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bleve/search/scorer/scorer_term_test.go

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Go

// Copyright (c) 2013 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 scorer
import (
"math"
"reflect"
"testing"
"github.com/blevesearch/bleve/index"
"github.com/blevesearch/bleve/search"
)
func TestTermScorer(t *testing.T) {
var docTotal uint64 = 100
var docTerm uint64 = 9
var queryTerm = []byte("beer")
var queryField = "desc"
var queryBoost = 1.0
scorer := NewTermQueryScorer(queryTerm, queryField, queryBoost, docTotal, docTerm, search.SearcherOptions{Explain: true})
idf := 1.0 + math.Log(float64(docTotal)/float64(docTerm+1.0))
tests := []struct {
termMatch *index.TermFieldDoc
result *search.DocumentMatch
}{
// test some simple math
{
termMatch: &index.TermFieldDoc{
ID: index.IndexInternalID("one"),
Freq: 1,
Norm: 1.0,
Vectors: []*index.TermFieldVector{
{
Field: "desc",
Pos: 1,
Start: 0,
End: 4,
},
},
},
result: &search.DocumentMatch{
IndexInternalID: index.IndexInternalID("one"),
Score: math.Sqrt(1.0) * idf,
Sort: []string{},
Expl: &search.Explanation{
Value: math.Sqrt(1.0) * idf,
Message: "fieldWeight(desc:beer in one), product of:",
Children: []*search.Explanation{
{
Value: 1,
Message: "tf(termFreq(desc:beer)=1",
},
{
Value: 1,
Message: "fieldNorm(field=desc, doc=one)",
},
{
Value: idf,
Message: "idf(docFreq=9, maxDocs=100)",
},
},
},
Locations: search.FieldTermLocationMap{
"desc": search.TermLocationMap{
"beer": []*search.Location{
{
Pos: 1,
Start: 0,
End: 4,
},
},
},
},
},
},
// test the same thing again (score should be cached this time)
{
termMatch: &index.TermFieldDoc{
ID: index.IndexInternalID("one"),
Freq: 1,
Norm: 1.0,
},
result: &search.DocumentMatch{
IndexInternalID: index.IndexInternalID("one"),
Score: math.Sqrt(1.0) * idf,
Sort: []string{},
Expl: &search.Explanation{
Value: math.Sqrt(1.0) * idf,
Message: "fieldWeight(desc:beer in one), product of:",
Children: []*search.Explanation{
{
Value: 1,
Message: "tf(termFreq(desc:beer)=1",
},
{
Value: 1,
Message: "fieldNorm(field=desc, doc=one)",
},
{
Value: idf,
Message: "idf(docFreq=9, maxDocs=100)",
},
},
},
},
},
// test a case where the sqrt isn't precalculated
{
termMatch: &index.TermFieldDoc{
ID: index.IndexInternalID("one"),
Freq: 65,
Norm: 1.0,
},
result: &search.DocumentMatch{
IndexInternalID: index.IndexInternalID("one"),
Score: math.Sqrt(65) * idf,
Sort: []string{},
Expl: &search.Explanation{
Value: math.Sqrt(65) * idf,
Message: "fieldWeight(desc:beer in one), product of:",
Children: []*search.Explanation{
{
Value: math.Sqrt(65),
Message: "tf(termFreq(desc:beer)=65",
},
{
Value: 1,
Message: "fieldNorm(field=desc, doc=one)",
},
{
Value: idf,
Message: "idf(docFreq=9, maxDocs=100)",
},
},
},
},
},
}
for _, test := range tests {
ctx := &search.SearchContext{
DocumentMatchPool: search.NewDocumentMatchPool(1, 0),
}
actual := scorer.Score(ctx, test.termMatch)
if !reflect.DeepEqual(actual, test.result) {
t.Errorf("expected %#v got %#v for %#v", test.result, actual, test.termMatch)
}
}
}
func TestTermScorerWithQueryNorm(t *testing.T) {
var docTotal uint64 = 100
var docTerm uint64 = 9
var queryTerm = []byte("beer")
var queryField = "desc"
var queryBoost = 3.0
scorer := NewTermQueryScorer(queryTerm, queryField, queryBoost, docTotal, docTerm, search.SearcherOptions{Explain: true})
idf := 1.0 + math.Log(float64(docTotal)/float64(docTerm+1.0))
scorer.SetQueryNorm(2.0)
expectedQueryWeight := 3 * idf * 3 * idf
actualQueryWeight := scorer.Weight()
if expectedQueryWeight != actualQueryWeight {
t.Errorf("expected query weight %f, got %f", expectedQueryWeight, actualQueryWeight)
}
tests := []struct {
termMatch *index.TermFieldDoc
result *search.DocumentMatch
}{
{
termMatch: &index.TermFieldDoc{
ID: index.IndexInternalID("one"),
Freq: 1,
Norm: 1.0,
},
result: &search.DocumentMatch{
IndexInternalID: index.IndexInternalID("one"),
Score: math.Sqrt(1.0) * idf * 3.0 * idf * 2.0,
Sort: []string{},
Expl: &search.Explanation{
Value: math.Sqrt(1.0) * idf * 3.0 * idf * 2.0,
Message: "weight(desc:beer^3.000000 in one), product of:",
Children: []*search.Explanation{
{
Value: 2.0 * idf * 3.0,
Message: "queryWeight(desc:beer^3.000000), product of:",
Children: []*search.Explanation{
{
Value: 3,
Message: "boost",
},
{
Value: idf,
Message: "idf(docFreq=9, maxDocs=100)",
},
{
Value: 2,
Message: "queryNorm",
},
},
},
{
Value: math.Sqrt(1.0) * idf,
Message: "fieldWeight(desc:beer in one), product of:",
Children: []*search.Explanation{
{
Value: 1,
Message: "tf(termFreq(desc:beer)=1",
},
{
Value: 1,
Message: "fieldNorm(field=desc, doc=one)",
},
{
Value: idf,
Message: "idf(docFreq=9, maxDocs=100)",
},
},
},
},
},
},
},
}
for _, test := range tests {
ctx := &search.SearchContext{
DocumentMatchPool: search.NewDocumentMatchPool(1, 0),
}
actual := scorer.Score(ctx, test.termMatch)
if !reflect.DeepEqual(actual, test.result) {
t.Errorf("expected %#v got %#v for %#v", test.result, actual, test.termMatch)
}
}
}