected.node.scale,
-      sourceVariable: selected.port.name,
-      mode: mode === "single" && selected.node.scale === target.node.scale ? "same_scale" : mode,
-    };
-    if (mode === "multi" && extraScales.length > 0) command.extraSourceScales = extraScales;
-    onCommand(command);
-  };
-
-  return (
-    

-      
Set Mapping

-      {sourceOptions.length === 0 ? (
-        
No output variable is available as a source.

-      ) : (
-        <>
-          
-          

-            
-            
-          

-          {mode === "multi" && candidateExtraScales.length > 0 && (
-            

-              {candidateExtraScales.map((scale) => (
-                
-              ))}
-            

-          )}
-          
-        
-      )}
-    

-  );
-}
-
-function InitializationPanel({
-  initializations,
-  disabled,
-  onCommand,
-}: {
-  initializations: InitializationDescriptor[];
-  disabled: boolean;
-  onCommand: (command: Record) => void;
-}) {
-  const grouped = useMemo(() => {
-    const groups = new Map();
-    for (const item of initializations) {
-      const group = groups.get(item.scale) ?? [];
-      group.push(item);
-      groups.set(item.scale, group);
-    }
-    return groups;
-  }, [initializations]);
-
-  if (initializations.length === 0) {
-    return 
No explicit status initialization is required by the current ModelMapping.
;
-  }
-
-  return (
-    

-      {[...grouped.entries()].map(([scale, items]) => (
-        

-          
{scale}

-          {items.map((item) => (
-            
-          ))}
-        

-      ))}
-    

-  );
-}
-
-function InitializationRow({
-  item,
-  disabled,
-  onCommand,
-}: {
-  item: InitializationDescriptor;
-  disabled: boolean;
-  onCommand: (command: Record) => void;
-}) {
-  const [value, setValue] = useState(item.value);
-  const [type, setType] = useState(item.type);
-
-  useEffect(() => {
-    setValue(item.value);
-    setType(item.type);
-  }, [item]);
-
-  return (
-    

-      
-       setValue(event.target.value)}
-        placeholder={item.provided ? "" : "initial value"}
-      />
-      
-      
-      {item.provided ? "Stored in Status" : "Missing from Status"}
-    

-  );
-}
-
-function MappingCodePanel({
-  code,
-  savePath,
-  lastSavedPath,
-  saveTargetPath,
-  autosavePath,
-  lastAutosavedPath,
-  onSavePathChange,
-  onSave,
-  disabled,
-}: {
-  code: string;
-  savePath: string;
-  lastSavedPath: string | null;
-  saveTargetPath: string | null;
-  autosavePath: string | null;
-  lastAutosavedPath: string | null;
-  onSavePathChange: (path: string) => void;
-  onSave: () => void;
-  disabled: boolean;
-}) {
-  const copyCode = useCallback(async () => {
-    if (!code) return;
-    await navigator.clipboard.writeText(code);
-  }, [code]);
-
-  return (
-    

-      

-        Current Julia mapping
-        
-      

-