Add :percentage normalization mode for hist

JuliaStats · Oct 18, 2024 · 63375a0 · 63375a0
1 parent 74ef7f0
commit 63375a0
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Showing 2 changed files with 10 additions and 5 deletions.
diff --git a/src/hist.jl b/src/hist.jl
@@ -475,11 +475,12 @@ arrays appropriately. See description of `normalize` for details. Returns `h`.
 
         if mode == :none
             # nothing to do
-        elseif mode == :pdf || mode == :density || mode == :probability
+        elseif mode == :pdf || mode == :density || mode == :probability || mode == :percentage
             if h.isdensity
-                if mode == :pdf || mode == :probability
+                if mode == :pdf || mode == :probability || mode == :percentage
                     # histogram already represents a density, just divide weights by norm
-                    s = 1/norm(h)
+                    multiplier = mode == :percentage ? 100.0 : 1.0
+                    s = 1 / norm(h) * multiplier
                     weights .*= s
                     for A in aux_weights
                         A .*= s
@@ -502,7 +503,8 @@ arrays appropriately. See description of `normalize` for details. Returns `h`.
                 else
                     # :probability - divide weights by sum of weights
                     nf = inv(sum(weights))
-                    weights .*= nf
+                    multiplier = mode == :percentage ? 100.0 : 1.0
+                    weights .*= nf * multiplier
                     for A in aux_weights
                         A .*= nf
                     end
@@ -531,7 +533,8 @@ Valid values for `mode` are:
 * `:probability`: Normalize by sum of weights only. Resulting histogram
    represents the fraction of probability mass for each bin and does not have
    norm 1.
-*  `:none`: Leaves histogram unchanged. Useful to simplify code that has to
+* `:percentage`: Normalize as a percentage of the sum of weights. 
+* `:none`: Leaves histogram unchanged. Useful to simplify code that has to
    conditionally apply different modes of normalization.
 
 Successive application of both `:probability` and `:density` normalization (in

diff --git a/test/hist.jl b/test/hist.jl
@@ -173,13 +173,15 @@ end
     @test normalize(h_density, mode = :pdf).weights ≈ h_pdf.weights
     @test normalize(h_density, mode = :density) == h_density
     @test normalize(h_density, mode = :probability).weights ≈ h_pdf.weights
+    @test normalize(h_density, mode = :percentage).weights ≈ h_pdf.weights * 100
 
     h_fraction = normalize(h, mode = :probability)
     @test sum(h_fraction.weights) ≈ 1
     @test h_fraction.isdensity == false
     @test normalize(h_fraction, mode = :pdf).weights ≈ h_pdf.weights
     @test normalize(h_fraction, mode = :density).weights ≈ h_pdf.weights
     @test normalize(h_fraction, mode = :probability).weights ≈ h_fraction.weights
+    @test normalize(h_fraction, mode = :percentage).weights ≈ h_fraction.weights * 100
 
     h_copy = deepcopy(float(h))
     @test @inferred(normalize!(h_copy, mode = :density)) == h_copy