gitea/vendor/github.com/blevesearch/bleve/analysis/freq.go

//  Copyright (c) 2014 Couchbase, Inc.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// 		http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.

package analysis

// TokenLocation represents one occurrence of a term at a particular location in
// a field. Start, End and Position have the same meaning as in analysis.Token.
// Field and ArrayPositions identify the field value in the source document.
// See document.Field for details.
type TokenLocation struct {
	Field          string
	ArrayPositions []uint64
	Start          int
	End            int
	Position       int
}

// TokenFreq represents all the occurrences of a term in all fields of a
// document.
type TokenFreq struct {
	Term      []byte
	Locations []*TokenLocation
	frequency int
}

func (tf *TokenFreq) Frequency() int {
	return tf.frequency
}

// TokenFrequencies maps document terms to their combined frequencies from all
// fields.
type TokenFrequencies map[string]*TokenFreq

func (tfs TokenFrequencies) MergeAll(remoteField string, other TokenFrequencies) {
	// walk the new token frequencies
	for tfk, tf := range other {
		// set the remoteField value in incoming token freqs
		for _, l := range tf.Locations {
			l.Field = remoteField
		}
		existingTf, exists := tfs[tfk]
		if exists {
			existingTf.Locations = append(existingTf.Locations, tf.Locations...)
			existingTf.frequency = existingTf.frequency + tf.frequency
		} else {
			tfs[tfk] = &TokenFreq{
				Term:      tf.Term,
				frequency: tf.frequency,
				Locations: make([]*TokenLocation, len(tf.Locations)),
			}
			copy(tfs[tfk].Locations, tf.Locations)
		}
	}
}

func TokenFrequency(tokens TokenStream, arrayPositions []uint64, includeTermVectors bool) TokenFrequencies {
	rv := make(map[string]*TokenFreq, len(tokens))

	if includeTermVectors {
		tls := make([]TokenLocation, len(tokens))
		tlNext := 0

		for _, token := range tokens {
			tls[tlNext] = TokenLocation{
				ArrayPositions: arrayPositions,
				Start:          token.Start,
				End:            token.End,
				Position:       token.Position,
			}

			curr, ok := rv[string(token.Term)]
			if ok {
				curr.Locations = append(curr.Locations, &tls[tlNext])
				curr.frequency++
			} else {
				rv[string(token.Term)] = &TokenFreq{
					Term:      token.Term,
					Locations: []*TokenLocation{&tls[tlNext]},
					frequency: 1,
				}
			}

			tlNext++
		}
	} else {
		for _, token := range tokens {
			curr, exists := rv[string(token.Term)]
			if exists {
				curr.frequency++
			} else {
				rv[string(token.Term)] = &TokenFreq{
					Term:      token.Term,
					frequency: 1,
				}
			}
		}
	}

	return rv
}