ce0b299d6f
this improves perf in the case where we're not doing any sorting as we avoid allocating memory and converting scores into numeric terms
252 lines
6.3 KiB
Go
252 lines
6.3 KiB
Go
// Copyright (c) 2013 Couchbase, Inc.
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// Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file
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// except in compliance with the License. You may obtain a copy of the License at
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// http://www.apache.org/licenses/LICENSE-2.0
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// Unless required by applicable law or agreed to in writing, software distributed under the
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// License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND,
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// either express or implied. See the License for the specific language governing permissions
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// and limitations under the License.
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package scorers
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import (
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"math"
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"reflect"
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"testing"
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"github.com/blevesearch/bleve/index"
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"github.com/blevesearch/bleve/search"
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)
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func TestTermScorer(t *testing.T) {
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var docTotal uint64 = 100
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var docTerm uint64 = 9
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var queryTerm = "beer"
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var queryField = "desc"
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var queryBoost = 1.0
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scorer := NewTermQueryScorer(queryTerm, queryField, queryBoost, docTotal, docTerm, true)
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idf := 1.0 + math.Log(float64(docTotal)/float64(docTerm+1.0))
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tests := []struct {
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termMatch *index.TermFieldDoc
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result *search.DocumentMatch
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}{
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// test some simple math
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{
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termMatch: &index.TermFieldDoc{
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ID: index.IndexInternalID("one"),
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Freq: 1,
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Norm: 1.0,
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Vectors: []*index.TermFieldVector{
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{
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Field: "desc",
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Pos: 1,
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Start: 0,
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End: 4,
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},
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},
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},
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result: &search.DocumentMatch{
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IndexInternalID: index.IndexInternalID("one"),
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Score: math.Sqrt(1.0) * idf,
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Sort: []interface{}{},
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Expl: &search.Explanation{
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Value: math.Sqrt(1.0) * idf,
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Message: "fieldWeight(desc:beer in one), product of:",
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Children: []*search.Explanation{
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{
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Value: 1,
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Message: "tf(termFreq(desc:beer)=1",
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},
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{
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Value: 1,
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Message: "fieldNorm(field=desc, doc=one)",
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},
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{
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Value: idf,
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Message: "idf(docFreq=9, maxDocs=100)",
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},
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},
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},
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Locations: search.FieldTermLocationMap{
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"desc": search.TermLocationMap{
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"beer": []*search.Location{
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{
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Pos: 1,
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Start: 0,
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End: 4,
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},
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},
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},
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},
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},
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},
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// test the same thing again (score should be cached this time)
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{
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termMatch: &index.TermFieldDoc{
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ID: index.IndexInternalID("one"),
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Freq: 1,
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Norm: 1.0,
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},
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result: &search.DocumentMatch{
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IndexInternalID: index.IndexInternalID("one"),
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Score: math.Sqrt(1.0) * idf,
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Sort: []interface{}{},
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Expl: &search.Explanation{
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Value: math.Sqrt(1.0) * idf,
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Message: "fieldWeight(desc:beer in one), product of:",
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Children: []*search.Explanation{
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{
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Value: 1,
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Message: "tf(termFreq(desc:beer)=1",
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},
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{
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Value: 1,
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Message: "fieldNorm(field=desc, doc=one)",
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},
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{
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Value: idf,
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Message: "idf(docFreq=9, maxDocs=100)",
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},
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},
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},
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},
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},
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// test a case where the sqrt isn't precalculated
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{
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termMatch: &index.TermFieldDoc{
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ID: index.IndexInternalID("one"),
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Freq: 65,
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Norm: 1.0,
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},
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result: &search.DocumentMatch{
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IndexInternalID: index.IndexInternalID("one"),
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Score: math.Sqrt(65) * idf,
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Sort: []interface{}{},
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Expl: &search.Explanation{
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Value: math.Sqrt(65) * idf,
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Message: "fieldWeight(desc:beer in one), product of:",
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Children: []*search.Explanation{
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{
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Value: math.Sqrt(65),
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Message: "tf(termFreq(desc:beer)=65",
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},
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{
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Value: 1,
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Message: "fieldNorm(field=desc, doc=one)",
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},
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{
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Value: idf,
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Message: "idf(docFreq=9, maxDocs=100)",
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},
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},
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},
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},
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},
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}
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for _, test := range tests {
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ctx := &search.SearchContext{
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DocumentMatchPool: search.NewDocumentMatchPool(1, 0),
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}
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actual := scorer.Score(ctx, test.termMatch)
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if !reflect.DeepEqual(actual, test.result) {
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t.Errorf("expected %#v got %#v for %#v", test.result, actual, test.termMatch)
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}
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}
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}
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func TestTermScorerWithQueryNorm(t *testing.T) {
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var docTotal uint64 = 100
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var docTerm uint64 = 9
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var queryTerm = "beer"
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var queryField = "desc"
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var queryBoost = 3.0
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scorer := NewTermQueryScorer(queryTerm, queryField, queryBoost, docTotal, docTerm, true)
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idf := 1.0 + math.Log(float64(docTotal)/float64(docTerm+1.0))
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scorer.SetQueryNorm(2.0)
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expectedQueryWeight := 3 * idf * 3 * idf
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actualQueryWeight := scorer.Weight()
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if expectedQueryWeight != actualQueryWeight {
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t.Errorf("expected query weight %f, got %f", expectedQueryWeight, actualQueryWeight)
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}
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tests := []struct {
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termMatch *index.TermFieldDoc
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result *search.DocumentMatch
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}{
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{
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termMatch: &index.TermFieldDoc{
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ID: index.IndexInternalID("one"),
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Freq: 1,
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Norm: 1.0,
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},
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result: &search.DocumentMatch{
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IndexInternalID: index.IndexInternalID("one"),
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Score: math.Sqrt(1.0) * idf * 3.0 * idf * 2.0,
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Sort: []interface{}{},
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Expl: &search.Explanation{
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Value: math.Sqrt(1.0) * idf * 3.0 * idf * 2.0,
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Message: "weight(desc:beer^3.000000 in one), product of:",
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Children: []*search.Explanation{
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{
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Value: 2.0 * idf * 3.0,
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Message: "queryWeight(desc:beer^3.000000), product of:",
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Children: []*search.Explanation{
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{
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Value: 3,
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Message: "boost",
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},
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{
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Value: idf,
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Message: "idf(docFreq=9, maxDocs=100)",
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},
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{
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Value: 2,
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Message: "queryNorm",
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},
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},
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},
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{
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Value: math.Sqrt(1.0) * idf,
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Message: "fieldWeight(desc:beer in one), product of:",
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Children: []*search.Explanation{
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{
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Value: 1,
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Message: "tf(termFreq(desc:beer)=1",
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},
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{
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Value: 1,
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Message: "fieldNorm(field=desc, doc=one)",
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},
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{
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Value: idf,
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Message: "idf(docFreq=9, maxDocs=100)",
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},
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},
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},
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},
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},
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},
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},
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}
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for _, test := range tests {
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ctx := &search.SearchContext{
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DocumentMatchPool: search.NewDocumentMatchPool(1, 0),
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}
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actual := scorer.Score(ctx, test.termMatch)
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if !reflect.DeepEqual(actual, test.result) {
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t.Errorf("expected %#v got %#v for %#v", test.result, actual, test.termMatch)
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}
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}
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}
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