Bump package, docs, and test compats (#134)

* Use MCMCDiagnosticTools in tests

* Bump IrrationalConstants compat

* Bump TransformVariables compat

* Increment patch number

Project.toml

@@ -1,7 +1,7 @@
 name = "Pathfinder"
 uuid = "b1d3bc72-d0e7-4279-b92f-7fa5d6d2d454"
 authors = ["Seth Axen <[email protected]> and contributors"]
-version = "0.7.1"
+version = "0.7.2"
 
 [deps]
 Accessors = "7d9f7c33-5ae7-4f3b-8dc6-eff91059b697"
@@ -41,7 +41,7 @@ Distributions = "0.25"
 DynamicPPL = "0.20, 0.21"
 Folds = "0.2"
 ForwardDiff = "0.10"
-IrrationalConstants = "0.1.1"
+IrrationalConstants = "0.1.1, 0.2"
 LogDensityProblems = "2"
 MCMCChains = "5"
 Optim = "1.4"

docs/Project.toml

@@ -24,6 +24,6 @@ LogDensityProblemsAD = "1, 2"
 Pathfinder = "0.7"
 StatsFuns = "0.9, 1"
 StatsPlots = "0.14, 0.15"
-TransformVariables = "0.6, 0.7"
+TransformVariables = "0.6, 0.7, 0.8"
 TransformedLogDensities = "1"
 Turing = "0.21, 0.22, 0.23, 0.24"

test/integration/AdvancedHMC/Project.toml

@@ -21,10 +21,10 @@ Distributions = "0.25"
 ForwardDiff = "0.10"
 LogDensityProblems = "1, 2"
 LogDensityProblemsAD = "1"
-MCMCDiagnosticTools = "0.1.3, 0.2"
+MCMCDiagnosticTools = "0.3"
 Optim = "1.4"
 Pathfinder = "0.7"
 StatsFuns = "0.9, 1"
-TransformVariables = "0.6, 0.7"
+TransformVariables = "0.6, 0.7, 0.8"
 TransformedLogDensities = "1"
 julia = "1.6"

test/integration/AdvancedHMC/runtests.jl

@@ -36,19 +36,23 @@ function (prob::RegressionProblem)(θ)
     return lp
 end
 
-function mean_and_mcse(f, θs)
-    zs = map(f, θs)
-    ms = mean(zs)
-    ses = map(mcse, eachrow(reduce(hcat, zs)))
+function as_draw_array(θs)
+    draw_param_mat = transpose(reduce(hcat, θs))
+    return reshape(draw_param_mat, size(draw_param_mat, 1), 1, size(draw_param_mat, 2))
+end
+
+function mean_and_mcse(θs)
+    ms = dropdims(mean(θs; dims=(1, 2)); dims=(1, 2))
+    ses = mcse(θs)
     return ms, ses
 end
 
-function compare_estimates(f, xs1, xs2, α=0.05)
+function compare_estimates(xs1, xs2, α=0.05)
     nparams = length(first(xs1))
     α /= nparams  # bonferroni correction
     p = α / 2
-    m1, s1 = mean_and_mcse(f, xs1)
-    m2, s2 = mean_and_mcse(f, xs2)
+    m1, s1 = mean_and_mcse(xs1)
+    m2, s2 = mean_and_mcse(xs2)
     zs = @. (m1 - m2) / sqrt(s1^2 + s2^2)
     @test all(norminvcdf(p) .< zs .< norminvccdf(p))
 end
@@ -96,9 +100,8 @@ end
         @test AdvancedHMC.∂H∂r(h, r) ≈ AdvancedHMC.∂H∂r(h_dense, r)
         kinetic = AdvancedHMC.GaussianKinetic()
         compare_estimates(
-            identity,
-            [rand(metric, kinetic) for _ in 1:10_000],
-            [rand(metric_dense, kinetic) for _ in 1:10_000],
+            as_draw_array([rand(metric, kinetic) for _ in 1:10_000]),
+            as_draw_array([rand(metric_dense, kinetic) for _ in 1:10_000]),
         )
     end
 
@@ -153,7 +156,7 @@ end
                 drop_warmup=true,
                 progress=false,
             )
-            compare_estimates(identity, samples2, samples1)
+            compare_estimates(as_draw_array(samples2), as_draw_array(samples1))
         end
 
         @testset "Initial point and metric" begin
@@ -173,7 +176,7 @@ end
                 drop_warmup=true,
                 progress=false,
             )
-            compare_estimates(identity, samples3, samples1)
+            compare_estimates(as_draw_array(samples3), as_draw_array(samples1))
         end
 
         @testset "Initial point and final metric" begin
@@ -193,7 +196,7 @@ end
                 drop_warmup=true,
                 progress=false,
             )
-            compare_estimates(identity, samples4, samples1)
+            compare_estimates(as_draw_array(samples4), as_draw_array(samples1))
         end
     end
 end

test/integration/DynamicHMC/Project.toml

@@ -17,10 +17,10 @@ TransformedLogDensities = "f9bc47f6-f3f8-4f3b-ab21-f8bc73906f26"
 DynamicHMC = "3"
 LogDensityProblems = "1, 2"
 LogDensityProblemsAD = "1"
-MCMCDiagnosticTools = "0.1.3, 0.2"
+MCMCDiagnosticTools = "0.3"
 Optim = "1.4"
 Pathfinder = "0.7"
 StatsFuns = "0.9, 1"
-TransformVariables = "0.6, 0.7"
+TransformVariables = "0.6, 0.7, 0.8"
 TransformedLogDensities = "1"
 julia = "1.6"

test/integration/DynamicHMC/runtests.jl

@@ -35,19 +35,18 @@ function (prob::RegressionProblem)(θ)
     return lp
 end
 
-function mean_and_mcse(f, θs)
-    zs = map(f, θs)
-    ms = mean(zs; dims=2)
-    ses = map(mcse, eachrow(zs))
+function mean_and_mcse(θs)
+    ms = dropdims(mean(θs; dims=(1, 2)); dims=(1, 2))
+    ses = mcse(θs)
     return ms, ses
 end
 
-function compare_estimates(f, xs1, xs2, α=0.05)
+function compare_estimates(xs1, xs2, α=0.05)
     nparams = first(size(xs1))
     α /= nparams  # bonferroni correction
     p = α / 2
-    m1, s1 = mean_and_mcse(f, xs1)
-    m2, s2 = mean_and_mcse(f, xs2)
+    m1, s1 = mean_and_mcse(xs1)
+    m2, s2 = mean_and_mcse(xs2)
     zs = @. (m1 - m2) / sqrt(s1^2 + s2^2)
     @test all(norminvcdf(p) .< zs .< norminvccdf(p))
 end
@@ -101,7 +100,8 @@ end
             )
             @test result_hmc2.κ.M⁻¹ isa Diagonal
             compare_estimates(
-                identity, result_hmc2.posterior_matrix, result_hmc1.posterior_matrix
+                DynamicHMC.stack_posterior_matrices([result_hmc2]),
+                DynamicHMC.stack_posterior_matrices([result_hmc1]),
             )
         end
 
@@ -119,7 +119,8 @@ end
             )
             @test result_hmc3.κ.M⁻¹ isa Symmetric
             compare_estimates(
-                identity, result_hmc3.posterior_matrix, result_hmc1.posterior_matrix
+                DynamicHMC.stack_posterior_matrices([result_hmc3]),
+                DynamicHMC.stack_posterior_matrices([result_hmc1]),
             )
         end
 
@@ -137,7 +138,8 @@ end
             )
             @test result_hmc4.κ.M⁻¹ === result_pf.fit_distribution.Σ
             compare_estimates(
-                identity, result_hmc4.posterior_matrix, result_hmc1.posterior_matrix
+                DynamicHMC.stack_posterior_matrices([result_hmc4]),
+                DynamicHMC.stack_posterior_matrices([result_hmc1]),
             )
         end
     end