fix tests after Sem refactor

Author: Alexey Stukalov

test/examples/multigroup/build_models.jl

@@ -7,20 +7,28 @@ const SEM = StructuralEquationModels
 obs_g1 = SemObservedData(data = dat_g1, observed_vars = SEM.observed_vars(specification_g1))
 obs_g2 = SemObservedData(data = dat_g2, observed_vars = SEM.observed_vars(specification_g2))
 
-model_ml_multigroup =
-    Sem(SemML(obs_g1, RAMSymbolic(specification_g1)), SemML(obs_g2, RAM(specification_g2)))
+model_ml_multigroup = Sem(
+    :Pasteur => SemML(obs_g1, RAMSymbolic(specification_g1)),
+    :Grant_White => SemML(obs_g2, RAM(specification_g2)),
+)
 
 @testset "Sem API" begin
     @test SEM.nsamples(model_ml_multigroup) == nsamples(obs_g1) + nsamples(obs_g2)
     @test SEM.nsem_terms(model_ml_multigroup) == 2
     @test length(SEM.sem_terms(model_ml_multigroup)) == 2
 end
 
+# replace observed using Dict of data matrices
 model_ml_multigroup3 = replace_observed(
-    model_ml_multigroup2,
-    column = :school,
-    specification = partable,
-    data = dat,
+    model_ml_multigroup,
+    Dict(:Pasteur => dat_g1, :Grant_White => dat_g2),
+)
+
+# replace observed using DataFrame with group column
+model_ml_multigroup4 = replace_observed(
+    model_ml_multigroup,
+    dat;
+    semterm_column = :school,
 )
 
 # gradients
@@ -42,8 +50,10 @@ end
 
 @testset "replace_observed_multigroup" begin
     sem_fit_1 = fit(semoptimizer, model_ml_multigroup)
-    sem_fit_2 = fit(semoptimizer, model_ml_multigroup3)
-    @test sem_fit_1.solution ≈ sem_fit_2.solution
+    sem_fit_3 = fit(semoptimizer, model_ml_multigroup3)
+    @test sem_fit_1.solution ≈ sem_fit_3.solution
+    sem_fit_4 = fit(semoptimizer, model_ml_multigroup4)
+    @test sem_fit_1.solution ≈ sem_fit_4.solution
 end
 
 @testset "fitmeasures/se_ml" begin
@@ -194,7 +204,7 @@ model_ls_multigroup = Sem(
 end
 
 @testset "ls_solution_multigroup" begin
-    solution = sem_fit(semoptimizer, model_ls_multigroup)
+    solution = fit(semoptimizer, model_ls_multigroup)
     update_estimate!(partable, solution)
     test_estimates(
         partable,

test/examples/political_democracy/constructor.jl

@@ -149,19 +149,14 @@ end
     )
     # set seed for simulation
     Random.seed!(83472834)
-    colnames = Symbol.(names(example_data("political_democracy")))
     # simulate data
     model_ml_new = replace_observed(
         model_ml,
-        data = rand(model_ml, params, 1_000_000),
-        specification = spec,
-        observed_vars = colnames,
+        rand(model_ml, params, 1_000_000),
     )
     model_ml_sym_new = replace_observed(
         model_ml_sym,
-        data = rand(model_ml_sym, params, 1_000_000),
-        specification = spec,
-        observed_vars = colnames,
+        rand(model_ml_sym, params, 1_000_000),
     )
     # fit models
     sol_ml = solution(fit(semoptimizer, model_ml_new))
@@ -346,21 +341,14 @@ end
     )
     # set seed for simulation
     Random.seed!(83472834)
-    colnames = Symbol.(names(example_data("political_democracy")))
     # simulate data
     model_ml_new = replace_observed(
         model_ml,
-        data = rand(model_ml, params, 1_000_000),
-        specification = spec,
-        observed_vars = colnames,
-        meanstructure = true,
+        rand(model_ml, params, 1_000_000),
     )
     model_ml_sym_new = replace_observed(
         model_ml_sym,
-        data = rand(model_ml_sym, params, 1_000_000),
-        specification = spec,
-        observed_vars = colnames,
-        meanstructure = true,
+        rand(model_ml_sym, params, 1_000_000),
     )
     # fit models
     sol_ml = solution(fit(semoptimizer, model_ml_new))

test/examples/recover_parameters/recover_parameters_twofact.jl

@@ -9,7 +9,7 @@ include(
     ),
 )
 
-x = Symbol.("x", 1:13)
+pars = Symbol.("x", 1:13)
 
 S = [
     :x1 0 0 0 0 0 0 0
@@ -42,7 +42,7 @@ A = [
     0 0 0 0 0 0 0    0
 ]
 
-ram_matrices = RAMMatrices(; A = A, S = S, F = F, param_labels = x, vars = nothing)
+ram_matrices = RAMMatrices(; A = A, S = S, F = F, param_labels = pars, vars = nothing)
 
 true_val = [
     repeat([1], 8)
@@ -55,8 +55,6 @@ start = [
     repeat([0.5], 4)
 ]
 
-observed = SemObservedData(data = x, specification = ram_matrices)
-
 implied_sym = RAMSymbolic(ram_matrices)
 
 implied_sym.Σ_eval!(implied_sym.Σ, true_val)
@@ -66,7 +64,9 @@ true_dist = MultivariateNormal(implied_sym.Σ)
 Random.seed!(1234)
 x = permutedims(rand(true_dist, 10^5), (2, 1))
 
-model_ml = Sem(observed, implied_sym; loss = SemML)
+observed = SemObservedData(data = x, specification = ram_matrices)
+
+model_ml = Sem(SemML(observed, implied_sym))
 
 objective!(model_ml, true_val)