Use OrderedDict for pointwise_loglikelihoods instead of Dict (#475)

What the title says!

Project.toml

@@ -1,6 +1,6 @@
 name = "DynamicPPL"
 uuid = "366bfd00-2699-11ea-058f-f148b4cae6d8"
-version = "0.22.3"
+version = "0.22.4"
 
 [deps]
 AbstractMCMC = "80f14c24-f653-4e6a-9b94-39d6b0f70001"

src/loglikelihoods.jl

@@ -5,7 +5,7 @@ struct PointwiseLikelihoodContext{A,Ctx} <: AbstractContext
 end
 
 function PointwiseLikelihoodContext(
-    likelihoods=Dict{VarName,Vector{Float64}}(),
+    likelihoods=OrderedDict{VarName,Vector{Float64}}(),
     context::AbstractContext=LikelihoodContext(),
 )
     return PointwiseLikelihoodContext{typeof(likelihoods),typeof(context)}(
@@ -20,7 +20,7 @@ function setchildcontext(context::PointwiseLikelihoodContext, child)
 end
 
 function Base.push!(
-    context::PointwiseLikelihoodContext{Dict{VarName,Vector{Float64}}},
+    context::PointwiseLikelihoodContext{<:AbstractDict{VarName,Vector{Float64}}},
     vn::VarName,
     logp::Real,
 )
@@ -30,13 +30,15 @@ function Base.push!(
 end
 
 function Base.push!(
-    context::PointwiseLikelihoodContext{Dict{VarName,Float64}}, vn::VarName, logp::Real
+    context::PointwiseLikelihoodContext{<:AbstractDict{VarName,Float64}},
+    vn::VarName,
+    logp::Real,
 )
     return context.loglikelihoods[vn] = logp
 end
 
 function Base.push!(
-    context::PointwiseLikelihoodContext{Dict{String,Vector{Float64}}},
+    context::PointwiseLikelihoodContext{<:AbstractDict{String,Vector{Float64}}},
     vn::VarName,
     logp::Real,
 )
@@ -46,13 +48,15 @@ function Base.push!(
 end
 
 function Base.push!(
-    context::PointwiseLikelihoodContext{Dict{String,Float64}}, vn::VarName, logp::Real
+    context::PointwiseLikelihoodContext{<:AbstractDict{String,Float64}},
+    vn::VarName,
+    logp::Real,
 )
     return context.loglikelihoods[string(vn)] = logp
 end
 
 function Base.push!(
-    context::PointwiseLikelihoodContext{Dict{String,Vector{Float64}}},
+    context::PointwiseLikelihoodContext{<:AbstractDict{String,Vector{Float64}}},
     vn::String,
     logp::Real,
 )
@@ -62,7 +66,9 @@ function Base.push!(
 end
 
 function Base.push!(
-    context::PointwiseLikelihoodContext{Dict{String,Float64}}, vn::String, logp::Real
+    context::PointwiseLikelihoodContext{<:AbstractDict{String,Float64}},
+    vn::String,
+    logp::Real,
 )
     return context.loglikelihoods[vn] = logp
 end
@@ -126,11 +132,11 @@ end
 """
     pointwise_loglikelihoods(model::Model, chain::Chains, keytype = String)
 
-Runs `model` on each sample in `chain` returning a `Dict{String, Matrix{Float64}}`
+Runs `model` on each sample in `chain` returning a `OrderedDict{String, Matrix{Float64}}`
 with keys corresponding to symbols of the observations, and values being matrices
 of shape `(num_chains, num_samples)`.
 
-`keytype` specifies what the type of the keys used in the returned `Dict` are.
+`keytype` specifies what the type of the keys used in the returned `OrderedDict` are.
 Currently, only `String` and `VarName` are supported.
 
 # Notes
@@ -179,25 +185,25 @@ julia> model = demo(randn(3), randn());
 julia> chain = sample(model, MH(), 10);
 
 julia> pointwise_loglikelihoods(model, chain)
-Dict{String,Array{Float64,2}} with 4 entries:
-  "xs[3]" => [-1.42862; -2.67573; … ; -1.66251; -1.66251]
+OrderedDict{String,Array{Float64,2}} with 4 entries:
   "xs[1]" => [-1.42932; -2.68123; … ; -1.66333; -1.66333]
   "xs[2]" => [-1.6724; -0.861339; … ; -1.62359; -1.62359]
+  "xs[3]" => [-1.42862; -2.67573; … ; -1.66251; -1.66251]
   "y"     => [-1.51265; -0.914129; … ; -1.5499; -1.5499]
 
 julia> pointwise_loglikelihoods(model, chain, String)
-Dict{String,Array{Float64,2}} with 4 entries:
-  "xs[3]" => [-1.42862; -2.67573; … ; -1.66251; -1.66251]
+OrderedDict{String,Array{Float64,2}} with 4 entries:
   "xs[1]" => [-1.42932; -2.68123; … ; -1.66333; -1.66333]
   "xs[2]" => [-1.6724; -0.861339; … ; -1.62359; -1.62359]
+  "xs[3]" => [-1.42862; -2.67573; … ; -1.66251; -1.66251]
   "y"     => [-1.51265; -0.914129; … ; -1.5499; -1.5499]
 
 julia> pointwise_loglikelihoods(model, chain, VarName)
-Dict{VarName,Array{Float64,2}} with 4 entries:
-  xs[2] => [-1.6724; -0.861339; … ; -1.62359; -1.62359]
-  y     => [-1.51265; -0.914129; … ; -1.5499; -1.5499]
+OrderedDict{VarName,Array{Float64,2}} with 4 entries:
   xs[1] => [-1.42932; -2.68123; … ; -1.66333; -1.66333]
+  xs[2] => [-1.6724; -0.861339; … ; -1.62359; -1.62359]
   xs[3] => [-1.42862; -2.67573; … ; -1.66251; -1.66251]
+  y     => [-1.51265; -0.914129; … ; -1.5499; -1.5499]
 ```
 
 ## Broadcasting
@@ -224,7 +230,7 @@ julia> ℓ = pointwise_loglikelihoods(m, VarInfo(m)); first.((ℓ[@varname(x[1])
 function pointwise_loglikelihoods(model::Model, chain, keytype::Type{T}=String) where {T}
     # Get the data by executing the model once
     vi = VarInfo(model)
-    context = PointwiseLikelihoodContext(Dict{T,Vector{Float64}}())
+    context = PointwiseLikelihoodContext(OrderedDict{T,Vector{Float64}}())
 
     iters = Iterators.product(1:size(chain, 1), 1:size(chain, 3))
     for (sample_idx, chain_idx) in iters
@@ -237,15 +243,15 @@ function pointwise_loglikelihoods(model::Model, chain, keytype::Type{T}=String)
 
     niters = size(chain, 1)
     nchains = size(chain, 3)
-    loglikelihoods = Dict(
+    loglikelihoods = OrderedDict(
         varname => reshape(logliks, niters, nchains) for
         (varname, logliks) in context.loglikelihoods
     )
     return loglikelihoods
 end
 
 function pointwise_loglikelihoods(model::Model, varinfo::AbstractVarInfo)
-    context = PointwiseLikelihoodContext(Dict{VarName,Vector{Float64}}())
+    context = PointwiseLikelihoodContext(OrderedDict{VarName,Vector{Float64}}())
     model(varinfo, context)
     return context.loglikelihoods
 end