fixed bugs

src/MultilevelChainSampler.jl

@@ -26,7 +26,9 @@ export sample
 export MetropolisHastings, ChristenFox
 export total_costs
 
-export nchains, info, states
+export nchains, info
+export is_multilevel
+export states
 export autocov, logpart, empirical_cdf
 export RejectionChains
 

src/algos/christen_fox.jl

@@ -41,7 +41,7 @@ function AbstractMCMC.samples(sample, model::AbstractMultilevelModel, ::Christen
     return (;
         rejections = [zeros(Int, length(model))],
         transitions = [sample[2:end]],
-        last_accepted = Ptr{Int}(0)
+        last_accepted = Ref{Int}(0)
     )
 end
 function AbstractMCMC.save!!(samples, sample, ::Integer, model::AbstractMultilevelModel, ::ChristenFox{true, P}; kwargs... ) where {P}

src/chains/all.jl

@@ -28,56 +28,3 @@ function Base.display(c::AbstractRejectionChains)
     end
 end
 
-
-#=abstract type AbstractRejectionChains <: AbstractMCMC.AbstractChains end
-
-#include("simple.jl")
-#include("multi.jl")
-
-#=
-struct RejectionChains{X, L, R, I} <: AbstractRejectionChains
-    states::Matrix{X}
-    logprobs::Matrix{L}
-    rejections::Matrix{R}
-end
-
-eltype(c::RejectionChains{X,L,R}) where {X,L,R} = X 
-size(c::RejectionChains, args...) = size(c.states, args...)
-
-function getindex(c::RejectionChains, n, m )
-    return RejectionChains(
-        c.states[n, m],
-        c.logprobs[n, m],
-        c.rejections[n, m]
-    )
-end
-
-function states(c::RejectionChains)
-    return fill.(c.states, c.rejections)
-end
-
-function get_info(c::RejectionChains)
-    s = size(c)
-    rejection_rate
-    (; )
-end
-=#
-
-function Base.show(io::IO, c::RejectionBasedChains)
-    print(io, "Chain ", size(c), " {", eltype(c), "}")
-end
-
-function Base.display(c::RejectionBasedChains)
-    println(c)
-    info = get_info(c)
-    nchains = size(c, 2)
-    for k = keys(info)
-        if nchains == 1
-            println(" ", k, " : ", info[k][1])
-        else
-            m, s = mean(info[k]), std(info[k])
-            println(" ", k, " : ", m, " ± ", s)
-        end
-    end
-end
-=#
\ No newline at end of file

test/test_chains.jl

@@ -9,16 +9,22 @@ using Revise
 using MultilevelChainSampler
 using CSV, DataFrames
 
+
 w = CyclicWalk()
 s = MetropolisHastings(w)
 
 f = LogDensity(x->-x^2/2)
-c = sample(f, s, MCMCSerial(), 100, 4)
+c = sample(f, s, MCMCSerial(), 300, 4)
 
 # Test conversion
 df = convert(Vector{DataFrame}, c)
 c2 = convert(RejectionChains, df)
 
-# Test 
 autocov(c)
+
+# Test multilevel 
 @test all( abs.( empirical_cdf(c, .5) .- 0.78045 ) .< 0.1 )
+
+g = MultilevelLogDensity([f,f])
+s3 = ChristenFox(w, true)
+c3 = sample(g, s3, MCMCSerial(), 300, 4)