20230712

paschermayr · Jul 12, 2023 · 700778f · 700778f · paschermayr · Jul 12, 2023
1 parent 166f0a4
commit 700778f
Show file tree

Hide file tree

Showing 4 changed files with 15 additions and 14 deletions.
diff --git a/Project.toml b/Project.toml
@@ -1,7 +1,7 @@
 name = "Baytes"
 uuid = "72ddfcfc-6e9d-43df-829b-7aed7c549d4f"
 authors = ["Patrick Aschermayr <p.aschermayr@gmail.com>"]
-version = "0.3.6"
+version = "0.3.7"
 
 [deps]
 ArgCheck = "dce04be8-c92d-5529-be00-80e4d2c0e197"
@@ -31,7 +31,7 @@ BaytesSMC = "0.3"
 DocStringExtensions = "0.8, 0.9"
 JLD2 = "0.4"
 MCMCDiagnosticTools = "0.3"
-ModelWrappers = "0.4"
+ModelWrappers = "0.5"
 PrettyTables = "2"
 ProgressMeter = "1.7"
 SimpleUnPack = "1"

diff --git a/src/Baytes.jl b/src/Baytes.jl
@@ -48,6 +48,8 @@ using ModelWrappers:
     ModelWrapper,
     Tagged,
     Objective,
+    length_constrained, 
+    length_unconstrained,
 #=    DiffObjective,
     AbstractDifferentiableTune,
     ℓObjectiveResult,

diff --git a/src/sampling/chain.jl b/src/sampling/chain.jl
@@ -141,7 +141,7 @@ function chainsummary(
     @unpack Ndigits, quantiles = printdefault
     @unpack progress = trace.summary
     @unpack tagged, paramnames = transform
-    Nparams = length(tagged)
+    Nparams = length_constrained(tagged)
     Nchains = length(transform.chains)
     ## Flatten parameter to 3D array
     computingtime = progress.enabled ? (progress.tlast - progress.tinit) : NaN

diff --git a/src/sampling/inference.jl b/src/sampling/inference.jl
@@ -140,7 +140,7 @@ function trace_to_3DArray(
     ## Get trace information
     @unpack tagged, chains, effective_iterations = transform
     ## Preallocate array
-    mcmcchain = zeros(length(effective_iterations), length(chains), length(tagged))
+    mcmcchain = zeros(length(effective_iterations), length(chains), length_constrained(tagged))
     ## Flatten corresponding parameter
     #!NOTE: Commented-out loop below is threadsave, but chain is not flattened in correct order, which might be troublesome for MCMC chain analysis.
 #    Threads.@threads for (idx, chain) in collect(enumerate(chains))
@@ -171,17 +171,16 @@ function trace_to_3DArrayᵤ(
     ## Get trace information
     @unpack tagged, chains, effective_iterations = transform
     ## Preallocate array
-    mcmcchain = zeros(length(effective_iterations), length(chains), length(tagged))
+    mcmcchain = zeros(length(effective_iterations), length(chains), length_unconstrained(tagged))
     ## Flatten corresponding parameter
     #!NOTE: This is threadsave, but chain is not flattened in correct order, which might be troublesome for MCMC chain analysis.
 #    Threads.@threads for (idx, chain) in collect(enumerate(chains))
     for (idx, chain) in collect(enumerate(chains))
         for (iter0, iterburnin) in enumerate(effective_iterations)
 #            mcmcchain[iter0, :, idx] .=
             mcmcchain[iter0, idx, :] .=
-                flatten(tagged.info.reconstruct,
-                    unconstrain(tagged.info.transform, subset(trace.val[chain][iterburnin], tagged.parameter) )
-                )
+#                flatten(tagged.info.reconstruct, unconstrain(tagged.info.transform, subset(trace.val[chain][iterburnin], tagged.parameter) ) )
+                ModelWrappers.unconstrain_flatten(tagged.info, subset(trace.val[chain][iterburnin], tagged.parameter))
         end
     end
     ## Return MCMCChain
@@ -205,7 +204,7 @@ function trace_to_2DArray(
     ## Get trace information
     @unpack tagged, chains, effective_iterations = transform
     ## Preallocate array
-    mcmcchain = zeros(length(effective_iterations) * length(chains), length(tagged))
+    mcmcchain = zeros(length(effective_iterations) * length(chains), length_constrained(tagged))
     ## Flatten corresponding parameter
     #!NOTE: This is threadsave, but chain is not flattened in correct order, which might be troublesome for MCMC chain analysis.
 #    Threads.@threads for (idx, chain) in collect(enumerate(chains))
@@ -235,17 +234,17 @@ function trace_to_2DArrayᵤ(
     ## Get trace information
     @unpack tagged, chains, effective_iterations = transform
     ## Preallocate array
-    mcmcchain = zeros(length(effective_iterations) * length(chains), length(tagged))
+    mcmcchain = zeros(length(effective_iterations) * length(chains), length_unconstrained(tagged))
     ## Flatten corresponding parameter
     #!NOTE: This is threadsave, but chain is not flattened in correct ordered, which might be troublesome for MCMC chain analysis.
 #    Threads.@threads for (idx, chain) in collect(enumerate(chains))
     iter = 0
     for (idx, chain) in collect(enumerate(chains))
         for (iter0, iterburnin) in enumerate(effective_iterations)
             iter += 1
-            mcmcchain[iter, :] .= flatten(tagged.info.reconstruct,
-                unconstrain(tagged.info.transform, subset(trace.val[chain][iterburnin], tagged.parameter) )
-            )
+            mcmcchain[iter, :] .= 
+#                flatten(tagged.info.reconstruct, unconstrain(tagged.info.transform, subset(trace.val[chain][iterburnin], tagged.parameter) ) )
+                ModelWrappers.unconstrain_flatten(tagged.info, subset(trace.val[chain][iterburnin], tagged.parameter))
         end
     end
     ## Return MCMCChain
@@ -329,7 +328,7 @@ function flatten_chainvals(
     ## Get trace information
     @unpack tagged, chains, effective_iterations = transform
     ## Preallocate array
-    mcmcchain = [ [ zeros(tagged.info.reconstruct.default.output, length(tagged)) for _ in eachindex(effective_iterations) ] for _ in eachindex(chains) ]
+    mcmcchain = [ [ zeros(tagged.info.reconstruct.default.output, length_constrained(tagged)) for _ in eachindex(effective_iterations) ] for _ in eachindex(chains) ]
     ## Flatten corresponding parameter
     #!NOTE: This is threadsave, but chain is not flattened in correct order, which might be troublesome for MCMC chain analysis, hence we opt out of it.
 #    Threads.@threads for (idx, chain) in collect(enumerate(chains))