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change mat64.Vec to []float64
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@@ -18,7 +18,7 @@ import (
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// data matrix x. cov should be a square matrix with the same number of
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// columns as the input data matrix x, or if it is nil then a new Dense
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// matrix will be constructed.
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func CovarianceMatrix(cov *mat64.Dense, x mat64.Matrix, wts mat64.Vec) *mat64.Dense {
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func CovarianceMatrix(cov *mat64.Dense, x mat64.Matrix, wts []float64) *mat64.Dense {
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// matrix version of the two pass algorithm. This doesn't use
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// the correction found in the Covariance and Variance functions.
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@@ -50,7 +50,7 @@ func CovarianceMatrix(cov *mat64.Dense, x mat64.Matrix, wts mat64.Vec) *mat64.De
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// normalization factor, typical n-1
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var N float64
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if wts != nil {
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if wr, _ := wts.Dims(); wr != r {
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if wr := len(wts); wr != r {
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panic("weight vector length mismatch")
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}
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