Merge branch 'master' into rylin/bayesnet_implementations

Project.toml

@@ -1,6 +1,6 @@
 name = "JuliaBUGS"
 uuid = "ba9fb4c0-828e-4473-b6a1-cd2560fee5bf"
-version = "0.7.0"
+version = "0.7.1"
 
 [deps]
 AbstractMCMC = "80f14c24-f653-4e6a-9b94-39d6b0f70001"

ext/JuliaBUGSMCMCChainsExt.jl

@@ -6,6 +6,7 @@ using JuliaBUGS.AbstractPPL
 using JuliaBUGS.BUGSPrimitives
 using JuliaBUGS.LogDensityProblems
 using JuliaBUGS.LogDensityProblemsAD
+using JuliaBUGS: Accessors
 using AbstractMCMC
 using MCMCChains: Chains
 

test/ext/mcmchains.jl

@@ -91,4 +91,36 @@
     @test means[:beta].nt.mean[1] ≈ 2.1 atol = 0.2
     @test means[:sigma].nt.mean[1] ≈ 0.9 atol = 0.2
     @test means[:gen_quant].nt.mean[1] ≈ 4.2 atol = 0.2
+
+    # test for more complicated varnames
+    model_def = @bugs begin
+        A[1, 1:3] ~ Dirichlet(ones(3))
+        A[2, 1:3] ~ Dirichlet(ones(3))
+        A[3, 1:3] ~ Dirichlet(ones(3))
+
+        mu[1:3] ~ MvNormal(zeros(3), 10 * Diagonal(ones(3)))
+        sigma[1] ~ InverseGamma(2, 3)
+        sigma[2] ~ InverseGamma(2, 3)
+        sigma[3] ~ InverseGamma(2, 3)
+    end
+    model = compile(model_def, (;))
+    ad_model = ADgradient(:ReverseDiff, model; compile=Val(true))
+    hmc_chain = AbstractMCMC.sample(ad_model, NUTS(0.8), 10; chain_type=Chains)
+    @test hmc_chain.name_map[:parameters] == [
+        Symbol("sigma[3]"),
+        Symbol("sigma[2]"),
+        Symbol("sigma[1]"),
+        Symbol("mu[1:3][1]"),
+        Symbol("mu[1:3][2]"),
+        Symbol("mu[1:3][3]"),
+        Symbol("A[3, 1:3][1]"),
+        Symbol("A[3, 1:3][2]"),
+        Symbol("A[3, 1:3][3]"),
+        Symbol("A[2, 1:3][1]"),
+        Symbol("A[2, 1:3][2]"),
+        Symbol("A[2, 1:3][3]"),
+        Symbol("A[1, 1:3][1]"),
+        Symbol("A[1, 1:3][2]"),
+        Symbol("A[1, 1:3][3]"),
+    ]
 end