From ba243188611a78a6a3f5a25c8a2574aca0fc4674 Mon Sep 17 00:00:00 2001
From: Milan Bouchet-Valat <nalimilan@club.fr>
Date: Wed, 24 Mar 2021 20:54:46 +0100
Subject: [PATCH] Fix detection of NaN in median() (#73)

There is no reliable way to know only from the array eltype whether entries
support `isnan` or not. Better leave to the compiler to optimize out the
`isa Number` check when possible.
---
 src/Statistics.jl | 2 +-
 test/runtests.jl  | 9 +++++++++
 2 files changed, 10 insertions(+), 1 deletion(-)

diff --git a/src/Statistics.jl b/src/Statistics.jl
index ac2d2426..29aae101 100644
--- a/src/Statistics.jl
+++ b/src/Statistics.jl
@@ -805,7 +805,7 @@ Like [`median`](@ref), but may overwrite the input vector.
 function median!(v::AbstractVector)
     isempty(v) && throw(ArgumentError("median of an empty array is undefined, $(repr(v))"))
     eltype(v)>:Missing && any(ismissing, v) && return missing
-    (eltype(v)<:AbstractFloat || eltype(v)>:AbstractFloat) && any(isnan, v) && return convert(eltype(v), NaN)
+    any(x -> x isa Number && isnan(x), v) && return convert(eltype(v), NaN)
     inds = axes(v, 1)
     n = length(inds)
     mid = div(first(inds)+last(inds),2)
diff --git a/test/runtests.jl b/test/runtests.jl
index e0377b46..00cdad10 100644
--- a/test/runtests.jl
+++ b/test/runtests.jl
@@ -67,6 +67,15 @@ end
     @test @inferred(median(Float16[1, 2, 3]))   === Float16(2)
     @test @inferred(median(Float32[1, 2, NaN])) === NaN32
     @test @inferred(median(Float32[1, 2, 3]))   === 2.0f0
+
+    # custom type implementing minimal interface
+    struct A
+        x
+    end
+    Statistics.middle(x::A, y::A) = A(middle(x.x, y.x))
+    Base.isless(x::A, y::A) = isless(x.x, y.x)
+    @test median([A(1), A(2)]) === A(1.5)
+    @test median(Any[A(1), A(2)]) === A(1.5)
 end
 
 @testset "mean" begin