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Adjust A/E ctc recipe #38

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Mar 14, 2025
Merged

Adjust A/E ctc recipe #38

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cf23935
Adjust A/E ctc recipe to changes in LegendSpecFits.jl#135
fhagemann Mar 14, 2025
f71f341
Add keyword argument to plot `normalized` A/E ctc distribution
fhagemann Mar 14, 2025
073f977
Add tests to plot the normalized A/E ctc distribution
fhagemann Mar 14, 2025
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10 changes: 5 additions & 5 deletions ext/LegendMakieLegendSpecFitsExt.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -809,12 +809,12 @@ module LegendMakieLegendSpecFitsExt

# plot report from ctc_aoe
function LegendMakie.lplot!(
report::NamedTuple{(:peak, :window, :fct, :bin_width, :bin_width_qdrift, :aoe_peak, :aoe_ctc, :qdrift_peak, :h_before, :h_after, :σ_before, :σ_after, :report_before, :report_after)};
report::NamedTuple{(:peak, :window, :fct, :bin_width, :bin_width_qdrift, :aoe_peak, :aoe_ctc, :aoe_ctc_norm, :qdrift_peak, :h_before, :h_after, :h_after_norm, :σ_before, :σ_after, :σ_after_norm, :report_before, :report_after, :report_after_norm)};
label_before = "Before correction", label_after = "After correction", levels = 15,
xlims = (-9,5), ylims = StatsBase.quantile.(Ref(report.qdrift_peak), (0.005, 0.995)), xticks = Makie.WilkinsonTicks(6,k_min=5), yticks = Makie.WilkinsonTicks(6,k_min=4),
title::AbstractString = "", titlesize = 18, titlegap = 0,
title::AbstractString = "", titlesize = 18, titlegap = 0, norm::Bool = false,
xlabel = "A/E classifier", ylabel = "Qdrift / E",
watermark::Bool = true, kwargs...
watermark::Bool = true, kwargs...
)

# Best results for figsize (600,600)
Expand All @@ -824,7 +824,7 @@ module LegendMakieLegendSpecFitsExt

ax = Makie.Axis(g[1,1], limits = (xlims,(0,nothing)), ylabel = "Counts / $(round(step(first(report.h_before.edges)), digits = 2))")
h_before = Makie.plot!(ax, report.h_before, color = :darkgrey)
h_after = Makie.plot!(ax, report.h_after, color = (:purple, 0.5))
h_after = Makie.plot!(ax, norm ? report.h_after_norm : report.h_after, color = (:purple, 0.5))

ax3 = Makie.Axis(g[1,2])
Makie.hidedecorations!(ax3)
Expand All @@ -833,7 +833,7 @@ module LegendMakieLegendSpecFitsExt

ax2 = Makie.Axis(g[2,1]; limits = (xlims, ylims), xticks, yticks, xlabel, ylabel)
k_before = KernelDensity.kde((report.aoe_peak, report.qdrift_peak))
k_after = KernelDensity.kde((report.aoe_ctc, report.qdrift_peak))
k_after = KernelDensity.kde((norm ? report.aoe_ctc_norm : report.aoe_ctc, report.qdrift_peak))
Makie.contourf!(ax2, k_before.x, k_before.y, k_before.density, levels = levels, colormap = :binary)
Makie.contour!(ax2, k_before.x, k_before.y, k_before.density, levels = levels - 1, color = :white)
Makie.contour!(ax2, k_after.x, k_after.y, k_after.density, levels = levels - 1, colormap = :plasma)
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13 changes: 9 additions & 4 deletions test/test_lplot.jl
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Expand Up @@ -188,12 +188,17 @@ end
@testset "A/E ctc correlation plot" begin
# generate fake A/E and Qdrift/E distribution
E0 = 550u"keV"
e_cal = fill(E0, 10_000)
aoe_corr = clamp.(vcat(-rand(Distributions.Exponential(5.0), 2_000), zeros(8_000)) .+ randn(10_000), -49.0, 7.0)
qdrift_e = max.(0, randn(10_000) .+ 5)
@test length(e_cal) == length(aoe_corr) == length(qdrift_e) == 10_000
e_cal = fill(E0, 100_000)
aoe_corr = clamp.(vcat(-rand(Distributions.Exponential(5.0), 20_000), zeros(80_000)) .+ randn(100_000), -49.0, 7.0)
qdrift_e = max.(0, randn(100_000) .+ 5)
# add some fake drift time dependency
fct = 0.1
aoe_corr .-= qdrift_e .* fct
aoe_corr .-= StatsBase.median(aoe_corr)
@test length(e_cal) == length(aoe_corr) == length(qdrift_e) == 100_000
result_aoe_ctc, report_aoe_ctc = LegendSpecFits.ctc_aoe(aoe_corr, e_cal, qdrift_e, [E0-10u"keV"])
@test_nowarn lplot(report_aoe_ctc, figsize = (600,600), title = "Test")
@test_nowarn lplot(report_aoe_ctc, norm = true, figsize = (600,600), title = "Test")
end

@testset "A/E survival fraction plots" begin
Expand Down