simulation: update rand()

Author: Alexey Stukalov

src/additional_functions/simulation.jl

@@ -2,14 +2,14 @@
 # simulate data
 ############################################################################################
 """
-    rand(sem::Union{Sem, SemLoss, SemImplied}, params, n)
-    rand(sem::Union{Sem, SemLoss, SemImplied}, n)
+    rand(sem::Union{Sem, SemLoss, SemImplied}, [params], n)
 
 Sample from the multivariate normal distribution implied by the SEM model.
 
 # Arguments
 - `sem`: SEM model to use. Ensemble models with multiple SEM terms are not supported.
-- `params`: SEM model parameters to simulate from.
+- `params`: optional SEM model parameters to simulate from, otherwise uses the
+  current state of implied covariances and means.
 - `n::Integer`: Number of samples to draw.
 
 # Examples
@@ -18,14 +18,10 @@ rand(model, start_simple(model), 100)
 ```
 """
 function Distributions.rand(implied::SemImplied, params, n::Integer)
-    update!(EvaluationTargets{true, false, false}(), implied, params)
-    return rand(implied, n)
-end
-
-Distributions.rand(implied::SemImplied, n::Integer) =
-    error("rand($(typeof(implied)), n) is not implemented")
-
-function Distributions.rand(implied::Union{RAM, RAMSymbolic}, n::Integer)
+    if !isnothing(params)
+        # update the implied covariances with the new model params
+        update!(EvaluationTargets{true, false, false}(), implied, params)
+    end
     Σ = Symmetric(implied.Σ)
     if MeanStruct(implied) === NoMeanStruct
         return permutedims(rand(MvNormal(Σ), n))
@@ -36,8 +32,8 @@ end
 
 Distributions.rand(loss::SemLoss, params, n::Integer) = rand(SEM.implied(loss), params, n)
 
-Distributions.rand(loss::SemLoss, n::Integer) = rand(SEM.implied(loss), n)
-
 Distributions.rand(model::Sem, params, n::Integer) = rand(sem_term(model), params, n)
 
-Distributions.rand(model::Sem, n::Integer) = rand(sem_term(model), n)
+# rand() overloads without SEM params
+Distributions.rand(implied::Union{SemImplied, SemLoss, Sem}, n::Integer) =
+    Distributions.rand(implied, nothing, n)