Implement sum, mean, var and cov for VectorOfSimilarVectors

Author: oschulz

REQUIRE

@@ -1,2 +1,3 @@
 julia 0.7
+Requires
 UnsafeArrays

src/ArraysOfArrays.jl

@@ -4,11 +4,18 @@ __precompile__(true)
 
 module ArraysOfArrays
 
+using Statistics
+
+using Requires
 using UnsafeArrays
 
 include("util.jl")
 include("functions.jl")
 include("array_of_similar_arrays.jl")
 include("vector_of_arrays.jl")
 
+function __init__()
+    @require StatsBase = "2913bbd2-ae8a-5f71-8c99-4fb6c76f3a91" include("statsbase_support.jl")
+end
+
 end # module

src/array_of_similar_arrays.jl

@@ -295,3 +295,41 @@ Base.convert(R::Type{VectorOfSimilarVectors}, A::AbstractVector{<:AbstractVector
 
 
 @inline Base.IndexStyle(A::VectorOfSimilarVectors) = IndexLinear()
+
+
+"""
+    sum(X::VectorOfSimilarVectors)
+
+Compute the sum of the elements vectors of `X`. Equivalent to `sum` of
+`flatview(X)` along dimension 2.
+"""
+Main.sum(X::VectorOfSimilarVectors{<:Real}) = sum(flatview(X); dims = 2)
+
+
+"""
+    mean(X::VectorOfSimilarVectors)
+
+Compute the mean of the elements vectors of `X`. Equivalent to `mean` of
+`flatview(X)` along dimension 2.
+"""
+Statistics.mean(X::VectorOfSimilarVectors) = mean(flatview(X); dims = 2)
+
+
+"""
+    cov(X::VectorOfSimilarVectors; corrected::Bool = true)
+    cov(X::VectorOfSimilarVectors, w::AbstractVector; corrected::Bool = true)
+
+Compute the covariance matrix between the elements of the elements of `X`
+along `X`. Equivalent to `cov` of `flatview(X)` along dimension 2.
+"""
+Statistics.cov(X::VectorOfSimilarVectors; corrected::Bool = true) =
+    cov(flatview(X); dims = 2, corrected = corrected)
+
+
+"""
+    cor(X::VectorOfSimilarVectors)
+
+Compute the Pearson correlation matrix between the elements of the elements of
+ `X` along `X`. Equivalent to `cor` of `flatview(X)` along dimension 2.
+"""
+Statistics.cor(X::VectorOfSimilarVectors) = cor(flatview(X); dims = 2)

src/statsbase_support.jl

@@ -0,0 +1,40 @@
+# This file is a part of ArraysOfArrays.jl, licensed under the MIT License (MIT).
+
+
+"""
+    sum(X::VectorOfSimilarVectors, w::StatsBase.AbstractWeights)
+
+Compute the sum of the elements vectors of `X` with weights `w`. Equivalent
+to `sum` of `flatview(X)` along dimension 2.
+"""
+Main.sum(X::VectorOfSimilarVectors, w::StatsBase.AbstractWeights) = sum(flatview(X), w, 2)
+
+
+"""
+    mean(X::VectorOfSimilarVectors, w::StatsBase.AbstractWeights)
+
+Compute the mean of the elements vectors of `X` with weights `w`. Equivalent
+to `mean` of `flatview(X)` along dimension 2.
+"""
+Statistics.mean(X::VectorOfSimilarVectors, w::StatsBase.AbstractWeights) = mean(flatview(X), w, 2)
+
+
+"""
+    cov(X::VectorOfSimilarVectors, w::StatsBase.AbstractWeights; corrected::Bool = true)
+
+Compute the covariance matrix between the elements of the elements of `X`
+along `X` with weights `w`. Equivalent to `cov` of `flatview(X)` along
+dimension 2.
+"""
+Statistics.cov(X::VectorOfSimilarVectors, w::StatsBase.AbstractWeights; corrected::Bool = true) =
+    cov(flatview(X), w, 2; corrected = corrected)
+
+
+"""
+    cor(X::VectorOfSimilarVectors, w::StatsBase.AbstractWeights)
+
+Compute the Pearson correlation matrix between the elements of the elements of
+ `X` along `X` with weights `w`. Equivalent to `cor` of `flatview(X)` along
+ dimension 2.
+"""
+Statistics.cor(X::VectorOfSimilarVectors, w::StatsBase.AbstractWeights) = cor(flatview(X), w, 2)