SemImply: vars and params API

Author: Alexey Stukalov

src/StructuralEquationModels.jl

@@ -50,6 +50,7 @@ include("observed/missing.jl")
 include("frontend/specification/Sem.jl")
 include("frontend/specification/documentation.jl")
 # imply
+include("imply/abstract.jl")
 include("imply/RAM/symbolic.jl")
 include("imply/RAM/generic.jl")
 include("imply/empty.jl")

src/imply/RAM/generic.jl

@@ -202,37 +202,10 @@ end
 ### Recommended methods
 ############################################################################################
 
-params(imply::RAM) = params(imply.ram_matrices)
-nparams(imply::RAM) = nparams(imply.ram_matrices)
-
 function update_observed(imply::RAM, observed::SemObserved; kwargs...)
     if n_man(observed) == size(imply.Σ, 1)
         return imply
     else
         return RAM(; observed = observed, kwargs...)
     end
 end
-
-############################################################################################
-### additional functions
-############################################################################################
-
-function check_acyclic(A::AbstractMatrix)
-    # check if the model is acyclic
-    acyclic = isone(det(I - A))
-
-    # check if A is lower or upper triangular
-    if istril(A)
-        @info "A matrix is lower triangular"
-        return LowerTriangular(A)
-    elseif istriu(A)
-        @info "A matrix is upper triangular"
-        return UpperTriangular(A)
-    else
-        if acyclic
-            @info "Your model is acyclic, specifying the A Matrix as either Upper or Lower Triangular can have great performance benefits.\n" maxlog =
-                1
-        end
-        return A
-    end
-end

src/imply/RAM/symbolic.jl

@@ -220,9 +220,6 @@ end
 ### Recommended methods
 ############################################################################################
 
-params(imply::RAMSymbolic) = params(imply.ram_matrices)
-nparams(imply::RAMSymbolic) = nparams(imply.ram_matrices)
-
 function update_observed(imply::RAMSymbolic, observed::SemObserved; kwargs...)
     if n_man(observed) == size(imply.Σ, 1)
         return imply

src/imply/abstract.jl

@@ -0,0 +1,30 @@
+
+vars(imply::SemImply) = vars(imply.ram_matrices)
+observed_vars(imply::SemImply) = observed_vars(imply.ram_matrices)
+latent_vars(imply::SemImply) = latent_vars(imply.ram_matrices)
+
+nvars(imply::SemImply) = nvars(imply.ram_matrices)
+nobserved_vars(imply::SemImply) = nobserved_vars(imply.ram_matrices)
+nlatent_vars(imply::SemImply) = nlatent_vars(imply.ram_matrices)
+
+params(imply::SemImply) = params(imply.ram_matrices)
+nparams(imply::SemImply) = nparams(imply.ram_matrices)
+
+function check_acyclic(A::AbstractMatrix)
+    # check if the model is acyclic
+    acyclic = isone(det(I-A))
+
+    # check if A is lower or upper triangular
+    if istril(A)
+        @info "A matrix is lower triangular"
+        return LowerTriangular(A)
+    elseif istriu(A)
+        @info "A matrix is upper triangular"
+        return UpperTriangular(A)
+    else
+        if acyclic
+            @info "Your model is acyclic, specifying the A Matrix as either Upper or Lower Triangular can have great performance benefits.\n" maxlog=1
+        end
+        return A
+    end
+end