Merge pull request #31 from devmotion/mcmcchains

Update for MCMCChains 4

Author: yebai

src/mcmcchains-connect.jl

@@ -12,21 +12,21 @@ function AbstractMCMC.bundle_samples(
     kwargs...
 )
     # Turn all the transitions into a vector-of-vectors.
-    vals = copy(reduce(hcat,[vcat(t.params, t.lp) for t in ts])')
+    vals = [vcat(t.params, t.lp) for t in ts]
 
     # Check if we received any parameter names.
     if ismissing(param_names)
-        param_names = ["param_$i" for i in 1:length(s.init_params)]
+        param_names = [Symbol(:param_, i) for i in 1:length(s.init_params)]
     else
-        # Deepcopy to be thread safe.
-        param_names = deepcopy(param_names)
+        # Generate new array to be thread safe.
+        param_names = Symbol.(param_names)
     end
 
     # Add the log density field to the parameter names.
-    push!(param_names, "lp")
+    push!(param_names, :lp)
 
     # Bundle everything up and return a Chains struct.
-    return Chains(vals, param_names, (internals=["lp"],))
+    return Chains(vals, param_names, (internals = [:lp],))
 end
 
 function AbstractMCMC.bundle_samples(
@@ -56,15 +56,15 @@ function AbstractMCMC.bundle_samples(
 
     # Check if we received any parameter names.
     if ismissing(param_names)
-        param_names = ["param_$i" for i in 1:length(ts[1][1].params)]
+        param_names = [Symbol(:param_, i) for i in 1:length(ts[1][1].params)]
     else
-        # Deepcopy to be thread safe.
-        param_names = deepcopy(param_names)
+        # Generate new array to be thread safe.
+        param_names = Symbol.(param_names)
     end
 
     # Add the log density field to the parameter names.
-    push!(param_names, "lp")
+    push!(param_names, :lp)
 
     # Bundle everything up and return a Chains struct.
-    return Chains(vals, param_names, (internals=["lp"],))
-end
+    return Chains(vals, param_names, (internals=[:lp],))
+end

test/emcee.jl

@@ -20,8 +20,8 @@
             chain = sample(model, sampler, 1_000;
                            param_names = ["s", "m"], chain_type = Chains)
 
-            @test mean(chain["s"].value) ≈ 49/24 atol=0.1
-            @test mean(chain["m"].value) ≈ 7/6 atol=0.1
+            @test mean(chain["s"]) ≈ 49/24 atol=0.1
+            @test mean(chain["m"]) ≈ 7/6 atol=0.1
         end
 
         @testset "transformed space" begin
@@ -45,8 +45,8 @@
             chain = sample(model, sampler, 1_000;
                            param_names = ["logs", "m"], chain_type = Chains)
 
-            @test mean(exp.(chain["logs"].value)) ≈ 49/24 atol=0.1
-            @test mean(chain["m"].value) ≈ 7/6 atol=0.1
+            @test mean(exp, chain["logs"]) ≈ 49/24 atol=0.1
+            @test mean(chain["m"]) ≈ 7/6 atol=0.1
         end
     end
 end

test/runtests.jl

@@ -58,14 +58,14 @@ using Test
 
         chain1 = sample(model, spl1, MCMCDistributed(), 10000, 4;
                         param_names=["μ", "σ"], chain_type=Chains)
-        @test mean(chain1["μ"].value) ≈ 0.0 atol=0.1
-        @test mean(chain1["σ"].value) ≈ 1.0 atol=0.1
+        @test mean(chain1["μ"]) ≈ 0.0 atol=0.1
+        @test mean(chain1["σ"]) ≈ 1.0 atol=0.1
 
         if VERSION >= v"1.3"
             chain2 = sample(model, spl1, MCMCThreads(), 10000, 4;
                             param_names=["μ", "σ"], chain_type=Chains)
-            @test mean(chain2["μ"].value) ≈ 0.0 atol=0.1
-            @test mean(chain2["σ"].value) ≈ 1.0 atol=0.1
+            @test mean(chain2["μ"]) ≈ 0.0 atol=0.1
+            @test mean(chain2["σ"]) ≈ 1.0 atol=0.1
         end
     end