fix after rebase

Author: vyudu

src/inputoutput.jl

@@ -317,16 +317,6 @@ function inputs_to_parameters!(state::TransformationState, inputsyms)
     @set! sys.unknowns = setdiff(unknowns(sys), keys(input_to_parameters))
     ps = parameters(sys)
 
-    if inputsyms !== nothing
-        # Change order of new parameters to correspond to user-provided order in argument `inputs`
-        d = Dict{Any, Int}()
-        for (i, inp) in enumerate(new_parameters)
-            d[inp] = i
-        end
-        permutation = [d[i] for i in inputsyms]
-        new_parameters = new_parameters[permutation]
-    end
-
     @set! sys.ps = [ps; new_parameters]
     @set! state.sys = sys
     @set! state.fullvars = new_fullvars
@@ -429,7 +419,7 @@ function add_input_disturbance(sys, dist::DisturbanceModel, inputs = Any[]; kwar
     augmented_sys = extend(augmented_sys, sys)
     ssys = structural_simplify(augmented_sys, inputs = all_inputs, disturbance_inputs = [d])
 
-    (f_oop, f_ip), dvs, p, io_sys = generate_control_function(ssys, all_inputs,
+    f, dvs, p, io_sys = generate_control_function(ssys, all_inputs,
         [d]; kwargs...)
-    (f_oop, f_ip), augmented_sys, dvs, p, io_sys
+    f, augmented_sys, dvs, p, io_sys
 end

src/linearization.jl

@@ -143,17 +143,6 @@ function eq_idxs(sys::AbstractSystem)
     diff_idxs, alge_idxs
 end
 
-"""
-Return the set of indexes of differential equations and algebraic equations in the simplified system.
-"""
-function eq_idxs(sys::AbstractSystem)
-    eqs = equations(sys)
-    alge_idxs = findall(!isdiffeq, eqs)
-    diff_idxs = setdiff(1:length(eqs), alge_idxs)
-
-    diff_idxs, alge_idxs
-end
-
 """
     $(TYPEDEF)
 
@@ -618,7 +607,7 @@ function markio!(state, orig_inputs, inputs, outputs, disturbances; check = true
         end
         (all(values(outputset)) || error(
             "Some specified outputs were not found in system. The following Dict indicates the found variables ",
-            outputset))
+        outputset))
     end
     state, orig_inputs
 end

src/systems/imperative_affect.jl

@@ -99,7 +99,20 @@ function Base.hash(a::ImperativeAffect, s::UInt)
     hash(a.ctx, s)
 end
 
-function namespace_affects(affect::ImperativeAffect, s)
+namespace_affects(af::ImperativeAffect, s) = namespace_affect(af, s)
+function namespace_affect(affect::ImperativeAffect, s)
+    rmn = []
+    for modded in modified(affect)
+        if symbolic_type(modded) == NotSymbolic() && modded isa AbstractArray
+            res = []
+            for m in modded
+                push!(res, renamespace(s, m))
+            end
+            push!(rmn, res)
+        else
+            push!(rmn, renamespace(s, modded))
+        end
+    end
     ImperativeAffect(func(affect),
         namespace_expr.(observed(affect), (s,)),
         observed_syms(affect),

src/systems/systemstructure.jl

@@ -688,7 +688,7 @@ function structural_simplify!(state::TearingState; simplify = false,
                     continue
                 end
                 disc_inputs = [inputs; clocked_inputs[i]]
-                ss, = _structural_simplification!(state; simplify, check_consistency,
+                ss, = _structural_simplify!(state; simplify, check_consistency,
                     inputs = disc_inputs, outputs, disturbance_inputs,
                     fully_determined, kwargs...)
                 append!(appended_parameters, inputs[i], unknowns(ss))

test/extensions/test_infiniteopt.jl

@@ -28,7 +28,7 @@ model = structural_simplify(model; inputs, outputs)
 f, dvs, psym, io_sys = ModelingToolkit.generate_control_function(
     model, split = false)
 
-f_obs = ModelingToolkit.build_explicit_observed_function(io_sys, [model.y]; inputs)
+f_obs = ModelingToolkit.build_explicit_observed_function(io_sys, outputs; inputs)
 
 expected_state_order = [model.θ, model.ω]
 permutation = [findfirst(isequal(x), expected_state_order) for x in dvs] # This maps our expected state order to the actual state order

test/input_output_handling.jl

@@ -450,7 +450,7 @@ end
     @mtkbuild sys = ODESystem(eqs, t, [x], [])
 
     f, dvs, ps, io_sys = ModelingToolkit.generate_control_function(sys)
-    @test f[1]([0.5], nothing, MTKParameters(io_sys, []), 0.0) ≈ [1.0]
+    @test f([0.5], nothing, MTKParameters(io_sys, []), 0.0) ≈ [1.0]
 end
 
 @testset "With callable symbolic" begin

test/jumpsystem.jl

@@ -391,8 +391,8 @@ let
     j1 = ConstantRateJump(p1, [x1 ~ Pre(x1) + 1])
     j2 = MassActionJump(p2, [x2 => 1], [x3 => -1])
     j3 = VariableRateJump(p3, [x3 ~ Pre(x3) + 1, x4 ~ Pre(x4) + 1])
-    j4 = MassActionJump(p4 * p5, [x1 => 1, x5 => 1], [x1 => -1, x5 => -1, x2 => 1])
-    @named js = JumpSystem([j1, j2, j3, j4], t, [x1, x2, x3, x4, x5], [p1, p2, p3, p4, p5])
+    j4 = MassActionJump(p4 * p4, [x1 => 1, x4 => 1], [x1 => -1, x4 => -1, x2 => 1])
+    @named js = JumpSystem([j1, j2, j3, j4], t, [x1, x2, x3, x4], [p1, p2, p3, p4])
 
     us = Set()
     ps = Set()

test/symbolic_events.jl

@@ -1305,3 +1305,30 @@ end
     sol = solve(prob, FBDF())
     @test prob.ps[g] == sol.ps[g]
 end
+
+@testset "Array parameter updates of parent components in ImperativeEffect" begin
+    function child(vals; name, max_time = 0.1)
+        vars = @variables begin
+            x(t) = 0.0
+        end
+        eqs = reduce(vcat, Symbolics.scalarize.([
+            D(x) ~ 1.0
+        ]))
+        reset = ModelingToolkit.ImperativeAffect(
+            modified = (; vals = Symbolics.scalarize(ParentScope.(vals)), x)) do m, o, _, i
+            @set! m.vals = m.vals .+ 1
+            @set! m.x = 0.0
+            return m
+        end
+        return ODESystem(eqs, t, vars, []; name = name,
+            continuous_events = [[x ~ max_time] => reset])
+    end
+    shared_pars = @parameters begin
+        vals(t)[1:2] = 0.0
+    end
+
+    @named sys = ODESystem(Equation[], t, [], Symbolics.scalarize(vals);
+        systems = [child(vals; name = :child)])
+    sys = structural_simplify(sys)
+    sol = solve(ODEProblem(sys, [], (0.0, 1.0)), Tsit5())
+end