Fix for regression with colorbar limits (#3874)
* Fix for regression * Remove call * Refactored to dispatching * Fixes * Unrolling loop * Change to IdDict in case objects mutated
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@ -2033,7 +2033,6 @@ function _update_subplot_args(
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lims_warned = true
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end
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end
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_update_subplot_colorbars(sp)
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end
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# -----------------------------------------------------------------------------
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@ -141,6 +141,7 @@ function (pgfx_plot::PGFPlotsXPlot)(plt::Plot{PGFPlotsXBackend})
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title_loc = sp[:titlelocation]
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bgc_inside = plot_color(sp[:background_color_inside])
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bgc_inside_a = alpha(bgc_inside)
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update_clims(sp)
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axis_opt = PGFPlotsX.Options(
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"point meta max" => get_clims(sp)[2],
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"point meta min" => get_clims(sp)[1],
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@ -5,11 +5,14 @@ process_clims(s::Union{Symbol,Nothing,Missing}) = ignorenan_extrema
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# don't specialize on ::Function otherwise python functions won't work
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process_clims(f) = f
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get_clims(sp::Subplot)::Tuple{Float64,Float64} = sp[:crange]
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get_clims(series::Series)::Tuple{Float64,Float64} = series[:crange]
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const sp_clims = IdDict{Subplot, Tuple{Float64, Float64}}()
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const series_clims = IdDict{Series, Tuple{Float64, Float64}}()
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get_clims(sp::Subplot)::Tuple{Float64,Float64} = haskey(sp_clims, sp) ? sp_clims[sp] : update_clims(sp)
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get_clims(series::Series)::Tuple{Float64,Float64} = haskey(series_clims, series) ? series_clims[series] : update_clims(series)
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get_clims(sp::Subplot, series::Series)::Tuple{Float64,Float64} =
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series[:colorbar_entry] ? sp[:crange] : series[:crange]
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series[:colorbar_entry] ? get_clims(sp) : get_clims(series)
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function update_clims(sp::Subplot, op = process_clims(sp[:clims]))::Tuple{Float64,Float64}
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zmin, zmax = Inf, -Inf
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@ -20,12 +23,11 @@ function update_clims(sp::Subplot, op = process_clims(sp[:clims]))::Tuple{Float6
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update_clims(series, op)
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end
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end
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return sp[:crange] = zmin <= zmax ? (zmin, zmax) : (NaN, NaN)
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return sp_clims[sp] = zmin <= zmax ? (zmin, zmax) : (NaN, NaN)
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end
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"""
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update_clims(::Series, op=Plots.ignorenan_extrema)
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Finds the limits for the colorbar by taking the "z-values" for the series and passing them into `op`,
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which must return the tuple `(zmin, zmax)`. The default op is the extrema of the finite
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values of the input. The value is stored as a series property, which is retrieved by `get_clims`.
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@ -33,21 +35,28 @@ values of the input. The value is stored as a series property, which is retrieve
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function update_clims(series::Series, op = ignorenan_extrema)::Tuple{Float64,Float64}
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zmin, zmax = Inf, -Inf
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z_colored_series = (:contour, :contour3d, :heatmap, :histogram2d, :surface, :hexbin)
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for vals in (
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series[:seriestype] in z_colored_series ? series[:z] : nothing,
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series[:line_z],
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series[:marker_z],
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series[:fill_z],
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)
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if (typeof(vals) <: AbstractSurface) && (eltype(vals.surf) <: Union{Missing,Real})
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zmin, zmax = _update_clims(zmin, zmax, op(vals.surf)...)
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elseif (vals !== nothing) && (eltype(vals) <: Union{Missing,Real})
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zmin, zmax = _update_clims(zmin, zmax, op(vals)...)
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end
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# keeping this unrolled has higher performance
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if series[:seriestype] ∈ z_colored_series && series[:z] !== nothing
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zmin, zmax = update_clims(zmin, zmax, series[:z], op)
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end
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return series[:crange] = zmin <= zmax ? (zmin, zmax) : (NaN, NaN)
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if series[:line_z] !== nothing
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zmin, zmax = update_clims(zmin, zmax, series[:line_z], op)
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end
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if series[:marker_z] !== nothing
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zmin, zmax = update_clims(zmin, zmax, series[:marker_z], op)
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end
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if series[:fill_z] !== nothing
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zmin, zmax = update_clims(zmin, zmax, series[:fill_z], op)
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end
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return series_clims[series] = zmin <= zmax ? (zmin, zmax) : (NaN, NaN)
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end
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update_clims(zmin, zmax, vals::AbstractSurface, op)::Tuple{Float64, Float64} = update_clims(zmin, zmax, vals.surf, op)
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update_clims(zmin, zmax, vals::Any, op)::Tuple{Float64, Float64} = _update_clims(zmin, zmax, op(vals)...)
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update_clims(zmin, zmax, ::Nothing, ::Any)::Tuple{Float64, Float64} = zmin, zmax
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_update_clims(zmin, zmax, emin, emax) = NaNMath.min(zmin, emin), NaNMath.max(zmax, emax)
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@enum ColorbarStyle cbar_gradient cbar_fill cbar_lines
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