fix implement rank plots using RecipesBase

Project.toml

@@ -7,26 +7,21 @@ HypothesisTests = "09f84164-cd44-5f33-b23f-e6b0d136a0d5"
 MultipleTesting = "f8716d33-7c4a-5097-896f-ce0ecbd3ef6b"
 ProgressMeter = "92933f4c-e287-5a05-a399-4b506db050ca"
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
+RecipesBase = "3cdcf5f2-1ef4-517c-9805-6587b60abb01"
 Requires = "ae029012-a4dd-5104-9daa-d747884805df"
 StatsBase = "2913bbd2-ae8a-5f71-8c99-4fb6c76f3a91"
 
-[weakdeps]
-Plots = "91a5bcdd-55d7-5caf-9e0b-520d859cae80"
-
-[extensions]
-MCMCTestingPlotsExt = "Plots"
-
 [compat]
 HypothesisTests = "0.11"
 MultipleTesting = "0.6"
 ProgressMeter = "1.9"
 Random = "1"
+RecipesBase = "1.3"
 Requires = "1"
 StatsBase = "0.34"
 julia = "1.6"
 
 [extras]
-Plots = "91a5bcdd-55d7-5caf-9e0b-520d859cae80"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
 
 [targets]

docs/make.jl

@@ -1,10 +1,16 @@
 using MCMCTesting
 using Documenter
+using Plots
 
 DocMeta.setdocmeta!(MCMCTesting, :DocTestSetup, :(using MCMCTesting); recursive=true)
 
 makedocs(;
-    modules=[MCMCTesting],
+    modules=[
+        MCMCTesting,
+        isdefined(Base, :get_extension) ?
+            Base.get_extension(MCMCTesting, :MCMCTestingPlotsExt) :
+            RecipesBase.apply_recipe
+    ],
     repo="https://github.com/Red-Portal/MCMCTesting.jl/blob/{commit}{path}#{line}",
     sitename="MCMCTesting.jl",
     format=Documenter.HTML(;

docs/src/example.md

@@ -194,8 +194,8 @@ rank_correct = simulate_ranks(test, TestSubject(model, Gibbs()); show_progress=f
 rank_wrong = simulate_ranks(test, TestSubject(model, GibbsWrongVar()); show_progress=false)
 
 param_names = ["θ1 mean", "θ2 mean", "θ1 var", "θ2 var"]
-plot(rank_wrong,    test; param_names)
-plot!(rank_correct, test; param_names)
+rankplot(test, rank_wrong; param_names)
+rankplot!(test, rank_correct; param_names)
 savefig("rankplot.svg")
 nothing
 ```

docs/src/general.md

@@ -28,13 +28,13 @@ The `model` and `kernel` are then passed to `MCMCTesting` through the following
 TestSubject
 ```
 
-## Simulating a P-Value Through `mcmctest`
+## Simulating a P-Value with `mcmctest`
 Each of the test internally run simulations and compute a single p-value through the following routine:
 ```@docs
 mcmctest
 ```
 
-## Increasing Power Through `seqmcmctest`
+## Increasing Power with `seqmcmctest`
 `seqmcmctest` (Algorithm 3[^gandyandscott2021]) sequentially calls `mcmctest` to increase the power and ensure a low false rejection rate.
 Furthermore, the p-values from each component of the statistics are combined through multiple hypothesis adjustment.
 

docs/src/index.md

@@ -12,6 +12,7 @@ Unlike simulation-based calibration (SBC; [^TBSVG2018][^YD2023][^MMKBPBHFGV2022]
 This is because the tests focus on maximizing the power for verify the validity of *individual Markov transitions* instead of a *set of samples*.
 Furthermore, unlike SBC, the approach of Gandy & Scott[^GS2021] is able to exactly satisfy the assumptions required for the theoretical guarantees.
 
+
 ## References
 [^GS2021]: Gandy, A., & Scott, J. (2020). Unit testing for MCMC and other Monte Carlo methods. arXiv preprint arXiv:2001.06465.
 [^G2004]: Geweke, J. (2004). Getting it right: Joint distribution tests of posterior simulators. Journal of the American Statistical Association, 99(467), 799-804.

docs/src/ranksim.md

@@ -10,10 +10,11 @@ For more information, refer to the documentation for the [exact rank test](@ref
 simulate_ranks
 ```
 
-## Visualizing Ranks
+## Visualizing Ranks with `Plots`
 We provide a `Plots` recipe for visualizing the ranks:
-```@docs
-MCMCTesting.plotranks
+
+```docs
+rankplot
 ```
 
 This can be used as follows:
@@ -24,10 +25,9 @@ using MCMCTesting
 # Set up the simulation
 
 ranks = simulate_ranks(test, subject)
-plot(ranks, test; param_names)
+rankplot(test, ranks; param_names)
 ```
 Also refer to the [tutorial](@ref tutorial) for a working example.
 
-
 ## References
 [^GS2021]: Gandy, A., & Scott, J. (2020). Unit testing for MCMC and other Monte Carlo methods. arXiv preprint arXiv:2001.06465.

src/MCMCTesting.jl

@@ -11,15 +11,16 @@ export
     markovchain_transition,
     mcmctest,
     seqmcmctest,
-    simulate_ranks
+    simulate_ranks,
+    RankPlot
 
 using HypothesisTests
 using MultipleTesting
 using ProgressMeter
 using Random
+using RecipesBase
 using StatsBase
 
-
 """
     sample_joint(rng, model)
 
@@ -120,10 +121,8 @@ struct TestSubject{M, K}
     kernel::K
 end
 
-
 abstract type AbstractMCMCTest end
 
-
 function markovchain_multiple_transition(
     rng::Random.AbstractRNG, model, kernel, n_steps::Int, θ, y
 )
@@ -137,16 +136,6 @@ include("defaults.jl")
 include("twosampletest.jl")
 include("exactranktest.jl")
 include("seqtest.jl")
+include("rankplot.jl")
 
-if !isdefined(Base, :get_extension)
-    using Requires
-end
-
-@static if !isdefined(Base, :get_extension)
-    function __init__()
-        @require Plots = "91a5bcdd-55d7-5caf-9e0b-520d859cae80" begin
-            include("../ext/MCMCTestingPlotsExt.jl")
-        end
-    end
-end
 end

ext/MCMCTestingPlotsExt.jl → src/rankplot.jl

@@ -1,28 +1,27 @@
 
-module MCMCTestingPlotsExt
-
-if isdefined(Base, :get_extension)
-    using Plots
-    using MCMCTesting
-else
-    using ..Plots
-    using ..MCMCTesting
-end
-
 """
-    plotranks(ranks, test; kwargs...)
+    rankplot(test, ranks; kwargs...)
 
-`Plots` recipe for plotting the simulated ranks from `simulate_ranks`.
-`Plots` must be imported *before* `MCMCTesting` to use this plot recipe.
+Plot the simulated ranks using `simulate_ranks`.
+
+!!! info
+    `Plots` must be imported *before* `MCMCTesting` to use this plot recipe.
 
 # Arguments
-- ranks: The output of `simulate_rank`.
 - test::ExactRankTest: The exact rank test object used to simulate the ranks.
+- ranks: The output of `simulate_rank`.
 
 # Keyword Arguments
 - stats_names: The name for the statistics used in the rank simulation. The default argument automatically assign default names. (Default: :auto). 
+- Keyword arguments corresponding `Plots` attributes, such as `bins`, `layout`, `size`, may apply.
 """
-@recipe function plotranks(ranks, test::ExactRankTest; stat_names=:auto)
+@userplot RankPlot
+@recipe function f(h::RankPlot; stat_names = :auto)
+    if length(h.args) != 2 || !(typeof(h.args[1]) <: ExactRankTest)
+        error("rankplot should be given a `<: ExctRankTest` as first argument. Got: $(typeof(h.args)).")
+    end
+    test, ranks = h.args
+
     n_max_rank = test.n_mcmc_steps
     n_samples  = test.n_samples
     binprob    = 1/n_max_rank
@@ -93,4 +92,3 @@ end
         end
     end
 end
-end

test/runtests.jl

@@ -89,11 +89,11 @@ include("models/normalnormalgibbs.jl")
         ranks = simulate_ranks(test, subject; show_progress=false)
 
         @testset  "default arguments" begin
-            plot(ranks, test)
+            rankplot(test, ranks)
         end
 
         @testset  "custom param names" begin
-            plot(ranks, test; param_names=["test$(idx)" for idx in size(ranks, 1)])
+            rankplot(test, ranks; param_names=["test$(idx)" for idx in size(ranks, 1)])
         end
     end
 end