Improve quantile in corner cases of collection eltype (#30938)

NEWS.md

@@ -70,6 +70,10 @@ Standard library changes
 
 * Fixed `repr` such that it displays `DateTime` as it would be entered in Julia ([#30200]).
 
+#### Statistics
+
+* `quantile` now accepts in all cases collections whose `eltype` is not a subtype of `Number` ([#30938]).
+
 #### Miscellaneous
 
 * Since environment variables on Windows are case-insensitive, `ENV` now converts its keys

stdlib/Statistics/src/Statistics.jl

@@ -853,19 +853,18 @@ function quantile!(q::AbstractArray, v::AbstractVector, p::AbstractArray;
  return q
 end
 
-quantile!(v::AbstractVector, p::AbstractArray; sorted::Bool=false) =
- quantile!(similar(p,float(eltype(v))), v, p; sorted=sorted)
+function quantile!(v::AbstractVector, p::Union{AbstractArray, Tuple{Vararg{Real}}};
+ sorted::Bool=false)
+ if !isempty(p)
+ minp, maxp = extrema(p)
+ _quantilesort!(v, sorted, minp, maxp)
+ end
+ return map(x->_quantile(v, x), p)
+end
 
 quantile!(v::AbstractVector, p::Real; sorted::Bool=false) =
  _quantile(_quantilesort!(v, sorted, p, p), p)
 
-function quantile!(v::AbstractVector, p::Tuple{Vararg{Real}}; sorted::Bool=false)
- isempty(p) && return ()
- minp, maxp = extrema(p)
- _quantilesort!(v, sorted, minp, maxp)
- return map(x->_quantile(v, x), p)
-end
-
 # Function to perform partial sort of v for quantiles in given range
 function _quantilesort!(v::AbstractArray, sorted::Bool, minp::Real, maxp::Real)
  isempty(v) && throw(ArgumentError("empty data vector"))
@@ -895,18 +894,12 @@ end
  h = f0 - t0
  i = trunc(Int,t0) + 1
 
- T = promote_type(eltype(v), typeof(v[1]*h))
-
- if h == 0
- return convert(T, v[i])
+ a = v[i]
+ b = v[i + (h > 0)]
+ if isfinite(a) && isfinite(b)
+ return a + h*(b-a)
  else
- a = v[i]
- b = v[i+1]
- if isfinite(a) && isfinite(b)
- return convert(T, a + h*(b-a))
- else
- return convert(T, (1-h)*a + h*b)
- end
+ return (1-h)*a + h*b
  end
 end
 

stdlib/Statistics/test/runtests.jl

@@ -474,12 +474,45 @@ end
  @test quantile([0,1],1e-18) == 1e-18
  @test quantile([1, 2, 3, 4],[]) == []
  @test quantile([1, 2, 3, 4], (0.5,)) == (2.5,)
- @test quantile([4, 9, 1, 5, 7, 8, 2, 3, 5, 17, 11], (0.1, 0.2, 0.4, 0.9)) == (2.0, 3.0, 5.0, 11.0)
+ @test quantile([4, 9, 1, 5, 7, 8, 2, 3, 5, 17, 11],
+ (0.1, 0.2, 0.4, 0.9)) == (2.0, 3.0, 5.0, 11.0)
+ @test quantile(Union{Int, Missing}[4, 9, 1, 5, 7, 8, 2, 3, 5, 17, 11],
+ [0.1, 0.2, 0.4, 0.9]) == [2.0, 3.0, 5.0, 11.0]
+ @test quantile(Any[4, 9, 1, 5, 7, 8, 2, 3, 5, 17, 11],
+ [0.1, 0.2, 0.4, 0.9]) == [2.0, 3.0, 5.0, 11.0]
+ @test quantile([4, 9, 1, 5, 7, 8, 2, 3, 5, 17, 11],
+ Any[0.1, 0.2, 0.4, 0.9]) == [2.0, 3.0, 5.0, 11.0]
+ @test quantile([4, 9, 1, 5, 7, 8, 2, 3, 5, 17, 11],
+ Any[0.1, 0.2, 0.4, 0.9]) isa Vector{Float64}
+ @test quantile(Any[4, 9, 1, 5, 7, 8, 2, 3, 5, 17, 11],
+ Any[0.1, 0.2, 0.4, 0.9]) == [2, 3, 5, 11]
+ @test quantile(Any[4, 9, 1, 5, 7, 8, 2, 3, 5, 17, 11],
+ Any[0.1, 0.2, 0.4, 0.9]) isa Vector{Float64}
  @test quantile([1, 2, 3, 4], ()) == ()
+ @test isempty(quantile([1, 2, 3, 4], Float64[]))
+ @test quantile([1, 2, 3, 4], Float64[]) isa Vector{Float64}
+ @test quantile([1, 2, 3, 4], []) isa Vector{Any}
+ @test quantile([1, 2, 3, 4], [0, 1]) isa Vector{Int}
+
+ @test quantile(Any[1, 2, 3], 0.5) isa Float64
+ @test quantile(Any[1, big(2), 3], 0.5) isa BigFloat
+ @test quantile(Any[1, 2, 3], Float16(0.5)) isa Float16
+ @test quantile(Any[1, Float16(2), 3], Float16(0.5)) isa Float16
+ @test quantile(Any[1, big(2), 3], Float16(0.5)) isa BigFloat
 
  @test_throws ArgumentError quantile([1, missing], 0.5)
  @test_throws ArgumentError quantile([1, NaN], 0.5)
  @test quantile(skipmissing([1, missing, 2]), 0.5) === 1.5
+
+ # make sure that type inference works correctly in normal cases
+ for T in [Int, BigInt, Float64, Float16, BigFloat, Rational{Int}, Rational{BigInt}]
+ for S in [Float64, Float16, BigFloat, Rational{Int}, Rational{BigInt}]
+ @inferred quantile(T[1, 2, 3], S(0.5))
+ @inferred quantile(T[1, 2, 3], S(0.6))
+ @inferred quantile(T[1, 2, 3], S[0.5, 0.6])
+ @inferred quantile(T[1, 2, 3], (S(0.5), S(0.6)))
+ end
+ end
 end
 
 # StatsBase issue 164