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Improve performance of unweighted ecdf #965

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2 changes: 1 addition & 1 deletion Project.toml
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Original file line number Diff line number Diff line change
@@ -1,7 +1,7 @@
name = "StatsBase"
uuid = "2913bbd2-ae8a-5f71-8c99-4fb6c76f3a91"
authors = ["JuliaStats"]
version = "0.34.6"
version = "0.34.7"

[deps]
AliasTables = "66dad0bd-aa9a-41b7-9441-69ab47430ed8"
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17 changes: 11 additions & 6 deletions src/empirical.jl
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Expand Up @@ -42,7 +42,7 @@ function (ecdf::ECDF)(v::AbstractVector{<:Real})
end

"""
ecdf(X; weights::AbstractWeights)
ecdf(X[; weights::AbstractVector{<:Real}])

Return an empirical cumulative distribution function (ECDF) based on a vector of samples
given in `X`. Optionally providing `weights` returns a weighted ECDF.
Expand All @@ -53,12 +53,17 @@ evaluate CDF values on other samples.
`extrema`, `minimum`, and `maximum` are supported to for obtaining the range over which
function is inside the interval ``(0,1)``; the function is defined for the whole real line.
"""
function ecdf(X::AbstractVector{<:Real}; weights::AbstractVector{<:Real}=Weights(Float64[]))
function ecdf(X::AbstractVector{<:Real}; weights::AbstractVector{<:Real}=weights(Float64[]))
any(isnan, X) && throw(ArgumentError("ecdf can not include NaN values"))
isempty(weights) || length(X) == length(weights) || throw(ArgumentError("data and weight vectors must be the same size," *
"got $(length(X)) and $(length(weights))"))
ord = sortperm(X)
ECDF(X[ord], isempty(weights) ? weights : Weights(weights[ord]))
_weights = weights isa AbstractWeights ? weights : StatsBase.weights(weights)
if isempty(_weights)
return ECDF(sort(X), _weights)
else
length(X) == length(_weights) || throw(ArgumentError("data and weight vectors must be the same size," *
"got $(length(X)) and $(length(_weights))"))
ord = sortperm(X)
ECDF(X[ord], _weights[ord])
end
end

minimum(ecdf::ECDF) = first(ecdf.sorted_values)
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