Update tests, use link or LogDensityFunction

src/JuliaBUGS.jl

@@ -156,7 +156,7 @@ function compile(model_def::Expr, data, inits)
     vars, array_sizes, array_bitmap, link_functions, node_args, node_functions, dependencies = program!(
         NodeFunctions(vars, array_sizes, array_bitmap), model_def, merged_data
     )
-    g = BUGSGraph(vars, link_functions, node_args, node_functions, dependencies)
+    g = BUGSGraph(vars, node_args, node_functions, dependencies)
     sorted_nodes = map(Base.Fix1(label_for, g), topological_sort(g))
     return BUGSModel(g, sorted_nodes, vars, array_sizes, merged_data, inits)
 end

src/model.jl

@@ -252,7 +252,7 @@ function AbstractPPL.evaluate!!(model::BUGSModel, ::DefaultContext)
                 value_transformed = transform(bijector(dist), value)
                 logp +=
                     logpdf(dist, value) +
-                    logabsdetjac(inverse(bijector(dist)), value_transformed)
+                    logabsdetjac(Bijectors.inverse(bijector(dist)), value_transformed)
             else
                 logp += logpdf(dist, value)
             end
@@ -286,7 +286,7 @@ function AbstractPPL.evaluate!!(
                     current_idx += l
                     # TODO: this use `DynamicPPL.reconstruct`, which needs attention when decoupling from DynamicPPL
                     value, logjac = DynamicPPL.with_logabsdet_jacobian_and_reconstruct(
-                        inverse(bijector(dist)), dist, value_transformed
+                        Bijectors.inverse(bijector(dist)), dist, value_transformed
                     )
                     logp += logpdf(dist, value) + logjac
                     vi = setindex!!(vi, value, vn)
@@ -332,7 +332,7 @@ function AbstractPPL.evaluate!!(model::MarkovBlanketCoveredBUGSModel, ::DefaultC
                 value_transformed = transform(bijector(dist), value)
                 logp +=
                     logpdf(dist, value) +
-                    logabsdetjac(inverse(bijector(dist)), value_transformed)
+                    logabsdetjac(Bijectors.inverse(bijector(dist)), value_transformed)
             else
                 logp += logpdf(dist, value)
             end
@@ -372,7 +372,7 @@ function AbstractPPL.evaluate!!(
                     current_idx += l
                     # TODO: this use `DynamicPPL.reconstruct`, which needs attention when decoupling from DynamicPPL
                     value, logjac = DynamicPPL.with_logabsdet_jacobian_and_reconstruct(
-                        inverse(bijector(dist)), dist, value_transformed
+                        Bijectors.inverse(bijector(dist)), dist, value_transformed
                     )
                     logp += logpdf(dist, value) + logjac
                     vi = setindex!!(vi, value, vn)

test/logp_tests/binomial.jl

@@ -13,7 +13,7 @@ dppl_model = dppl_gamma_model()
 
 bugs_logp =
     JuliaBUGS.evaluate!!(
-        DynamicPPL.settrans!!(bugs_model, false), DefaultBUGSContext()
+        DynamicPPL.settrans!!(bugs_model, false), DefaultContext()
     ).logp
 params_vi = JuliaBUGS.get_params_varinfo(bugs_model, vi)
 # test if JuliaBUGS and DynamicPPL agree on parameters in the model
@@ -29,7 +29,7 @@ t_p = DynamicPPL.LogDensityFunction(
 @test bugs_logp ≈ LogDensityProblems.logdensity(p, [10.0]) rtol = 1E-6
 
 bugs_logp =
-    JuliaBUGS.evaluate!!(DynamicPPL.settrans!!(bugs_model, true), DefaultBUGSContext()).logp
+    JuliaBUGS.evaluate!!(DynamicPPL.settrans!!(bugs_model, true), DefaultContext()).logp
 @test bugs_logp ≈
     LogDensityProblems.logdensity(t_p, [transform(bijector(dbin(0.1, 10)), 10.0)]) rtol =
-    1E-6
+    1E-6

test/logp_tests/blockers.jl

@@ -3,7 +3,7 @@ data = JuliaBUGS.BUGSExamples.VOLUME_I[:blockers].data
 inits = JuliaBUGS.BUGSExamples.VOLUME_I[:blockers].inits[1]
 
 bugs_model = compile(bugs_model_def, data, inits)
-vi = JuliaBUGS.get_varinfo(bugs_model)
+vi = bugs_model.varinfo
 
 @model function blockers(rc, rt, nc, nt, Num)
     d ~ dnorm(0.0, 1.0E-6)
@@ -36,7 +36,7 @@ dppl_model = blockers(rc, rt, nc, nt, Num)
 
 bugs_logp =
     JuliaBUGS.evaluate!!(
-        DynamicPPL.settrans!!(bugs_model, false), DefaultBUGSContext()
+        DynamicPPL.settrans!!(bugs_model, false), DefaultContext()
     ).logp
 params_vi = JuliaBUGS.get_params_varinfo(bugs_model, vi)
 # test if JuliaBUGS and DynamicPPL agree on parameters in the model
@@ -50,11 +50,11 @@ dppl_logp =
 @test bugs_logp ≈ dppl_logp rtol = 1E-6
 
 bugs_logp =
-    JuliaBUGS.evaluate!!(DynamicPPL.settrans!!(bugs_model, true), DefaultBUGSContext()).logp
+    JuliaBUGS.evaluate!!(DynamicPPL.settrans!!(bugs_model, true), DefaultContext()).logp
 dppl_logp =
     DynamicPPL.evaluate!!(
         dppl_model,
-        DynamicPPL.settrans!!(get_params_varinfo(bugs_model), true),
+        DynamicPPL.link!!(get_params_varinfo(bugs_model), dppl_model),
         DynamicPPL.DefaultContext(),
     )[2].logp
 @test bugs_logp ≈ dppl_logp rtol = 1E-6

test/logp_tests/bones.jl

@@ -3,7 +3,7 @@ data = JuliaBUGS.BUGSExamples.VOLUME_I[:bones].data
 inits = JuliaBUGS.BUGSExamples.VOLUME_I[:bones].inits[1]
 
 bugs_model = compile(bugs_model_def, data, inits)
-vi = JuliaBUGS.get_varinfo(bugs_model)
+vi = bugs_model.varinfo
 
 @model function bones(grade, nChild, nInd, ncat, gamma, delta)
     theta = Vector{Real}(undef, nChild)
@@ -38,7 +38,7 @@ dppl_model = bones(grade, nChild, nInd, ncat, gamma, delta)
 
 bugs_logp =
     JuliaBUGS.evaluate!!(
-        DynamicPPL.settrans!!(bugs_model, false), DefaultBUGSContext()
+        DynamicPPL.settrans!!(bugs_model, false), DefaultContext()
     ).logp
 params_vi = JuliaBUGS.get_params_varinfo(bugs_model, vi)
 # test if JuliaBUGS and DynamicPPL agree on parameters in the model
@@ -52,11 +52,11 @@ dppl_logp =
 @test bugs_logp ≈ dppl_logp rtol = 1E-6
 
 bugs_logp =
-    JuliaBUGS.evaluate!!(DynamicPPL.settrans!!(bugs_model, true), DefaultBUGSContext()).logp
+    JuliaBUGS.evaluate!!(DynamicPPL.settrans!!(bugs_model, true), DefaultContext()).logp
 dppl_logp =
     DynamicPPL.evaluate!!(
         dppl_model,
-        DynamicPPL.settrans!!(get_params_varinfo(bugs_model), true),
+        DynamicPPL.link!!(get_params_varinfo(bugs_model), dppl_model),
         DynamicPPL.DefaultContext(),
     )[2].logp
 @test bugs_logp ≈ dppl_logp rtol = 1E-6

test/logp_tests/dogs.jl

@@ -3,7 +3,7 @@ data = JuliaBUGS.BUGSExamples.VOLUME_I[:dogs].data
 inits = JuliaBUGS.BUGSExamples.VOLUME_I[:dogs].inits[1]
 
 bugs_model = compile(bugs_model_def, data, inits)
-vi = JuliaBUGS.get_varinfo(bugs_model)
+vi = bugs_model.varinfo
 
 @model function dogs(Dogs, Trials, Y, y)
     # Initialize matrices
@@ -41,7 +41,7 @@ dppl_model = dogs(Dogs, Trials, Y, 1 .- Y)
 
 bugs_logp =
     JuliaBUGS.evaluate!!(
-        DynamicPPL.settrans!!(bugs_model, false), DefaultBUGSContext()
+        DynamicPPL.settrans!!(bugs_model, false), DefaultContext()
     ).logp
 
 dppl_logp =
@@ -52,11 +52,11 @@ dppl_logp =
 @test bugs_logp ≈ dppl_logp rtol = 1E-6
 
 bugs_logp =
-    JuliaBUGS.evaluate!!(DynamicPPL.settrans!!(bugs_model, true), DefaultBUGSContext()).logp
+    JuliaBUGS.evaluate!!(DynamicPPL.settrans!!(bugs_model, true), DefaultContext()).logp
 dppl_logp =
     DynamicPPL.evaluate!!(
         dppl_model,
-        DynamicPPL.settrans!!(get_params_varinfo(bugs_model), true),
+        DynamicPPL.link!!(get_params_varinfo(bugs_model), dppl_model),
         DynamicPPL.DefaultContext(),
     )[2].logp
 @test bugs_logp ≈ dppl_logp rtol = 1E-6

test/logp_tests/gamma.jl

@@ -14,7 +14,7 @@ dppl_model = dppl_gamma_model()
 
 bugs_logp =
     JuliaBUGS.evaluate!!(
-        DynamicPPL.settrans!!(bugs_model, false), DefaultBUGSContext()
+        DynamicPPL.settrans!!(bugs_model, false), DefaultContext()
     ).logp
 params_vi = JuliaBUGS.get_params_varinfo(bugs_model, vi)
 # test if JuliaBUGS and DynamicPPL agree on parameters in the model
@@ -30,7 +30,7 @@ t_p = DynamicPPL.LogDensityFunction(
 @test bugs_logp ≈ LogDensityProblems.logdensity(p, [10.0]) rtol = 1E-6
 
 bugs_logp =
-    JuliaBUGS.evaluate!!(DynamicPPL.settrans!!(bugs_model, true), DefaultBUGSContext()).logp
+    JuliaBUGS.evaluate!!(DynamicPPL.settrans!!(bugs_model, true), DefaultContext()).logp
 @test bugs_logp ≈
     LogDensityProblems.logdensity(t_p, [transform(bijector(dgamma(0.001, 0.001)), 10.0)]) rtol =
     1E-6

test/logp_tests/rats.jl

@@ -23,6 +23,7 @@ model_def = @bugs begin
     alpha0 = alpha_c - xbar * beta_c
 end
 bugs_model = compile(model_def, data, inits);
+vi = bugs_model.varinfo
 
 @model function rats(Y, x, xbar, N, T)
     tau_c ~ dgamma(0.001, 0.001)
@@ -53,15 +54,27 @@ bugs_model = compile(model_def, data, inits);
 end
 dppl_model = rats(Y, x, xbar, N, T)
 
-vi, bugs_logp = get_vi_logp(bugs_model, false)
+bugs_model = DynamicPPL.settrans!!(bugs_model, false)
+bugs_logp = JuliaBUGS.evaluate!!(bugs_model, DefaultContext()).logp
 params_vi = JuliaBUGS.get_params_varinfo(bugs_model, vi)
 # test if JuliaBUGS and DynamicPPL agree on parameters in the model
 @test params_in_dppl_model(dppl_model) == keys(params_vi)
 
-vi, dppl_logp = get_vi_logp(dppl_model, vi, false)
+dppl_logp =
+    DynamicPPL.evaluate!!(
+        dppl_model, DynamicPPL.settrans!!(vi, false), DynamicPPL.DefaultContext()
+    )[2].logp
 @test bugs_logp ≈ -174029.387 rtol = 1E-6 # reference value from ProbPALA
 @test bugs_logp ≈ dppl_logp rtol = 1E-6
 
-vi, bugs_logp = get_vi_logp(bugs_model, true)
-vi, dppl_logp = get_vi_logp(dppl_model, vi, true)
+dppl_logp =
+    DynamicPPL.evaluate!!(
+        dppl_model,
+        link!!(get_params_varinfo(bugs_model), dppl_model),
+        DynamicPPL.DefaultContext(),
+    )[2].logp 
+bugs_logp = JuliaBUGS.evaluate!!(DynamicPPL.settrans!!(bugs_model, true), DefaultContext()).logp
 @test bugs_logp ≈ dppl_logp rtol = 1E-6
+
+@test bugs_model.param_length ==
+    LogDensityProblems.dimension(DynamicPPL.LogDensityFunction(dppl_model))

test/runtests.jl

@@ -15,7 +15,7 @@ using JuliaBUGS:
     Stochastic,
     Logical,
     evaluate!!,
-    DefaultBUGSContext,
+    DefaultContext,
     BUGSGraph,
     stochastic_neighbors,
     stochastic_inneighbors,
@@ -26,9 +26,7 @@ using JuliaBUGS:
     LogDensityContext,
     ConcreteNodeInfo,
     SimpleVarInfo,
-    get_params_varinfo,
-    get_varinfo,
-    transformation
+    get_params_varinfo
 using JuliaBUGS.BUGSPrimitives
 using JuliaBUGS.BUGSPrimitives: mean
 using LogDensityProblems, LogDensityProblemsAD