go-enry/classifier.go
2017-06-15 13:02:59 +02:00

97 lines
2.5 KiB
Go

package enry
import (
"math"
"sort"
"gopkg.in/src-d/enry.v1/internal/tokenizer"
)
// Classifier is the interface in charge to detect the possible languages of the given content based on a set of
// candidates. Candidates is a map which can be used to assign weights to languages dynamically.
type Classifier interface {
Classify(content []byte, candidates map[string]float64) (languages []string)
}
type classifier struct {
languagesLogProbabilities map[string]float64
tokensLogProbabilities map[string]map[string]float64
tokensTotal float64
}
type scoredLanguage struct {
language string
score float64
}
// Classify returns a sorted slice of possible languages sorted by decreasing language's probability
func (c *classifier) Classify(content []byte, candidates map[string]float64) []string {
if len(content) == 0 {
return nil
}
var languages map[string]float64
if len(candidates) == 0 {
languages = c.knownLangs()
} else {
languages = make(map[string]float64, len(candidates))
for candidate, weight := range candidates {
if lang, ok := GetLanguageByAlias(candidate); ok {
candidate = lang
}
languages[candidate] = weight
}
}
tokens := tokenizer.Tokenize(content)
scoredLangs := make([]*scoredLanguage, 0, len(languages))
for language := range languages {
scoredLang := &scoredLanguage{
language: language,
score: c.tokensLogProbability(tokens, language) + c.languagesLogProbabilities[language],
}
scoredLangs = append(scoredLangs, scoredLang)
}
return sortLanguagesByScore(scoredLangs)
}
func sortLanguagesByScore(scoredLangs []*scoredLanguage) []string {
sort.SliceStable(scoredLangs, func(i, j int) bool { return scoredLangs[j].score < scoredLangs[i].score })
sortedLanguages := make([]string, 0, len(scoredLangs))
for _, scoredLang := range scoredLangs {
sortedLanguages = append(sortedLanguages, scoredLang.language)
}
return sortedLanguages
}
func (c *classifier) knownLangs() map[string]float64 {
langs := make(map[string]float64, len(c.languagesLogProbabilities))
for lang := range c.languagesLogProbabilities {
langs[lang]++
}
return langs
}
func (c *classifier) tokensLogProbability(tokens []string, language string) float64 {
var sum float64
for _, token := range tokens {
sum += c.tokenProbability(token, language)
}
return sum
}
func (c *classifier) tokenProbability(token, language string) float64 {
tokenProb, ok := c.tokensLogProbabilities[language][token]
if !ok {
tokenProb = math.Log(1.000000 / c.tokensTotal)
}
return tokenProb
}