Merge branch 'main' into graph-visualization

Author: VEZY

.github/workflows/Benchmarks.yml

@@ -22,3 +22,6 @@ jobs:
         with:
           julia-version: ${{ matrix.version }}
           bench-on: ${{ github.event.pull_request.head.sha }}
+          extra-pkgs: |
+            https://github.com/PalmStudio/XPalm.jl#main
+            https://github.com/VEZY/PlantBiophysics.jl#master

README.md

@@ -233,52 +233,52 @@ The package is designed to be easily scalable, and can be used to simulate model
 
 ```julia
 mapping = ModelMapping(
-    "Scene" => ToyDegreeDaysCumulModel(),
-    "Plant" => (
+    :Scene => ToyDegreeDaysCumulModel(),
+    :Plant => (
         MultiScaleModel(
             model=ToyLAIModel(),
             mapped_variables=[
-                :TT_cu => "Scene",
+                :TT_cu => :Scene,
             ],
         ),
         Beer(0.6),
         MultiScaleModel(
             model=ToyAssimModel(),
-            mapped_variables=[:soil_water_content => "Soil"],
+            mapped_variables=[:soil_water_content => :Soil],
         ),
         MultiScaleModel(
             model=ToyCAllocationModel(),
             mapped_variables=[
-                :carbon_demand => ["Leaf", "Internode"],
-                :carbon_allocation => ["Leaf", "Internode"]
+                :carbon_demand => [:Leaf, :Internode],
+                :carbon_allocation => [:Leaf, :Internode]
             ],
         ),
         MultiScaleModel(
             model=ToyPlantRmModel(),
-            mapped_variables=[:Rm_organs => ["Leaf" => :Rm, "Internode" => :Rm],],
+            mapped_variables=[:Rm_organs => [:Leaf => :Rm, :Internode => :Rm],],
         ),
     ),
-    "Internode" => (
+    :Internode => (
         MultiScaleModel(
             model=ToyCDemandModel(optimal_biomass=10.0, development_duration=200.0),
-            mapped_variables=[:TT => "Scene",],
+            mapped_variables=[:TT => :Scene,],
         ),
         MultiScaleModel(
             model=ToyInternodeEmergence(TT_emergence=20.0),
-            mapped_variables=[:TT_cu => "Scene"],
+            mapped_variables=[:TT_cu => :Scene],
         ),
         ToyMaintenanceRespirationModel(1.5, 0.06, 25.0, 0.6, 0.004),
         Status(carbon_biomass=1.0)
     ),
-    "Leaf" => (
+    :Leaf => (
         MultiScaleModel(
             model=ToyCDemandModel(optimal_biomass=10.0, development_duration=200.0),
-            mapped_variables=[:TT => "Scene",],
+            mapped_variables=[:TT => :Scene,],
         ),
         ToyMaintenanceRespirationModel(2.1, 0.06, 25.0, 1.0, 0.025),
         Status(carbon_biomass=1.0)
     ),
-    "Soil" => (
+    :Soil => (
         ToySoilWaterModel(),
     ),
 );
@@ -305,11 +305,11 @@ And run the simulation:
 
 ```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,),
+    :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, outputs=out_vars, executor=SequentialEx());

benchmark/benchmarks.jl

@@ -44,8 +44,8 @@ SUITE[suite_name]["XPalm_setup"] = @benchmarkable xpalm_default_param_create() s
 palm, models, out_vars, meteo = xpalm_default_param_create()
 sim_outputs = xpalm_default_param_run(palm, models, out_vars, meteo)
 
-SUITE[suite_name]["XPalm_run"] = @benchmarkable xpalm_default_param_run($palm, $models, $out_vars, $meteo) seconds = 120
-SUITE[suite_name]["XPalm_convert_outputs"] = @benchmarkable xpalm_default_param_convert_outputs($sim_outputs) seconds = 120
+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)
 
 #tune!(SUITE)
 #results = run(SUITE, verbose=true)

benchmark/test-PSE-benchmark.jl

@@ -28,21 +28,21 @@ 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, 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
     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, 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.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, 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)
 
     end
 
@@ -60,62 +60,62 @@ function do_benchmark_on_heavier_mtg()
 
     #similar to the mtg growth test but with a much lower emergence threshold
     mapping = ModelMapping(
-        "Scene" => ToyDegreeDaysCumulModel(),
-        "Plant" => (
+        :Scene => ToyDegreeDaysCumulModel(),
+        :Plant => (
             MultiScaleModel(
                 model=ToyLAIModel(),
                 mapped_variables=[
-                    :TT_cu => "Scene",
+                    :TT_cu => :Scene,
                 ],
             ),
             PlantSimEngine.Examples.Beer(0.6),
             MultiScaleModel(
                 model=ToyCAllocationModel(),
                 mapped_variables=[
-                    :carbon_assimilation => ["Leaf"],
-                    :carbon_demand => ["Leaf", "Internode"],
-                    :carbon_allocation => ["Leaf", "Internode"]
+                    :carbon_assimilation => [:Leaf],
+                    :carbon_demand => [:Leaf, :Internode],
+                    :carbon_allocation => [:Leaf, :Internode]
                 ],
             ),
             MultiScaleModel(
                 model=ToyPlantRmModel(),
-                mapped_variables=[:Rm_organs => ["Leaf" => :Rm, "Internode" => :Rm],],
+                mapped_variables=[:Rm_organs => [:Leaf => :Rm, :Internode => :Rm],],
             ),
         ),
-        "Internode" => (
+        :Internode => (
             MultiScaleModel(
                 model=ToyCDemandModel(optimal_biomass=10.0, development_duration=200.0),
-                mapped_variables=[:TT => "Scene",],
+                mapped_variables=[:TT => :Scene,],
             ),
             MultiScaleModel(
                 model=ToyInternodeCrazyEmergence(TT_emergence=1.0),
-                mapped_variables=[:TT_cu => "Scene"],
+                mapped_variables=[:TT_cu => :Scene],
             ),
             ToyMaintenanceRespirationModel(1.5, 0.06, 25.0, 0.6, 0.004),
             Status(carbon_biomass=1.0)
         ),
-        "Leaf" => (
+        :Leaf => (
             MultiScaleModel(
                 model=ToyAssimModel(),
-                mapped_variables=[:soil_water_content => "Soil", :aPPFD => "Plant"],
+                mapped_variables=[:soil_water_content => :Soil, :aPPFD => :Plant],
             ),
             MultiScaleModel(
                 model=ToyCDemandModel(optimal_biomass=10.0, development_duration=200.0),
-                mapped_variables=[:TT => "Scene",],
+                mapped_variables=[:TT => :Scene,],
             ),
             ToyMaintenanceRespirationModel(2.1, 0.06, 25.0, 1.0, 0.025),
             Status(carbon_biomass=1.0)
         ),
-        "Soil" => (
+        :Soil => (
             ToySoilWaterModel(),
         ),
     )
 
     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,),
+        :Leaf => (:carbon_assimilation, :carbon_demand, :soil_water_content, :carbon_allocation),
+        :Internode => (:carbon_allocation, :TT_cu_emergence),
+        :Plant => (:carbon_allocation,),
+        :Soil => (:soil_water_content,),
     )
 
     out = run!(mtg, mapping, meteo_day, tracked_outputs=out_vars, executor=SequentialEx())

benchmark/test-multirate-buffer-benchmark.jl

@@ -31,12 +31,12 @@ function PlantSimEngine.run!(::MRBenchConsumer24Model, models, status, meteo, co
 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))
+    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))
+        Node(internode, MultiScaleTreeGraph.NodeMTG("+", :Leaf, i, 2))
     end
 
     return mtg
@@ -46,30 +46,30 @@ function setup_multirate_buffer_benchmark(; nleaves=2000, ndays=30)
     mtg = _build_multirate_benchmark_mtg(nleaves)
 
     mapping = ModelMapping(
-        "Leaf" => (
+        :Leaf => (
             ModelSpec(MRBenchSourceModel(Ref(0))) |> TimeStepModel(1.0),
         ),
-        "Plant" => (
+        :Plant => (
             ModelSpec(MRBenchConsumer4Model()) |>
-            MultiScaleModel([:X => ["Leaf"]]) |>
+            MultiScaleModel([:X => [:Leaf]]) |>
             TimeStepModel(ClockSpec(4.0, 1.0)) |>
-            InputBindings(; X=(process=:mrbenchsource, var=:X, scale="Leaf", policy=Integrate())),
+            InputBindings(; X=(process=:mrbenchsource, var=:X, scale=:Leaf, policy=Integrate())),
             ModelSpec(MRBenchConsumer24Model()) |>
-            MultiScaleModel([:X => ["Leaf"]]) |>
+            MultiScaleModel([:X => [:Leaf]]) |>
             TimeStepModel(ClockSpec(24.0, 1.0)) |>
-            InputBindings(; X=(process=:mrbenchsource, var=:X, scale="Leaf", policy=Integrate())),
+            InputBindings(; X=(process=:mrbenchsource, var=:X, scale=:Leaf, policy=Integrate())),
         ),
     )
 
     nsteps = 24 * ndays
     meteo = Weather(repeat([Atmosphere(T=20.0, Wind=1.0, Rh=0.65)], nsteps))
 
     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(: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)),
     ]
 
-    tracked = Dict("Plant" => (:Y4, :Y24), "Leaf" => (:X,))
+    tracked = Dict(:Plant => (:Y4, :Y24), :Leaf => (:X,))
     return mtg, mapping, meteo, reqs, tracked, nsteps
 end
 

benchmark/test-xpalm.jl

@@ -47,6 +47,8 @@ function xpalm_default_param_convert_outputs(sim_outputs)
 end
 
 
+println(Pkg.status("XPalm"))
+
 #=@testset "XPalm simple test" begin
     # default number of seconds is 5
     b_XP = @benchmark xpalm_default_param_run() seconds = 120

docs/src/API/API_public.md

@@ -70,8 +70,8 @@ Scope selection detail:
 ### 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))
+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)
 
@@ -126,23 +126,23 @@ Use `Integrate` for accumulation semantics and `Aggregate` for summary-statistic
 ```julia
 ModelSpec(DailyModel()) |>
 TimeStepModel(ClockSpec(24.0, 1.0)) |>
-InputBindings(; a=(process=:hourly_assim, var=:A, scale="Leaf", policy=Integrate(SumReducer())))
+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())))
+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))))
+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))))
+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())))
+InputBindings(; a=(process=:hourly_assim, var=:A, scale=:Leaf, policy=Integrate(PlantMeteo.DurationSumReducer())))
 ```
 
 Built-in reducer types are:

docs/src/model_execution.md

@@ -142,7 +142,7 @@ aggregates over that civil day (including later timesteps from that day when ava
 
 ```julia
 mapping = ModelMapping(
-    "Leaf" => (
+    :Leaf => (
         ModelSpec(LeafSourceModel()) |> TimeStepModel(1.0),
         ModelSpec(LeafConsumerModel()) |>
         TimeStepModel(ClockSpec(2.0, 1.0)) |>
@@ -155,13 +155,13 @@ mapping = ModelMapping(
 
 ```julia
 mapping = ModelMapping(
-    "Leaf" => (
+    :Leaf => (
         ModelSpec(HourlyAssimModel()) |> TimeStepModel(1.0),
     ),
-    "Plant" => (
+    :Plant => (
         ModelSpec(DailyCarbonOfferModel()) |>
         TimeStepModel(ClockSpec(24.0, 1.0)) |>
-        InputBindings(; A=(process=:hourlyassim, var=:A, scale="Leaf", policy=Integrate())),
+        InputBindings(; A=(process=:hourlyassim, var=:A, scale=:Leaf, policy=Integrate())),
     ),
 )
 ```
@@ -170,7 +170,7 @@ mapping = ModelMapping(
 
 ```julia
 mapping = ModelMapping(
-    "Leaf" => (
+    :Leaf => (
         ModelSpec(SlowSourceModel()) |> TimeStepModel(ClockSpec(2.0, 1.0)),
         ModelSpec(FastConsumerModel()) |>
         TimeStepModel(1.0) |>
@@ -195,7 +195,7 @@ on each `ModelSpec`.
 You can export selected variables at a requested rate from temporal streams:
 
 ```julia
-req = OutputRequest("Leaf", :carbon_assimilation;
+req = OutputRequest(:Leaf, :carbon_assimilation;
     name=:A_daily,
     process=:toyassim,
     policy=Integrate(),

docs/src/multiscale/multiscale_considerations.md

@@ -44,7 +44,7 @@ Some models, like the ones we've seen in single-scale simulations, work on a ver
 
 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.
+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).
 

docs/src/multiscale/single_to_multiscale.md

@@ -51,7 +51,7 @@ 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.
+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: