mirror of
https://github.com/VictoriaMetrics/VictoriaMetrics.git
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87 lines
2.0 KiB
Go
87 lines
2.0 KiB
Go
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package smetrics
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import (
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"math"
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)
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// The Jaro distance. The result is 1 for equal strings, and 0 for completely different strings.
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func Jaro(a, b string) float64 {
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// If both strings are zero-length, they are completely equal,
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// therefore return 1.
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if len(a) == 0 && len(b) == 0 {
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return 1
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}
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// If one string is zero-length, strings are completely different,
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// therefore return 0.
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if len(a) == 0 || len(b) == 0 {
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return 0
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}
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// Define the necessary variables for the algorithm.
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la := float64(len(a))
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lb := float64(len(b))
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matchRange := int(math.Max(0, math.Floor(math.Max(la, lb)/2.0)-1))
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matchesA := make([]bool, len(a))
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matchesB := make([]bool, len(b))
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var matches float64 = 0
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// Step 1: Matches
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// Loop through each character of the first string,
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// looking for a matching character in the second string.
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for i := 0; i < len(a); i++ {
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start := int(math.Max(0, float64(i-matchRange)))
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end := int(math.Min(lb-1, float64(i+matchRange)))
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for j := start; j <= end; j++ {
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if matchesB[j] {
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continue
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}
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if a[i] == b[j] {
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matchesA[i] = true
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matchesB[j] = true
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matches++
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break
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}
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}
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}
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// If there are no matches, strings are completely different,
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// therefore return 0.
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if matches == 0 {
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return 0
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}
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// Step 2: Transpositions
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// Loop through the matches' arrays, looking for
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// unaligned matches. Count the number of unaligned matches.
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unaligned := 0
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j := 0
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for i := 0; i < len(a); i++ {
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if !matchesA[i] {
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continue
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}
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for !matchesB[j] {
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j++
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}
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if a[i] != b[j] {
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unaligned++
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}
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j++
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}
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// The number of unaligned matches divided by two, is the number of _transpositions_.
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transpositions := math.Floor(float64(unaligned / 2))
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// Jaro distance is the average between these three numbers:
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// 1. matches / length of string A
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// 2. matches / length of string B
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// 3. (matches - transpositions/matches)
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// So, all that divided by three is the final result.
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return ((matches / la) + (matches / lb) + ((matches - transpositions) / matches)) / 3.0
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}
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