@@ -35,8 +35,8 @@ NaNMath.sum(A)
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##### Examples:
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```julia
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- using NaNMath as nm
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- nm .sum([1., 2., NaN]) # result: 3.0
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+ using NaNMath
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+ NaNMath .sum([1., 2., NaN]) # result: 3.0
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```
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"""
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function sum (x:: AbstractArray{T} ) where T<: AbstractFloat
@@ -72,8 +72,8 @@ NaNMath.maximum(A)
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##### Examples:
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```julia
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- using NaNMath as nm
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- nm .maximum([1., 2., NaN]) # result: 2.0
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+ using NaNMath
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+ NaNMath .maximum([1., 2., NaN]) # result: 2.0
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```
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"""
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function maximum (x:: AbstractArray{T} ) where T<: AbstractFloat
@@ -99,8 +99,8 @@ NaNMath.minimum(A)
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##### Examples:
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```julia
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- using NaNMath as nm
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- nm .minimum([1., 2., NaN]) # result: 1.0
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+ using NaNMath
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+ NaNMath .minimum([1., 2., NaN]) # result: 1.0
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```
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"""
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function minimum (x:: AbstractArray{T} ) where T<: AbstractFloat
@@ -126,8 +126,8 @@ NaNMath.extrema(A)
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##### Examples:
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```julia
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- using NaNMath as nm
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- nm .extrema([1., 2., NaN]) # result: 1.0, 2.0
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+ using NaNMath
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+ NaNMath .extrema([1., 2., NaN]) # result: 1.0, 2.0
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```
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"""
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function extrema (x:: AbstractArray{T} ) where T<: AbstractFloat
@@ -156,8 +156,8 @@ NaNMath.mean(A)
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##### Examples:
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```julia
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- using NaNMath as nm
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- nm .mean([1., 2., NaN]) # result: 1.5
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+ using NaNMath
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+ NaNMath .mean([1., 2., NaN]) # result: 1.5
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```
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"""
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function mean (x:: AbstractArray{T} ) where T<: AbstractFloat
@@ -201,8 +201,8 @@ NaNMath.var(A)
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##### Examples:
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```julia
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- using NaNMath as nm
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- nm .var([1., 2., NaN]) # result: 0.5
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+ using NaNMath
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+ NaNMath .var([1., 2., NaN]) # result: 0.5
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```
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"""
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function var (x:: Vector{T} ) where T<: AbstractFloat
@@ -235,8 +235,8 @@ NaNMath.std(A)
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##### Examples:
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```julia
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- using NaNMath as nm
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- nm .std([1., 2., NaN]) # result: 0.7071067811865476
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+ using NaNMath
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+ NaNMath .std([1., 2., NaN]) # result: 0.7071067811865476
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```
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"""
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function std (x:: Vector{T} ) where T<: AbstractFloat
@@ -313,3 +313,4 @@ for f in (:min, :max)
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end
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end
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+
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