60 lines
1.4 KiB
Go
60 lines
1.4 KiB
Go
package types
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import (
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"fmt"
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"gonum.org/v1/gonum/mat"
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)
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type PCA struct {
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svd *mat.SVD
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}
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func (pca *PCA) FitTransform(x []SeriesExtend, lookback, feature int) ([]SeriesExtend, error) {
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if err := pca.Fit(x, lookback); err != nil {
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return nil, err
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}
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return pca.Transform(x, lookback, feature), nil
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}
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func (pca *PCA) Fit(x []SeriesExtend, lookback int) error {
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vec := make([]float64, lookback*len(x))
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for i, xx := range x {
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mean := xx.Mean(lookback)
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for j := 0; j < lookback; j++ {
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vec[i+j*i] = xx.Last(j) - mean
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}
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}
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pca.svd = &mat.SVD{}
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diffMatrix := mat.NewDense(lookback, len(x), vec)
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if ok := pca.svd.Factorize(diffMatrix, mat.SVDThin); !ok {
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return fmt.Errorf("Unable to factorize")
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}
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return nil
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}
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func (pca *PCA) Transform(x []SeriesExtend, lookback int, features int) (result []SeriesExtend) {
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result = make([]SeriesExtend, features)
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vTemp := new(mat.Dense)
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pca.svd.VTo(vTemp)
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var ret mat.Dense
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vec := make([]float64, lookback*len(x))
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for i, xx := range x {
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for j := 0; j < lookback; j++ {
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vec[i+j*i] = xx.Last(j)
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}
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}
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newX := mat.NewDense(lookback, len(x), vec)
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ret.Mul(newX, vTemp)
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newMatrix := mat.NewDense(lookback, features, nil)
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newMatrix.Copy(&ret)
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for i := 0; i < features; i++ {
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queue := NewQueue(lookback)
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for j := 0; j < lookback; j++ {
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queue.Update(newMatrix.At(lookback-j-1, i))
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}
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result[i] = queue
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}
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return result
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}
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