Introduce merge; fix a couple of refactor residual bugs

Author: BenChung

ext/ModelTestingCalibration.jl

@@ -20,8 +20,7 @@ function ModelTesting.validate(model::AbstractTimeDependentSystem, data; pem_coe
         filter(arg->first(arg) != :model_transformations, experiment_kwargs)...)
     # no search space - this is just a validation run
     i = InverseProblem([experiment], nothing, search_space)
-    sim_sol = simulate(experiment, i)
-    return compare_discrete_to_continous(sim_sol, data)
+    return simulate(experiment, i)
 end
 
 end

src/ModelTesting.jl

@@ -5,4 +5,5 @@ using ModelingToolkit, DifferentialEquations, DiffEqDevTools, SymbolicIndexingIn
 include("test/measured.jl")
 include("test/continuous/delta_sol.jl")
 include("test/discrete/single_shooting.jl")
+include("test/discrete/merge.jl")
 end

src/test/discrete/merge.jl

@@ -0,0 +1,23 @@
+function merge_results(
+    results...
+)
+    for (name, result) in results 
+        @assert "timestamp" ∈ names(result) "Each result must have a column `timestamp`; the result set $(name) is missing this."
+    end
+
+    merged = nothing
+    for (name, result) in results
+        col_rename(n) = string(n) == "timestamp" ? Symbol(n) : namespace_symbol(name, n)
+        if isnothing(merged)
+            merged = rename(result, names(result) .=> col_rename.(names(result)))
+        else 
+            merged = outerjoin(merged, result; 
+                on=:timestamp, 
+                validate=(true, true), 
+                renamecols = (x -> x) => col_rename)
+        end
+        display(merged)
+    end
+    return merged
+end
+export merge_results

test/timeseries.jl

@@ -41,6 +41,8 @@ tol = 1e-6
         @test results_bad[:l∞] > tol
         @test results_bad[:l2] > tol
         @test results_bad[:final] > tol
+
+        merge_results(:reference => d1, :good => d2, :bad => d3)
     end
     @testset "Model-Model Continous Comparison" begin 
         @variables t 
@@ -84,11 +86,12 @@ end
             push!(data, [t, ref_sol(t, idxs=fol.x) + randn() * 0.1, ref_sol(t, idxs=fol.y) * randn() * 0.1])
         end
 
-        results_bad = ModelTesting.validate(fol, data; search_space=[fol.τ => (0.5,0.5)], params = [fol.τ => 0.5], u0 = [fol.x => 0.0])
-        results_good = ModelTesting.validate(fol, data; search_space=[fol.τ => (1.0,1.0)], params = [fol.τ => 1.0], u0 = [fol.x => 0.0])
-        @test results_good[:metrics][:l∞] < results_bad[:metrics][:l∞]
-        @test results_good[:metrics][:l2] < results_bad[:metrics][:l2]
-        CSV.write("results.csv", results_bad[:data])
-        display(results_good[:data])
+        sim_bad = discretize_solution(ModelTesting.validate(fol, data; search_space=[fol.τ => (0.5,0.5)], params = [fol.τ => 0.5], u0 = [fol.x => 0.0]), data)
+        sim_good = discretize_solution(ModelTesting.validate(fol, data; search_space=[fol.τ => (1.0,1.0)], params = [fol.τ => 1.0], u0 = [fol.x => 0.0]), data)
+        results_good = compare_discrete(fol, data, sim_good)
+        results_bad = compare_discrete(fol, data, sim_bad)
+
+        @test results_good[:l∞] < results_bad[:l∞]
+        @test results_good[:l2] < results_bad[:l2]
     end
 end