remove dep on DynamicPPL

Project.toml

@@ -29,7 +29,6 @@ Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
 [weakdeps]
 AdvancedHMC = "0bf59076-c3b1-5ca4-86bd-e02cd72cde3d"
 AdvancedMH = "5b7e9947-ddc0-4b3f-9b55-0d8042f74170"
-DynamicPPL = "366bfd00-2699-11ea-058f-f148b4cae6d8"
 GLMakie = "e9467ef8-e4e7-5192-8a1a-b1aee30e663a"
 GraphMakie = "1ecd5474-83a3-4783-bb4f-06765db800d2"
 GraphPlot = "a2cc645c-3eea-5389-862e-a155d0052231"
@@ -38,10 +37,9 @@ MCMCChains = "c7f686f2-ff18-58e9-bc7b-31028e88f75d"
 [extensions]
 JuliaBUGSAdvancedHMCExt = ["AdvancedHMC", "MCMCChains"]
 JuliaBUGSAdvancedMHExt = ["AdvancedMH", "MCMCChains"]
-JuliaBUGSDynamicPPLExt = ["DynamicPPL"]
 JuliaBUGSGraphMakieExt = ["GraphMakie", "GLMakie"]
 JuliaBUGSGraphPlotExt = ["GraphPlot"]
-JuliaBUGSMCMCChainsExt = ["DynamicPPL", "MCMCChains"]
+JuliaBUGSMCMCChainsExt = ["MCMCChains"]
 
 [compat]
 ADTypes = "1.6"
@@ -54,7 +52,6 @@ BangBang = "0.4.1"
 Bijectors = "0.13"
 Distributions = "0.23.8, 0.24, 0.25"
 Documenter = "0.27, 1"
-DynamicPPL = "0.25, 0.26, 0.27, 0.28, 0.29"
 GLMakie = "0.10"
 GraphMakie = "0.5"
 GraphPlot = "0.6"
@@ -86,4 +83,4 @@ ReverseDiff = "37e2e3b7-166d-5795-8a7a-e32c996b4267"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
 
 [targets]
-test = ["AbstractMCMC", "ADTypes", "AdvancedHMC", "AdvancedMH", "DynamicPPL", "MCMCChains", "LogDensityProblemsAD", "ReverseDiff", "Test"]
+test = ["AbstractMCMC", "ADTypes", "AdvancedHMC", "AdvancedMH", "MCMCChains", "LogDensityProblemsAD", "ReverseDiff", "Test"]

ext/JuliaBUGSMCMCChainsExt.jl

@@ -6,7 +6,6 @@ using JuliaBUGS.AbstractPPL
 using JuliaBUGS.BUGSPrimitives
 using JuliaBUGS.LogDensityProblems
 using JuliaBUGS.LogDensityProblemsAD
-using DynamicPPL
 using AbstractMCMC
 using MCMCChains: Chains
 
@@ -50,6 +49,28 @@ function JuliaBUGS.gen_chains(
     )
 end
 
+# copied from DynamicPPL
+varname_leaves(vn::VarName, ::Real) = [vn]
+function varname_leaves(vn::VarName, val::AbstractArray{<:Union{Real,Missing}})
+    return (
+        VarName(vn, Accessors.IndexLens(Tuple(I)) ∘ getoptic(vn)) for
+        I in CartesianIndices(val)
+    )
+end
+function varname_leaves(vn::VarName, val::AbstractArray)
+    return Iterators.flatten(
+        varname_leaves(VarName(vn, Accessors.IndexLens(Tuple(I)) ∘ getoptic(vn)), val[I])
+        for I in CartesianIndices(val)
+    )
+end
+function varname_leaves(vn::VarName, val::NamedTuple)
+    iter = Iterators.map(keys(val)) do sym
+        optic = Accessors.PropertyLens{sym}()
+        varname_leaves(VarName(vn, optic ∘ getoptic(vn)), optic(val))
+    end
+    return Iterators.flatten(iter)
+end
+
 function JuliaBUGS.gen_chains(
     model::JuliaBUGS.BUGSModel,
     samples,
@@ -84,13 +105,13 @@ function JuliaBUGS.gen_chains(
 
     param_name_leaves = collect(
         Iterators.flatten([
-            collect(DynamicPPL.varname_leaves(vn, param_vals[1][i])) for
+            collect(varname_leaves(vn, param_vals[1][i])) for
             (i, vn) in enumerate(param_vars)
         ],),
     )
     generated_varname_leaves = collect(
         Iterators.flatten([
-            collect(DynamicPPL.varname_leaves(vn, generated_quantities[1][i])) for
+            collect(varname_leaves(vn, generated_quantities[1][i])) for
             (i, vn) in enumerate(generated_vars)
         ],),
     )

src/model.jl

@@ -260,6 +260,23 @@ function getparams(model::BUGSModel)
     return param_vals
 end
 
+function getparams_as_ordereddict(model::BUGSModel)
+    d = OrderedDict{VarName,Any}()
+    for v in model.parameters
+        if !model.transformed
+            d[v] = AbstractPPL.get(model.evaluation_env, v)
+        else
+            (; node_function, node_args, loop_vars) = model.g[v]
+            args = prepare_arg_values(node_args, model.evaluation_env, loop_vars)
+            dist = node_function(; args...)
+            d[v] = Bijectors.transform(
+                Bijectors.bijector(dist), AbstractPPL.get(model.evaluation_env, v)
+            )
+        end
+    end
+    return d
+end
+
 """
     settrans(model::BUGSModel, bool::Bool=!(model.transformed))