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Fix up spacing in docstrings
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3 files changed

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-8
lines changed

3 files changed

+8
-8
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src/cov.jl

Lines changed: 4 additions & 5 deletions
Original file line numberDiff line numberDiff line change
@@ -188,7 +188,8 @@ cov(ce::CovarianceEstimator, x::AbstractVector, y::AbstractVector) =
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error("cov is not defined for $(typeof(ce)), $(typeof(x)) and $(typeof(y))")
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"""
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cov(ce::CovarianceEstimator, X::AbstractMatrix, [w::AbstractWeights]; mean=nothing, dims::Int=1)
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cov(ce::CovarianceEstimator, X::AbstractMatrix, [w::AbstractWeights];
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mean=nothing, dims::Int=1)
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Compute the covariance matrix of the matrix `X` along dimension `dims`
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using estimator `ce`. A weighting vector `w` can be specified.
@@ -238,10 +239,8 @@ function cor(ce::CovarianceEstimator, x::AbstractVector, y::AbstractVector)
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end
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"""
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cor(
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ce::CovarianceEstimator, X::AbstractMatrix, [w::AbstractWeights];
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mean=nothing, dims::Int=1
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)
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cor(ce::CovarianceEstimator, X::AbstractMatrix, [w::AbstractWeights];
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mean=nothing, dims::Int=1)
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Compute the correlation matrix of the matrix `X` along dimension `dims`
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using estimator `ce`. A weighting vector `w` can be specified.

src/hist.jl

Lines changed: 2 additions & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -459,7 +459,8 @@ float(h::Histogram{T,N}) where {T,N} = Histogram(h.edges, float(h.weights), h.cl
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"""
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normalize!(h::Histogram{T,N}, aux_weights::Array{T,N}...; mode::Symbol=:pdf) where {T<:AbstractFloat,N}
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normalize!(h::Histogram{T,N}, aux_weights::Array{T,N}...;
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mode::Symbol=:pdf) where {T<:AbstractFloat,N}
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Normalize the histogram `h` and optionally scale one or more auxiliary weight
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arrays appropriately. See description of `normalize` for details. Returns `h`.

src/transformations.jl

Lines changed: 2 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -341,8 +341,8 @@ end
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"""
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standardize(DT, X; dims=nothing, kwargs...)
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Return a standardized copy of vector or matrix `X` along dimensions `dims`
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using transformation `DT` which is a subtype of `AbstractDataTransform`:
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Return a standardized copy of vector or matrix `X` along dimensions `dims`
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using transformation `DT` which is a subtype of `AbstractDataTransform`:
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- `ZScoreTransform`
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- `UnitRangeTransform`

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