Fix handling of -0.0 in histograms (#768)

`searchsortedfirst` and `searchsortedlast` use `isless` for comparisons
and therefore consider `-0.0` to be different from `0.0`. This means
that these two values do not end up in the same bin when an edge is 0.
This does not make much sense statistically, but even worse is that
when an extreme edge is 0, `-0.0` is not counted at all.

Fix this by replacing `-0.0` with `0.0` before the search.

src/hist.jl

@@ -191,6 +191,14 @@ mutable struct Histogram{T<:Real,N,E} <: AbstractHistogram{T,N,E}
         closed == :right || closed == :left || error("closed must :left or :right")
         isdensity && !(T <: AbstractFloat) && error("Density histogram must have float-type weights")
         _edges_nbins(edges) == size(weights) || error("Histogram edge vectors must be 1 longer than corresponding weight dimensions")
+        # We do not handle -0.0 in ranges correctly in `binindex` for performance
+        # Constructing ranges starting or ending with -0.0 is very hard,
+        # and ranges containing -0.0 elsewhere virtually impossible,
+        # but check this just in case as it is cheap
+        foreach(edges) do e
+            e isa AbstractRange && any(isequal(-0.0), e) &&
+                throw(ArgumentError("ranges containing -0.0 not allowed in edges"))
+        end
         new{T,N,E}(edges,weights,closed,isdensity)
     end
 end
@@ -226,11 +234,25 @@ binindex(h::AbstractHistogram{T,1}, x::Real) where {T} = binindex(h, (x,))[1]
 binindex(h::Histogram{T,N}, xs::NTuple{N,Real}) where {T,N} =
     map((edge, x) -> _edge_binindex(edge, h.closed, x), h.edges, xs)
 
+_normalize_zero(x::AbstractFloat) = isequal(x, -0.0) ? zero(x) : x
+_normalize_zero(x::Any) = x
+
+# Always treat -0.0 like 0.0
 @inline function _edge_binindex(edge::AbstractVector, closed::Symbol, x::Real)
-    if closed == :right
-        searchsortedfirst(edge, x) - 1
+    if closed === :right
+        return searchsortedfirst(edge, _normalize_zero(x), by=_normalize_zero) - 1
+    else
+        return searchsortedlast(edge, _normalize_zero(x), by=_normalize_zero)
+    end
+end
+# Passing by=_normalize_zero for ranges would have a large performance hit
+# as it would force using the AbstractVector fallback
+# This is not worth it given that it is very difficult to construct a range containing -0.0
+@inline function _edge_binindex(edge::AbstractRange, closed::Symbol, x::Real)
+    if closed === :right
+        return searchsortedfirst(edge, _normalize_zero(x)) - 1
     else
-        searchsortedlast(edge, x)
+        return searchsortedlast(edge, _normalize_zero(x))
     end
 end
 

test/hist.jl

@@ -224,4 +224,44 @@ end
     @test StatsBase.midpoints(range(0, stop = 1, length = 5)) == 0.125:0.25:0.875
 end
 
+@testset "histogram with -0.0" begin
+    @test fit(Histogram, [-0.0, 1.0]) == fit(Histogram, [0.0, 1.0])
+    @test fit(Histogram, [-0.0, 1.0], closed=:right) ==
+        fit(Histogram, [0.0, 1.0], closed=:right)
+    @test fit(Histogram, [-0.0, -1.0]) == fit(Histogram, [0.0, -1.0])
+    @test fit(Histogram, [-0.0, -1.0], closed=:right) ==
+        fit(Histogram, [0.0, -1.0], closed=:right)
+
+    @test fit(Histogram, [-0.0, 1.0], [-0.0, 0.5]) ==
+        fit(Histogram, [0.0, 1.0], [0.0, 0.5]) ==
+        fit(Histogram, [-0.0, 1.0], [0.0, 0.5]) ==
+        fit(Histogram, [0.0, 1.0], [-0.0, 0.5]) ==
+        fit(Histogram, [0.0, 1.0], 0.0:0.5:0.5) ==
+        fit(Histogram, [-0.0, 1.0], 0.0:0.5:0.5)
+    @test fit(Histogram, [-0.0, 1.0], [-0.5, -0.0]) ==
+        fit(Histogram, [0.0, 1.0], [-0.5, -0.0]) ==
+        fit(Histogram, [-0.0, 1.0], [-0.5, 0.0]) ==
+        fit(Histogram, [0.0, 1.0], [-0.5, 0.0]) ==
+        fit(Histogram, [-0.0, 1.0], -0.5:0.5:0.0) ==
+        fit(Histogram, [0.0, 1.0], -0.5:0.5:0.0)
+    @test fit(Histogram, [-0.0, 1.0], [-0.5, -0.0], closed=:right) ==
+        fit(Histogram, [0.0, 1.0], [-0.5, 0.0], closed=:right) ==
+        fit(Histogram, [0.0, 1.0], -0.5:0.5:0.0, closed=:right)
+    @test fit(Histogram, [-0.0, 1.0], [-0.0, 0.5], closed=:right) ==
+        fit(Histogram, [0.0, 1.0], [0.0, 0.5], closed=:right) ==
+        fit(Histogram, [0.0, 1.0], [-0.0, 0.5], closed=:right) ==
+        fit(Histogram, [-0.0, 1.0], [0.0, 0.5], closed=:right) ==
+        fit(Histogram, [0.0, 1.0], 0.0:0.5:0.5, closed=:right) ==
+        fit(Histogram, [-0.0, 1.0], 0.0:0.5:0.5, closed=:right)
+    @test fit(Histogram, [-0.0, 1.0], [-0.5, -0.0], closed=:right) ==
+        fit(Histogram, [0.0, 1.0], [-0.5, 0.0], closed=:right) ==
+        fit(Histogram, [0.0, 1.0], [-0.5, -0.0], closed=:right) ==
+        fit(Histogram, [-0.0, 1.0], [-0.5, 0.0], closed=:right) ==
+        fit(Histogram, [0.0, 1.0], -0.5:0.5:0.0, closed=:right) ==
+        fit(Histogram, [-0.0, 1.0], -0.5:0.5:0.0, closed=:right)
+
+    @test_throws ArgumentError fit(Histogram, [-0.5], LinRange(-1.0, -0.0, 3))
+    @test_throws ArgumentError fit(Histogram, [-0.5], UnitRange(-0.0, 1.0))
+end
+
 end # @testset "StatsBase.Histogram"