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document MCMC plots
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‎.github/workflows/ci.yml‎

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matrix:
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# https://youtu.be/fQJrEQIRPZU?list=PLP8iPy9hna6Tze1CReUAQweWHyNdXaPNb&t=967
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group:
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- Basic
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- MCMCChains
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- CairoMakie
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#- JET
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version:

‎Project.toml‎

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StatsBase = "2913bbd2-ae8a-5f71-8c99-4fb6c76f3a91"
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[weakdeps]
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AbstractMCMC = "80f14c24-f653-4e6a-9b94-39d6b0f70001"
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AlgebraOfGraphics = "cbdf2221-f076-402e-a563-3d30da359d67"
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CairoMakie = "13f3f980-e62b-5c42-98c6-ff1f3baf88f0"
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Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f"
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MCMCChains = "c7f686f2-ff18-58e9-bc7b-31028e88f75d"
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Makie = "ee78f7c6-11fb-53f2-987a-cfe4a2b5a57a"
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[extensions]
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FigureHelpersAoGExt = ["CairoMakie", "AlgebraOfGraphics"]
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FigureHelpersCairoMakieExt = ["CairoMakie", "KernelDensity"]
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FigureHelpersMCMCChainsExt = "MCMCChains"
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FigureHelpersAoGExt = ["Makie", "AlgebraOfGraphics"]
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FigureHelpersMakieAbstractMCMCExt = ["Makie", "AbstractMCMC"]
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FigureHelpersMakieDistributionsExt = ["Makie", "Distributions"]
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FigureHelpersMakieExt = ["Makie", "KernelDensity"]
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[compat]
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AbstractMCMC = "5.7.2"
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AlgebraOfGraphics = "0.9.4, 0.10"
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CairoMakie = "0.13.2"
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Distributions = "0.25.120"
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KernelDensity = "0.6.10"
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MCMCChains = "6.0.7"
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Makie = "0.21.9"
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Parameters = "0.12.3"
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StatsBase = "0.34.5"
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julia = "1.10"

‎README.md‎

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# FigureHelpers.jl
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Concepts in Julia that have not found its proper package.
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Conveniently adjust figure properties for publication and presentation.
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‎docs/Project.toml‎

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[deps]
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CairoMakie = "13f3f980-e62b-5c42-98c6-ff1f3baf88f0"
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Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f"
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Documenter = "e30172f5-a6a5-5a46-863b-614d45cd2de4"
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FigureHelpers = "9ae22f58-2487-4805-bfc5-386577db46c8"
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MCMCChains = "c7f686f2-ff18-58e9-bc7b-31028e88f75d"
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Missings = "e1d29d7a-bbdc-5cf2-9ac0-f12de2c33e28"

‎docs/make.jl‎

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using Documenter
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using FigureHelpers
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using CairoMakie, Distributions
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push!(LOAD_PATH,"../src/")
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makedocs(sitename="FigureHelpers.jl",

‎docs/src/makie.md‎

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axis_contents
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```
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## Tailored plots
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## Plots of univariate Distributions
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```@setup doc
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using FigureHelpers
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using CairoMakie
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```
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```@example doc
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using Distributions
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d = LogNormal()
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fig = density_dist(d; normalize=true, label="normalized");
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density_dist!(content(fig[1, 1]), d) # unnormalized into the same figure
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fig
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```
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```@docs
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density_dist
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```
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## Plots of MCMCChains
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### Overview: combined trace-plot with density plot.
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For `linkaxes=true`, all the density plots are on the same x-scale.
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```@setup doc
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using FigureHelpers
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using CairoMakie
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```
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```@example doc
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using MCMCChains
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chn = Chains(rand(500, 2, 3), [:a, :b]);
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fig = plot_chn(chn; linkaxes=true)
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fig
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```
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```@docs
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plot_chn
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```
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### Tailored density plot
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Supports more keyword arguments to adjust color and labels.
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```@example doc
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using MCMCChains
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chn = Chains(rand(500, 2, 3), [:a, :b]);
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fig = density_params(chn, ["a","b"], labels=["bla","foo","bar"]);
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fig[:, 2] = Legend(fig, content(fig[1,1]), "Chain", framevisible = false)
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fig
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```
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```@docs
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density_params
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```
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‎ext/FigureHelpersAoGExt.jl‎

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end
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isdefined(Base, :get_extension) ?
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(using CairoMakie,AlgebraOfGraphics) : (using ..CairoMakie,..AlgebraOfGraphics)
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using Makie, AlgebraOfGraphics
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import FigureHelpers as CP
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using FigureHelpers
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‎ext/FigureHelpersMCMCChainsExt.jl‎

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import FigureHelpers as CM
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using FigureHelpers
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using MCMCChains
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function CP.density_params(chns, pars=names(chns, :parameters);
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makie_config::MakieConfig=MakieConfig(),
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fig = figure_conf(cm2inch.((8.3,8.3/1.618)); makie_config),
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column = 1, xlims=nothing,
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labels=nothing, colors = nothing, ylabels = nothing, normalize = false,
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kwargs_axis = repeat([()],length(pars)),
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prange = (0.025, 0.975), # do not extend x-scale to outliers
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kwargs...
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)
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n_chains = size(chns,3)
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n_samples = length(chns)
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labels_ch = isnothing(labels) ? string.(1:n_chains) : string.(labels)
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ylabels = isnothing(ylabels) ? string.(pars) : ylabels
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!isnothing(xlims) && (length(xlims) != length(pars)) && error(
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"Expected length(xlims)=$(length(xlims)) (each a Tuple or nothing) to be length(pars)=$(length(pars))")
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for (i, param) in enumerate(pars)
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ax = Axis(fig[i, column]; ylabel=ylabels[i], yaxisposition = :right, kwargs_axis[i]...)
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if isnothing(colors)
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pal = fig.scene.theme.palette
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#pal = ax.palette
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colors = pal.color[]
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end
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for i_chain in 1:n_chains
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_values = chns[:, param, i_chain]
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if !isnothing(prange)
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qmin,qmax = StatsBase.quantile(_values, prange)
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_values = _values[qmin .<= _values .<= qmax]
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end
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col = colors[i_chain]
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if normalize
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k = KernelDensity.kde(_values)
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md = maximum(k.density)
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lines!(ax, k.x, k.density ./ md; label=labels_ch[i_chain], color = col, kwargs...)
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else
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density!(ax, _values; label=labels_ch[i_chain], color = (col, 0.3), strokecolor = col, strokewidth = 1,
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#strokearound = true,
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kwargs...)
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end
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end
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xlim = CP.passnothing(getindex)(xlims, i)
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!isnothing(xlim) && xlims!(ax, xlim)
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#hideydecorations!(ax, ticklabels=false, ticks=false, grid=false)
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hideydecorations!(ax, label=false, ticklabels=true)
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# if i < length(params)
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# hidexdecorations!(ax; grid=false)
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# else
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# ax.xlabel = "Parameter estimate"
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# end
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end
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# axes = [only(contents(fig[i, 2])) for i in 1:length(params)]
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# linkxaxes!(axes...)
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#axislegend(only(contents(fig[2, column])))
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fig
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end
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function histogram_params(chns, pars=names(chns, :parameters);
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makie_config::MakieConfig=MakieConfig(),
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fig = figure_conf(cm2inch.((8.3,8.3/1.618)); makie_config),
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column = 1, xlims=nothing,
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labels=nothing, colors = nothing, ylabels = nothing, normalization = :pdf,
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kwargs_axis = repeat([()],length(pars)),
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ylimits = (0,1),
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kwargs...
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)
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n_chains = size(chns,3)
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n_samples = length(chns)
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labels_ch = isnothing(labels) ? string.(1:n_chains) : string.(labels)
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ylabels = isnothing(ylabels) ? string.(pars) : ylabels
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!isnothing(xlims) && (length(xlims) != length(pars)) && error(
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"Expected length(xlims)=$(length(xlims)) (each a Tuple or nothing) to be length(pars)=$(length(pars))")
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for (i, param) in enumerate(pars)
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ax = Axis(fig[i, column]; ylabel=ylabels[i], kwargs_axis[i]...)
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ylims!(ax, ylimits)
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if isnothing(colors)
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colors = ax.palette.color[]
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end
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for i_chain in 1:n_chains
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_values = chns[:, param, i_chain]
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col = colors[i_chain]
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hist!(ax, _values; label=labels_ch[i_chain], color = (col, 0.3), strokecolor = col, strokewidth = 1,
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normalization,
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#strokearound = true,
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kwargs...)
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end
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xlim = passnothing(getindex)(xlims, i)
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!isnothing(xlim) && xlims!(ax, xlim)
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#hideydecorations!(ax, ticklabels=false, ticks=false, grid=false)
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hideydecorations!(ax, label=false, ticklabels=true)
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# if i < length(params)
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# hidexdecorations!(ax; grid=false)
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# else
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# ax.xlabel = "Parameter estimate"
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# end
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end
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# axes = [only(contents(fig[i, 2])) for i in 1:length(params)]
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# linkxaxes!(axes...)
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#axislegend(only(contents(fig[2, column])))
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fig
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end
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end # module
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