dc9e069ff2
Changed `matcher.Matches(file)` to `matcher.MatchesOrParentMatches(file)`:
cli/command/image/build/context.go:95:9: SA1019: matcher.Matches is deprecated: This implementation is buggy (it only checks a single parent dir against the pattern) and will be removed soon. Use either MatchesOrParentMatches or MatchesUsingParentResults instead. (staticcheck)
return matcher.Matches(file)
^
And updated a test to match the JSON omitting empty RootFS.Type fields (in
practice, this field should never be empty in real situations, and always
be "layer"). Changed the test to use subtests to easier find which case
is failing.
full diff: 343665850e...83b51522df
Signed-off-by: Sebastiaan van Stijn <github@gone.nl>
86 lines
1.8 KiB
Go
86 lines
1.8 KiB
Go
package compress
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import "math"
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// Estimate returns a normalized compressibility estimate of block b.
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// Values close to zero are likely uncompressible.
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// Values above 0.1 are likely to be compressible.
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// Values above 0.5 are very compressible.
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// Very small lengths will return 0.
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func Estimate(b []byte) float64 {
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if len(b) < 16 {
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return 0
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}
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// Correctly predicted order 1
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hits := 0
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lastMatch := false
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var o1 [256]byte
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var hist [256]int
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c1 := byte(0)
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for _, c := range b {
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if c == o1[c1] {
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// We only count a hit if there was two correct predictions in a row.
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if lastMatch {
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hits++
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}
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lastMatch = true
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} else {
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lastMatch = false
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}
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o1[c1] = c
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c1 = c
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hist[c]++
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}
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// Use x^0.6 to give better spread
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prediction := math.Pow(float64(hits)/float64(len(b)), 0.6)
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// Calculate histogram distribution
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variance := float64(0)
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avg := float64(len(b)) / 256
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for _, v := range hist {
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Δ := float64(v) - avg
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variance += Δ * Δ
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}
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stddev := math.Sqrt(float64(variance)) / float64(len(b))
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exp := math.Sqrt(1 / float64(len(b)))
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// Subtract expected stddev
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stddev -= exp
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if stddev < 0 {
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stddev = 0
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}
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stddev *= 1 + exp
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// Use x^0.4 to give better spread
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entropy := math.Pow(stddev, 0.4)
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// 50/50 weight between prediction and histogram distribution
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return math.Pow((prediction+entropy)/2, 0.9)
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}
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// ShannonEntropyBits returns the number of bits minimum required to represent
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// an entropy encoding of the input bytes.
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// https://en.wiktionary.org/wiki/Shannon_entropy
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func ShannonEntropyBits(b []byte) int {
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if len(b) == 0 {
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return 0
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}
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var hist [256]int
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for _, c := range b {
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hist[c]++
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}
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shannon := float64(0)
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invTotal := 1.0 / float64(len(b))
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for _, v := range hist[:] {
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if v > 0 {
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n := float64(v)
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shannon += math.Ceil(-math.Log2(n*invTotal) * n)
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}
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}
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return int(math.Ceil(shannon))
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}
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