Add aoecorrectionplot! and lplot! for fits with components and A/E correction plots

[fhagemann]

Just as shown in the tests:

using LegendMakie, CairoMakie
using LegendSpecFits

using Distributions
using Unitful

e_cal = rand(Distributions.Exponential(300), 5_000_000) .+ 300
μA, μB, σA, σB = 1.01, 4e-6, 5e-3, 12.0
myμ(E) = μA - μB * E
myσ(E) = sqrt(σA^2 + σB^2/E^2)
aoe = [let _μ = myμ(E), _σ = myσ(E); (rand() < 0.2 ? -rand(Distributions.Exponential(5*_σ)) : 0) + _σ*randn() + _μ; end for E in e_cal]

compton_bands = collect((550:50:2350)u"keV")
compton_window = 20u"keV"
compton_band_peakhists = LegendSpecFits.generate_aoe_compton_bands(aoe, e_cal*u"keV", compton_bands, compton_window)
result_fit, report_fit = LegendSpecFits.fit_aoe_compton(compton_band_peakhists.peakhists, compton_band_peakhists.peakstats, compton_bands, uncertainty=true)
μs = [result_fit[band].μ for band in compton_bands]
σs = [result_fit[band].σ for band in compton_bands]
result_fit_single, report_fit_single = LegendSpecFits.fit_aoe_corrections(compton_bands, μs, σs)

# Compton band (individual) fit
lplot(report_fit[first(compton_bands)])

# A/E correction plots
lplot(report_fit_single.report_μ, col = 1, figsize = (1200,420))
lplot!(report_fit_single.report_σ, col = 2)
LegendMakie.add_watermarks!()

[codecov]

Codecov Report

All modified and coverable lines are covered by tests ✅

Project coverage is 88.58%. Comparing base (e95e826) to head (9eb0e34).
Report is 7 commits behind head on main.

Additional details and impacted files

@@            Coverage Diff             @@
##             main       #3      +/-   ##
==========================================
+ Coverage   81.25%   88.58%   +7.33%     
==========================================
  Files           7        8       +1     
  Lines         112      184      +72     
==========================================
+ Hits           91      163      +72     
  Misses         21       21              

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[fhagemann]

The last commit also includes testing the plots for the A/E combined fit.

result_fit_combined, report_fit_combined = LegendSpecFits.fit_aoe_compton_combined(compton_band_peakhists.peakhists, compton_band_peakhists.peakstats, compton_bands, result_fit_single, uncertainty=true)

# A/E combined fit plots
lplot(report_fit_single.report_μ, report_fit_combined.report_μ, col = 1, figsize = (1200,420))
lplot!(report_fit_single.report_σ, report_fit_combined.report_σ, col = 2)