Add corner-cases to tests, fix typo exposed by those tests (doesn't a…

…ffect XPalm in its current state)

examples/dummy.jl

@@ -18,7 +18,7 @@ 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
 end
-PlantSimEngine.TimeStepDependencyTrait(::Type{<:Process1Model}) = PlantSimEngine.IsTimeStepIndependent()
+PlantSimEngine.TimeStepDependencyTrait(::Type{<:Process1Model}) = PlantSimEngine.IsTimeStepDependent()
 PlantSimEngine.ObjectDependencyTrait(::Type{<:Process1Model}) = PlantSimEngine.IsObjectIndependent()
 
 

src/internal_tests_import.jl

@@ -0,0 +1,33 @@
+"""
+A sub-module with corner-cases intended to be used for tests, and a dependency graph generator to be used for some randomly seeded tests.
+They may be of interest to modelers, or developers willing to tinker with PlantSimEngine.
+
+"""
+module InternalTests
+
+using PlantSimEngine, MultiScaleTreeGraph, PlantMeteo, Statistics
+
+outs = Dict(
+    "E1" => ( :out1,:out),
+    "E2" => (:out2,),)
+
+#tupl = (1, 2, 3)
+#tuple2 = (2, 4)
+#outs = Dict{String, Tuple{Vararg{Symbol}}}("1" .=> tupl, "2" => tuple2)
+#=outs_ = Dict{String, Vector{Symbol}}()
+    for i in keys(outs)
+        outs_[i] = [outs[i]...]
+    end=#
+    #outs_ = Dict{String, Vector{Symbol}}(i => Vector(outs[i]...) for i in keys(outs))
+    outs_ = Dict(i => Vector(outs[i]...) for i in keys(outs))
+
+
+# Processes:
+export 
+
+# Models:
+export 
+
+
+
+end

src/run.jl

@@ -86,6 +86,45 @@ julia> (models[:var4],models[:var6])
 """
 run!
 
+#todo vector of modellists case
+function run2!(
+    object,
+    meteo=nothing,
+    constants=PlantMeteo.Constants(),
+    extra=nothing;
+    check=true,
+    nsteps=nothing,
+    outputs=nothing,
+    executor=ThreadedEx()
+)
+    isnothing(nsteps) && (nsteps = get_nsteps(meteo))
+
+    default_scale = "Default"
+
+    mtg = MultiScaleTreeGraph.Node(MultiScaleTreeGraph.NodeMTG("/", default_scale, 0, 0),)
+
+    mapping = Dict(
+        default_scale => (
+        SingleModelScale1(),
+        Status(in = 1.0, in1 = 1.0),
+        ),
+    )
+
+    sim = GraphSimulation(object, mapping, nsteps=nsteps, check=check, outputs=outputs)
+    run!(
+        sim,
+        meteo,
+        constants,
+        extra;
+        check=check,
+        executor=executor
+    )
+
+    return sim
+
+end
+
+
 # Managing one or several objects, one or several time-steps:
 
 # This is the default function called by the user, which uses traits