Fix SampleFromUniform

src/context_implementations.jl

@@ -103,24 +103,48 @@ function observe(spl::Sampler, weight)
     error("DynamicPPL.observe: unmanaged inference algorithm: $(typeof(spl))")
 end
 
+# If parameters exist, they are used and not overwritten.
 function assume(
-    spl::Union{SampleFromPrior, SampleFromUniform},
+    spl::SampleFromPrior,
     dist::Distribution,
     vn::VarName,
     vi::VarInfo,
 )
     if haskey(vi, vn)
         if is_flagged(vi, vn, "del")
             unset_flag!(vi, vn, "del")
-            r = spl isa SampleFromUniform ? init(dist) : rand(dist)
+            r = rand(dist)
             vi[vn] = vectorize(dist, r)
+            settrans!(vi, false, vn)
             setorder!(vi, vn, get_num_produce(vi))
         else
-        r = vi[vn]
+            r = vi[vn]
         end
     else
-        r = isa(spl, SampleFromUniform) ? init(dist) : rand(dist)
+        r = rand(dist)
+        push!(vi, vn, r, dist, spl)
+        settrans!(vi, false, vn)
+    end
+    return r, Bijectors.logpdf_with_trans(dist, r, istrans(vi, vn))
+end
+
+# Always overwrites the parameters with new ones.
+function assume(
+    spl::SampleFromUniform,
+    dist::Distribution,
+    vn::VarName,
+    vi::VarInfo,
+)
+    if haskey(vi, vn)
+        unset_flag!(vi, vn, "del")
+        r = init(dist)
+        vi[vn] = vectorize(dist, r)
+        settrans!(vi, true, vn)
+        setorder!(vi, vn, get_num_produce(vi))
+    else
+        r = init(dist)
         push!(vi, vn, r, dist, spl)
+        settrans!(vi, true, vn)
     end
     # NOTE: The importance weight is not correctly computed here because
     #       r is genereated from some uniform distribution which is different from the prior

src/utils.jl

@@ -117,8 +117,8 @@ end
 
 # ROBUST INITIALISATIONS
 # Uniform rand with range 2; ref: https://mc-stan.org/docs/2_19/reference-manual/initialization.html
-randrealuni() = Real(2rand())
-randrealuni(args...) = map(Real, 2rand(args...))
+randrealuni() = 4 * rand() - 2
+randrealuni(args...) = 4 .* rand(args...) .- 2
 
 const Transformable = Union{TransformDistribution, SimplexDistribution, PDMatDistribution}
 

src/varinfo.jl

@@ -820,6 +820,7 @@ Return the current value(s) of the random variables sampled by `spl` in `vi`.
 The value(s) may or may not be transformed to Euclidean space.
 """
 getindex(vi::AbstractVarInfo, spl::SampleFromPrior) = copy(getall(vi))
+getindex(vi::AbstractVarInfo, spl::SampleFromUniform) = copy(getall(vi))
 getindex(vi::UntypedVarInfo, spl::Sampler) = copy(getval(vi, _getranges(vi, spl)))
 function getindex(vi::TypedVarInfo, spl::Sampler)
     # Gets the ranges as a NamedTuple

test/varinfo.jl

@@ -6,7 +6,7 @@ using DynamicPPL: Selector, reconstruct, invlink, CACHERESET,
     set_flag!, unset_flag!, VarInfo, TypedVarInfo,
     getlogp, setlogp!, resetlogp!, acclogp!, vectorize,
     setorder!, updategid!
-using DynamicPPL
+using DynamicPPL, LinearAlgebra
 using Distributions
 using ForwardDiff: Dual
 using Test
@@ -167,32 +167,32 @@ include(dir*"/test/test_utils/AllUtils.jl")
         meta = vi.metadata
         model(vi, SampleFromUniform())
 
-        @test all(x -> ~istrans(vi, x), meta.vns)
+        @test all(x -> istrans(vi, x), meta.vns)
         alg = HMC(0.1, 5)
         spl = Sampler(alg, model)
         v = copy(meta.vals)
-        link!(vi, spl)
-        @test all(x -> istrans(vi, x), meta.vns)
         invlink!(vi, spl)
         @test all(x -> ~istrans(vi, x), meta.vns)
-        @test meta.vals == v
+        link!(vi, spl)
+        @test all(x -> istrans(vi, x), meta.vns)
+        @test norm(meta.vals - v) <= 1e-6
 
         vi = TypedVarInfo(vi)
         meta = vi.metadata
         alg = HMC(0.1, 5)
         spl = Sampler(alg, model)
-        @test all(x -> ~istrans(vi, x), meta.s.vns)
-        @test all(x -> ~istrans(vi, x), meta.m.vns)
-        v_s = copy(meta.s.vals)
-        v_m = copy(meta.m.vals)
-        link!(vi, spl)
         @test all(x -> istrans(vi, x), meta.s.vns)
         @test all(x -> istrans(vi, x), meta.m.vns)
+        v_s = copy(meta.s.vals)
+        v_m = copy(meta.m.vals)
         invlink!(vi, spl)
         @test all(x -> ~istrans(vi, x), meta.s.vns)
         @test all(x -> ~istrans(vi, x), meta.m.vns)
-        @test meta.s.vals == v_s
-        @test meta.m.vals == v_m
+        link!(vi, spl)
+        @test all(x -> istrans(vi, x), meta.s.vns)
+        @test all(x -> istrans(vi, x), meta.m.vns)
+        @test norm(meta.s.vals - v_s) <= 1e-6
+        @test norm(meta.m.vals - v_m) <= 1e-6
     end
     @testset "setgid!" begin
         vi = VarInfo()