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Fix NaN and missing detection in quantile() #72

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Merged
merged 1 commit into from
Mar 24, 2021
Merged

Fix NaN and missing detection in quantile() #72

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6 changes: 4 additions & 2 deletions src/Statistics.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -960,8 +960,10 @@ function _quantilesort!(v::AbstractArray, sorted::Bool, minp::Real, maxp::Real)
# only need to perform partial sort
sort!(v, 1, lv, Base.Sort.PartialQuickSort(lo:hi), Base.Sort.Forward)
end
ismissing(v[end]) && throw(ArgumentError("quantiles are undefined in presence of missing values"))
isnan(v[end]) && throw(ArgumentError("quantiles are undefined in presence of NaNs"))
if (sorted && (ismissing(v[end]) || (v[end] isa Number && isnan(v[end])))) ||
any(x -> ismissing(x) || (x isa Number && isnan(x)), v)
throw(ArgumentError("quantiles are undefined in presence of NaNs or missing values"))
end
return v
end

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11 changes: 9 additions & 2 deletions test/runtests.jl
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Expand Up @@ -557,8 +557,15 @@ end
@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)
# Need a large vector to actually check consequences of partial sorting
x = rand(50)
for sorted in (false, true)
x[10] = NaN
@test_throws ArgumentError quantile(x, 0.5, sorted=sorted)
x = Vector{Union{Float64, Missing}}(x)
x[10] = missing
@test_throws ArgumentError quantile(x, 0.5, sorted=sorted)
end
@test quantile(skipmissing([1, missing, 2]), 0.5) === 1.5
@test quantile([1], 0.5) === 1.0

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