func (s *ConjunctionQueryScorer) Score(constituents []*search.DocumentMatch) *search.DocumentMatch {
rv := search.DocumentMatch{
ID: constituents[0].ID,
}
var sum float64
var childrenExplanations []*search.Explanation
if s.explain {
childrenExplanations = make([]*search.Explanation, len(constituents))
}
locations := []search.FieldTermLocationMap{}
for i, docMatch := range constituents {
sum += docMatch.Score
if s.explain {
childrenExplanations[i] = docMatch.Expl
}
if docMatch.Locations != nil {
locations = append(locations, docMatch.Locations)
}
}
rv.Score = sum
if s.explain {
rv.Expl = &search.Explanation{Value: sum, Message: "sum of:", Children: childrenExplanations}
}
if len(locations) == 1 {
rv.Locations = locations[0]
} else if len(locations) > 1 {
rv.Locations = search.MergeLocations(locations)
}
return &rv
}
func (s *ConstantScorer) Score(id string) *search.DocumentMatch {
var scoreExplanation *search.Explanation
score := s.constant
if s.explain {
scoreExplanation = &search.Explanation{
Value: score,
Message: fmt.Sprintf("ConstantScore()"),
}
}
// if the query weight isn't 1, multiply
if s.queryWeight != 1.0 {
score = score * s.queryWeight
if s.explain {
childExplanations := make([]*search.Explanation, 2)
childExplanations[0] = s.queryWeightExplanation
childExplanations[1] = scoreExplanation
scoreExplanation = &search.Explanation{
Value: score,
Message: fmt.Sprintf("weight(^%f), product of:", s.boost),
Children: childExplanations,
}
}
}
rv := search.DocumentMatch{
ID: id,
Score: score,
}
if s.explain {
rv.Expl = scoreExplanation
}
return &rv
}
func (s *TermQueryScorer) Score(termMatch *index.TermFieldDoc) *search.DocumentMatch {
var scoreExplanation *search.Explanation
// need to compute score
var tf float64
if termMatch.Freq < MaxSqrtCache {
tf = SqrtCache[int(termMatch.Freq)]
} else {
tf = math.Sqrt(float64(termMatch.Freq))
}
score := tf * termMatch.Norm * s.idf
if s.explain {
childrenExplanations := make([]*search.Explanation, 3)
childrenExplanations[0] = &search.Explanation{
Value: tf,
Message: fmt.Sprintf("tf(termFreq(%s:%s)=%d", s.queryField, string(s.queryTerm), termMatch.Freq),
}
childrenExplanations[1] = &search.Explanation{
Value: termMatch.Norm,
Message: fmt.Sprintf("fieldNorm(field=%s, doc=%s)", s.queryField, termMatch.ID),
}
childrenExplanations[2] = s.idfExplanation
scoreExplanation = &search.Explanation{
Value: score,
Message: fmt.Sprintf("fieldWeight(%s:%s in %s), product of:", s.queryField, string(s.queryTerm), termMatch.ID),
Children: childrenExplanations,
}
}
// if the query weight isn't 1, multiply
if s.queryWeight != 1.0 {
score = score * s.queryWeight
if s.explain {
childExplanations := make([]*search.Explanation, 2)
childExplanations[0] = s.queryWeightExplanation
childExplanations[1] = scoreExplanation
scoreExplanation = &search.Explanation{
Value: score,
Message: fmt.Sprintf("weight(%s:%s^%f in %s), product of:", s.queryField, string(s.queryTerm), s.queryBoost, termMatch.ID),
Children: childExplanations,
}
}
}
rv := search.DocumentMatch{
ID: termMatch.ID,
Score: score,
}
if s.explain {
rv.Expl = scoreExplanation
}
if termMatch.Vectors != nil && len(termMatch.Vectors) > 0 {
rv.Locations = make(search.FieldTermLocationMap)
for _, v := range termMatch.Vectors {
tlm := rv.Locations[v.Field]
if tlm == nil {
tlm = make(search.TermLocationMap)
}
loc := search.Location{
Pos: float64(v.Pos),
Start: float64(v.Start),
End: float64(v.End),
}
locations := tlm[s.queryTerm]
if locations == nil {
locations = make(search.Locations, 1)
locations[0] = &loc
} else {
locations = append(locations, &loc)
}
tlm[s.queryTerm] = locations
rv.Locations[v.Field] = tlm
}
}
return &rv
}