From cadfbe8971c274e3f9d48b327d4edbb773b374a8 Mon Sep 17 00:00:00 2001 From: William Thompson Date: Sun, 25 Dec 2022 12:55:48 -0800 Subject: [PATCH 01/15] WIP Makie backend --- Project.toml | 4 +- src/PairPlots.jl | 499 ++++++++++++++++++++++++++++------------------- 2 files changed, 302 insertions(+), 201 deletions(-) diff --git a/Project.toml b/Project.toml index 47a5d65..2eded83 100644 --- a/Project.toml +++ b/Project.toml @@ -6,8 +6,10 @@ version = "0.6.0" [deps] Contour = "d38c429a-6771-53c6-b99e-75d170b6e991" Latexify = "23fbe1c1-3f47-55db-b15f-69d7ec21a316" +Makie = "ee78f7c6-11fb-53f2-987a-cfe4a2b5a57a" Measures = "442fdcdd-2543-5da2-b0f3-8c86c306513e" NamedTupleTools = "d9ec5142-1e00-5aa0-9d6a-321866360f50" +OrderedCollections = "bac558e1-5e72-5ebc-8fee-abe8a469f55d" PolygonOps = "647866c9-e3ac-4575-94e7-e3d426903924" Printf = "de0858da-6303-5e67-8744-51eddeeeb8d7" RecipesBase = "3cdcf5f2-1ef4-517c-9805-6587b60abb01" @@ -19,9 +21,9 @@ Tables = "bd369af6-aec1-5ad0-b16a-f7cc5008161c" [compat] Contour = "0.5.7" +Latexify = "0.15" Measures = "0.3.1" NamedTupleTools = "0.13.7" -Latexify = "0.15" PolygonOps = "0.1.1" RecipesBase = "1" Requires = "1" diff --git a/src/PairPlots.jl b/src/PairPlots.jl index a716ff1..76ba991 100644 --- a/src/PairPlots.jl +++ b/src/PairPlots.jl @@ -1,208 +1,329 @@ module PairPlots +Base.Experimental.@optlevel 0 + +export pairplot, TableSeries, ConfidenceLimits -using RecipesBase -using Measures -using NamedTupleTools using Tables +using Printf +using Latexify: latexify +using Statistics: quantile +using OrderedCollections: OrderedDict + +#= +Goals: +* Revise interface +* Supoprt multiple chains +* Simpler styling... +* truth values, markers +* Support plotting distributions directly +* -> MultinomialGaussian fitting for clean ellipses + + +We have two axes of customization, a bit like grammer of graphics. +We have: + * data kinds, e.g. mix of Distribution and Table series + * visualization kinds, e.g. hexbin vs. contour vs... + * This may in theory vary at each position. + + +want to kep basic pairplot(chain) +also want +pairplot( + PairPlots.Series(chain, color=...), + PairPlots.Series(chain, color=...), + PairPlots.Lines((a=1, b=2,)), + PairPlots.Marker(chain, color=...), + +) -using Statistics -using StatsBase +pairplot( + Series(chains, color=red, scatter=true, ) +) -using Printf -using Requires -using StaticArrays -using PolygonOps -using Contour -using Latexify - -function corner end -# We pull in Plots only using Requires instead of as a diret dependency, so -# that upstream packages can add us as a dependency e.g. for visualizing -# a custom datastructure without needing all of Plots. -# Give the user a helpful error message if they have not imported Plots yet -corner(args...; kwargs...) = error("You must run `using Plots` before using this package.") -export corner - -function hist(a, truths, histfunc, hist_kwargs, plotpercentiles, percentiles_kwargs, truths_kwargs, titlefmt, unit) - - x, h = histfunc(vec(a), hist_kwargs.nbins) - - if length(x) == 1 - @warn "1D histgoram has only one bin" - # RecipesBase.plot!(; framestyle=:none, title="invalid", hist_kwargs.subplot, hist_kwargs.inset, ) - # return - end +try to make still work if a series is missing a column. - minx, maxx = extrema(a) - extent = maxx - minx - # h_scaled = h ./ maximum(h) .* extent - # h_scaled .+= minx - h_scaled = h - pcs = [] - a_sorted = sort(vec(a)) - if length(plotpercentiles) > 0 - pcs = quantile(a_sorted, plotpercentiles./100, sorted=true) - end - # WIP: replace the title with an annotation so that the margins don't get messed up. - if get(hist_kwargs, :title, "") != "" - pcs_title = quantile(a_sorted, [0.16, 0.5, 0.84], sorted=true) - med = pcs_title[2] - low = med - pcs_title[1] - high = pcs_title[3] - med - title = @eval (@sprintf($titlefmt, $(hist_kwargs.title), $(pcs_title[2]), $high, $low, $unit)) - xc = mean(x) - yc = maximum(h_scaled) * 1.15 - hist_kwargs = (;hist_kwargs..., title) - end - hist_kwargs = delete(hist_kwargs, :nbins) - percentiles_kwargs = delete(percentiles_kwargs,:title) - # p = RecipesBase.plot() - kw = merge((;seriestype=:step), hist_kwargs) - if kw.seriestype==:step - x = x .- step(x)/2 - end - RecipesBase.plot!(x, h_scaled; kw...) - # RecipesBase.plot!(x, h_scaled; kw.inset, kw.subplot) - # RecipesBase.plot!(x, h_scaled; kw.inset, kw.subplot, kw.seriestype, kw.xrotation, kw.yrotation, kw.tick_direction, kw.grid, kw.yformatter, kw.xlims, yticks) +=# - if length(pcs) > 0 - RecipesBase.plot!(pcs; seriestype=:vline, percentiles_kwargs...) - end +abstract type AbstractSeries end - length(truths) > 0 && RecipesBase.plot!(collect(truths); truths_kwargs..., seriestype=:vline) - # return p +struct TableSeries1 <: AbstractSeries + table + kwargs end -function hist(a, b, truthsa, truthsb, histfunc, hist2d_kwargs, contour_kwargs, scatter_kwargs, truths_kwargs, plotcontours, plotscatter, filterscatter) - - x, y, H = histfunc(vec(a), vec(b), hist2d_kwargs.nbins) - - threeD = get(hist2d_kwargs, :seriestype, nothing) == :wireframe - - # Calculate levels for contours - levels = 1 .- exp.(-0.5 .* (0.5:0.5:2.1).^2) - ii = sortperm(reshape(H,:)) - h2flat = H[ii] - sm = cumsum(h2flat) - sm /= sm[end] - if all(isnan, sm) || length(H) <= 1 - @warn "Could not compute valid contours" - plotcontours = false - V = [0] - else - V = sort(map(v0 -> h2flat[sm .≤ v0][end], levels)) - if any(==(0), diff(V)) - @warn "Too few points to create valid contours" - end +TableSeries(data; kwargs...) = TableSeries1(data, kwargs) + + +# """ + +# - table: Data table +# - labels: Vector of labels for each column. +# - units: Vector of units for each column. +# - kwargs: Keyword arguments to forward to the plotting library +# """ +# function series( +# table, +# # labels = latexify.(Tables.columnnames(table), env=:raw), +# # units = ["" for _ in labels]; +# kwargs... +# ) +# if Tables.istable(table) +# TableSeries1(table; kwargs) +# elseif +# Series2(table, labels, units; kwargs...) +# end + +struct ConfidenceLimits6 <: AbstractSeries + limits + titlefmt + kwargs +end +function ConfidenceLimits(table, fmt_str="\$\\mathrm{%.2f^{+%.2f}_{-%.2f}}\$"; kwargs...) + cn = colnames(table) + limits = map(cn) do colname + percentiles = quantile(vec(table[colname]), (0.16, 0.5, 0.84)) + cen = percentiles[2] + low = cen - percentiles[1] + high = percentiles[3] - cen + colname => (low, cen, high) end + return ConfidenceLimits6(OrderedDict(limits), fmt_str, kwargs) +end - # # Exclude histogram spaces outside the outer contour - # masked_weights = fill(NaN, size(H)) - # # # Old method of masking out histogram squares - # # # if plotscatter && !threeD - # # # mask = H .>= V[1] - # # # else - # # # mask = trues(size(H)) - # # # end - # if plotscatter &&!threeD - # mask = H .> V[1] - # else - # mask = trues(size(H)) - # end - # masked_weights[mask] .= H[mask] - masked_weights = H - - levels_final = [0; V; maximum(H) * (1 + 1e-4)] - - # p = RecipesBase.plot() - if threeD - scatter_kwargs = merge(scatter_kwargs, (; seriestype=:scatter3d)) - # if !hasproperty(contour_kwargs, :seriestype) - # contour_kwargs = merge(contour_kwargs, (;seriestype=:contour3d)) - # end - plotcontours = false - end - RecipesBase.plot!(x, y, masked_weights; seriestype=:heatmap, hist2d_kwargs...) - - # We place a line of zeros on all sides of the histogram - # for the sake of cleaner contours. - pad_x = [first(x)-step(x); x; last(x)+step(x)] - pad_y = [first(y)-step(y); y; last(y)+step(y)] - pad_H = [ - zeros(size(H,2))' 0 0 - zeros(size(H,1)) H zeros(size(H,1)) - zeros(size(H,2))' 0 0 - ] - if plotcontours - # RecipesBase.plot!(x, y, H; seriestype=:contour, levels=levels_final, colorbar=:none, contour_kwargs...) - +struct Lines1 <: AbstractSeries + table + kwargs +end +Lines = Lines1 + +struct Marker1 <: AbstractSeries + table + kwargs +end +Marker = Marker1 + +# # Fallback for single series +# @nospecialize function pairplot(args::Any...; kwargs...) +# pairplot(Series(args...; kwargs...)) +# end + + +abstract type VizType end +abstract type VizTypeBody <: VizType end + +struct HexBin <: VizTypeBody + kwargs +end +HexBin(;kwargs...) = HexBin(kwargs) + +abstract type VizTypeDiag <: VizType end +struct Hist1D <: VizTypeDiag + kwargs +end +Hist1D(;kwargs...) = Hist1D(kwargs) + + +colnames(t::TableSeries1) = Tables.columnnames(t.table) +colnames(t::ConfidenceLimits6) = keys(t.limits) +colnames(t::NamedTuple) = keys(t) +colnames(t::AbstractDict) = keys(t) + + +using Makie + +@nospecialize + +GridPosTypes = Union{Figure, GridPosition, GridSubposition} + +# Create a pairplot without providing a figure +# @nospecialize +function pairplot( + bodyplottypes::VizTypeBody, + diagplottypes::VizTypeDiag, + series::AbstractSeries...; + figure=(;), + kwargs..., +) + fig = Figure(;figure...) + pairplot(fig.layout, bodyplottypes, diagplottypes, series..., ) +end + +# Create a pairplot by plotting into a grid position of a figure. +function pairplot( + grid::Makie.GridLayout, + bodyplottypes::VizTypeBody, + diagplottypes::VizTypeDiag, + series::AbstractSeries...; + labels = Dict(), + units = Dict(), + axis=(;) +) + + # We support multiple series that may have disjoint columns + # Get the ordered union of all table columns. + columns = unique(Iterators.flatten(map(colnames, series))) + + # Map of column key to label text. + # By default, just latexify the column key but allow override. + label_map = Dict( + name => Makie.latexstring("\\mathrm{", latexify(name, env=:raw), "}") + for name in columns + ) + label_map = merge(label_map, labels) + + # Similarly for units. By default empty string, but allow override. + units_map = Dict( + name => L"" + for name in columns + ) + units_map = merge(units_map, units) + + # Rather than computing limits in this version, let's try to rely on + # Makie doing a good job of linking axes. + + N = length(columns) + + # Keep lists of axes by row number and by column number. + # We'll use these afterwards to link axes together. + axes_by_row = Dict{Int,Vector{Axis}}() + axes_by_col = Dict{Int,Vector{Axis}}() + sizehint!(axes_by_col, N) + sizehint!(axes_by_row, N) + + # Build grid of nxn plots + for row_ind in 1:N, col_ind in 1:N + + # TODO: make this optional + if row_ind < col_ind + continue + end - # calculate the outer contour manually - c = contours(pad_x,pad_y,pad_H', V) - points = scatter_filtering(b, a, x,y, first(Contour.levels(c))) - elseif filterscatter - c = contours(pad_x,pad_y,pad_H', [V[1]]) - end + colname_row = columns[row_ind] + colname_col = columns[col_ind] + + ax = Axis( + grid[row_ind, col_ind]; + ylabel=label_map[colname_row], + xlabel=label_map[colname_col], + xgridvisible=false, + ygridvisible=false, + alignmode = row_ind == 1 ? Inside() : Makie.Mixed(;left=nothing, right=nothing, bottom=nothing, top=Makie.Protrusion(0.0)), + axis..., + ) + + axes_by_col[col_ind]= push!(get(axes_by_col, col_ind, Axis[]), ax) + if row_ind != col_ind + axes_by_row[row_ind]= push!(get(axes_by_row, row_ind, Axis[]), ax) + end - if filterscatter - points = scatter_filtering(b, a, x,y, first(Contour.levels(c))) - else - points = (b,a) - end - if plotscatter - # TODO: handle threeD - if get(scatter_kwargs, :seriestype, nothing) == :scatter3d - z = zeros(size(y)) - RecipesBase.plot!(b, a, z; scatter_kwargs...) - else - RecipesBase.plot!(points; seriestype=:scatter, scatter_kwargs...) + # For each slot, loop through all series and fill it in accordingly. + # We have two slot types: bodyplot, like a 3D histogram, and diagplot, along the diagonal + for ser in series + cn = colnames(ser) + # We only include + if colname_row in cn && colname_col in cn + if row_ind == col_ind + # Label(grid[row_ind, col_ind], string(colname_row), + # halign = :center, + # valign=:bottom, + # tellwidth=false, + # tellheight=false + # ) + diagplot(ax, diagplottypes, ser, colname_row) + else + bodyplot(ax, bodyplottypes, ser, colname_row, colname_col) + end + end end - end - if plotcontours - # RecipesBase.plot!(x, y, H; seriestype=:contour, levels=levels_final, colorbar=:none, contour_kwargs...) - for level in Contour.levels(c), poly in lines(level) - xs, ys = coordinates(poly) - RecipesBase.plot!(xs, ys; levels=levels_final, colorbar=:none, contour_kwargs...) + # Hide labels etc. as needed for a compact view + if row_ind < N + Makie.hidexdecorations!(ax, grid=false) end - + if col_ind > 1 || row_ind == 1 + Makie.hideydecorations!(ax, grid=false) + end + + end + + # Link all axes + for axes in values(axes_by_row) + Makie.linkyaxes!(axes...) + end + for axes in values(axes_by_col) + Makie.linkxaxes!(axes...) end - length(truthsa) > 0 && RecipesBase.plot!(collect(truthsa); truths_kwargs..., seriestype=:hline) - length(truthsb) > 0 && RecipesBase.plot!(collect(truthsb); truths_kwargs..., seriestype=:vline) - nothing + Makie.rowgap!(grid, Makie.Fixed(0)) + Makie.colgap!(grid, Makie.Fixed(0)) + + + + return Base.@locals + end -emptyplot() = RecipesBase.plot(framestyle=:none, background_color_inside=:transparent) +# Note: stephist coming soon in a Makie PR -# Default histogram calculations -""" - prepare_hist(vector, nbins) +function diagplot(ax::Axis, viztype::Hist1D, series::TableSeries1, colname) + dat = series.table[colname] -Use the StatsBase function to return a centered histogram from `vector` with `nbins`. -Must return a tuple of bin centres, followed by bin weights (of the same length). -""" -function prepare_hist(a, nbins) - h = fit(Histogram, vec(a); nbins) - # x = first(only(h.edges))+step(only(h.edges))/2 : step(only(h.edges)) : last(only(h.edges))-step(only(h.edges))/2 - x = range(first(h.edges[1])+step(h.edges[1])/2, step=step(h.edges[1]), length=size(h.weights,1)) - return x, h.weights + h = Makie.hist!( + ax, + dat; + color=:gray, + viztype.kwargs... + ) + Makie.ylims!(ax,low=0) end -""" - prepare_hist(vector, nbins) - -Use the StatsBase function to return a centered histogram from `vector` with `nbins`x`nbins`. -Must return a tuple of bin centres along the horizontal, bin centres along the vertical, -and a matrix of bin weights (of matching dimensions). -""" -function prepare_hist(a, b, nbins) - h = fit(Histogram, (vec(a),vec(b)); nbins) - y = range(first(h.edges[1])+step(h.edges[1])/2, step=step(h.edges[1]), length=size(h.weights,1)) - x = range(first(h.edges[2])+step(h.edges[2])/2, step=step(h.edges[2]), length=size(h.weights,2)) - return x, y, h.weights +function diagplot(ax::Axis, viztype::Any, series::ConfidenceLimits6, colname) + low, mid, high = series.limits[colname] + + title = @eval (@sprintf($(series.titlefmt), $mid, $high, $low)) + ax.title = Makie.latexstring(ax.title[], title) + + + Makie.vlines!(ax, [mid-low, mid, mid+high]; linestyle=:dash, color=:black, series.kwargs...) +end + +function bodyplot(ax::Axis, viztype::VizTypeBody, series::TableSeries1, colname_row, colname_col) + + Makie.hexbin!(ax, series.table[colname_col], series.table[colname_row]; viztype.kwargs...) +end + +function bodyplot(ax::Axis, viztype::Any, series::ConfidenceLimits6, colname_row, colname_col) + # No-op end +##### + +# # Default histogram calculations +# """ +# prepare_hist(vector, nbins) + +# Use the StatsBase function to return a centered histogram from `vector` with `nbins`. +# Must return a tuple of bin centres, followed by bin weights (of the same length). +# """ +# function prepare_hist(a, nbins) +# h = fit(Histogram, vec(a); nbins) +# x = range(first(h.edges[1])+step(h.edges[1])/2, step=step(h.edges[1]), length=size(h.weights,1)) +# return x, h.weights +# end +# """ +# prepare_hist(vector, nbins) + +# Use the StatsBase function to return a centered histogram from `vector` with `nbins`x`nbins`. +# Must return a tuple of bin centres along the horizontal, bin centres along the vertical, +# and a matrix of bin weights (of matching dimensions). +# """ +# function prepare_hist(a, b, nbins) +# h = fit(Histogram, (vec(a),vec(b)); nbins) +# y = range(first(h.edges[1])+step(h.edges[1])/2, step=step(h.edges[1]), length=size(h.weights,1)) +# x = range(first(h.edges[2])+step(h.edges[2])/2, step=step(h.edges[2]), length=size(h.weights,2)) +# return x, y, h.weights +# end + # Filter the scatter plot to remove points inside the first contour # for performance and better display function scatter_filtering(b, a, x,y, level) @@ -227,26 +348,4 @@ function scatter_filtering(b, a, x,y, level) end - -# Special support for MCMCChains. -# They have additional table fields :iteration and :chain that should not be shown -# by default. -# In future, we might add the ability to colour the output by chain number. -function __init__() - @require MCMCChains="c7f686f2-ff18-58e9-bc7b-31028e88f75d" begin - function corner(chains::MCMCChains.Chains, args...; kwargs...) - props = keys(chains) - # values = (reshape(chains[prop].data,:) for prop in props) - values = [vec(chains[prop].data) for prop in props] - table = namedtuple(props, values) - return corner(table, args...; kwargs...) - end - end - - @require Plots="91a5bcdd-55d7-5caf-9e0b-520d859cae80" include("corner.jl") - - nothing end - - -end # module From 5e2ae03b9e83deafd569f79f564e4b6e205dd42f Mon Sep 17 00:00:00 2001 From: William Thompson Date: Sun, 25 Dec 2022 15:05:43 -0800 Subject: [PATCH 02/15] More plot kinds --- src/PairPlots.jl | 96 +++++++++++++++++++++++++++++++++++++++--------- 1 file changed, 79 insertions(+), 17 deletions(-) diff --git a/src/PairPlots.jl b/src/PairPlots.jl index 76ba991..84e19aa 100644 --- a/src/PairPlots.jl +++ b/src/PairPlots.jl @@ -3,10 +3,11 @@ Base.Experimental.@optlevel 0 export pairplot, TableSeries, ConfidenceLimits +using Makie: Makie using Tables using Printf using Latexify: latexify -using Statistics: quantile +using StatsBase: fit, quantile, Histogram, sturges using OrderedCollections: OrderedDict #= @@ -103,11 +104,6 @@ struct Marker1 <: AbstractSeries end Marker = Marker1 -# # Fallback for single series -# @nospecialize function pairplot(args::Any...; kwargs...) -# pairplot(Series(args...; kwargs...)) -# end - abstract type VizType end abstract type VizTypeBody <: VizType end @@ -117,12 +113,30 @@ struct HexBin <: VizTypeBody end HexBin(;kwargs...) = HexBin(kwargs) +struct Contour1 <: VizTypeBody + kwargs +end +Contour1(;kwargs...) = Contour1(kwargs) + +struct Contourf1 <: VizTypeBody + kwargs +end +Contourf1(;kwargs...) = Contourf1(kwargs) + + +## Diagonals + abstract type VizTypeDiag <: VizType end struct Hist1D <: VizTypeDiag kwargs end Hist1D(;kwargs...) = Hist1D(kwargs) +struct Density1 <: VizTypeDiag + kwargs +end +Density1(;kwargs...) = Density1(kwargs) + colnames(t::TableSeries1) = Tables.columnnames(t.table) colnames(t::ConfidenceLimits6) = keys(t.limits) @@ -130,7 +144,6 @@ colnames(t::NamedTuple) = keys(t) colnames(t::AbstractDict) = keys(t) -using Makie @nospecialize @@ -146,7 +159,8 @@ function pairplot( kwargs..., ) fig = Figure(;figure...) - pairplot(fig.layout, bodyplottypes, diagplottypes, series..., ) + pairplot(fig.layout, bodyplottypes, diagplottypes, series...; kwargs...) + return fig end # Create a pairplot by plotting into a grid position of a figure. @@ -208,7 +222,11 @@ function pairplot( xlabel=label_map[colname_col], xgridvisible=false, ygridvisible=false, + # Ensure any axis title that gets added doesn't break the tight layout alignmode = row_ind == 1 ? Inside() : Makie.Mixed(;left=nothing, right=nothing, bottom=nothing, top=Makie.Protrusion(0.0)), + xautolimitmargin=(0f0,0f0), + yautolimitmargin=(0f0,0f0), + # User options axis..., ) @@ -259,40 +277,84 @@ function pairplot( Makie.colgap!(grid, Makie.Fixed(0)) - - return Base.@locals + return end # Note: stephist coming soon in a Makie PR -function diagplot(ax::Axis, viztype::Hist1D, series::TableSeries1, colname) +function diagplot(ax::Axis, viz::Hist1D, series::TableSeries1, colname) dat = series.table[colname] h = Makie.hist!( ax, dat; color=:gray, - viztype.kwargs... + viz.kwargs..., + series.kwargs..., ) Makie.ylims!(ax,low=0) end -function diagplot(ax::Axis, viztype::Any, series::ConfidenceLimits6, colname) + +function diagplot(ax::Axis, viz::Density1, series::TableSeries1, colname) + dat = series.table[colname] + + h = Makie.density!( + ax, + dat; + color=:gray, + viz.kwargs..., + series.kwargs..., + ) + Makie.ylims!(ax,low=0) +end +function diagplot(ax::Axis, viz::Any, series::ConfidenceLimits6, colname) low, mid, high = series.limits[colname] title = @eval (@sprintf($(series.titlefmt), $mid, $high, $low)) ax.title = Makie.latexstring(ax.title[], title) - Makie.vlines!(ax, [mid-low, mid, mid+high]; linestyle=:dash, color=:black, series.kwargs...) + Makie.vlines!( + ax, + [mid-low, mid, mid+high]; + linestyle=:dash, + color=:black, + viz.kwargs..., + series.kwargs..., + ) end -function bodyplot(ax::Axis, viztype::VizTypeBody, series::TableSeries1, colname_row, colname_col) +function bodyplot(ax::Axis, viz::HexBin, series::TableSeries1, colname_row, colname_col) + Makie.hexbin!( + ax, + series.table[colname_col], + series.table[colname_row]; + viz.kwargs..., + series.kwargs..., + ) +end + +function bodyplot(ax::Axis, viz::Contour1, series::TableSeries1, colname_row, colname_col) + + h = fit(Histogram, (vec(series.table[colname_row]),vec(series.table[colname_col])); nbins=get(series.kwargs, :bins, sturges(length(series.table[colname_row])))) + y = range(first(h.edges[1])+step(h.edges[1])/2, step=step(h.edges[1]), length=size(h.weights,1)) + x = range(first(h.edges[2])+step(h.edges[2])/2, step=step(h.edges[2]), length=size(h.weights,2)) + + Makie.contour!(ax, x, y, transpose(h.weights); viz.kwargs..., series.kwargs...) +end + +function bodyplot(ax::Axis, viz::Contourf1, series::TableSeries1, colname_row, colname_col) - Makie.hexbin!(ax, series.table[colname_col], series.table[colname_row]; viztype.kwargs...) + h = fit(Histogram, (vec(series.table[colname_row]),vec(series.table[colname_col])); nbins=get(series.kwargs, :bins, sturges(length(series.table[colname_row])))) + y = range(first(h.edges[1])+step(h.edges[1])/2, step=step(h.edges[1]), length=size(h.weights,1)) + x = range(first(h.edges[2])+step(h.edges[2])/2, step=step(h.edges[2]), length=size(h.weights,2)) + + Makie.contourf!(ax, x, y, transpose(h.weights); interpolate=false, viz.kwargs..., series.kwargs...) end -function bodyplot(ax::Axis, viztype::Any, series::ConfidenceLimits6, colname_row, colname_col) + +function bodyplot(ax::Axis, viz::Any, series::ConfidenceLimits6, colname_row, colname_col) # No-op end From 6cabe2cbdd229b6fbc3c9f0a77ce1ec39213f666 Mon Sep 17 00:00:00 2001 From: William Thompson Date: Mon, 26 Dec 2022 10:39:19 -0800 Subject: [PATCH 03/15] API improvements --- Project.toml | 1 + src/PairPlots.jl | 473 ++++++++++++++++++++++++++++++++++------------- 2 files changed, 343 insertions(+), 131 deletions(-) diff --git a/Project.toml b/Project.toml index 2eded83..ecfa805 100644 --- a/Project.toml +++ b/Project.toml @@ -5,6 +5,7 @@ version = "0.6.0" [deps] Contour = "d38c429a-6771-53c6-b99e-75d170b6e991" +Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f" Latexify = "23fbe1c1-3f47-55db-b15f-69d7ec21a316" Makie = "ee78f7c6-11fb-53f2-987a-cfe4a2b5a57a" Measures = "442fdcdd-2543-5da2-b0f3-8c86c306513e" diff --git a/src/PairPlots.jl b/src/PairPlots.jl index 84e19aa..b5f5f9a 100644 --- a/src/PairPlots.jl +++ b/src/PairPlots.jl @@ -1,13 +1,15 @@ module PairPlots Base.Experimental.@optlevel 0 -export pairplot, TableSeries, ConfidenceLimits +export pairplot, TableSeries, DistSeries using Makie: Makie using Tables using Printf +using Contour: Contour as ContourLib using Latexify: latexify using StatsBase: fit, quantile, Histogram, sturges +using Distributions using OrderedCollections: OrderedDict #= @@ -48,61 +50,73 @@ try to make still work if a series is missing a column. abstract type AbstractSeries end - -struct TableSeries1 <: AbstractSeries +struct TableSeries2 <: AbstractSeries + label table kwargs end -TableSeries(data; kwargs...) = TableSeries1(data, kwargs) - - -# """ +TableSeries(data; label=nothing, kwargs...) = TableSeries2(label, data, kwargs) -# - table: Data table -# - labels: Vector of labels for each column. -# - units: Vector of units for each column. -# - kwargs: Keyword arguments to forward to the plotting library -# """ -# function series( -# table, -# # labels = latexify.(Tables.columnnames(table), env=:raw), -# # units = ["" for _ in labels]; -# kwargs... -# ) -# if Tables.istable(table) -# TableSeries1(table; kwargs) -# elseif -# Series2(table, labels, units; kwargs...) -# end -struct ConfidenceLimits6 <: AbstractSeries - limits - titlefmt +# TODO: adapt to product_distribution +struct DistSeries2 <: AbstractSeries + label + keys + dist kwargs end -function ConfidenceLimits(table, fmt_str="\$\\mathrm{%.2f^{+%.2f}_{-%.2f}}\$"; kwargs...) - cn = colnames(table) - limits = map(cn) do colname - percentiles = quantile(vec(table[colname]), (0.16, 0.5, 0.84)) - cen = percentiles[2] - low = cen - percentiles[1] - high = percentiles[3] - cen - colname => (low, cen, high) +function DistSeries(dists::UnivariateDistribution...; label=nothing, kwargs...) + keys = Symbol.(string.(1:length(dists))) + DistSeries(label, keys, dists...; kwargs...) +end +function DistSeries(keys, dists::UnivariateDistribution...; kwargs...) + DistSeries(keys, product_distribution(dists); kwargs...) +end +function DistSeries(dist::MultivariateDistribution; kwargs...) + keys = Symbol.(string.(1:length(dist))) + DistSeries(keys, dist; kwargs...) +end +function DistSeries(keys, dist::MultivariateDistribution; kwargs...) + if length(keys) != length(dist) + error("length of keys do not match dimensions of distribution") end - return ConfidenceLimits6(OrderedDict(limits), fmt_str, kwargs) + DistSeries2(keys, dist, kwargs) end - -struct Lines1 <: AbstractSeries - table - kwargs +function DistSeries(keys, dist::MultivariateDistribution; kwargs...) + if length(keys) != length(dist) + error("length of keys do not match dimensions of distribution") + end + DistSeries2(keys, dist, kwargs) end -Lines = Lines1 -struct Marker1 <: AbstractSeries - table + + +# struct ConfidenceLimits6 <: AbstractSeries +# limits +# titlefmt +# kwargs +# end +struct MarginConfidenceLimits <: VizTypeDiag + titlefmt kwargs end -Marker = Marker1 +function MarginConfidenceLimits(titlefmt="\$\\mathrm{%.2f^{+%.2f}_{-%.2f}}\$"; kwargs...) + return MarginConfidenceLimits(titlefmt, kwargs) +end + +# struct Lines1 <: AbstractSeries +# table +# kwargs +# end +# Lines = Lines1 + +# struct Marker1 <: AbstractSeries +# table +# kwargs +# end +# Marker = Marker1 + +## Body abstract type VizType end @@ -113,33 +127,42 @@ struct HexBin <: VizTypeBody end HexBin(;kwargs...) = HexBin(kwargs) -struct Contour1 <: VizTypeBody +struct Contour2 <: VizTypeBody + sigmas + kwargs +end +Contour2(;sigmas=0.5:0.5:2.1, kwargs...) = Contour2(sigmas, kwargs) + +struct Contourf2 <: VizTypeBody + sigmas kwargs end -Contour1(;kwargs...) = Contour1(kwargs) +Contourf2(;sigmas=0.5:0.5:2.1, kwargs...) = Contourf2(sigmas, kwargs) -struct Contourf1 <: VizTypeBody +struct Scatter <: VizTypeBody kwargs end -Contourf1(;kwargs...) = Contourf1(kwargs) +Scatter(;kwargs...) = Scatter(kwargs) + ## Diagonals abstract type VizTypeDiag <: VizType end -struct Hist1D <: VizTypeDiag +struct MarginHist <: VizTypeDiag kwargs end -Hist1D(;kwargs...) = Hist1D(kwargs) +MarginHist(;kwargs...) = MarginHist(kwargs) -struct Density1 <: VizTypeDiag +struct MarginDensity <: VizTypeDiag kwargs end -Density1(;kwargs...) = Density1(kwargs) +MarginDensity(;kwargs...) = MarginDensity(kwargs) -colnames(t::TableSeries1) = Tables.columnnames(t.table) -colnames(t::ConfidenceLimits6) = keys(t.limits) +colnames(t::TableSeries2) = Tables.columnnames(t.table) +colnames(t::DistSeries2) = t.keys +colnames(t::MarginConfidenceLimits) = keys(t.limits) colnames(t::NamedTuple) = keys(t) colnames(t::AbstractDict) = keys(t) @@ -151,32 +174,156 @@ GridPosTypes = Union{Figure, GridPosition, GridSubposition} # Create a pairplot without providing a figure # @nospecialize +# function pairplot( +# bodyplottypes::VizTypeBody, +# diagplottypes::VizTypeDiag, +# series::AbstractSeries...; +# figure=(;), +# kwargs..., +# ) +# fig = Figure(;figure...) +# pairplot(fig.layout, bodyplottypes, diagplottypes, series...; kwargs...) +# return fig +# end + +# # Create a pairplot by plotting into a grid position of a figure. +# function pairplot( +# grid::Makie.GridLayout, +# bodyplottypes::VizTypeBody, +# diagplottypes::VizTypeDiag, +# series::AbstractSeries...; +# labels = Dict(), +# units = Dict(), +# axis=(;) +# ) + +# # We support multiple series that may have disjoint columns +# # Get the ordered union of all table columns. +# columns = unique(Iterators.flatten(map(colnames, series))) + +# # Map of column key to label text. +# # By default, just latexify the column key but allow override. +# label_map = Dict( +# name => Makie.latexstring("\\mathrm{", latexify(name, env=:raw), "}") +# for name in columns +# ) +# label_map = merge(label_map, labels) + +# # Similarly for units. By default empty string, but allow override. +# units_map = Dict( +# name => L"" +# for name in columns +# ) +# units_map = merge(units_map, units) + +# # Rather than computing limits in this version, let's try to rely on +# # Makie doing a good job of linking axes. + +# N = length(columns) + +# # Keep lists of axes by row number and by column number. +# # We'll use these afterwards to link axes together. +# axes_by_row = Dict{Int,Vector{Axis}}() +# axes_by_col = Dict{Int,Vector{Axis}}() +# sizehint!(axes_by_col, N) +# sizehint!(axes_by_row, N) + +# # Build grid of nxn plots +# for row_ind in 1:N, col_ind in 1:N + +# # TODO: make this optional +# if row_ind < col_ind +# continue +# end + +# colname_row = columns[row_ind] +# colname_col = columns[col_ind] + +# ax = Axis( +# grid[row_ind, col_ind]; +# ylabel=label_map[colname_row], +# xlabel=label_map[colname_col], +# xgridvisible=false, +# ygridvisible=false, +# # Ensure any axis title that gets added doesn't break the tight layout +# alignmode = row_ind == 1 ? Inside() : Makie.Mixed(;left=nothing, right=nothing, bottom=nothing, top=Makie.Protrusion(0.0)), +# xautolimitmargin=(0f0,0f0), +# yautolimitmargin=(0f0,0f0), +# # User options +# axis..., +# ) + +# axes_by_col[col_ind]= push!(get(axes_by_col, col_ind, Axis[]), ax) +# if row_ind != col_ind +# axes_by_row[row_ind]= push!(get(axes_by_row, row_ind, Axis[]), ax) +# end + +# # For each slot, loop through all series and fill it in accordingly. +# # We have two slot types: bodyplot, like a 3D histogram, and diagplot, along the diagonal +# for ser in series +# cn = colnames(ser) +# # We only include +# if colname_row in cn && colname_col in cn +# if row_ind == col_ind +# # Label(grid[row_ind, col_ind], string(colname_row), +# # halign = :center, +# # valign=:bottom, +# # tellwidth=false, +# # tellheight=false +# # ) +# diagplot(ax, diagplottypes, ser, colname_row) +# else +# bodyplot(ax, bodyplottypes, ser, colname_row, colname_col) +# end +# end +# end + +# # Hide labels etc. as needed for a compact view +# if row_ind < N +# Makie.hidexdecorations!(ax, grid=false) +# end +# if col_ind > 1 || row_ind == 1 +# Makie.hideydecorations!(ax, grid=false) +# end + +# end + +# # Link all axes +# for axes in values(axes_by_row) +# Makie.linkyaxes!(axes...) +# end +# for axes in values(axes_by_col) +# Makie.linkxaxes!(axes...) +# end + +# Makie.rowgap!(grid, Makie.Fixed(0)) +# Makie.colgap!(grid, Makie.Fixed(0)) + +# return + +# end function pairplot( - bodyplottypes::VizTypeBody, - diagplottypes::VizTypeDiag, - series::AbstractSeries...; + pairs::Pair{<:AbstractSeries}...; figure=(;), kwargs..., ) fig = Figure(;figure...) - pairplot(fig.layout, bodyplottypes, diagplottypes, series...; kwargs...) + pairplot(fig.layout, pairs...; kwargs...) return fig end # Create a pairplot by plotting into a grid position of a figure. function pairplot( grid::Makie.GridLayout, - bodyplottypes::VizTypeBody, - diagplottypes::VizTypeDiag, - series::AbstractSeries...; + pairs::Pair{<:AbstractSeries}...; labels = Dict(), units = Dict(), - axis=(;) + diagaxis=(;), + bodyaxis=(;), ) - # We support multiple series that may have disjoint columns # Get the ordered union of all table columns. - columns = unique(Iterators.flatten(map(colnames, series))) + columns = unique(Iterators.flatten(Iterators.map(colnames∘first, pairs))) # Map of column key to label text. # By default, just latexify the column key but allow override. @@ -216,7 +363,12 @@ function pairplot( colname_row = columns[row_ind] colname_col = columns[col_ind] - ax = Axis( + if row_ind == col_ind + kw = diagaxis + else + kw = bodyaxis + end + ax = Makie.Axis( grid[row_ind, col_ind]; ylabel=label_map[colname_row], xlabel=label_map[colname_col], @@ -227,7 +379,7 @@ function pairplot( xautolimitmargin=(0f0,0f0), yautolimitmargin=(0f0,0f0), # User options - axis..., + kw..., ) axes_by_col[col_ind]= push!(get(axes_by_col, col_ind, Axis[]), ax) @@ -237,20 +389,17 @@ function pairplot( # For each slot, loop through all series and fill it in accordingly. # We have two slot types: bodyplot, like a 3D histogram, and diagplot, along the diagonal - for ser in series - cn = colnames(ser) - # We only include + for (series_i,(series, vizlayers)) in enumerate(pairs) + cn = colnames(series) if colname_row in cn && colname_col in cn - if row_ind == col_ind - # Label(grid[row_ind, col_ind], string(colname_row), - # halign = :center, - # valign=:bottom, - # tellwidth=false, - # tellheight=false - # ) - diagplot(ax, diagplottypes, ser, colname_row) - else - bodyplot(ax, bodyplottypes, ser, colname_row, colname_col) + for vizlayer in vizlayers + if row_ind == col_ind && vizlayer isa VizTypeDiag + diagplot(ax, vizlayer, series_i, series, colname_row) + elseif row_ind != col_ind && vizlayer isa VizTypeBody + bodyplot(ax, vizlayer, series_i, series, colname_row, colname_col) + else + # skip + end end end end @@ -276,115 +425,177 @@ function pairplot( Makie.rowgap!(grid, Makie.Fixed(0)) Makie.colgap!(grid, Makie.Fixed(0)) - return end # Note: stephist coming soon in a Makie PR -function diagplot(ax::Axis, viz::Hist1D, series::TableSeries1, colname) - dat = series.table[colname] +function diagplot(ax::Axis, viz::MarginHist, series_i, series::TableSeries2, colname) + dat = getproperty(series.table, colname) h = Makie.hist!( ax, dat; - color=:gray, - viz.kwargs..., + color=Cycled(series_i), series.kwargs..., + viz.kwargs..., ) Makie.ylims!(ax,low=0) end -function diagplot(ax::Axis, viz::Density1, series::TableSeries1, colname) - dat = series.table[colname] +function diagplot(ax::Axis, viz::MarginDensity, series_i, series::TableSeries2, colname) + dat = getproperty(series.table, colname) h = Makie.density!( ax, dat; - color=:gray, + color=Cycled(series_i), + series.kwargs..., viz.kwargs..., + ) + Makie.ylims!(ax,low=0) +end + + +function diagplot(ax::Axis, viz::MarginDensity, series_i, series::DistSeries2, colname) + col_ind = findfirst(==(colname), series.keys) + + # TODO: temporary: work out a better way + D = rand(series.dist, 10000) + dat = view(D, col_ind, :) # the "column" index of the series actually indexes rows here + + h = Makie.density!( + ax, + dat; + color=Cycled(series_i), series.kwargs..., + viz.kwargs..., ) Makie.ylims!(ax,low=0) end -function diagplot(ax::Axis, viz::Any, series::ConfidenceLimits6, colname) - low, mid, high = series.limits[colname] - title = @eval (@sprintf($(series.titlefmt), $mid, $high, $low)) - ax.title = Makie.latexstring(ax.title[], title) +function diagplot(ax::Axis, viz::MarginConfidenceLimits, series_i, series::TableSeries2, colname) + percentiles = quantile(vec(getproperty(series.table, colname)), (0.16, 0.5, 0.84)) + mid = percentiles[2] + low = mid - percentiles[1] + high = percentiles[3] - mid + + title = @eval (@sprintf($(viz.titlefmt), $mid, $high, $low)) + ax.title = Makie.latexstring(ax.title[], title) Makie.vlines!( ax, [mid-low, mid, mid+high]; linestyle=:dash, - color=:black, - viz.kwargs..., + color=Cycled(series_i), + depth_shift=-10f0, series.kwargs..., + viz.kwargs..., ) end -function bodyplot(ax::Axis, viz::HexBin, series::TableSeries1, colname_row, colname_col) +function bodyplot(ax::Axis, viz::HexBin, series_i, series::TableSeries2, colname_row, colname_col) Makie.hexbin!( ax, - series.table[colname_col], - series.table[colname_row]; - viz.kwargs..., + getproperty(series.table, colname_col), + getproperty(series.table, colname_row); series.kwargs..., + viz.kwargs..., ) end -function bodyplot(ax::Axis, viz::Contour1, series::TableSeries1, colname_row, colname_col) +function bodyplot(ax::Axis, viz::HexBin, series_i, series::DistSeries2, colname_row, colname_col) + + #TODO + col_ind = findfirst(==(colname_col), series.keys) + row_ind = findfirst(==(colname_row), series.keys) - h = fit(Histogram, (vec(series.table[colname_row]),vec(series.table[colname_col])); nbins=get(series.kwargs, :bins, sturges(length(series.table[colname_row])))) + # TODO: temporary: work out a better way + D = rand(series.dist, 50000) + + Makie.hexbin!( + ax, + view(D, col_ind, :), + view(D, row_ind, :),; + series.kwargs..., + viz.kwargs..., + ) +end + +# Given a series and two columns, return a ContourLib.contours object. +function prep_contours(series::TableSeries2, sigmas, colname_row, colname_col) + h = fit(Histogram, (vec(getproperty(series.table, colname_row)),vec(getproperty(series.table, colname_col))); nbins=get(series.kwargs, :bins, sturges(length(getproperty(series.table, colname_row))))) y = range(first(h.edges[1])+step(h.edges[1])/2, step=step(h.edges[1]), length=size(h.weights,1)) x = range(first(h.edges[2])+step(h.edges[2])/2, step=step(h.edges[2]), length=size(h.weights,2)) + h = h.weights + + # Calculate levels for contours + levels = 1 .- exp.(-0.5 .* (sigmas).^2) + ii = sortperm(reshape(h,:)) + h2flat = h[ii] + sm = cumsum(h2flat) + sm /= sm[end] + if all(isnan, sm) || length(h) <= 1 + @warn "Could not compute valid contours" + plotcontours = false + V = [0] + else + V = sort(map(v0 -> h2flat[sm .≤ v0][end], levels)) + if any(==(0), diff(V)) + @warn "Too few points to create valid contours" + end + end + levels_final = [0; V; maximum(h) * (1 + 1e-4)] + + pad_x = [first(x)-step(x); x; last(x)+step(x)] + pad_y = [first(y)-step(y); y; last(y)+step(y)] + pad_h = [ + zeros(size(h,2))' 0 0 + zeros(size(h,1)) h zeros(size(h,1)) + zeros(size(h,2))' 0 0 + ] + c = ContourLib.contours(pad_x,pad_y,pad_h', V) +end + +function bodyplot(ax::Axis, viz::Contour2, series_i, series, colname_row, colname_col) + + c = prep_contours(series::TableSeries2, viz.sigmas, colname_row, colname_col) + + color = get(viz.kwargs, :color, Cycled(series_i)) + color = get(series.kwargs, :color, color) - Makie.contour!(ax, x, y, transpose(h.weights); viz.kwargs..., series.kwargs...) + levels = ContourLib.levels(c) + for (i,level) in enumerate(levels), poly in ContourLib.lines(level) + xs, ys = ContourLib.coordinates(poly) + # Makie.poly!(ax, Makie.Point2f.(zip(xs,ys)); strokewidth=2, series.kwargs..., viz.kwargs..., color=:transparent, strokecolor=color)#(color, i/length(levels))) + Makie.lines!(ax, xs, ys;series.kwargs..., viz.kwargs..., color)#(color, i/length(levels))) + end end -function bodyplot(ax::Axis, viz::Contourf1, series::TableSeries1, colname_row, colname_col) +function bodyplot(ax::Axis, viz::Contourf2, series_i, series::TableSeries2, colname_row, colname_col) - h = fit(Histogram, (vec(series.table[colname_row]),vec(series.table[colname_col])); nbins=get(series.kwargs, :bins, sturges(length(series.table[colname_row])))) - y = range(first(h.edges[1])+step(h.edges[1])/2, step=step(h.edges[1]), length=size(h.weights,1)) - x = range(first(h.edges[2])+step(h.edges[2])/2, step=step(h.edges[2]), length=size(h.weights,2)) + c = prep_contours(series::TableSeries2, viz.sigmas, colname_row, colname_col) + + color = get(viz.kwargs, :color, Cycled(series_i)) + color = get(series.kwargs, :color, color) - Makie.contourf!(ax, x, y, transpose(h.weights); interpolate=false, viz.kwargs..., series.kwargs...) + levels = ContourLib.levels(c) + for (i,level) in enumerate(levels), poly in ContourLib.lines(level) + xs, ys = ContourLib.coordinates(poly) + Makie.poly!(ax, Makie.Point2f.(zip(xs,ys)); series.kwargs..., viz.kwargs..., color=color)#(color, 1/length(levels))) + end end -function bodyplot(ax::Axis, viz::Any, series::ConfidenceLimits6, colname_row, colname_col) - # No-op +function bodyplot(ax::Axis, viz::Scatter, series_i, series::TableSeries2, colname_row, colname_col) + + Makie.scatter!(ax, getproperty(series.table, colname_col), getproperty(series.table, colname_row); series.kwargs..., viz.kwargs...) end -##### -# # Default histogram calculations -# """ -# prepare_hist(vector, nbins) -# Use the StatsBase function to return a centered histogram from `vector` with `nbins`. -# Must return a tuple of bin centres, followed by bin weights (of the same length). -# """ -# function prepare_hist(a, nbins) -# h = fit(Histogram, vec(a); nbins) -# x = range(first(h.edges[1])+step(h.edges[1])/2, step=step(h.edges[1]), length=size(h.weights,1)) -# return x, h.weights -# end -# """ -# prepare_hist(vector, nbins) - -# Use the StatsBase function to return a centered histogram from `vector` with `nbins`x`nbins`. -# Must return a tuple of bin centres along the horizontal, bin centres along the vertical, -# and a matrix of bin weights (of matching dimensions). -# """ -# function prepare_hist(a, b, nbins) -# h = fit(Histogram, (vec(a),vec(b)); nbins) -# y = range(first(h.edges[1])+step(h.edges[1])/2, step=step(h.edges[1]), length=size(h.weights,1)) -# x = range(first(h.edges[2])+step(h.edges[2])/2, step=step(h.edges[2]), length=size(h.weights,2)) -# return x, y, h.weights -# end # Filter the scatter plot to remove points inside the first contour # for performance and better display From 5ad3d8d569bfff532df05668b091402f5b5e0164 Mon Sep 17 00:00:00 2001 From: William Thompson Date: Tue, 27 Dec 2022 09:18:36 -0800 Subject: [PATCH 04/15] Makie MVP --- Project.toml | 3 +- examples/example.jl | 17 ++ src/PairPlots.jl | 482 +++++++++++++++----------------------------- src/precompile.jl | 13 ++ 4 files changed, 195 insertions(+), 320 deletions(-) create mode 100644 examples/example.jl create mode 100644 src/precompile.jl diff --git a/Project.toml b/Project.toml index ecfa805..0d11fca 100644 --- a/Project.toml +++ b/Project.toml @@ -6,15 +6,16 @@ version = "0.6.0" [deps] Contour = "d38c429a-6771-53c6-b99e-75d170b6e991" Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f" +KernelDensity = "5ab0869b-81aa-558d-bb23-cbf5423bbe9b" Latexify = "23fbe1c1-3f47-55db-b15f-69d7ec21a316" Makie = "ee78f7c6-11fb-53f2-987a-cfe4a2b5a57a" Measures = "442fdcdd-2543-5da2-b0f3-8c86c306513e" NamedTupleTools = "d9ec5142-1e00-5aa0-9d6a-321866360f50" -OrderedCollections = "bac558e1-5e72-5ebc-8fee-abe8a469f55d" PolygonOps = "647866c9-e3ac-4575-94e7-e3d426903924" Printf = "de0858da-6303-5e67-8744-51eddeeeb8d7" RecipesBase = "3cdcf5f2-1ef4-517c-9805-6587b60abb01" Requires = "ae029012-a4dd-5104-9daa-d747884805df" +SnoopPrecompile = "66db9d55-30c0-4569-8b51-7e840670fc0c" StaticArrays = "90137ffa-7385-5640-81b9-e52037218182" Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2" StatsBase = "2913bbd2-ae8a-5f71-8c99-4fb6c76f3a91" diff --git a/examples/example.jl b/examples/example.jl new file mode 100644 index 0000000..7581edd --- /dev/null +++ b/examples/example.jl @@ -0,0 +1,17 @@ +using GLMakie, PairPlots, Distributions + + +# Generate some data to visualize +N = 100_000 +a = [2randn(N÷2) .+ 6; randn(N÷2)] +b = [3randn(N÷2); 2randn(N÷2)] +c = randn(N) +d = c .+ 0.6randn(N) + +# Pass data in a format compatible with Tables.jl +# Here, simply a named tuple of vectors. +table = (;a, b, c, d) + +## + +pairplot(table) diff --git a/src/PairPlots.jl b/src/PairPlots.jl index b5f5f9a..d8da41c 100644 --- a/src/PairPlots.jl +++ b/src/PairPlots.jl @@ -1,122 +1,27 @@ module PairPlots Base.Experimental.@optlevel 0 -export pairplot, TableSeries, DistSeries +export pairplot using Makie: Makie using Tables using Printf +using KernelDensity: KernelDensity using Contour: Contour as ContourLib using Latexify: latexify -using StatsBase: fit, quantile, Histogram, sturges -using Distributions -using OrderedCollections: OrderedDict - -#= -Goals: -* Revise interface -* Supoprt multiple chains -* Simpler styling... -* truth values, markers -* Support plotting distributions directly -* -> MultinomialGaussian fitting for clean ellipses - - -We have two axes of customization, a bit like grammer of graphics. -We have: - * data kinds, e.g. mix of Distribution and Table series - * visualization kinds, e.g. hexbin vs. contour vs... - * This may in theory vary at each position. - - -want to kep basic pairplot(chain) -also want -pairplot( - PairPlots.Series(chain, color=...), - PairPlots.Series(chain, color=...), - PairPlots.Lines((a=1, b=2,)), - PairPlots.Marker(chain, color=...), - -) - -pairplot( - Series(chains, color=red, scatter=true, ) -) - -try to make still work if a series is missing a column. - - -=# +using StatsBase: fit, quantile, Histogram +using Distributions: pdf +using StaticArrays +using PolygonOps abstract type AbstractSeries end -struct TableSeries2 <: AbstractSeries +struct Series <: AbstractSeries label table kwargs end -TableSeries(data; label=nothing, kwargs...) = TableSeries2(label, data, kwargs) - - -# TODO: adapt to product_distribution -struct DistSeries2 <: AbstractSeries - label - keys - dist - kwargs -end -function DistSeries(dists::UnivariateDistribution...; label=nothing, kwargs...) - keys = Symbol.(string.(1:length(dists))) - DistSeries(label, keys, dists...; kwargs...) -end -function DistSeries(keys, dists::UnivariateDistribution...; kwargs...) - DistSeries(keys, product_distribution(dists); kwargs...) -end -function DistSeries(dist::MultivariateDistribution; kwargs...) - keys = Symbol.(string.(1:length(dist))) - DistSeries(keys, dist; kwargs...) -end -function DistSeries(keys, dist::MultivariateDistribution; kwargs...) - if length(keys) != length(dist) - error("length of keys do not match dimensions of distribution") - end - DistSeries2(keys, dist, kwargs) -end -function DistSeries(keys, dist::MultivariateDistribution; kwargs...) - if length(keys) != length(dist) - error("length of keys do not match dimensions of distribution") - end - DistSeries2(keys, dist, kwargs) -end - - - -# struct ConfidenceLimits6 <: AbstractSeries -# limits -# titlefmt -# kwargs -# end -struct MarginConfidenceLimits <: VizTypeDiag - titlefmt - kwargs -end -function MarginConfidenceLimits(titlefmt="\$\\mathrm{%.2f^{+%.2f}_{-%.2f}}\$"; kwargs...) - return MarginConfidenceLimits(titlefmt, kwargs) -end - -# struct Lines1 <: AbstractSeries -# table -# kwargs -# end -# Lines = Lines1 - -# struct Marker1 <: AbstractSeries -# table -# kwargs -# end -# Marker = Marker1 - -## Body +Series(data; label=nothing, kwargs...) = Series(label, data, kwargs) abstract type VizType end @@ -127,28 +32,42 @@ struct HexBin <: VizTypeBody end HexBin(;kwargs...) = HexBin(kwargs) -struct Contour2 <: VizTypeBody +struct Hist <: VizTypeBody + kwargs +end +Hist(;kwargs...) = Hist(kwargs) + +struct Contour <: VizTypeBody sigmas kwargs end -Contour2(;sigmas=0.5:0.5:2.1, kwargs...) = Contour2(sigmas, kwargs) +Contour(;sigmas=0.5:0.5:2.1, kwargs...) = Contour(sigmas, kwargs) -struct Contourf2 <: VizTypeBody +struct Contourf <: VizTypeBody sigmas kwargs end -Contourf2(;sigmas=0.5:0.5:2.1, kwargs...) = Contourf2(sigmas, kwargs) +Contourf(;sigmas=0.5:0.5:2.1, kwargs...) = Contourf(sigmas, kwargs) struct Scatter <: VizTypeBody kwargs + filtersigma end -Scatter(;kwargs...) = Scatter(kwargs) - +Scatter(;filtersigma=nothing, kwargs...) = Scatter(kwargs, filtersigma) ## Diagonals abstract type VizTypeDiag <: VizType end + +struct MarginConfidenceLimits <: VizTypeDiag + titlefmt + kwargs +end +function MarginConfidenceLimits(titlefmt="\$\\mathrm{%.2f^{+%.2f}_{-%.2f}}\$"; kwargs...) + return MarginConfidenceLimits(titlefmt, kwargs) +end + struct MarginHist <: VizTypeDiag kwargs end @@ -160,164 +79,65 @@ end MarginDensity(;kwargs...) = MarginDensity(kwargs) -colnames(t::TableSeries2) = Tables.columnnames(t.table) -colnames(t::DistSeries2) = t.keys +colnames(t::Series) = Tables.columnnames(t.table) colnames(t::MarginConfidenceLimits) = keys(t.limits) colnames(t::NamedTuple) = keys(t) colnames(t::AbstractDict) = keys(t) +GridPosTypes = Union{Makie.Figure, Makie.GridPosition, Makie.GridSubposition} -@nospecialize - -GridPosTypes = Union{Figure, GridPosition, GridSubposition} - -# Create a pairplot without providing a figure -# @nospecialize -# function pairplot( -# bodyplottypes::VizTypeBody, -# diagplottypes::VizTypeDiag, -# series::AbstractSeries...; -# figure=(;), -# kwargs..., -# ) -# fig = Figure(;figure...) -# pairplot(fig.layout, bodyplottypes, diagplottypes, series...; kwargs...) -# return fig -# end - -# # Create a pairplot by plotting into a grid position of a figure. -# function pairplot( -# grid::Makie.GridLayout, -# bodyplottypes::VizTypeBody, -# diagplottypes::VizTypeDiag, -# series::AbstractSeries...; -# labels = Dict(), -# units = Dict(), -# axis=(;) -# ) - -# # We support multiple series that may have disjoint columns -# # Get the ordered union of all table columns. -# columns = unique(Iterators.flatten(map(colnames, series))) - -# # Map of column key to label text. -# # By default, just latexify the column key but allow override. -# label_map = Dict( -# name => Makie.latexstring("\\mathrm{", latexify(name, env=:raw), "}") -# for name in columns -# ) -# label_map = merge(label_map, labels) - -# # Similarly for units. By default empty string, but allow override. -# units_map = Dict( -# name => L"" -# for name in columns -# ) -# units_map = merge(units_map, units) - -# # Rather than computing limits in this version, let's try to rely on -# # Makie doing a good job of linking axes. - -# N = length(columns) - -# # Keep lists of axes by row number and by column number. -# # We'll use these afterwards to link axes together. -# axes_by_row = Dict{Int,Vector{Axis}}() -# axes_by_col = Dict{Int,Vector{Axis}}() -# sizehint!(axes_by_col, N) -# sizehint!(axes_by_row, N) - -# # Build grid of nxn plots -# for row_ind in 1:N, col_ind in 1:N -# # TODO: make this optional -# if row_ind < col_ind -# continue -# end - -# colname_row = columns[row_ind] -# colname_col = columns[col_ind] - -# ax = Axis( -# grid[row_ind, col_ind]; -# ylabel=label_map[colname_row], -# xlabel=label_map[colname_col], -# xgridvisible=false, -# ygridvisible=false, -# # Ensure any axis title that gets added doesn't break the tight layout -# alignmode = row_ind == 1 ? Inside() : Makie.Mixed(;left=nothing, right=nothing, bottom=nothing, top=Makie.Protrusion(0.0)), -# xautolimitmargin=(0f0,0f0), -# yautolimitmargin=(0f0,0f0), -# # User options -# axis..., -# ) - -# axes_by_col[col_ind]= push!(get(axes_by_col, col_ind, Axis[]), ax) -# if row_ind != col_ind -# axes_by_row[row_ind]= push!(get(axes_by_row, row_ind, Axis[]), ax) -# end - -# # For each slot, loop through all series and fill it in accordingly. -# # We have two slot types: bodyplot, like a 3D histogram, and diagplot, along the diagonal -# for ser in series -# cn = colnames(ser) -# # We only include -# if colname_row in cn && colname_col in cn -# if row_ind == col_ind -# # Label(grid[row_ind, col_ind], string(colname_row), -# # halign = :center, -# # valign=:bottom, -# # tellwidth=false, -# # tellheight=false -# # ) -# diagplot(ax, diagplottypes, ser, colname_row) -# else -# bodyplot(ax, bodyplottypes, ser, colname_row, colname_col) -# end -# end -# end - -# # Hide labels etc. as needed for a compact view -# if row_ind < N -# Makie.hidexdecorations!(ax, grid=false) -# end -# if col_ind > 1 || row_ind == 1 -# Makie.hideydecorations!(ax, grid=false) -# end - -# end - -# # Link all axes -# for axes in values(axes_by_row) -# Makie.linkyaxes!(axes...) -# end -# for axes in values(axes_by_col) -# Makie.linkxaxes!(axes...) -# end - -# Makie.rowgap!(grid, Makie.Fixed(0)) -# Makie.colgap!(grid, Makie.Fixed(0)) - -# return - -# end function pairplot( - pairs::Pair{<:AbstractSeries}...; + @nospecialize input...; figure=(;), kwargs..., ) - fig = Figure(;figure...) - pairplot(fig.layout, pairs...; kwargs...) + N = length(input)+1 + fig = Makie.Figure(; + resolution=(300N, 300N), + figure... + ) + pairplot(fig.layout, input...; kwargs...) return fig end +# Fallback defaults for convenience +function pairplot( + grid::Makie.GridLayout, + @nospecialize datapairs::Any...; + kwargs..., +) + # Default to grayscale for a single series + TS = if length(datapairs) <= 1 + dat -> Series(dat; color=Makie.RGBA(0., 0., 0., 0.5)) + else + dat -> Series(dat) + end + defaults((data,vizlayers)::Pair) = TS(data) => vizlayers + defaults(data::Any) = TS(data) => ( + PairPlots.HexBin(colormap=Makie.cgrad([:transparent, :black]),bins=32), + PairPlots.Scatter(filtersigma=0.5), + PairPlots.Contour(), + PairPlots.MarginDensity( + color=:transparent, + strokecolor=:black, + strokewidth=1.5f0 + ), + PairPlots.MarginConfidenceLimits() + ) + + seriespairs = map(defaults, datapairs) + pairplot(grid, seriespairs...; kwargs...) + return +end + # Create a pairplot by plotting into a grid position of a figure. function pairplot( grid::Makie.GridLayout, - pairs::Pair{<:AbstractSeries}...; - labels = Dict(), - units = Dict(), + @nospecialize pairs::Pair{<:AbstractSeries}...; + labels::AbstractDict{Symbol} = Dict{Symbol,Any}(), + units::AbstractDict{Symbol} = Dict{Symbol,Any}(), diagaxis=(;), bodyaxis=(;), ) @@ -331,11 +151,11 @@ function pairplot( name => Makie.latexstring("\\mathrm{", latexify(name, env=:raw), "}") for name in columns ) - label_map = merge(label_map, labels) + label_map = merge(label_map, Dict(labels)) # Similarly for units. By default empty string, but allow override. units_map = Dict( - name => L"" + name => Makie.L"" for name in columns ) units_map = merge(units_map, units) @@ -347,16 +167,22 @@ function pairplot( # Keep lists of axes by row number and by column number. # We'll use these afterwards to link axes together. - axes_by_row = Dict{Int,Vector{Axis}}() - axes_by_col = Dict{Int,Vector{Axis}}() + axes_by_row = Dict{Int,Vector{Makie.Axis}}() + axes_by_col = Dict{Int,Vector{Makie.Axis}}() sizehint!(axes_by_col, N) sizehint!(axes_by_row, N) + + # Check if there are any diagonal vizualization layers + anydiag_viz = mapreduce((|), pairs, init=false) do (series, vizlayers) + any(v->isa(v, VizTypeDiag), vizlayers) + end # Build grid of nxn plots for row_ind in 1:N, col_ind in 1:N - # TODO: make this optional - if row_ind < col_ind + # TODO: make this first condition optional to enable a full grid + # Also skip diagonals if no diagonal viz layers + if row_ind < col_ind || !anydiag_viz continue end @@ -375,16 +201,16 @@ function pairplot( xgridvisible=false, ygridvisible=false, # Ensure any axis title that gets added doesn't break the tight layout - alignmode = row_ind == 1 ? Inside() : Makie.Mixed(;left=nothing, right=nothing, bottom=nothing, top=Makie.Protrusion(0.0)), + alignmode = row_ind == 1 ? Makie.Inside() : Makie.Mixed(;left=nothing, right=nothing, bottom=nothing, top=Makie.Protrusion(0.0)), xautolimitmargin=(0f0,0f0), - yautolimitmargin=(0f0,0f0), + yautolimitmargin= row_ind == col_ind ? (0f0, 0.05f0) : (0f0,0f0), # User options kw..., ) - axes_by_col[col_ind]= push!(get(axes_by_col, col_ind, Axis[]), ax) + axes_by_col[col_ind]= push!(get(axes_by_col, col_ind, Makie.Axis[]), ax) if row_ind != col_ind - axes_by_row[row_ind]= push!(get(axes_by_row, row_ind, Axis[]), ax) + axes_by_row[row_ind]= push!(get(axes_by_row, row_ind, Makie.Axis[]), ax) end # For each slot, loop through all series and fill it in accordingly. @@ -425,32 +251,35 @@ function pairplot( Makie.rowgap!(grid, Makie.Fixed(0)) Makie.colgap!(grid, Makie.Fixed(0)) + # We sometimes end up with an extra first row if there are no diagonal vizualization layers + Makie.trim!(grid) + return end # Note: stephist coming soon in a Makie PR -function diagplot(ax::Axis, viz::MarginHist, series_i, series::TableSeries2, colname) +function diagplot(ax::Makie.Axis, viz::MarginHist, series_i, series::Series, colname) dat = getproperty(series.table, colname) h = Makie.hist!( ax, dat; - color=Cycled(series_i), + color=Makie.Cycled(series_i), series.kwargs..., viz.kwargs..., ) Makie.ylims!(ax,low=0) end -function diagplot(ax::Axis, viz::MarginDensity, series_i, series::TableSeries2, colname) +function diagplot(ax::Makie.Axis, viz::MarginDensity, series_i, series::Series, colname) dat = getproperty(series.table, colname) h = Makie.density!( ax, dat; - color=Cycled(series_i), + color=Makie.Cycled(series_i), series.kwargs..., viz.kwargs..., ) @@ -458,24 +287,7 @@ function diagplot(ax::Axis, viz::MarginDensity, series_i, series::TableSeries2, end -function diagplot(ax::Axis, viz::MarginDensity, series_i, series::DistSeries2, colname) - col_ind = findfirst(==(colname), series.keys) - - # TODO: temporary: work out a better way - D = rand(series.dist, 10000) - dat = view(D, col_ind, :) # the "column" index of the series actually indexes rows here - - h = Makie.density!( - ax, - dat; - color=Cycled(series_i), - series.kwargs..., - viz.kwargs..., - ) - Makie.ylims!(ax,low=0) -end - -function diagplot(ax::Axis, viz::MarginConfidenceLimits, series_i, series::TableSeries2, colname) +function diagplot(ax::Makie.Axis, viz::MarginConfidenceLimits, series_i, series::Series, colname) percentiles = quantile(vec(getproperty(series.table, colname)), (0.16, 0.5, 0.84)) mid = percentiles[2] @@ -489,48 +301,63 @@ function diagplot(ax::Axis, viz::MarginConfidenceLimits, series_i, series::Table ax, [mid-low, mid, mid+high]; linestyle=:dash, - color=Cycled(series_i), + color=Makie.Cycled(series_i), depth_shift=-10f0, series.kwargs..., viz.kwargs..., ) end -function bodyplot(ax::Axis, viz::HexBin, series_i, series::TableSeries2, colname_row, colname_col) +function bodyplot(ax::Makie.Axis, viz::HexBin, series_i, series::Series, colname_row, colname_col) Makie.hexbin!( ax, getproperty(series.table, colname_col), getproperty(series.table, colname_row); + bins=32, + colormap=Makie.cgrad([:transparent, :black]), series.kwargs..., viz.kwargs..., ) end -function bodyplot(ax::Axis, viz::HexBin, series_i, series::DistSeries2, colname_row, colname_col) +function bodyplot(ax::Makie.Axis, viz::Hist, series_i, series::Series, colname_row, colname_col) - #TODO - col_ind = findfirst(==(colname_col), series.keys) - row_ind = findfirst(==(colname_row), series.keys) + xdat = getproperty(series.table, colname_col) + ydat = getproperty(series.table, colname_row) - # TODO: temporary: work out a better way - D = rand(series.dist, 50000) + + bins = get(series.kwargs, :bins, 32) + bins = get(viz.kwargs, :bins, bins) - Makie.hexbin!( + h = fit(Histogram, (vec(xdat),vec(ydat)); nbins=bins) + x = range(first(h.edges[1])+step(h.edges[1])/2, step=step(h.edges[1]), length=size(h.weights,1)) + y = range(first(h.edges[2])+step(h.edges[2])/2, step=step(h.edges[2]), length=size(h.weights,2)) + + Makie.heatmap!( ax, - view(D, col_ind, :), - view(D, row_ind, :),; + x, + y, + h.weights; + colormap=Makie.cgrad([:transparent, :black]), series.kwargs..., viz.kwargs..., ) end -# Given a series and two columns, return a ContourLib.contours object. -function prep_contours(series::TableSeries2, sigmas, colname_row, colname_col) - h = fit(Histogram, (vec(getproperty(series.table, colname_row)),vec(getproperty(series.table, colname_col))); nbins=get(series.kwargs, :bins, sturges(length(getproperty(series.table, colname_row))))) - y = range(first(h.edges[1])+step(h.edges[1])/2, step=step(h.edges[1]), length=size(h.weights,1)) - x = range(first(h.edges[2])+step(h.edges[2])/2, step=step(h.edges[2]), length=size(h.weights,2)) - h = h.weights +function prep_contours(series::Series, sigmas, colname_row, colname_col) + + xdat = getproperty(series.table, colname_col) + ydat = getproperty(series.table, colname_row) + k = KernelDensity.kde((xdat, ydat)) + ik = KernelDensity.InterpKDE(k) + exx = extrema(xdat) + exy = extrema(ydat) + N = 100 + x = range(first(exx), last(exx), length=N) + y = range(first(exy), last(exy), length=N) + h = pdf.(Ref(ik), x, y') + # Calculate levels for contours levels = 1 .- exp.(-0.5 .* (sigmas).^2) ii = sortperm(reshape(h,:)) @@ -549,6 +376,8 @@ function prep_contours(series::TableSeries2, sigmas, colname_row, colname_col) end levels_final = [0; V; maximum(h) * (1 + 1e-4)] + # Place a row and column of zeros around all sides of the data grid + # to ensure the contours link up nicely. pad_x = [first(x)-step(x); x; last(x)+step(x)] pad_y = [first(y)-step(y); y; last(y)+step(y)] pad_h = [ @@ -556,30 +385,31 @@ function prep_contours(series::TableSeries2, sigmas, colname_row, colname_col) zeros(size(h,1)) h zeros(size(h,1)) zeros(size(h,2))' 0 0 ] - c = ContourLib.contours(pad_x,pad_y,pad_h', V) + c = ContourLib.contours(pad_x,pad_y,pad_h, V) end -function bodyplot(ax::Axis, viz::Contour2, series_i, series, colname_row, colname_col) - c = prep_contours(series::TableSeries2, viz.sigmas, colname_row, colname_col) +function bodyplot(ax::Makie.Axis, viz::Contour, series_i, series, colname_row, colname_col) + + c = prep_contours(series::Series, viz.sigmas, colname_row, colname_col) - color = get(viz.kwargs, :color, Cycled(series_i)) - color = get(series.kwargs, :color, color) + color = get(series.kwargs, :color, Makie.Cycled(series_i)) + color = get(viz.kwargs, :color, color) levels = ContourLib.levels(c) for (i,level) in enumerate(levels), poly in ContourLib.lines(level) xs, ys = ContourLib.coordinates(poly) # Makie.poly!(ax, Makie.Point2f.(zip(xs,ys)); strokewidth=2, series.kwargs..., viz.kwargs..., color=:transparent, strokecolor=color)#(color, i/length(levels))) - Makie.lines!(ax, xs, ys;series.kwargs..., viz.kwargs..., color)#(color, i/length(levels))) + Makie.lines!(ax, xs, ys; strokewidth=1.5, series.kwargs..., viz.kwargs..., color) end end -function bodyplot(ax::Axis, viz::Contourf2, series_i, series::TableSeries2, colname_row, colname_col) +function bodyplot(ax::Makie.Axis, viz::Contourf, series_i, series::Series, colname_row, colname_col) - c = prep_contours(series::TableSeries2, viz.sigmas, colname_row, colname_col) + c = prep_contours(series::Series, viz.sigmas, colname_row, colname_col) - color = get(viz.kwargs, :color, Cycled(series_i)) - color = get(series.kwargs, :color, color) + color = get(series.kwargs, :color, Makie.Cycled(series_i)) + color = get(viz.kwargs, :color, color) levels = ContourLib.levels(c) for (i,level) in enumerate(levels), poly in ContourLib.lines(level) @@ -589,36 +419,50 @@ function bodyplot(ax::Axis, viz::Contourf2, series_i, series::TableSeries2, coln end -function bodyplot(ax::Axis, viz::Scatter, series_i, series::TableSeries2, colname_row, colname_col) +function bodyplot(ax::Makie.Axis, viz::Scatter, series_i, series::Series, colname_row, colname_col) - Makie.scatter!(ax, getproperty(series.table, colname_col), getproperty(series.table, colname_row); series.kwargs..., viz.kwargs...) -end + xall = getproperty(series.table, colname_col) + yall = getproperty(series.table, colname_row) + if isnothing(viz.filtersigma) + Makie.scatter!(ax, xall, yall; markersize=1f0, series.kwargs..., viz.kwargs...) + return + end + + c = prep_contours(series, [viz.filtersigma], colname_row, colname_col) + levels = ContourLib.levels(c) + xfilt, yfilt = scatter_filtering(xall, yall, first(levels)) + Makie.scatter!(ax, xfilt, yfilt; markersize=1f0, series.kwargs..., viz.kwargs...) + +end # Filter the scatter plot to remove points inside the first contour # for performance and better display -function scatter_filtering(b, a, x,y, level) +function scatter_filtering(x,y, level) - inds = eachindex(b,a) + inds = eachindex(x,y) outside = trues(size(inds)) # calculate the outer contour manually - for poly in lines(level) - xs, ys = coordinates(poly) + for poly in ContourLib.lines(level) + xs, ys = ContourLib.coordinates(poly) poly = SVector.(xs,ys) push!(poly, SVector(xs[begin], ys[begin])) - # poly = [xs ys; xs[begin] ys[begin]] + # Could benchmark threading this for i in inds - point = SVector(b[i],a[i]) + point = SVector(x[i],y[i]) # This logic does not seem to be 100% right ins = inpolygon(point, poly, in=false, on=true, out=true) outside[i] &= ins end end - return b[outside], a[outside] + return view(x, outside), view(y, outside) end +include("precompile.jl") + end + diff --git a/src/precompile.jl b/src/precompile.jl new file mode 100644 index 0000000..fbf42d6 --- /dev/null +++ b/src/precompile.jl @@ -0,0 +1,13 @@ + +using SnoopPrecompile + + +@precompile_all_calls begin + # Our "toy workload" that exercise the code you want to precompile + table = (; + # These are just from randn(100) but don't actually call into Random etc. here + a=[-0.34354309486711065, -1.0995966004923408, -1.031706382670448, 0.3183044791424319, 0.67787316130825, 1.1324681536249555, 1.2939921062585586, -0.6582203791206142, 1.4695904633205077, 1.5427816212385765, 1.4823524032258817, 0.42815319406559155, -0.4578923008551234, 0.9541115645590403, -1.1768032568149391, 0.09746177747481431, 0.5676618046059924, -0.07301172550842665, 0.2133270257363731, 0.6249497564601051, 0.030033374314663457, 0.9989897307774964, -0.14633638359521245, -0.13984783088967517, -0.07318127088482887, -0.8827464255133538, -0.1551292742796804, -0.5626619648286509, 1.195609759941277, 0.18044593019778774, 0.9906068677115775, 1.067415336363193, -0.09019199880824731, -0.0733557563698599, 1.2365757473020829, 0.6421378506716701, 0.911971133386629, -0.6604354172921325, 1.248280591046975, 2.086058112053022, -1.1209441193889569, -1.8264659931287404, -0.02394457072094552, -0.31598589415658596, 0.14129402137020985, -1.47055974020114, -0.5647486968155041, 0.6213177557341366, 1.47339588963977, 0.5718280587675062, 1.0992536620777364, -0.31467898547034223, -0.33036645614726445, 1.2610107709091767, 0.041089383886570026, -0.8468181989917779, -0.22891621657661404, -0.9619057469455553, -0.31564076522391055, 1.5426666354392973, 0.37072922620724014, -1.294821169478836, -0.3750959408197882, 0.15235550226977407, -1.1352802216110054, -1.4474576663572862, 1.9765748857275764, -1.691136450322534, 0.22417169521718713, -1.014501941287588, 0.9819618489485618, -1.0309264365918522, -0.46725203203010973, -1.9280180251605148, -0.5775542280478414, 3.305450570359804, 0.17791649755099412, -1.3493878073525758, 1.7952206907296888, 0.10818984149605794, -0.8436885213045058, -0.009094522169231267, -1.9067584282323635, -0.4555136343244378, 0.7041913638409038, -0.08615324254645132, 0.07379284355120926, 0.5436464877324115, 0.06375117639292655, -0.42987929424629967, -0.43876721563140775, -1.2559740614842871, -1.0434458219115856, -0.5415017141491355, 0.5924642659992275, 1.54568956318039, 0.8633157674590743, 1.1005805635355026, -1.910737345963861, -0.4742674166832837], + b=[-0.8350547364341157, -0.038903436082298126, -0.7428209115538095, -1.4702332997988619, 0.2929901876823982, 1.480656821045197, -0.7496016270089672, -1.1816175524449404, -0.8929201507386697, -0.4513027458407115, -0.03467987003478814, -0.01703216323285711, 2.269208613937625, -1.122760313412779, -1.690293811059567, 0.35637058611995015, -0.5492956660472131, 0.46065703485294224, 0.4437979543972946, 0.28240840472432244, 0.690877660142549, -2.5626640462814136, 0.05775480227672292, 0.3471312190888867, 1.724863523389576, -0.30223523085282833, -0.9081864727632714, -0.9755930057667722, -0.8633376120374543, -0.6320827659443491, -0.8996197573701549, 1.3098637982582648, 0.7259306350309777, -0.6677231848170275, -0.24152809622940857, 2.1413209082677906, -1.6229571597346615, 1.6318320479372053, 0.5061999438250513, 1.8722835557539328, -0.28755361383607164, -0.39835043144482646, -1.9191542821529093, 0.1861362910513889, -1.7370796754676385, -0.5847017666989085, -0.6139627808148969, -0.5828743912421838, 0.23866575269053403, 1.1395769333095256, 0.03673066354212003, -1.0246047274123449, 0.81119369428263, -0.2413679376829325, -0.16850699998847837, 0.7193564163546119, -1.0250120470351711, -0.020112597427054398, 1.4023645771518407, -1.2964559002213754, 0.004640153954934036, -1.5456922587361066, -1.1892087658060522, -0.5803343106096389, 1.3773763927487954, -1.5428894968829066, -0.6571326425215163, -0.16942661520407568, 0.3902986077040804, -0.5102558720576744, -1.7157849780094623, 1.6557540726543791, 1.5039386944282804, 0.041349457163033926, 1.726208631975933, 1.5872756183910883, 0.3571235862890753, 0.03145711944329936, -1.0810465561583815, 0.2542573690863064, -0.8061299707651735, 0.6202116497962467, -0.5558158303191691, -0.9388942510860714, 0.850513949232004, -0.4858445604340498, 0.7199256833112352, -0.48438425564853616, 0.0201633201948252, 1.01586069947111, -1.2132268468503575, -0.2566512612879169, -0.08918635759129184, -0.36100301648947447, 0.026391614522651263, 0.7647120517033543, 1.2084488286459771, -0.19298755667218181, 0.1995911553994999, 0.025362662538195947] + ) + pairplot(table) +end From ebdc6fca78546cc9e67abbe3b7dec3b79d2dc926 Mon Sep 17 00:00:00 2001 From: William Thompson Date: Tue, 27 Dec 2022 10:25:10 -0800 Subject: [PATCH 05/15] More flexible call signature --- src/PairPlots.jl | 93 +++++++++++++++++++++++++++++++----------------- 1 file changed, 61 insertions(+), 32 deletions(-) diff --git a/src/PairPlots.jl b/src/PairPlots.jl index d8da41c..7749bf6 100644 --- a/src/PairPlots.jl +++ b/src/PairPlots.jl @@ -108,30 +108,68 @@ function pairplot( @nospecialize datapairs::Any...; kwargs..., ) - # Default to grayscale for a single series - TS = if length(datapairs) <= 1 - dat -> Series(dat; color=Makie.RGBA(0., 0., 0., 0.5)) + # Default to grayscale for a single series. + # Otherwise fall back to cycling the colours ourselves. + # The Makie color cycle functionality isn't quite flexible enough (but almost!). + + + if length(datapairs) == 1 + single_series_color = Makie.RGBA(0., 0., 0., 0.5) + single_series_default_viz = ( + PairPlots.HexBin(colormap=Makie.cgrad([:transparent, :black]),bins=32), + PairPlots.Scatter(filtersigma=0.5), + PairPlots.Contour(), + PairPlots.MarginDensity( + color=:transparent, + strokecolor=:black, + strokewidth=1.5f0 + ), + PairPlots.MarginConfidenceLimits() + ) + defaults1((data,vizlayers)::Pair) = Series(data; color=single_series_color) => vizlayers + defaults1(series::Series) = series => single_series_default_viz + defaults1(data::Any) = Series(data; color=single_series_color) => single_series_default_viz + pairplot(grid, defaults1(first(datapairs)); kwargs...) else - dat -> Series(dat) + series_i = 0 + function SeriesDefaults(dat) + series_i += 1 + wc = Makie.wong_colors(0.5) + if series_i in axes(wc,1) + color = wc[series_i] + else + color = Makie.RGBA(0., 0., 0., 0.5) + end + return Series(dat; color, strokecolor=color) + end + multi_series_default_viz = ( + PairPlots.Scatter(filtersigma=0.5), + PairPlots.Contourf(), + PairPlots.MarginDensity( + color=:transparent, + strokewidth=2.5f0 + ) + ) + defaults((data,vizlayers)::Pair) = SeriesDefaults(data) => vizlayers + defaults(series::Series) = series => multi_series_default_viz + defaults(data::Any) = SeriesDefaults(data) => multi_series_default_viz + pairplot(grid, map(defaults, datapairs)...; kwargs...) end - defaults((data,vizlayers)::Pair) = TS(data) => vizlayers - defaults(data::Any) = TS(data) => ( - PairPlots.HexBin(colormap=Makie.cgrad([:transparent, :black]),bins=32), - PairPlots.Scatter(filtersigma=0.5), - PairPlots.Contour(), - PairPlots.MarginDensity( - color=:transparent, - strokecolor=:black, - strokewidth=1.5f0 - ), - PairPlots.MarginConfidenceLimits() - ) - seriespairs = map(defaults, datapairs) - pairplot(grid, seriespairs...; kwargs...) return end +# Handle plotting into a GridPosition instead of a GridLayout +function pairplot( + gridpos::Makie.GridPosition, + @nospecialize datapairs::Any...; + kwargs..., +) + grid = Makie.GridLayout(gridpos) + pairplot(grid, datapairs...; kwargs...) + return grid +end + # Create a pairplot by plotting into a grid position of a figure. function pairplot( grid::Makie.GridLayout, @@ -182,7 +220,7 @@ function pairplot( # TODO: make this first condition optional to enable a full grid # Also skip diagonals if no diagonal viz layers - if row_ind < col_ind || !anydiag_viz + if row_ind < col_ind || (row_ind==col_ind && !anydiag_viz) continue end @@ -248,8 +286,8 @@ function pairplot( Makie.linkxaxes!(axes...) end - Makie.rowgap!(grid, Makie.Fixed(0)) - Makie.colgap!(grid, Makie.Fixed(0)) + # Makie.rowgap!(grid, 0) + # Makie.colgap!(grid, 0) # We sometimes end up with an extra first row if there are no diagonal vizualization layers Makie.trim!(grid) @@ -266,7 +304,6 @@ function diagplot(ax::Makie.Axis, viz::MarginHist, series_i, series::Series, col h = Makie.hist!( ax, dat; - color=Makie.Cycled(series_i), series.kwargs..., viz.kwargs..., ) @@ -279,7 +316,6 @@ function diagplot(ax::Makie.Axis, viz::MarginDensity, series_i, series::Series, h = Makie.density!( ax, dat; - color=Makie.Cycled(series_i), series.kwargs..., viz.kwargs..., ) @@ -301,7 +337,6 @@ function diagplot(ax::Makie.Axis, viz::MarginConfidenceLimits, series_i, series: ax, [mid-low, mid, mid+high]; linestyle=:dash, - color=Makie.Cycled(series_i), depth_shift=-10f0, series.kwargs..., viz.kwargs..., @@ -393,28 +428,22 @@ function bodyplot(ax::Makie.Axis, viz::Contour, series_i, series, colname_row, c c = prep_contours(series::Series, viz.sigmas, colname_row, colname_col) - color = get(series.kwargs, :color, Makie.Cycled(series_i)) - color = get(viz.kwargs, :color, color) - levels = ContourLib.levels(c) for (i,level) in enumerate(levels), poly in ContourLib.lines(level) xs, ys = ContourLib.coordinates(poly) # Makie.poly!(ax, Makie.Point2f.(zip(xs,ys)); strokewidth=2, series.kwargs..., viz.kwargs..., color=:transparent, strokecolor=color)#(color, i/length(levels))) - Makie.lines!(ax, xs, ys; strokewidth=1.5, series.kwargs..., viz.kwargs..., color) + Makie.lines!(ax, xs, ys; strokewidth=1.5, series.kwargs..., viz.kwargs...) end end function bodyplot(ax::Makie.Axis, viz::Contourf, series_i, series::Series, colname_row, colname_col) c = prep_contours(series::Series, viz.sigmas, colname_row, colname_col) - - color = get(series.kwargs, :color, Makie.Cycled(series_i)) - color = get(viz.kwargs, :color, color) levels = ContourLib.levels(c) for (i,level) in enumerate(levels), poly in ContourLib.lines(level) xs, ys = ContourLib.coordinates(poly) - Makie.poly!(ax, Makie.Point2f.(zip(xs,ys)); series.kwargs..., viz.kwargs..., color=color)#(color, 1/length(levels))) + Makie.poly!(ax, Makie.Point2f.(zip(xs,ys)); series.kwargs..., viz.kwargs...)#(color, 1/length(levels))) end end From 7672a2f35827295fcb90ae4545a441382f81028a Mon Sep 17 00:00:00 2001 From: William Thompson Date: Tue, 27 Dec 2022 10:32:12 -0800 Subject: [PATCH 06/15] Fix inversion of sigmas --- src/PairPlots.jl | 16 ++++++++++------ 1 file changed, 10 insertions(+), 6 deletions(-) diff --git a/src/PairPlots.jl b/src/PairPlots.jl index 7749bf6..0896844 100644 --- a/src/PairPlots.jl +++ b/src/PairPlots.jl @@ -41,13 +41,13 @@ struct Contour <: VizTypeBody sigmas kwargs end -Contour(;sigmas=0.5:0.5:2.1, kwargs...) = Contour(sigmas, kwargs) +Contour(;sigmas=1:2, kwargs...) = Contour(sigmas, kwargs) struct Contourf <: VizTypeBody sigmas kwargs end -Contourf(;sigmas=0.5:0.5:2.1, kwargs...) = Contourf(sigmas, kwargs) +Contourf(;sigmas=1:2, kwargs...) = Contourf(sigmas, kwargs) struct Scatter <: VizTypeBody kwargs @@ -93,9 +93,13 @@ function pairplot( figure=(;), kwargs..., ) - N = length(input)+1 + + # TODO: auto size figure based on the number of columns. + # We need to resolve all the inputs first, so this fix will + # require inverting the pairplot method cascade to do inputs, + # then the grid/gridpos/figure argument last. fig = Makie.Figure(; - resolution=(300N, 300N), + resolution=(800, 800), figure... ) pairplot(fig.layout, input...; kwargs...) @@ -117,7 +121,7 @@ function pairplot( single_series_color = Makie.RGBA(0., 0., 0., 0.5) single_series_default_viz = ( PairPlots.HexBin(colormap=Makie.cgrad([:transparent, :black]),bins=32), - PairPlots.Scatter(filtersigma=0.5), + PairPlots.Scatter(filtersigma=2), PairPlots.Contour(), PairPlots.MarginDensity( color=:transparent, @@ -394,7 +398,7 @@ function prep_contours(series::Series, sigmas, colname_row, colname_col) h = pdf.(Ref(ik), x, y') # Calculate levels for contours - levels = 1 .- exp.(-0.5 .* (sigmas).^2) + levels = 1 .- exp.(-0.5 .* (1 ./sigmas).^2) ii = sortperm(reshape(h,:)) h2flat = h[ii] sm = cumsum(h2flat) From 9f50175d7af2bbcd213ab4fb24413cfbce6917be Mon Sep 17 00:00:00 2001 From: William Thompson Date: Tue, 27 Dec 2022 11:41:34 -0800 Subject: [PATCH 07/15] Better defaults for larger numbers of tables --- src/PairPlots.jl | 82 +++++++++++++++++++++++++++--------------------- 1 file changed, 46 insertions(+), 36 deletions(-) diff --git a/src/PairPlots.jl b/src/PairPlots.jl index 0896844..34bd983 100644 --- a/src/PairPlots.jl +++ b/src/PairPlots.jl @@ -116,48 +116,58 @@ function pairplot( # Otherwise fall back to cycling the colours ourselves. # The Makie color cycle functionality isn't quite flexible enough (but almost!). + single_series_color = Makie.RGBA(0., 0., 0., 0.5) + single_series_default_viz = ( + PairPlots.HexBin(colormap=Makie.cgrad([:transparent, :black]),bins=32), + PairPlots.Scatter(filtersigma=2), + PairPlots.Contour(), + PairPlots.MarginDensity( + color=:transparent, + strokecolor=:black, + strokewidth=1.5f0 + ), + PairPlots.MarginConfidenceLimits() + ) - if length(datapairs) == 1 - single_series_color = Makie.RGBA(0., 0., 0., 0.5) - single_series_default_viz = ( - PairPlots.HexBin(colormap=Makie.cgrad([:transparent, :black]),bins=32), - PairPlots.Scatter(filtersigma=2), - PairPlots.Contour(), - PairPlots.MarginDensity( - color=:transparent, - strokecolor=:black, - strokewidth=1.5f0 - ), - PairPlots.MarginConfidenceLimits() + series_i = 0 + function SeriesDefaults(dat) + series_i += 1 + wc = Makie.wong_colors(0.5) + color = wc[mod1(series_i, length(wc))] + return Series(dat; color, strokecolor=color) + end + multi_series_default_viz = ( + PairPlots.Scatter(filtersigma=0.5), + PairPlots.Contourf(), + PairPlots.MarginDensity( + color=:transparent, + strokewidth=2.5f0 ) + ) + many_series_default_viz = ( + PairPlots.Contour(sigmas=[1]), + PairPlots.MarginDensity( + color=:transparent, + strokewidth=2.5f0 + ) + ) + + if length(datapairs) == 1 + defaults1((data,vizlayers)::Pair) = Series(data; color=single_series_color) => vizlayers defaults1(series::Series) = series => single_series_default_viz defaults1(data::Any) = Series(data; color=single_series_color) => single_series_default_viz pairplot(grid, defaults1(first(datapairs)); kwargs...) - else - series_i = 0 - function SeriesDefaults(dat) - series_i += 1 - wc = Makie.wong_colors(0.5) - if series_i in axes(wc,1) - color = wc[series_i] - else - color = Makie.RGBA(0., 0., 0., 0.5) - end - return Series(dat; color, strokecolor=color) - end - multi_series_default_viz = ( - PairPlots.Scatter(filtersigma=0.5), - PairPlots.Contourf(), - PairPlots.MarginDensity( - color=:transparent, - strokewidth=2.5f0 - ) - ) - defaults((data,vizlayers)::Pair) = SeriesDefaults(data) => vizlayers - defaults(series::Series) = series => multi_series_default_viz - defaults(data::Any) = SeriesDefaults(data) => multi_series_default_viz - pairplot(grid, map(defaults, datapairs)...; kwargs...) + elseif length(datapairs) <= 5 + defaults_upto5((data,vizlayers)::Pair) = SeriesDefaults(data) => vizlayers + defaults_upto5(series::Series) = series => multi_series_default_viz + defaults_upto5(data::Any) = SeriesDefaults(data) => multi_series_default_viz + pairplot(grid, map(defaults_upto5, datapairs)...; kwargs...) + else # More than 5 series + defaults_morethan5((data,vizlayers)::Pair) = SeriesDefaults(data) => vizlayers + defaults_morethan5(series::Series) = series => many_series_default_viz + defaults_morethan5(data::Any) = SeriesDefaults(data) => many_series_default_viz + pairplot(grid, map(defaults_morethan5, datapairs)...; kwargs...) end return From b4b6784fb8f33af1bbfb317d7dcb416eb9251a1c Mon Sep 17 00:00:00 2001 From: William Thompson Date: Wed, 28 Dec 2022 11:32:36 -0800 Subject: [PATCH 08/15] Code cleanup and doc strings --- Project.toml | 1 + examples/example.jl | 44 +++++ src/PairPlots.jl | 399 ++++++++++++++++++++++++++++++++++++-------- 3 files changed, 375 insertions(+), 69 deletions(-) diff --git a/Project.toml b/Project.toml index 0d11fca..3013d7b 100644 --- a/Project.toml +++ b/Project.toml @@ -11,6 +11,7 @@ Latexify = "23fbe1c1-3f47-55db-b15f-69d7ec21a316" Makie = "ee78f7c6-11fb-53f2-987a-cfe4a2b5a57a" Measures = "442fdcdd-2543-5da2-b0f3-8c86c306513e" NamedTupleTools = "d9ec5142-1e00-5aa0-9d6a-321866360f50" +OrderedCollections = "bac558e1-5e72-5ebc-8fee-abe8a469f55d" PolygonOps = "647866c9-e3ac-4575-94e7-e3d426903924" Printf = "de0858da-6303-5e67-8744-51eddeeeb8d7" RecipesBase = "3cdcf5f2-1ef4-517c-9805-6587b60abb01" diff --git a/examples/example.jl b/examples/example.jl index 7581edd..2c000a7 100644 --- a/examples/example.jl +++ b/examples/example.jl @@ -15,3 +15,47 @@ table = (;a, b, c, d) ## pairplot(table) + + +## Logo +N = 400_000 +a = randn(N) +b = randn(N) +c = randn(N) +table = (;a,b,c) + +for cname in (:green,:red,:purple) + color = getproperty(Makie.Colors.JULIA_LOGO_COLORS, cname) + fig = pairplot( + table => ( + PairPlots.HexBin(colormap=Makie.cgrad([:transparent, color]),bins=32), + PairPlots.Scatter(filtersigma=2,color=color), + PairPlots.Contour(), + PairPlots.MarginDensity( + color=:transparent, + strokecolor=color, + strokewidth=1.5f0 + ) + ), + bodyaxis=(; + xlabelvisible=false, + xticksvisible=false, + xticklabelsvisible=false, + ylabelvisible=false, + yticksvisible=false, + yticklabelsvisible=false, + ), + diagaxis=(; + xlabelvisible=false, + xticksvisible=false, + xticklabelsvisible=false, + ylabelvisible=false, + yticksvisible=false, + yticklabelsvisible=false, + ), + ) + rowgap!(fig.layout,0.0) + colgap!(fig.layout,0.0) + save("logo-$cname.png", fig) +end + diff --git a/src/PairPlots.jl b/src/PairPlots.jl index 34bd983..c1d52ab 100644 --- a/src/PairPlots.jl +++ b/src/PairPlots.jl @@ -1,5 +1,4 @@ module PairPlots -Base.Experimental.@optlevel 0 export pairplot @@ -8,75 +7,211 @@ using Tables using Printf using KernelDensity: KernelDensity using Contour: Contour as ContourLib +using OrderedCollections: OrderedDict using Latexify: latexify using StatsBase: fit, quantile, Histogram using Distributions: pdf using StaticArrays using PolygonOps +""" + AstractSeries + +Represents some kind of series in PairPlots. +""" abstract type AbstractSeries end -struct Series <: AbstractSeries - label - table - kwargs -end -Series(data; label=nothing, kwargs...) = Series(label, data, kwargs) +struct Series{T,K} <: AbstractSeries where {T,K} + label::Union{String,Nothing} + table::T + kwargs::K +end +""" + Series(data; label=nothing, kwargs=...) + +A data series in PairPlots. Wraps a Tables.jl compatible table. +You can optionally pass a label for this series to use in the plot legend. +Keyword arguments are forwarded to every plot call for this series. + +Examples: +```julia +ser = Series(table; label="series 1", color=:red) +``` +""" +function Series(data; label=nothing, kwargs...) + if !Tables.istable(data) + error("PairPlots expects a matrix or Tables.jl compatible table for each series.") + end + Series(label, data, kwargs) +end +""" + Series(matrix::AbstractMatrix; label=nothing, kwargs...) + +Convenience constructor to build a Series from an abstract matrix. +The columns are named accordingly to the axes of the Matrix (usually :1 though N). +""" +function Series(data::AbstractMatrix; label=nothing, kwargs...) + column_labels = [Symbol(i) for i in axes(data,1)] + table = NamedTuple([ + collabel => col + for (collabel, col) in zip(column_labels, eachrow(data)) + ]) + Series(label, table, kwargs) +end +"""" +A type of PairPlots vizualization. +""" abstract type VizType end + +"""" +A type of PairPlots vizualization that compares two variables. +""" abstract type VizTypeBody <: VizType end +## Note: these are deliberately not concretely typed. They just store keyword arguments +## that will vary as the user is modifying plots. No point in specializing on them. + +""" + HexBin(;kwargs...) + +Plot two variables against eachother using a Makie Hex Bin series. +`kwargs` are forwarded to the plot function and can be used to control +the number of bins and the appearance. +""" struct HexBin <: VizTypeBody kwargs + HexBin(;kwargs...) = new(kwargs) end -HexBin(;kwargs...) = HexBin(kwargs) -struct Hist <: VizTypeBody +""" + Hist(;kwargs...) + Hist(histprep_function; kwargs...) + +Plot two variables against eachother using a 2D histogram heatmap. +`kwargs` are forwarded to the plot function and can be used to control +the number of bins and the appearance. + +!!! note + You can optionally pass a function to override how the histogram is calculated. + It should have the signature: `prepare_hist(xs, ys, nbins)` and return + a vector of horizontal bin centers, vertical bin centers, and a matrix of weights. + + !!! tip + Your `prepare_hist` function it does not have to obey `nbins` +""" +struct Hist{T} <: VizTypeBody where T + prepare_hist::T kwargs + Hist(prepare_hist=prepare_hist;kwargs...) = new{typeof(prepare_hist)}(prepare_hist, kwargs) end -Hist(;kwargs...) = Hist(kwargs) + +""" + Contour(;sigmas=1:2, kwargs...) + +Plot two variables against eachother using a contour plot. The contours cover the area under a Gaussian +given by `sigmas`, which must be `<: AbstractVector`. `kwargs` are forwarded to the plot function and can +be used to control the appearance. + +KernelDensity.jl is used to produce smoother contours. + +!!! note + Contours are calculated using Contour.jl and plotted as a Makie line series. + +See also: Contourf +""" struct Contour <: VizTypeBody sigmas kwargs + Contour(;sigmas=1:2, kwargs...) = new(sigmas, kwargs) end -Contour(;sigmas=1:2, kwargs...) = Contour(sigmas, kwargs) +""" + Contourf(;sigmas=1:2, kwargs...) + +Plot two variables against eachother using a filled contour plot. The contours cover the area under a Gaussian +given by `sigmas`, which must be `<: AbstractVector`. `kwargs` are forwarded to the plot function and can +be used to control the appearance. + +KernelDensity.jl is used to produce smoother contours. + +See also: Contour +""" struct Contourf <: VizTypeBody sigmas kwargs + Contourf(;sigmas=1:2, kwargs...) = new(sigmas, kwargs) end -Contourf(;sigmas=1:2, kwargs...) = Contourf(sigmas, kwargs) +""" + Scatter(;kwargs...) + +Plot two variables against eachother using a scatter plot.`kwargs` are forwarded to the plot function and can +be used to control the appearance. +""" struct Scatter <: VizTypeBody kwargs filtersigma + Scatter(;filtersigma=nothing, kwargs...) = new(kwargs, filtersigma) end -Scatter(;filtersigma=nothing, kwargs...) = Scatter(kwargs, filtersigma) ## Diagonals +"""" + VizTypeBody +A type of PairPlots vizualization that only shows one variable. Used +for the plots along the diagonal. +""" abstract type VizTypeDiag <: VizType end + +""" + MarginConfidenceLimits(;titlefmt="\$\\mathrm{%.2f^{+%.2f}_{-%.2f}}\$", kwargs...) +""" struct MarginConfidenceLimits <: VizTypeDiag - titlefmt + titlefmt::String kwargs + function MarginConfidenceLimits(titlefmt="\$\\mathrm{%.2f^{+%.2f}_{-%.2f}}\$"; kwargs...) + return new(titlefmt, kwargs) + end end -function MarginConfidenceLimits(titlefmt="\$\\mathrm{%.2f^{+%.2f}_{-%.2f}}\$"; kwargs...) - return MarginConfidenceLimits(titlefmt, kwargs) -end -struct MarginHist <: VizTypeDiag +""" + MarginHist(;kwargs...) + MarginHist(histprep_function; kwargs...) + +Plot a marginal histogram of a single variable along the diagonal of the grid. +`kwargs` are forwarded to the plot function and can be used to control +the number of bins and the appearance. + +!!! tip + You can optionally pass a function to override how the histogram is calculated. + It should have the signature: `prepare_hist(xs, nbins)` and return + a vector of bin centers and a vector of weights. + + !!! note + Your `prepare_hist` function it does not have to obey `nbins` +""" +struct MarginHist{T} <: VizTypeDiag where T + prepare_hist::T kwargs + MarginHist(prepare_hist=prepare_hist;kwargs...) = new{typeof(prepare_hist)}(prepare_hist, kwargs) end -MarginHist(;kwargs...) = MarginHist(kwargs) +""" + MarginDensity(;kwargs...) + +Plot the smoothed marginal density of a variable along the diagonal of the grid, using Makie's `density` +function. `kwargs` are forwarded to the plot function and can be used to control +the appearance. +""" struct MarginDensity <: VizTypeDiag kwargs + MarginDensity(;kwargs...) = new(kwargs) end -MarginDensity(;kwargs...) = MarginDensity(kwargs) colnames(t::Series) = Tables.columnnames(t.table) @@ -87,7 +222,17 @@ colnames(t::AbstractDict) = keys(t) GridPosTypes = Union{Makie.Figure, Makie.GridPosition, Makie.GridSubposition} +""" + pairplot(inputs...; figure=(;), kwargs...) +Convenience method to generate a new Makie figure with resolution (800,800) +and then call `pairplot` as usual. Returns the figure. + +Example: +```julia +fig = pairplot(table) +``` +""" function pairplot( @nospecialize input...; figure=(;), @@ -106,7 +251,88 @@ function pairplot( return fig end -# Fallback defaults for convenience + +""" + pairplot(gridpos::Makie.GridPosition, inputs...; kwargs...) + +Create a pair plot at a given grid position of a Makie figure. + +Example +```julia +fig = Figure() +pairplot(fig[2,3], table) +fig +``` +""" +function pairplot( + gridpos::Makie.GridPosition, + @nospecialize datapairs::Any...; + kwargs..., +) + grid = Makie.GridLayout(gridpos) + pairplot(grid, datapairs...; kwargs...) + return grid +end + +""" + pairplot(gridpos::Makie.GridLayout, inputs...; kwargs...) + +Convenience function to create a reasonable pair plot given +one or more inputs that aren't full specified. +Wraps input tables in PairPlots.Series() with a distinct color specified +for each series. + +Here are the defaults applied for a single data table: +```julia +pairplot(fig[1,1], table) == # approximately the following: +pairplot( + PairPlots.Series(table, color=Makie.RGBA(0., 0., 0., 0.5)) => ( + PairPlots.HexBin(colormap=Makie.cgrad([:transparent, :black]),bins=32), + PairPlots.Scatter(filtersigma=2), + PairPlots.Contour(), + PairPlots.MarginDensity( + color=:transparent, + strokecolor=:black, + strokewidth=1.5f0 + ), + PairPlots.MarginConfidenceLimits() + ) +) +``` + +Here are the defaults applied for 2 to 5 data tables: +```julia +pairplot(fig[1,1], table1, table2) == # approximately the following: +pairplot( + PairPlots.Series(table1, color=Makie.wong_colors(0.5)[1]) => ( + PairPlots.Scatter(filtersigma=2), + PairPlots.Contourf(), + PairPlots.MarginDensity( + color=:transparent, + strokewidth=2.5f0 + ) + ), + PairPlots.Series(table2, color=Makie.wong_colors(0.5)[2]) => ( + PairPlots.Scatter(filtersigma=2), + PairPlots.Contourf(), + PairPlots.MarginDensity( + color=:transparent, + strokewidth=2.5f0 + ) + ), +) + +For 6 or more tables, the defaults are approximately: +```julia +PairPlots.Series(table1, color=Makie.wong_colors(0.5)[series_i]) => ( + PairPlots.Contour(sigmas=[1]), + PairPlots.MarginDensity( + color=:transparent, + strokewidth=2.5f0 + ) +) +``` +""" function pairplot( grid::Makie.GridLayout, @nospecialize datapairs::Any...; @@ -137,7 +363,7 @@ function pairplot( return Series(dat; color, strokecolor=color) end multi_series_default_viz = ( - PairPlots.Scatter(filtersigma=0.5), + PairPlots.Scatter(filtersigma=2), PairPlots.Contourf(), PairPlots.MarginDensity( color=:transparent, @@ -173,23 +399,25 @@ function pairplot( return end -# Handle plotting into a GridPosition instead of a GridLayout -function pairplot( - gridpos::Makie.GridPosition, - @nospecialize datapairs::Any...; - kwargs..., -) - grid = Makie.GridLayout(gridpos) - pairplot(grid, datapairs...; kwargs...) - return grid -end - # Create a pairplot by plotting into a grid position of a figure. + +""" + pairplot(gridpos::Makie.GridLayout, inputs...; kwargs...) + +Main PairPlots function. Create a pair plot by plotting into a grid +layout within a Makie figure. + +Inputs should be one or more `Pair` of PairPlots.AbstractSeries => tuple of VizType. + +Additional arguments: +* labels: customize the axes labels with a Dict of column name (symbol) to string, Makie rich text, or LaTeX string. +* diagaxis: customize the Makie.Axis of plots along the diagonal with a named tuple of keyword arguments. +* bodyaxis: customize the Makie.Axis of plots under the diagonal with a named tuple of keyword arguments. +""" function pairplot( grid::Makie.GridLayout, @nospecialize pairs::Pair{<:AbstractSeries}...; labels::AbstractDict{Symbol} = Dict{Symbol,Any}(), - units::AbstractDict{Symbol} = Dict{Symbol,Any}(), diagaxis=(;), bodyaxis=(;), ) @@ -204,13 +432,7 @@ function pairplot( for name in columns ) label_map = merge(label_map, Dict(labels)) - - # Similarly for units. By default empty string, but allow override. - units_map = Dict( - name => Makie.L"" - for name in columns - ) - units_map = merge(units_map, units) + # Rather than computing limits in this version, let's try to rely on # Makie doing a good job of linking axes. @@ -246,8 +468,15 @@ function pairplot( else kw = bodyaxis end + + # Hide first row if no diagonal viz layers + row_ind_fig = row_ind + if !anydiag_viz + row_ind_fig = row_ind - 1 + end + ax = Makie.Axis( - grid[row_ind, col_ind]; + grid[row_ind_fig, col_ind]; ylabel=label_map[colname_row], xlabel=label_map[colname_col], xgridvisible=false, @@ -267,14 +496,14 @@ function pairplot( # For each slot, loop through all series and fill it in accordingly. # We have two slot types: bodyplot, like a 3D histogram, and diagplot, along the diagonal - for (series_i,(series, vizlayers)) in enumerate(pairs) + for (series, vizlayers) in pairs cn = colnames(series) if colname_row in cn && colname_col in cn for vizlayer in vizlayers if row_ind == col_ind && vizlayer isa VizTypeDiag - diagplot(ax, vizlayer, series_i, series, colname_row) + diagplot(ax, vizlayer, series, colname_row) elseif row_ind != col_ind && vizlayer isa VizTypeBody - bodyplot(ax, vizlayer, series_i, series, colname_row, colname_col) + bodyplot(ax, vizlayer, series, colname_row, colname_col) else # skip end @@ -299,12 +528,7 @@ function pairplot( for axes in values(axes_by_col) Makie.linkxaxes!(axes...) end - - # Makie.rowgap!(grid, 0) - # Makie.colgap!(grid, 0) - - # We sometimes end up with an extra first row if there are no diagonal vizualization layers - Makie.trim!(grid) + # Wishlist: link x axis of bottom right diagonal plot with y axis of bottom row. return @@ -312,22 +536,31 @@ end # Note: stephist coming soon in a Makie PR -function diagplot(ax::Makie.Axis, viz::MarginHist, series_i, series::Series, colname) +function diagplot(ax::Makie.Axis, viz::MarginHist, series::Series, colname) dat = getproperty(series.table, colname) - h = Makie.hist!( - ax, - dat; + bins = get(series.kwargs, :bins, 32) + bins = get(viz.kwargs, :bins, bins) + + # h = fit(Histogram, vec(dat); nbins=bins) + # x = range(first(h.edges[1])+step(h.edges[1])/2, step=step(h.edges[1]), length=size(h.weights,1)) + + x, weights = viz.prepare_hist(dat, bins) + + + Makie.stairs!( + ax, x, weights; + gap = 0, series.kwargs..., viz.kwargs..., ) Makie.ylims!(ax,low=0) end -function diagplot(ax::Makie.Axis, viz::MarginDensity, series_i, series::Series, colname) +function diagplot(ax::Makie.Axis, viz::MarginDensity, series::Series, colname) dat = getproperty(series.table, colname) - h = Makie.density!( + Makie.density!( ax, dat; series.kwargs..., @@ -337,7 +570,7 @@ function diagplot(ax::Makie.Axis, viz::MarginDensity, series_i, series::Series, end -function diagplot(ax::Makie.Axis, viz::MarginConfidenceLimits, series_i, series::Series, colname) +function diagplot(ax::Makie.Axis, viz::MarginConfidenceLimits, series::Series, colname) percentiles = quantile(vec(getproperty(series.table, colname)), (0.16, 0.5, 0.84)) mid = percentiles[2] @@ -357,7 +590,7 @@ function diagplot(ax::Makie.Axis, viz::MarginConfidenceLimits, series_i, series: ) end -function bodyplot(ax::Makie.Axis, viz::HexBin, series_i, series::Series, colname_row, colname_col) +function bodyplot(ax::Makie.Axis, viz::HexBin, series::Series, colname_row, colname_col) Makie.hexbin!( ax, getproperty(series.table, colname_col), @@ -369,7 +602,7 @@ function bodyplot(ax::Makie.Axis, viz::HexBin, series_i, series::Series, colname ) end -function bodyplot(ax::Makie.Axis, viz::Hist, series_i, series::Series, colname_row, colname_col) +function bodyplot(ax::Makie.Axis, viz::Hist, series::Series, colname_row, colname_col) xdat = getproperty(series.table, colname_col) ydat = getproperty(series.table, colname_row) @@ -378,15 +611,17 @@ function bodyplot(ax::Makie.Axis, viz::Hist, series_i, series::Series, colname_r bins = get(series.kwargs, :bins, 32) bins = get(viz.kwargs, :bins, bins) - h = fit(Histogram, (vec(xdat),vec(ydat)); nbins=bins) - x = range(first(h.edges[1])+step(h.edges[1])/2, step=step(h.edges[1]), length=size(h.weights,1)) - y = range(first(h.edges[2])+step(h.edges[2])/2, step=step(h.edges[2]), length=size(h.weights,2)) + # h = fit(Histogram, (vec(xdat),vec(ydat)); nbins=bins) + # x = range(first(h.edges[1])+step(h.edges[1])/2, step=step(h.edges[1]), length=size(h.weights,1)) + # y = range(first(h.edges[2])+step(h.edges[2])/2, step=step(h.edges[2]), length=size(h.weights,2)) + + x, y, weights = viz.prepare_hist(xdat, ydat, bins) Makie.heatmap!( ax, x, y, - h.weights; + weights; colormap=Makie.cgrad([:transparent, :black]), series.kwargs..., viz.kwargs..., @@ -415,7 +650,6 @@ function prep_contours(series::Series, sigmas, colname_row, colname_col) sm /= sm[end] if all(isnan, sm) || length(h) <= 1 @warn "Could not compute valid contours" - plotcontours = false V = [0] else V = sort(map(v0 -> h2flat[sm .≤ v0][end], levels)) @@ -423,7 +657,6 @@ function prep_contours(series::Series, sigmas, colname_row, colname_col) @warn "Too few points to create valid contours" end end - levels_final = [0; V; maximum(h) * (1 + 1e-4)] # Place a row and column of zeros around all sides of the data grid # to ensure the contours link up nicely. @@ -435,10 +668,11 @@ function prep_contours(series::Series, sigmas, colname_row, colname_col) zeros(size(h,2))' 0 0 ] c = ContourLib.contours(pad_x,pad_y,pad_h, V) + return c end -function bodyplot(ax::Makie.Axis, viz::Contour, series_i, series, colname_row, colname_col) +function bodyplot(ax::Makie.Axis, viz::Contour, series, colname_row, colname_col) c = prep_contours(series::Series, viz.sigmas, colname_row, colname_col) @@ -450,7 +684,7 @@ function bodyplot(ax::Makie.Axis, viz::Contour, series_i, series, colname_row, c end end -function bodyplot(ax::Makie.Axis, viz::Contourf, series_i, series::Series, colname_row, colname_col) +function bodyplot(ax::Makie.Axis, viz::Contourf, series::Series, colname_row, colname_col) c = prep_contours(series::Series, viz.sigmas, colname_row, colname_col) @@ -462,7 +696,7 @@ function bodyplot(ax::Makie.Axis, viz::Contourf, series_i, series::Series, colna end -function bodyplot(ax::Makie.Axis, viz::Scatter, series_i, series::Series, colname_row, colname_col) +function bodyplot(ax::Makie.Axis, viz::Scatter, series::Series, colname_row, colname_col) xall = getproperty(series.table, colname_col) yall = getproperty(series.table, colname_row) @@ -480,6 +714,33 @@ function bodyplot(ax::Makie.Axis, viz::Scatter, series_i, series::Series, colnam end +# Default histogram calculations +""" + prepare_hist(vector, nbins) + +Use the StatsBase function to return a centered histogram from `vector` with `nbins`. +Must return a tuple of bin centres, followed by bin weights (of the same length). +""" +function prepare_hist(a, nbins) + h = fit(Histogram, vec(a); nbins) + x = range(first(h.edges[1])+step(h.edges[1])/2, step=step(h.edges[1]), length=size(h.weights,1)) + return x, h.weights +end +""" + prepare_hist(vector, nbins) + +Use the StatsBase function to return a centered histogram from `vector` with `nbins`x`nbins`. +Must return a tuple of bin centres along the horizontal, bin centres along the vertical, +and a matrix of bin weights (of matching dimensions). +""" +function prepare_hist(a, b, nbins) + h = fit(Histogram, (vec(a),vec(b)); nbins) + x = range(first(h.edges[1])+step(h.edges[1])/2, step=step(h.edges[1]), length=size(h.weights,1)) + y = range(first(h.edges[2])+step(h.edges[2])/2, step=step(h.edges[2]), length=size(h.weights,2)) + return x, y, h.weights +end + + # Filter the scatter plot to remove points inside the first contour # for performance and better display From b5d186697cc7d979601873b2d4d9e65c3b4ff89a Mon Sep 17 00:00:00 2001 From: William Thompson Date: Wed, 28 Dec 2022 11:33:11 -0800 Subject: [PATCH 09/15] Write docs --- docs/.gitignore | 1 + docs/Project.toml | 6 + docs/make.jl | 24 + docs/src/api.md | 19 + docs/src/assets/logo.png | Bin 0 -> 1837170 bytes docs/src/assets/theme.css | 10 + docs/src/getting-started.md | 58 + docs/src/guide.md | 236 + docs/src/index.md | 17 + images/3d-mesh-2.png | Bin 159184 -> 0 bytes images/3d-mesh-2.svg | 4519 --- images/3d-mesh.png | Bin 579790 -> 0 bytes images/3d-mesh.svg | 5909 --- images/basic.png | Bin 420340 -> 0 bytes images/basic.svg | 70087 --------------------------------- images/lens-1d.svg | 21767 ----------- images/lens-2d.svg | 25748 ------------- images/lens-custom.svg | 21932 ----------- images/lens-gallery.png | Bin 415395 -> 0 bytes images/logo.jl | 23 - images/logo.png | Bin 106461 -> 0 bytes images/minimal.png | Bin 266807 -> 0 bytes images/minimal.svg | 31756 --------------- images/single-variable.png | Bin 11230 -> 0 bytes images/single-variable.svg | 72 - images/themed.png | Bin 573861 -> 0 bytes images/themed.svg | 70094 ---------------------------------- 27 files changed, 371 insertions(+), 251907 deletions(-) create mode 100644 docs/.gitignore create mode 100644 docs/Project.toml create mode 100644 docs/make.jl create mode 100644 docs/src/api.md create mode 100644 docs/src/assets/logo.png create mode 100644 docs/src/assets/theme.css create mode 100644 docs/src/getting-started.md create mode 100644 docs/src/guide.md create mode 100644 docs/src/index.md delete mode 100644 images/3d-mesh-2.png delete mode 100644 images/3d-mesh-2.svg delete mode 100644 images/3d-mesh.png delete mode 100644 images/3d-mesh.svg delete mode 100644 images/basic.png delete mode 100644 images/basic.svg delete mode 100644 images/lens-1d.svg delete mode 100644 images/lens-2d.svg delete mode 100644 images/lens-custom.svg delete mode 100644 images/lens-gallery.png delete mode 100644 images/logo.jl delete mode 100644 images/logo.png delete mode 100644 images/minimal.png delete mode 100644 images/minimal.svg delete mode 100644 images/single-variable.png delete mode 100644 images/single-variable.svg delete mode 100644 images/themed.png delete mode 100644 images/themed.svg diff --git a/docs/.gitignore b/docs/.gitignore new file mode 100644 index 0000000..567609b --- /dev/null +++ b/docs/.gitignore @@ -0,0 +1 @@ +build/ diff --git a/docs/Project.toml b/docs/Project.toml new file mode 100644 index 0000000..d6cd969 --- /dev/null +++ b/docs/Project.toml @@ -0,0 +1,6 @@ +[deps] +CairoMakie = "13f3f980-e62b-5c42-98c6-ff1f3baf88f0" +DataFrames = "a93c6f00-e57d-5684-b7b6-d8193f3e46c0" +Documenter = "e30172f5-a6a5-5a46-863b-614d45cd2de4" +MakieCore = "20f20a25-4f0e-4fdf-b5d1-57303727442b" +PairPlots = "43a3c2be-4208-490b-832a-a21dcd55d7da" diff --git a/docs/make.jl b/docs/make.jl new file mode 100644 index 0000000..7326cac --- /dev/null +++ b/docs/make.jl @@ -0,0 +1,24 @@ +using Documenter, CairoMakie, PairPlots + +ENV["DATAFRAMES_ROWS"] = 5 + +makedocs( + sitename="PairPlots.jl", + pages=[ + "Home" => "index.md", + "Getting Started" => "getting-started.md", + "Guide" => "guide.md", + "API" => "api.md", + ], + format = Documenter.HTML( + prettyurls = get(ENV, "CI", nothing) == "true", + assets = ["assets/theme.css"], + ), +) + + +deploydocs( + repo = "github.com/sefffal/PairPlots.jl.git", + devbranch = "master", + push_preview = true +) diff --git a/docs/src/api.md b/docs/src/api.md new file mode 100644 index 0000000..10e6983 --- /dev/null +++ b/docs/src/api.md @@ -0,0 +1,19 @@ +# API Documentation + + +```@docs +pairplot +PairPlots.AbstractSeries +PairPlots.Series +PairPlots.VizType +PairPlots.VizTypeBody +PairPlots.VizTypeDiag +PairPlots.HexBin +PairPlots.Hist +PairPlots.Contour +PairPlots.Contourf +PairPlots.Scatter +PairPlots.MarginConfidenceLimits +PairPlots.MarginHist +PairPlots.MarginDensity +``` diff --git a/docs/src/assets/logo.png b/docs/src/assets/logo.png new file mode 100644 index 0000000000000000000000000000000000000000..f1d47c9eb139eb6135299fab795b739b24a2b300 GIT binary patch literal 1837170 zcmeFZcT|(v+CCh0)Un|i5j!$AR1i>U(gzV4ItU3JM5IPQx)3Q=Mj1e*2}myi5{Lq! 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