SpecFit updates for improvements

Project.toml

@@ -9,22 +9,23 @@ BAT = "c0cd4b16-88b7-57fa-983b-ab80aecada7e"
 ChangesOfVariables = "9e997f8a-9a97-42d5-a9f1-ce6bfc15e2c0"
 DensityInterface = "b429d917-457f-4dbc-8f4c-0cc954292b1d"
 Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f"
+Documenter = "e30172f5-a6a5-5a46-863b-614d45cd2de4"
 FillArrays = "1a297f60-69ca-5386-bcde-b61e274b549b"
 Formatting = "59287772-0a20-5a39-b81b-1366585eb4c0"
 ForwardDiff = "f6369f11-7733-5829-9624-2563aa707210"
 IntervalSets = "8197267c-284f-5f27-9208-e0e47529a953"
 InverseFunctions = "3587e190-3f89-42d0-90ee-14403ec27112"
 IrrationalConstants = "92d709cd-6900-40b7-9082-c6be49f344b6"
+LegendDataManagement = "9feedd95-f0e0-423f-a8dc-de0970eae6b3"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 LinearRegression = "92481ed7-9fb7-40fd-80f2-46fd0f076581"
 LsqFit = "2fda8390-95c7-5789-9bda-21331edee243"
+Measurements = "eff96d63-e80a-5855-80a2-b1b0885c5ab7"
 Optim = "429524aa-4258-5aef-a3af-852621145aeb"
-Plots = "91a5bcdd-55d7-5caf-9e0b-520d859cae80"
 PropDicts = "4dc08600-4268-439e-8673-d706fafbb426"
 RadiationSpectra = "4f207c7e-01da-51d7-a1a0-c8c06dd1d883"
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
 RecipesBase = "3cdcf5f2-1ef4-517c-9805-6587b60abb01"
-Requires = "ae029012-a4dd-5104-9daa-d747884805df"
 Roots = "f2b01f46-fcfa-551c-844a-d8ac1e96c665"
 SnoopPrecompile = "66db9d55-30c0-4569-8b51-7e840670fc0c"
 SpecialFunctions = "276daf66-3868-5448-9aa4-cd146d93841b"
@@ -55,16 +56,16 @@ ForwardDiff = "0.10"
 IntervalSets = "0.7"
 InverseFunctions = "0.1"
 IrrationalConstants = "0.1, 0.2"
+LegendDataManagement = "0.2.7"
 LinearAlgebra = "1"
 LinearRegression = "0.2"
 LsqFit = "0.14, 0.15"
+Measurements = "2"
 Optim = "1"
-Plots = "1"
 PropDicts = "0.2"
 RadiationSpectra = "0.5"
 Random = "1"
 RecipesBase = "1"
-Requires = "1"
 Roots = "2"
 SnoopPrecompile = "1"
 SpecialFunctions = "0.10, 1, 2"

ext/LegendSpecFitsRecipesBaseExt.jl

@@ -12,17 +12,16 @@ using StatsBase, LinearAlgebra
     legend := :bottomright
     @series begin
         seriestype := :histogram
-        # y := report.f_fit.(x)
-        bins --> 2000
+        bins --> :fd
+        # bins --> 2000
         normalize --> :pdf
         label := "Data"
-        # label := @sprintf("μ = %s ± %s\nσ = %s ± %s\nn = %d", report.μ, report.μ_err, report.σ, report.σ_err, report.n)
         x[x .> cuts.low .&& x .< cuts.high]
         # x
     end
     @series begin
         color := :red
-        label := format("Normal Fit (μ = ({:.2f} ± {:.2f})µs, σ = ({:.2f} ± {:.2f})µs", ustrip.([report.μ, report.μ_err, report.σ, report.σ_err])...)
+        label := format("Normal Fit (μ = ({:.2f} ± {:.2f}), σ = ({:.2f} ± {:.2f})", ustrip.([report.μ, report.μ_err, report.σ, report.σ_err])...)
         lw := 3
         ustrip(cuts.low):0.00001:ustrip(cuts.high), t -> report.f_fit(t)
     end
@@ -66,8 +65,8 @@ end
     gridlinewidth := 0.5
     # xscale := :log10
     # yscale := :log10
-    ylims := (1, 5)
-    xlims := (1, 5)
+    ylims := (1, 8)
+    xlims := (0.5, 5)
     @series begin
         seriestype := :scatter
         u"µs", NoUnits
@@ -86,41 +85,68 @@ end
     end
 end
 
-@recipe function f(report::NamedTuple{(:v, :h, :f_fit, :f_sig, :f_lowEtail, :f_bck)}; show_label::Bool)
+@recipe function f(report:: NamedTuple{(:wl, :min_sf, :min_sf_err, :a_grid_wl_sg, :sfs, :sfs_err)})
+    xlabel := "Window Length (ns)"
+    ylabel := "SEP Surrival Fraction (%)"
+    grid := :true
+    gridcolor := :black
+    gridalpha := 0.2
+    gridlinewidth := 0.5
+    ylims := (0, 30)
+    @series begin
+        seriestype := :scatter
+        label := "SF"
+        yerror --> report.sfs_err
+        ustrip.(report.a_grid_wl_sg), report.sfs
+    end
+    @series begin
+        seriestype := :hline
+        label := "Min. SF (WT: $(report.wl))"
+        color := :red
+        linewidth := 2.5
+        [report.min_sf]
+    end
+end
+
+@recipe function f(report::NamedTuple{(:v, :h, :f_fit, :f_sig, :f_lowEtail, :f_bck)}; show_label=true, show_fit=true)
     xlabel := "Energy (keV)"
     ylabel := "Counts"
     legend := :bottomright
     yscale := :log10
-    ylims := (1, 1.2*report.f_sig(report.v.μ))
+    ylim_max = max(5*report.f_sig(report.v.μ), 5*maximum(report.h.weights))
+    ylim_max = ifelse(ylim_max == 0.0, 1e5, ylim_max)
+    ylims := (1, ylim_max)
     @series begin
         seriestype := :stepbins
         label := ifelse(show_label, "Data", "")
         bins --> :sqrt
         LinearAlgebra.normalize(report.h, mode = :density)
     end
-    @series begin
-        seriestype := :line
-        label := ifelse(show_label, "Best Fit", "")
-        color := :red
-        minimum(report.h.edges[1]):0.1:maximum(report.h.edges[1]), report.f_fit
-    end
-    @series begin
-        seriestype := :line
-        label := ifelse(show_label, "Signal", "")
-        color := :green
-        minimum(report.h.edges[1]):0.1:maximum(report.h.edges[1]), report.f_sig
-    end
-    @series begin
-        seriestype := :line
-        label := ifelse(show_label, "Low Energy Tail", "")
-        color := :blue
-        minimum(report.h.edges[1]):0.1:maximum(report.h.edges[1]), report.f_lowEtail
-    end
-    @series begin
-        seriestype := :line
-        label := ifelse(show_label, "Background", "")
-        color := :black
-        minimum(report.h.edges[1]):0.1:maximum(report.h.edges[1]), report.f_bck
+    if show_fit
+        @series begin
+            seriestype := :line
+            label := ifelse(show_label, "Best Fit", "")
+            color := :red
+            minimum(report.h.edges[1]):0.1:maximum(report.h.edges[1]), report.f_fit
+        end
+        @series begin
+            seriestype := :line
+            label := ifelse(show_label, "Signal", "")
+            color := :green
+            minimum(report.h.edges[1]):0.1:maximum(report.h.edges[1]), report.f_sig
+        end
+        @series begin
+            seriestype := :line
+            label := ifelse(show_label, "Low Energy Tail", "")
+            color := :blue
+            minimum(report.h.edges[1]):0.1:maximum(report.h.edges[1]), report.f_lowEtail
+        end
+        @series begin
+            seriestype := :line
+            label := ifelse(show_label, "Background", "")
+            color := :black
+            minimum(report.h.edges[1]):0.1:maximum(report.h.edges[1]), report.f_bck
+        end
     end
 end
 
@@ -182,7 +208,7 @@ end
     end
 end
 
-@recipe function f(report::NamedTuple{(:h_calsimple, :h_uncal, :c, :fep_guess, :peakhists, :peakstats)}; cal::Bool)
+@recipe function f(report::NamedTuple{(:h_calsimple, :h_uncal, :c, :fep_guess, :peakhists, :peakstats)}; cal=true)
     ylabel := "Counts"
     legend := :topright
     yscale := :log10
@@ -216,7 +242,7 @@ end
     end
 end
 
-@recipe function f(report_ctc::NamedTuple{(:peak, :window, :fct, :bin_width, :bin_width_qdrift, :e_peak, :e_ctc, :qdrift_peak, :h_before, :h_after)})
+@recipe function f(report_ctc::NamedTuple{(:peak, :window, :fct, :bin_width, :bin_width_qdrift, :e_peak, :e_ctc, :qdrift_peak, :h_before, :h_after, :fwhm_before, :fwhm_after, :err, :report_before, :report_after)})
     layout := (2,2)
     thickness_scaling := 2.0
     size := (2400, 1600)
@@ -252,10 +278,33 @@ end
         label := "Before CTC"
         xlabel := "Energy (keV)"
         ylabel := "Counts"
+        title := "FWHM $(round(report_ctc.fwhm_before, digits=2))±$(round(report_ctc.err.fwhm_before, digits=2))keV"
         yscale := :log10
         subplot := 3
         report_ctc.h_before
     end
+    # @series begin
+    #     # seriestype := :stepbins
+    #     color := :red
+    #     # label := "Before CTC"
+    #     # xlabel := "Energy (keV)"
+    #     # ylabel := "Counts"
+    #     # yscale := :log10
+    #     subplot := 3
+    #     # report_ctc.h_before
+    #     minimum(report_ctc.e_peak):0.001:maximum(report_ctc.e_peak), t -> report_ctc.report_before.f_fit(t)
+    # end
+    # @series begin
+    #     # seriestype := :stepbins
+    #     color := :red
+    #     # label := "Before CTC"
+    #     # xlabel := "Energy (keV)"
+    #     # ylabel := "Counts"
+    #     # yscale := :log10
+    #     subplot := 4
+    #     # report_ctc.h_before
+    #     minimum(report_ctc.e_peak):0.001:maximum(report_ctc.e_peak), t -> report_ctc.report_after.f_fit(t)
+    # end
     @series begin
         seriestype := :stepbins
         color := :red
@@ -272,11 +321,58 @@ end
         label := "After CTC"
         xlabel := "Energy (keV)"
         ylabel := "Counts"
+        title := "FWHM $(round(report_ctc.fwhm_after, digits=2))±$(round(report_ctc.err.fwhm_after, digits=2))keV"
         yscale := :log10
         subplot := 4
         report_ctc.h_after
     end
 end
 
+@recipe function f(report_window_cut::NamedTuple{(:h, :f_fit, :x_fit, :low_cut, :high_cut, :low_cut_fit, :high_cut_fit, :center, :σ)})
+    xlims := (ustrip(report_window_cut.center - 5*report_window_cut.σ), ustrip(report_window_cut.center + 5*report_window_cut.σ))
+    @series begin
+        seriestype := :barbins
+        alpha := 0.5
+        label := "Data"
+        report_window_cut.h        
+    end
+    @series begin
+        seriestype := :line
+        label := "Best Fit"
+        color := :red
+        linewidth := 3
+        report_window_cut.x_fit, report_window_cut.f_fit
+    end
+    @series begin
+        seriestype := :vline
+        label := "Cut Window"
+        color := :green
+        linewidth := 3
+        ustrip.([report_window_cut.low_cut, report_window_cut.high_cut])
+    end
+    # @series begin
+    #     seriestype := :vline
+    #     label := "Center"
+    #     color := :blue
+    #     linewidth := 3
+    #     ustrip.([report_window_cut.center])
+    # end
+    @series begin
+        seriestype := :vline
+        label := "Fit Window"
+        color := :orange
+        linewidth := 3
+        ustrip.([report_window_cut.low_cut_fit, report_window_cut.high_cut_fit])
+    end
+    @series begin
+        seriestype := :vspan
+        label := ""
+        color := :lightgreen
+        alpha := 0.2
+        ustrip.([report_window_cut.low_cut, report_window_cut.high_cut])
+    end
+
+end
+
 
 end # module LegendSpecFitsRecipesBaseExt

src/LegendSpecFits.jl

@@ -13,33 +13,35 @@ using Random
 
 using ArgCheck
 using ArraysOfArrays
+using BAT
 using Distributions
 using FillArrays
+using ForwardDiff
+using IntervalSets
 using InverseFunctions
 using IrrationalConstants
+using LegendDataManagement
+using LinearRegression
+using LsqFit
+using Optim
+using PropDicts
 using RadiationSpectra
+using Roots
 using SpecialFunctions
 using StatsBase
 using StructArrays
 using Tables
+using TypedTables
 using Unitful
 using ValueShapes
-using IntervalSets
-using Roots
-using BAT
-using LsqFit
-using Optim
-using ForwardDiff
-using LinearRegression
-using PropDicts
 
 include("utils.jl")
 include("peakshapes.jl")
 include("likelihoods.jl")
 include("priors.jl")
 include("cut.jl")
 include("aoefit.jl")
-include("optimization.jl")
+include("filter_optimization.jl")
 include("singlefit.jl")
 include("specfit.jl")
 include("fwhm.jl")
@@ -48,18 +50,8 @@ include("auto_calibration.jl")
 include("aoe_calibration.jl")
 include("specfit_combined.jl")
 include("ctc.jl")
-
-# @static if !isdefined(Base, :get_extension)
-#     using Requires
-#     include("../ext/LegendSpecFitsRecipesBaseExt.jl")
-# end
-
+include("qc.jl")
+include("gof.jl")
 include("precompile.jl")
 
-function __init__()
-    @static if !isdefined(Base, :get_extension)
-        @require BAT = "c0cd4b16-88b7-57fa-983b-ab80aecada7e" include("../ext/LegendSpecFitsBATExt.jl")
-    end
-end
-
 end # module