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.Stable(byScore(scoredLangs)) 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 } type byScore []*scoredLanguage func (b byScore) Len() int { return len(b) } func (b byScore) Swap(i, j int) { b[i], b[j] = b[j], b[i] } func (b byScore) Less(i, j int) bool { return b[j].score < b[i].score }