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improve comments
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@@ -16,26 +16,28 @@ func CovarianceMatrix(x mat64.Matrix) *mat64.Dense {
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// the correction found in the Covariance and Variance functions.
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// the correction found in the Covariance and Variance functions.
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r, _ := x.Dims()
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r, _ := x.Dims()
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// determine the mean of each of the columns
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b := ones(1, r)
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b := ones(1, r)
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b.Mul(b, x)
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b.Mul(b, x)
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b.Scale(1/float64(r), b)
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b.Scale(1/float64(r), b)
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// todo: avoid unneeded memory expansion here.
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mu := b.RowView(0)
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mu := b.RowView(0)
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// this could also be done with a clone & row viewer
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// subtract the mean from the data
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xc := mat64.DenseCopyOf(x)
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xc := mat64.DenseCopyOf(x)
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for i := 0; i < r; i++ {
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for i := 0; i < r; i++ {
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rv := xc.RowView(i)
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rv := xc.RowView(i)
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for j, mean := range(mu) {
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for j, mean := range mu {
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rv[j] -= mean
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rv[j] -= mean
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}
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}
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}
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}
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// todo: avoid matrix copy
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// todo: avoid matrix copy?
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xt := new(mat64.Dense)
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xt := new(mat64.Dense)
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xt.TCopy(xc)
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xt.TCopy(xc)
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// It would be nice if we could indicate that this was a symmetric
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// matrix.
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ss := new(mat64.Dense)
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ss := new(mat64.Dense)
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ss.Mul(xt, xc)
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ss.Mul(xt, xc)
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ss.Scale(1/float64(r-1), ss)
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ss.Scale(1/float64(r-1), ss)
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