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03129c9129
Split the catch-all values.go into one file per concept, each mirrored by its test: distance.go, norm.go, stats.go, product.go, centroid.go, plus the mean methods folded into mean.go and Copy/Dim/Sum into vector.go. Remove values.go, values_test.go, and values_more_test.go so functionality and tests live where developers expect them. Hoist the two 512-dimensional face embeddings shared by the distance, norm, and cosine tests into fixtures_test.go, removing the previous triplication, and decompose the monolithic TestVector into per-concept tests. Close pre-existing coverage gaps in the integer converters and the GeometricMean/HarmonicMean method wrappers, bringing the package to 100% statement coverage. Pure code movement; no behavior change.
53 lines
971 B
Go
53 lines
971 B
Go
package vector
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import "math"
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// Sd calculates the vector's standard deviation.
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func (v Vector) Sd() float64 {
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return math.Sqrt(v.Variance())
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}
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// Variance calculates the vector's variance.
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func (v Vector) Variance() float64 {
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return v.variance(v.Mean())
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}
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// variance returns the sample variance around the given mean.
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// Empty and single-element vectors have zero variance by convention,
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// which also avoids a division by zero in the n-1 denominator.
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func (v Vector) variance(mean float64) float64 {
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n := float64(len(v))
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if n < 2 {
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return 0
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}
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ss := 0.0
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for _, f := range v {
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d := f - mean
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ss += d * d
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}
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return ss / (n - 1)
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}
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// Cor returns the Pearson correlation between two vectors.
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func Cor(a, b Vector) (float64, error) {
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n := float64(len(a))
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xy, err := Product(a, b)
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if err != nil {
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return NaN(), err
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}
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sx := a.Sd()
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sy := b.Sd()
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mx := a.Mean()
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my := b.Mean()
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r := (xy.Sum() - n*mx*my) / ((n - 1) * sx * sy)
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return r, nil
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}
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