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lunr - npm Package Compare versions

Comparing version 2.1.3 to 2.1.4

bug.html

29

lib/builder.js

@@ -221,3 +221,4 @@ /*!

fieldRefs = Object.keys(this.fieldTermFrequencies),
fieldRefsLength = fieldRefs.length
fieldRefsLength = fieldRefs.length,
termIdfCache = Object.create(null)

@@ -237,12 +238,20 @@ for (var i = 0; i < fieldRefsLength; i++) {

termIndex = this.invertedIndex[term]._index,
idf = lunr.idf(this.invertedIndex[term], this.documentCount),
score = idf * ((this._k1 + 1) * tf) / (this._k1 * (1 - this._b + this._b * (fieldLength / this.averageFieldLength[field])) + tf),
scoreWithPrecision = Math.round(score * 1000) / 1000
// Converts 1.23456789 to 1.234.
// Reducing the precision so that the vectors take up less
// space when serialised. Doing it now so that they behave
// the same before and after serialisation. Also, this is
// the fastest approach to reducing a number's precision in
// JavaScript.
idf, score, scoreWithPrecision
if (termIdfCache[term] === undefined) {
idf = lunr.idf(this.invertedIndex[term], this.documentCount)
termIdfCache[term] = idf
} else {
idf = termIdfCache[term]
}
score = idf * ((this._k1 + 1) * tf) / (this._k1 * (1 - this._b + this._b * (fieldLength / this.averageFieldLength[field])) + tf)
scoreWithPrecision = Math.round(score * 1000) / 1000
// Converts 1.23456789 to 1.234.
// Reducing the precision so that the vectors take up less
// space when serialised. Doing it now so that they behave
// the same before and after serialisation. Also, this is
// the fastest approach to reducing a number's precision in
// JavaScript.
fieldVector.insert(termIndex, scoreWithPrecision)

@@ -249,0 +258,0 @@ }

@@ -1,5 +0,5 @@

lunr.FieldRef = function (docRef, fieldName) {
lunr.FieldRef = function (docRef, fieldName, stringValue) {
this.docRef = docRef
this.fieldName = fieldName
this._stringValue = fieldName + lunr.FieldRef.joiner + docRef
this._stringValue = stringValue
}

@@ -19,7 +19,11 @@

return new lunr.FieldRef (docRef, fieldRef)
return new lunr.FieldRef (docRef, fieldRef, s)
}
lunr.FieldRef.prototype.toString = function () {
if (this._stringValue == undefined) {
this._stringValue = this.fieldName + lunr.FieldRef.joiner + this.docRef
}
return this._stringValue
}

@@ -134,3 +134,4 @@ /*!

matchingFields = Object.create(null),
queryVectors = Object.create(null)
queryVectors = Object.create(null),
termFieldCache = Object.create(null)

@@ -196,3 +197,4 @@ fn.call(query, query)

fieldPosting = posting[field],
matchingDocumentRefs = Object.keys(fieldPosting)
matchingDocumentRefs = Object.keys(fieldPosting),
termField = expandedTerm + "/" + field

@@ -207,3 +209,3 @@ /*

*/
if (!(field in queryVectors)) {
if (queryVectors[field] === undefined) {
queryVectors[field] = new lunr.Vector

@@ -219,2 +221,10 @@ }

/**
* If we've already seen this term, field combo then we've already collected
* the matching documents and metadata, no need to go through all that again
*/
if (termFieldCache[termField]) {
continue
}
for (var l = 0; l < matchingDocumentRefs.length; l++) {

@@ -229,14 +239,14 @@ /*

matchingFieldRef = new lunr.FieldRef (matchingDocumentRef, field),
documentMetadata, matchData
metadata = fieldPosting[matchingDocumentRef],
fieldMatch
documentMetadata = fieldPosting[matchingDocumentRef]
matchData = new lunr.MatchData (expandedTerm, field, documentMetadata)
if (matchingFieldRef in matchingFields) {
matchingFields[matchingFieldRef].combine(matchData)
if ((fieldMatch = matchingFields[matchingFieldRef]) === undefined) {
matchingFields[matchingFieldRef] = new lunr.MatchData (expandedTerm, field, metadata)
} else {
matchingFields[matchingFieldRef] = matchData
fieldMatch.add(expandedTerm, term, metadata)
}
}
termFieldCache[termField] = true
}

@@ -248,3 +258,4 @@ }

var matchingFieldRefs = Object.keys(matchingFields),
results = {}
results = [],
matches = Object.create(null)

@@ -263,9 +274,10 @@ for (var i = 0; i < matchingFieldRefs.length; i++) {

fieldVector = this.fieldVectors[fieldRef],
score = queryVectors[fieldRef.fieldName].similarity(fieldVector)
score = queryVectors[fieldRef.fieldName].similarity(fieldVector),
docMatch
if (docRef in results) {
results[docRef].score += score
results[docRef].matchData.combine(matchingFields[fieldRef])
if ((docMatch = matches[docRef]) !== undefined) {
docMatch.score += score
docMatch.matchData.combine(matchingFields[fieldRef])
} else {
results[docRef] = {
var match = {
ref: docRef,

@@ -275,2 +287,4 @@ score: score,

}
matches[docRef] = match
results.push(match)
}

@@ -280,12 +294,7 @@ }

/*
* The results object needs to be converted into a list
* of results, sorted by score before being returned.
* Sort the results objects by score, highest first.
*/
return Object.keys(results)
.map(function (key) {
return results[key]
})
.sort(function (a, b) {
return b.score - a.score
})
return results.sort(function (a, b) {
return b.score - a.score
})
}

@@ -292,0 +301,0 @@

@@ -73,1 +73,33 @@ /**

}
/**
* Add metadata for a term/field pair to this instance of match data.
*
* @param {string} term - The term this match data is associated with
* @param {string} field - The field in which the term was found
* @param {object} metadata - The metadata recorded about this term in this field
*/
lunr.MatchData.prototype.add = function (term, field, metadata) {
if (!(term in this.metadata)) {
this.metadata[term] = Object.create(null)
this.metadata[term][field] = metadata
return
}
if (!(field in this.metadata[term])) {
this.metadata[term][field] = metadata
return
}
var metadataKeys = Object.keys(metadata)
for (var i = 0; i < metadataKeys.length; i++) {
var key = metadataKeys[i]
if (key in this.metadata[term][field]) {
this.metadata[term][field][key] = this.metadata[term][field][key].concat(metadata[key])
} else {
this.metadata[term][field][key] = metadata[key]
}
}
}
{
"name": "lunr",
"description": "Simple full-text search in your browser.",
"version": "2.1.3",
"version": "2.1.4",
"author": "Oliver Nightingale",

@@ -22,3 +22,3 @@ "keywords": [

"eslint": "3.4.x",
"jsdoc": "3.4.x",
"jsdoc": "3.5.x",
"mocha": "3.0.x",

@@ -25,0 +25,0 @@ "mustache": "2.2.x",

@@ -56,2 +56,10 @@ suite('search', function () {

})
this.add('typeahead', function () {
idx.query(function (q) {
q.term("pl", { boost: 100, usePipeline: true })
q.term("pl", { boost: 10, usePipeline: false, wildcard: lunr.Query.wildcard.TRAILING })
q.term("pl", { boost: 1, editDistance: 1 })
})
})
})

@@ -498,2 +498,42 @@ suite('search', function () {

})
suite('typeahead style search', function () {
suite('no results found', function () {
setup(function () {
this.results = this.idx.query(function (q) {
q.term("xyz", { boost: 100, usePipeline: true })
q.term("xyz", { boost: 10, usePipeline: false, wildcard: lunr.Query.wildcard.TRAILING })
q.term("xyz", { boost: 1, editDistance: 1 })
})
})
test('no results found', function () {
assert.lengthOf(this.results, 0)
})
})
suite('results found', function () {
setup(function () {
this.results = this.idx.query(function (q) {
q.term("pl", { boost: 100, usePipeline: true })
q.term("pl", { boost: 10, usePipeline: false, wildcard: lunr.Query.wildcard.TRAILING })
q.term("pl", { boost: 1, editDistance: 1 })
})
})
test('two results found', function () {
assert.lengthOf(this.results, 2)
})
test('matching documents returned', function () {
assert.equal('b', this.results[0].ref)
assert.equal('c', this.results[1].ref)
})
test('matching terms returned', function () {
assert.sameMembers(['plumb', 'plant'], Object.keys(this.results[0].matchData.metadata))
assert.sameMembers(['plumb', 'plant'], Object.keys(this.results[1].matchData.metadata))
})
})
})
})

@@ -171,2 +171,10 @@ suite('lunr.TokenSet', function () {

test('wildcard matches zero or more characters', function () {
var x = lunr.TokenSet.fromString('foo'),
y = lunr.TokenSet.fromString('foo*'),
z = x.intersect(y)
assert.sameMembers(['foo'], z.toArray())
})
test('intersect with fuzzy string substitution', function () {

@@ -173,0 +181,0 @@ var x1 = lunr.TokenSet.fromString('bar'),

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