mdf_amr should return MH in sorted order

cgarling · Sep 28, 2024 · 12e4975 · 12e4975
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diff --git a/src/fitting/mdf.jl b/src/fitting/mdf.jl
@@ -12,7 +12,7 @@ Calculates the mass-weighted metallicity distribution function given a set of *s
 P_j = \\frac{ \\sum_k r_{j,k} \\, [\\text{M} / \\text{H}]_k}{\\sum_{j,k} r_{j,k} \\, [\\text{M} / \\text{H}]_k}
 ```
 
-where ``r_{j,k}`` are the elements of `coeffs` where ``j`` indexes over unique entries in `logAge` and ``k`` indexes over unique entries in `metallicities.` This is the same nomenclature used in the [the documentation on constrained metallicity evolutions](@ref metal_evo_intro).
+where ``r_{j,k}`` are the elements of `coeffs` where ``j`` indexes over unique entries in `logAge` and ``k`` indexes over unique entries in `metallicities.` This is the same nomenclature used in the [the documentation on constrained metallicity evolutions](@ref metal_evo_intro). The return values are sorted so that `unique_MH` is in increasing order.
 
 # Examples
 ```jldoctest; setup = :(import StarFormationHistories: mdf_amr)
@@ -30,7 +30,8 @@ function mdf_amr(coeffs::AbstractVector{<:Number}, # Stellar mass coefficients
     unique_MH = unique(metallicities)
     mass_mdf = [sum(coeffs[idx]) for idx in (findall( ==(i), metallicities) for i in unique_MH)]
     mass_mdf ./= sum(mass_mdf) # Normalize to sum probability = 1
-    return unique_MH, mass_mdf
+    p = sortperm(unique_MH) # Return in sorted order of unique_MH
+    return unique_MH[p], mass_mdf[p]
 end
 
 # function mdf_amr(stellar_masses::AbstractVector{<:Number},

diff --git a/test/runtests.jl b/test/runtests.jl
@@ -619,11 +619,12 @@ const rtols = (1e-3, 1e-7) # Relative tolerance levels to use for the above floa
                             @test isapprox(result3.mle.μ, result4.mle.μ)
 
                             @testset "mdf_amr" begin
-                                # @test SFH.mdf_amr(SFRs, logAge, MH, relweights; relweightsmin=0)[1] == unique_MH
-                                # println(SFH.mdf_amr(SFRs, logAge, MH, relweights; relweightsmin=0)[2])
                                 mdf_result1 = SFH.mdf_amr([1.0,2.0,3.0,4.0],[1.0,2.0,1.0,2.0],[-2.0,-2.0,-1.0,-1.0])
                                 @test mdf_result1[1] ≈ [-2.0, -1.0]
                                 @test mdf_result1[2] ≈ [0.3, 0.7]
+                                # Test mdf_x is always returned in sorted order
+                                mdf_result2 = SFH.mdf_amr(reverse([1.0,2.0,3.0,4.0]),[1.0,2.0,1.0,2.0],reverse([-2.0,-2.0,-1.0,-1.0]))
+                                @test all(mdf_result1 .== mdf_result2)
                             end
                         end
                     end