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https://github.com/photoprism/photoprism.git
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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.
32 lines
964 B
Go
32 lines
964 B
Go
package vector
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import (
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"testing"
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"github.com/stretchr/testify/assert"
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)
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func TestVector_EuclideanNorm(t *testing.T) {
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a := Vector{1, 2, 3, 4, 6, 5}
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b := Vector{2, 1, 3, 4, 5, 6}
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d := Vector{0, 0, 0, 0, 0, 0}
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e := Vector{}
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assert.InDelta(t, 9.539392014169456, a.EuclideanNorm(), 0.01)
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assert.InDelta(t, 9.539392014169456, b.EuclideanNorm(), 0.01)
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assert.Equal(t, a.EuclideanNorm(), b.EuclideanNorm())
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assert.InDelta(t, 0.9999999779072661, faceEmbeddingB.EuclideanNorm(), 0.01)
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assert.InDelta(t, 0, d.EuclideanNorm(), 0.01)
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assert.InDelta(t, 0, e.EuclideanNorm(), 0.01)
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assert.Equal(t, d.EuclideanNorm(), e.EuclideanNorm())
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}
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func TestNorm(t *testing.T) {
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t.Run("Euclidean", func(t *testing.T) {
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assert.InDelta(t, 5.0, Norm(Vector{3, -4}, 2.0), 0.00001)
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})
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t.Run("Manhattan", func(t *testing.T) {
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// L1 norm uses absolute values, so negatives contribute their magnitude.
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assert.InDelta(t, 5.0, Norm(Vector{1, -2, 2}, 1.0), 0.00001)
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})
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}
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