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/**
* lunr - http://lunrjs.com - A bit like Solr, but much smaller and not as bright - 2.1.2
* Copyright (C) 2017 Oliver Nightingale
* @license MIT
*/
;(function(){
/**
* A convenience function for configuring and constructing
* a new lunr Index.
*
* A lunr.Builder instance is created and the pipeline setup
* with a trimmer, stop word filter and stemmer.
*
* This builder object is yielded to the configuration function
* that is passed as a parameter, allowing the list of fields
* and other builder parameters to be customised.
*
* All documents _must_ be added within the passed config function.
*
* @example
* var idx = lunr(function () {
* this.field('title')
* this.field('body')
* this.ref('id')
*
* documents.forEach(function (doc) {
* this.add(doc)
* }, this)
* })
*
* @see {@link lunr.Builder}
* @see {@link lunr.Pipeline}
* @see {@link lunr.trimmer}
* @see {@link lunr.stopWordFilter}
* @see {@link lunr.stemmer}
* @namespace {function} lunr
*/
var lunr = function (config) {
var builder = new lunr.Builder
builder.pipeline.add(
lunr.trimmer,
lunr.stopWordFilter,
lunr.stemmer
)
builder.searchPipeline.add(
lunr.stemmer
)
config.call(builder, builder)
return builder.build()
}
lunr.version = "2.1.2"
/*!
* lunr.utils
* Copyright (C) 2017 Oliver Nightingale
*/
/**
* A namespace containing utils for the rest of the lunr library
*/
lunr.utils = {}
/**
* Print a warning message to the console.
*
* @param {String} message The message to be printed.
* @memberOf Utils
*/
lunr.utils.warn = (function (global) {
/* eslint-disable no-console */
return function (message) {
if (global.console && console.warn) {
console.warn(message)
}
}
/* eslint-enable no-console */
})(this)
/**
* Convert an object to a string.
*
* In the case of `null` and `undefined` the function returns
* the empty string, in all other cases the result of calling
* `toString` on the passed object is returned.
*
* @param {Any} obj The object to convert to a string.
* @return {String} string representation of the passed object.
* @memberOf Utils
*/
lunr.utils.asString = function (obj) {
if (obj === void 0 || obj === null) {
return ""
} else {
return obj.toString()
}
}
lunr.FieldRef = function (docRef, fieldName) {
this.docRef = docRef
this.fieldName = fieldName
this._stringValue = fieldName + lunr.FieldRef.joiner + docRef
}
lunr.FieldRef.joiner = "/"
lunr.FieldRef.fromString = function (s) {
var n = s.indexOf(lunr.FieldRef.joiner)
if (n === -1) {
throw "malformed field ref string"
}
var fieldRef = s.slice(0, n),
docRef = s.slice(n + 1)
return new lunr.FieldRef (docRef, fieldRef)
}
lunr.FieldRef.prototype.toString = function () {
return this._stringValue
}
/**
* A function to calculate the inverse document frequency for
* a posting. This is shared between the builder and the index
*
* @private
* @param {object} posting - The posting for a given term
* @param {number} documentCount - The total number of documents.
*/
lunr.idf = function (posting, documentCount) {
var documentsWithTerm = 0
for (var fieldName in posting) {
if (fieldName == '_index') continue // Ignore the term index, its not a field
documentsWithTerm += Object.keys(posting[fieldName]).length
}
var x = (documentCount - documentsWithTerm + 0.5) / (documentsWithTerm + 0.5)
return Math.log(1 + Math.abs(x))
}
/**
* A token wraps a string representation of a token
* as it is passed through the text processing pipeline.
*
* @constructor
* @param {string} [str=''] - The string token being wrapped.
* @param {object} [metadata={}] - Metadata associated with this token.
*/
lunr.Token = function (str, metadata) {
this.str = str || ""
this.metadata = metadata || {}
}
/**
* Returns the token string that is being wrapped by this object.
*
* @returns {string}
*/
lunr.Token.prototype.toString = function () {
return this.str
}
/**
* A token update function is used when updating or optionally
* when cloning a token.
*
* @callback lunr.Token~updateFunction
* @param {string} str - The string representation of the token.
* @param {Object} metadata - All metadata associated with this token.
*/
/**
* Applies the given function to the wrapped string token.
*
* @example
* token.update(function (str, metadata) {
* return str.toUpperCase()
* })
*
* @param {lunr.Token~updateFunction} fn - A function to apply to the token string.
* @returns {lunr.Token}
*/
lunr.Token.prototype.update = function (fn) {
this.str = fn(this.str, this.metadata)
return this
}
/**
* Creates a clone of this token. Optionally a function can be
* applied to the cloned token.
*
* @param {lunr.Token~updateFunction} [fn] - An optional function to apply to the cloned token.
* @returns {lunr.Token}
*/
lunr.Token.prototype.clone = function (fn) {
fn = fn || function (s) { return s }
return new lunr.Token (fn(this.str, this.metadata), this.metadata)
}
/*!
* lunr.tokenizer
* Copyright (C) 2017 Oliver Nightingale
*/
/**
* A function for splitting a string into tokens ready to be inserted into
* the search index. Uses `lunr.tokenizer.separator` to split strings, change
* the value of this property to change how strings are split into tokens.
*
* This tokenizer will convert its parameter to a string by calling `toString` and
* then will split this string on the character in `lunr.tokenizer.separator`.
* Arrays will have their elements converted to strings and wrapped in a lunr.Token.
*
* @static
* @param {?(string|object|object[])} obj - The object to convert into tokens
* @returns {lunr.Token[]}
*/
lunr.tokenizer = function (obj) {
if (obj == null || obj == undefined) {
return []
}
if (Array.isArray(obj)) {
return obj.map(function (t) {
return new lunr.Token(lunr.utils.asString(t).toLowerCase())
})
}
var str = obj.toString().trim().toLowerCase(),
len = str.length,
tokens = []
for (var sliceEnd = 0, sliceStart = 0; sliceEnd <= len; sliceEnd++) {
var char = str.charAt(sliceEnd),
sliceLength = sliceEnd - sliceStart
if ((char.match(lunr.tokenizer.separator) || sliceEnd == len)) {
if (sliceLength > 0) {
tokens.push(
new lunr.Token (str.slice(sliceStart, sliceEnd), {
position: [sliceStart, sliceLength],
index: tokens.length
})
)
}
sliceStart = sliceEnd + 1
}
}
return tokens
}
/**
* The separator used to split a string into tokens. Override this property to change the behaviour of
* `lunr.tokenizer` behaviour when tokenizing strings. By default this splits on whitespace and hyphens.
*
* @static
* @see lunr.tokenizer
*/
lunr.tokenizer.separator = /[\s\-]+/
/*!
* lunr.Pipeline
* Copyright (C) 2017 Oliver Nightingale
*/
/**
* lunr.Pipelines maintain an ordered list of functions to be applied to all
* tokens in documents entering the search index and queries being ran against
* the index.
*
* An instance of lunr.Index created with the lunr shortcut will contain a
* pipeline with a stop word filter and an English language stemmer. Extra
* functions can be added before or after either of these functions or these
* default functions can be removed.
*
* When run the pipeline will call each function in turn, passing a token, the
* index of that token in the original list of all tokens and finally a list of
* all the original tokens.
*
* The output of functions in the pipeline will be passed to the next function
* in the pipeline. To exclude a token from entering the index the function
* should return undefined, the rest of the pipeline will not be called with
* this token.
*
* For serialisation of pipelines to work, all functions used in an instance of
* a pipeline should be registered with lunr.Pipeline. Registered functions can
* then be loaded. If trying to load a serialised pipeline that uses functions
* that are not registered an error will be thrown.
*
* If not planning on serialising the pipeline then registering pipeline functions
* is not necessary.
*
* @constructor
*/
lunr.Pipeline = function () {
this._stack = []
}
lunr.Pipeline.registeredFunctions = Object.create(null)
/**
* A pipeline function maps lunr.Token to lunr.Token. A lunr.Token contains the token
* string as well as all known metadata. A pipeline function can mutate the token string
* or mutate (or add) metadata for a given token.
*
* A pipeline function can indicate that the passed token should be discarded by returning
* null. This token will not be passed to any downstream pipeline functions and will not be
* added to the index.
*
* Multiple tokens can be returned by returning an array of tokens. Each token will be passed
* to any downstream pipeline functions and all will returned tokens will be added to the index.
*
* Any number of pipeline functions may be chained together using a lunr.Pipeline.
*
* @interface lunr.PipelineFunction
* @param {lunr.Token} token - A token from the document being processed.
* @param {number} i - The index of this token in the complete list of tokens for this document/field.
* @param {lunr.Token[]} tokens - All tokens for this document/field.
* @returns {(?lunr.Token|lunr.Token[])}
*/
/**
* Register a function with the pipeline.
*
* Functions that are used in the pipeline should be registered if the pipeline
* needs to be serialised, or a serialised pipeline needs to be loaded.
*
* Registering a function does not add it to a pipeline, functions must still be
* added to instances of the pipeline for them to be used when running a pipeline.
*
* @param {lunr.PipelineFunction} fn - The function to check for.
* @param {String} label - The label to register this function with
*/
lunr.Pipeline.registerFunction = function (fn, label) {
if (label in this.registeredFunctions) {
lunr.utils.warn('Overwriting existing registered function: ' + label)
}
fn.label = label
lunr.Pipeline.registeredFunctions[fn.label] = fn
}
/**
* Warns if the function is not registered as a Pipeline function.
*
* @param {lunr.PipelineFunction} fn - The function to check for.
* @private
*/
lunr.Pipeline.warnIfFunctionNotRegistered = function (fn) {
var isRegistered = fn.label && (fn.label in this.registeredFunctions)
if (!isRegistered) {
lunr.utils.warn('Function is not registered with pipeline. This may cause problems when serialising the index.\n', fn)
}
}
/**
* Loads a previously serialised pipeline.
*
* All functions to be loaded must already be registered with lunr.Pipeline.
* If any function from the serialised data has not been registered then an
* error will be thrown.
*
* @param {Object} serialised - The serialised pipeline to load.
* @returns {lunr.Pipeline}
*/
lunr.Pipeline.load = function (serialised) {
var pipeline = new lunr.Pipeline
serialised.forEach(function (fnName) {
var fn = lunr.Pipeline.registeredFunctions[fnName]
if (fn) {
pipeline.add(fn)
} else {
throw new Error('Cannot load unregistered function: ' + fnName)
}
})
return pipeline
}
/**
* Adds new functions to the end of the pipeline.
*
* Logs a warning if the function has not been registered.
*
* @param {lunr.PipelineFunction[]} functions - Any number of functions to add to the pipeline.
*/
lunr.Pipeline.prototype.add = function () {
var fns = Array.prototype.slice.call(arguments)
fns.forEach(function (fn) {
lunr.Pipeline.warnIfFunctionNotRegistered(fn)
this._stack.push(fn)
}, this)
}
/**
* Adds a single function after a function that already exists in the
* pipeline.
*
* Logs a warning if the function has not been registered.
*
* @param {lunr.PipelineFunction} existingFn - A function that already exists in the pipeline.
* @param {lunr.PipelineFunction} newFn - The new function to add to the pipeline.
*/
lunr.Pipeline.prototype.after = function (existingFn, newFn) {
lunr.Pipeline.warnIfFunctionNotRegistered(newFn)
var pos = this._stack.indexOf(existingFn)
if (pos == -1) {
throw new Error('Cannot find existingFn')
}
pos = pos + 1
this._stack.splice(pos, 0, newFn)
}
/**
* Adds a single function before a function that already exists in the
* pipeline.
*
* Logs a warning if the function has not been registered.
*
* @param {lunr.PipelineFunction} existingFn - A function that already exists in the pipeline.
* @param {lunr.PipelineFunction} newFn - The new function to add to the pipeline.
*/
lunr.Pipeline.prototype.before = function (existingFn, newFn) {
lunr.Pipeline.warnIfFunctionNotRegistered(newFn)
var pos = this._stack.indexOf(existingFn)
if (pos == -1) {
throw new Error('Cannot find existingFn')
}
this._stack.splice(pos, 0, newFn)
}
/**
* Removes a function from the pipeline.
*
* @param {lunr.PipelineFunction} fn The function to remove from the pipeline.
*/
lunr.Pipeline.prototype.remove = function (fn) {
var pos = this._stack.indexOf(fn)
if (pos == -1) {
return
}
this._stack.splice(pos, 1)
}
/**
* Runs the current list of functions that make up the pipeline against the
* passed tokens.
*
* @param {Array} tokens The tokens to run through the pipeline.
* @returns {Array}
*/
lunr.Pipeline.prototype.run = function (tokens) {
var stackLength = this._stack.length
for (var i = 0; i < stackLength; i++) {
var fn = this._stack[i]
tokens = tokens.reduce(function (memo, token, j) {
var result = fn(token, j, tokens)
if (result === void 0 || result === '') return memo
return memo.concat(result)
}, [])
}
return tokens
}
/**
* Convenience method for passing a string through a pipeline and getting
* strings out. This method takes care of wrapping the passed string in a
* token and mapping the resulting tokens back to strings.
*
* @param {string} str - The string to pass through the pipeline.
* @returns {string[]}
*/
lunr.Pipeline.prototype.runString = function (str) {
var token = new lunr.Token (str)
return this.run([token]).map(function (t) {
return t.toString()
})
}
/**
* Resets the pipeline by removing any existing processors.
*
*/
lunr.Pipeline.prototype.reset = function () {
this._stack = []
}
/**
* Returns a representation of the pipeline ready for serialisation.
*
* Logs a warning if the function has not been registered.
*
* @returns {Array}
*/
lunr.Pipeline.prototype.toJSON = function () {
return this._stack.map(function (fn) {
lunr.Pipeline.warnIfFunctionNotRegistered(fn)
return fn.label
})
}
/*!
* lunr.Vector
* Copyright (C) 2017 Oliver Nightingale
*/
/**
* A vector is used to construct the vector space of documents and queries. These
* vectors support operations to determine the similarity between two documents or
* a document and a query.
*
* Normally no parameters are required for initializing a vector, but in the case of
* loading a previously dumped vector the raw elements can be provided to the constructor.
*
* For performance reasons vectors are implemented with a flat array, where an elements
* index is immediately followed by its value. E.g. [index, value, index, value]. This
* allows the underlying array to be as sparse as possible and still offer decent
* performance when being used for vector calculations.
*
* @constructor
* @param {Number[]} [elements] - The flat list of element index and element value pairs.
*/
lunr.Vector = function (elements) {
this._magnitude = 0
this.elements = elements || []
}
/**
* Calculates the position within the vector to insert a given index.
*
* This is used internally by insert and upsert. If there are duplicate indexes then
* the position is returned as if the value for that index were to be updated, but it
* is the callers responsibility to check whether there is a duplicate at that index
*
* @param {Number} insertIdx - The index at which the element should be inserted.
* @returns {Number}
*/
lunr.Vector.prototype.positionForIndex = function (index) {
// For an empty vector the tuple can be inserted at the beginning
if (this.elements.length == 0) {
return 0
}
var start = 0,
end = this.elements.length / 2,
sliceLength = end - start,
pivotPoint = Math.floor(sliceLength / 2),
pivotIndex = this.elements[pivotPoint * 2]
while (sliceLength > 1) {
if (pivotIndex < index) {
start = pivotPoint
}
if (pivotIndex > index) {
end = pivotPoint
}
if (pivotIndex == index) {
break
}
sliceLength = end - start
pivotPoint = start + Math.floor(sliceLength / 2)
pivotIndex = this.elements[pivotPoint * 2]
}
if (pivotIndex == index) {
return pivotPoint * 2
}
if (pivotIndex > index) {
return pivotPoint * 2
}
if (pivotIndex < index) {
return (pivotPoint + 1) * 2
}
}
/**
* Inserts an element at an index within the vector.
*
* Does not allow duplicates, will throw an error if there is already an entry
* for this index.
*
* @param {Number} insertIdx - The index at which the element should be inserted.
* @param {Number} val - The value to be inserted into the vector.
*/
lunr.Vector.prototype.insert = function (insertIdx, val) {
this.upsert(insertIdx, val, function () {
throw "duplicate index"
})
}
/**
* Inserts or updates an existing index within the vector.
*
* @param {Number} insertIdx - The index at which the element should be inserted.
* @param {Number} val - The value to be inserted into the vector.
* @param {function} fn - A function that is called for updates, the existing value and the
* requested value are passed as arguments
*/
lunr.Vector.prototype.upsert = function (insertIdx, val, fn) {
this._magnitude = 0
var position = this.positionForIndex(insertIdx)
if (this.elements[position] == insertIdx) {
this.elements[position + 1] = fn(this.elements[position + 1], val)
} else {
this.elements.splice(position, 0, insertIdx, val)
}
}
/**
* Calculates the magnitude of this vector.
*
* @returns {Number}
*/
lunr.Vector.prototype.magnitude = function () {
if (this._magnitude) return this._magnitude
var sumOfSquares = 0,
elementsLength = this.elements.length
for (var i = 1; i < elementsLength; i += 2) {
var val = this.elements[i]
sumOfSquares += val * val
}
return this._magnitude = Math.sqrt(sumOfSquares)
}
/**
* Calculates the dot product of this vector and another vector.
*
* @param {lunr.Vector} otherVector - The vector to compute the dot product with.
* @returns {Number}
*/
lunr.Vector.prototype.dot = function (otherVector) {
var dotProduct = 0,
a = this.elements, b = otherVector.elements,
aLen = a.length, bLen = b.length,
aVal = 0, bVal = 0,
i = 0, j = 0
while (i < aLen && j < bLen) {
aVal = a[i], bVal = b[j]
if (aVal < bVal) {
i += 2
} else if (aVal > bVal) {
j += 2
} else if (aVal == bVal) {
dotProduct += a[i + 1] * b[j + 1]
i += 2
j += 2
}
}
return dotProduct
}
/**
* Calculates the cosine similarity between this vector and another
* vector.
*
* @param {lunr.Vector} otherVector - The other vector to calculate the
* similarity with.
* @returns {Number}
*/
lunr.Vector.prototype.similarity = function (otherVector) {
return this.dot(otherVector) / (this.magnitude() * otherVector.magnitude())
}
/**
* Converts the vector to an array of the elements within the vector.
*
* @returns {Number[]}
*/
lunr.Vector.prototype.toArray = function () {
var output = new Array (this.elements.length / 2)
for (var i = 1, j = 0; i < this.elements.length; i += 2, j++) {
output[j] = this.elements[i]
}
return output
}
/**
* A JSON serializable representation of the vector.
*
* @returns {Number[]}
*/
lunr.Vector.prototype.toJSON = function () {
return this.elements
}
/* eslint-disable */
/*!
* lunr.stemmer
* Copyright (C) 2017 Oliver Nightingale
* Includes code from - http://tartarus.org/~martin/PorterStemmer/js.txt
*/
/**
* lunr.stemmer is an english language stemmer, this is a JavaScript
* implementation of the PorterStemmer taken from http://tartarus.org/~martin
*
* @static
* @implements {lunr.PipelineFunction}
* @param {lunr.Token} token - The string to stem
* @returns {lunr.Token}
* @see {@link lunr.Pipeline}
*/
lunr.stemmer = (function(){
var step2list = {
"ational" : "ate",
"tional" : "tion",
"enci" : "ence",
"anci" : "ance",
"izer" : "ize",
"bli" : "ble",
"alli" : "al",
"entli" : "ent",
"eli" : "e",
"ousli" : "ous",
"ization" : "ize",
"ation" : "ate",
"ator" : "ate",
"alism" : "al",
"iveness" : "ive",
"fulness" : "ful",
"ousness" : "ous",
"aliti" : "al",
"iviti" : "ive",
"biliti" : "ble",
"logi" : "log"
},
step3list = {
"icate" : "ic",
"ative" : "",
"alize" : "al",
"iciti" : "ic",
"ical" : "ic",
"ful" : "",
"ness" : ""
},
c = "[^aeiou]", // consonant
v = "[aeiouy]", // vowel
C = c + "[^aeiouy]*", // consonant sequence
V = v + "[aeiou]*", // vowel sequence
mgr0 = "^(" + C + ")?" + V + C, // [C]VC... is m>0
meq1 = "^(" + C + ")?" + V + C + "(" + V + ")?$", // [C]VC[V] is m=1
mgr1 = "^(" + C + ")?" + V + C + V + C, // [C]VCVC... is m>1
s_v = "^(" + C + ")?" + v; // vowel in stem
var re_mgr0 = new RegExp(mgr0);
var re_mgr1 = new RegExp(mgr1);
var re_meq1 = new RegExp(meq1);
var re_s_v = new RegExp(s_v);
var re_1a = /^(.+?)(ss|i)es$/;
var re2_1a = /^(.+?)([^s])s$/;
var re_1b = /^(.+?)eed$/;
var re2_1b = /^(.+?)(ed|ing)$/;
var re_1b_2 = /.$/;
var re2_1b_2 = /(at|bl|iz)$/;
var re3_1b_2 = new RegExp("([^aeiouylsz])\\1$");
var re4_1b_2 = new RegExp("^" + C + v + "[^aeiouwxy]$");
var re_1c = /^(.+?[^aeiou])y$/;
var re_2 = /^(.+?)(ational|tional|enci|anci|izer|bli|alli|entli|eli|ousli|ization|ation|ator|alism|iveness|fulness|ousness|aliti|iviti|biliti|logi)$/;
var re_3 = /^(.+?)(icate|ative|alize|iciti|ical|ful|ness)$/;
var re_4 = /^(.+?)(al|ance|ence|er|ic|able|ible|ant|ement|ment|ent|ou|ism|ate|iti|ous|ive|ize)$/;
var re2_4 = /^(.+?)(s|t)(ion)$/;
var re_5 = /^(.+?)e$/;
var re_5_1 = /ll$/;
var re3_5 = new RegExp("^" + C + v + "[^aeiouwxy]$");
var porterStemmer = function porterStemmer(w) {
var stem,
suffix,
firstch,
re,
re2,
re3,
re4;
if (w.length < 3) { return w; }
firstch = w.substr(0,1);
if (firstch == "y") {
w = firstch.toUpperCase() + w.substr(1);
}
// Step 1a
re = re_1a
re2 = re2_1a;
if (re.test(w)) { w = w.replace(re,"$1$2"); }
else if (re2.test(w)) { w = w.replace(re2,"$1$2"); }
// Step 1b
re = re_1b;
re2 = re2_1b;
if (re.test(w)) {
var fp = re.exec(w);
re = re_mgr0;
if (re.test(fp[1])) {
re = re_1b_2;
w = w.replace(re,"");
}
} else if (re2.test(w)) {
var fp = re2.exec(w);
stem = fp[1];
re2 = re_s_v;
if (re2.test(stem)) {
w = stem;
re2 = re2_1b_2;
re3 = re3_1b_2;
re4 = re4_1b_2;
if (re2.test(w)) { w = w + "e"; }
else if (re3.test(w)) { re = re_1b_2; w = w.replace(re,""); }
else if (re4.test(w)) { w = w + "e"; }
}
}
// Step 1c - replace suffix y or Y by i if preceded by a non-vowel which is not the first letter of the word (so cry -> cri, by -> by, say -> say)
re = re_1c;
if (re.test(w)) {
var fp = re.exec(w);
stem = fp[1];
w = stem + "i";
}
// Step 2
re = re_2;
if (re.test(w)) {
var fp = re.exec(w);
stem = fp[1];
suffix = fp[2];
re = re_mgr0;
if (re.test(stem)) {
w = stem + step2list[suffix];
}
}
// Step 3
re = re_3;
if (re.test(w)) {
var fp = re.exec(w);
stem = fp[1];
suffix = fp[2];
re = re_mgr0;
if (re.test(stem)) {
w = stem + step3list[suffix];
}
}
// Step 4
re = re_4;
re2 = re2_4;
if (re.test(w)) {
var fp = re.exec(w);
stem = fp[1];
re = re_mgr1;
if (re.test(stem)) {
w = stem;
}
} else if (re2.test(w)) {
var fp = re2.exec(w);
stem = fp[1] + fp[2];
re2 = re_mgr1;
if (re2.test(stem)) {
w = stem;
}
}
// Step 5
re = re_5;
if (re.test(w)) {
var fp = re.exec(w);
stem = fp[1];
re = re_mgr1;
re2 = re_meq1;
re3 = re3_5;
if (re.test(stem) || (re2.test(stem) && !(re3.test(stem)))) {
w = stem;
}
}
re = re_5_1;
re2 = re_mgr1;
if (re.test(w) && re2.test(w)) {
re = re_1b_2;
w = w.replace(re,"");
}
// and turn initial Y back to y
if (firstch == "y") {
w = firstch.toLowerCase() + w.substr(1);
}
return w;
};
return function (token) {
return token.update(porterStemmer);
}
})();
lunr.Pipeline.registerFunction(lunr.stemmer, 'stemmer')
/*!
* lunr.stopWordFilter
* Copyright (C) 2017 Oliver Nightingale
*/
/**
* lunr.generateStopWordFilter builds a stopWordFilter function from the provided
* list of stop words.
*
* The built in lunr.stopWordFilter is built using this generator and can be used
* to generate custom stopWordFilters for applications or non English languages.
*
* @param {Array} token The token to pass through the filter
* @returns {lunr.PipelineFunction}
* @see lunr.Pipeline
* @see lunr.stopWordFilter
*/
lunr.generateStopWordFilter = function (stopWords) {
var words = stopWords.reduce(function (memo, stopWord) {
memo[stopWord] = stopWord
return memo
}, {})
return function (token) {
if (token && words[token.toString()] !== token.toString()) return token
}
}
/**
* lunr.stopWordFilter is an English language stop word list filter, any words
* contained in the list will not be passed through the filter.
*
* This is intended to be used in the Pipeline. If the token does not pass the
* filter then undefined will be returned.
*
* @implements {lunr.PipelineFunction}
* @params {lunr.Token} token - A token to check for being a stop word.
* @returns {lunr.Token}
* @see {@link lunr.Pipeline}
*/
lunr.stopWordFilter = lunr.generateStopWordFilter([
'a',
'able',
'about',
'across',
'after',
'all',
'almost',
'also',
'am',
'among',
'an',
'and',
'any',
'are',
'as',
'at',
'be',
'because',
'been',
'but',
'by',
'can',
'cannot',
'could',
'dear',
'did',
'do',
'does',
'either',
'else',
'ever',
'every',
'for',
'from',
'get',
'got',
'had',
'has',
'have',
'he',
'her',
'hers',
'him',
'his',
'how',
'however',
'i',
'if',
'in',
'into',
'is',
'it',
'its',
'just',
'least',
'let',
'like',
'likely',
'may',
'me',
'might',
'most',
'must',
'my',
'neither',
'no',
'nor',
'not',
'of',
'off',
'often',
'on',
'only',
'or',
'other',
'our',
'own',
'rather',
'said',
'say',
'says',
'she',
'should',
'since',
'so',
'some',
'than',
'that',
'the',
'their',
'them',
'then',
'there',
'these',
'they',
'this',
'tis',
'to',
'too',
'twas',
'us',
'wants',
'was',
'we',
'were',
'what',
'when',
'where',
'which',
'while',
'who',
'whom',
'why',
'will',
'with',
'would',
'yet',
'you',
'your'
])
lunr.Pipeline.registerFunction(lunr.stopWordFilter, 'stopWordFilter')
/*!
* lunr.trimmer
* Copyright (C) 2017 Oliver Nightingale
*/
/**
* lunr.trimmer is a pipeline function for trimming non word
* characters from the beginning and end of tokens before they
* enter the index.
*
* This implementation may not work correctly for non latin
* characters and should either be removed or adapted for use
* with languages with non-latin characters.
*
* @static
* @implements {lunr.PipelineFunction}
* @param {lunr.Token} token The token to pass through the filter
* @returns {lunr.Token}
* @see lunr.Pipeline
*/
lunr.trimmer = function (token) {
return token.update(function (s) {
return s.replace(/^\W+/, '').replace(/\W+$/, '')
})
}
lunr.Pipeline.registerFunction(lunr.trimmer, 'trimmer')
/*!
* lunr.TokenSet
* Copyright (C) 2017 Oliver Nightingale
*/
/**
* A token set is used to store the unique list of all tokens
* within an index. Token sets are also used to represent an
* incoming query to the index, this query token set and index
* token set are then intersected to find which tokens to look
* up in the inverted index.
*
* A token set can hold multiple tokens, as in the case of the
* index token set, or it can hold a single token as in the
* case of a simple query token set.
*
* Additionally token sets are used to perform wildcard matching.
* Leading, contained and trailing wildcards are supported, and
* from this edit distance matching can also be provided.
*
* Token sets are implemented as a minimal finite state automata,
* where both common prefixes and suffixes are shared between tokens.
* This helps to reduce the space used for storing the token set.
*
* @constructor
*/
lunr.TokenSet = function () {
this.final = false
this.edges = {}
this.id = lunr.TokenSet._nextId
lunr.TokenSet._nextId += 1
}
/**
* Keeps track of the next, auto increment, identifier to assign
* to a new tokenSet.
*
* TokenSets require a unique identifier to be correctly minimised.
*
* @private
*/
lunr.TokenSet._nextId = 1
/**
* Creates a TokenSet instance from the given sorted array of words.
*
* @param {String[]} arr - A sorted array of strings to create the set from.
* @returns {lunr.TokenSet}
* @throws Will throw an error if the input array is not sorted.
*/
lunr.TokenSet.fromArray = function (arr) {
var builder = new lunr.TokenSet.Builder
for (var i = 0, len = arr.length; i < len; i++) {
builder.insert(arr[i])
}
builder.finish()
return builder.root
}
/**
* Creates a token set from a query clause.
*
* @private
* @param {Object} clause - A single clause from lunr.Query.
* @param {string} clause.term - The query clause term.
* @param {number} [clause.editDistance] - The optional edit distance for the term.
* @returns {lunr.TokenSet}
*/
lunr.TokenSet.fromClause = function (clause) {
if ('editDistance' in clause) {
return lunr.TokenSet.fromFuzzyString(clause.term, clause.editDistance)
} else {
return lunr.TokenSet.fromString(clause.term)
}
}
/**
* Creates a token set representing a single string with a specified
* edit distance.
*
* Insertions, deletions, substitutions and transpositions are each
* treated as an edit distance of 1.
*
* Increasing the allowed edit distance will have a dramatic impact
* on the performance of both creating and intersecting these TokenSets.
* It is advised to keep the edit distance less than 3.
*
* @param {string} str - The string to create the token set from.
* @param {number} editDistance - The allowed edit distance to match.
* @returns {lunr.Vector}
*/
lunr.TokenSet.fromFuzzyString = function (str, editDistance) {
var root = new lunr.TokenSet
var stack = [{
node: root,
editsRemaining: editDistance,
str: str
}]
while (stack.length) {
var frame = stack.pop()
// no edit
if (frame.str.length > 0) {
var char = frame.str.charAt(0),
noEditNode
if (char in frame.node.edges) {
noEditNode = frame.node.edges[char]
} else {
noEditNode = new lunr.TokenSet
frame.node.edges[char] = noEditNode
}
if (frame.str.length == 1) {
noEditNode.final = true
} else {
stack.push({
node: noEditNode,
editsRemaining: frame.editsRemaining,
str: frame.str.slice(1)
})
}
}
// deletion
// can only do a deletion if we have enough edits remaining
// and if there are characters left to delete in the string
if (frame.editsRemaining > 0 && frame.str.length > 1) {
var char = frame.str.charAt(1),
deletionNode
if (char in frame.node.edges) {
deletionNode = frame.node.edges[char]
} else {
deletionNode = new lunr.TokenSet
frame.node.edges[char] = deletionNode
}
if (frame.str.length <= 2) {
deletionNode.final = true
} else {
stack.push({
node: deletionNode,
editsRemaining: frame.editsRemaining - 1,
str: frame.str.slice(2)
})
}
}
// deletion
// just removing the last character from the str
if (frame.editsRemaining > 0 && frame.str.length == 1) {
frame.node.final = true
}
// substitution
// can only do a substitution if we have enough edits remaining
// and if there are characters left to substitute
if (frame.editsRemaining > 0 && frame.str.length >= 1) {
if ("*" in frame.node.edges) {
var substitutionNode = frame.node.edges["*"]
} else {
var substitutionNode = new lunr.TokenSet
frame.node.edges["*"] = substitutionNode
}
if (frame.str.length == 1) {
substitutionNode.final = true
} else {
stack.push({
node: substitutionNode,
editsRemaining: frame.editsRemaining - 1,
str: frame.str.slice(1)
})
}
}
// insertion
// can only do insertion if there are edits remaining
if (frame.editsRemaining > 0) {
if ("*" in frame.node.edges) {
var insertionNode = frame.node.edges["*"]
} else {
var insertionNode = new lunr.TokenSet
frame.node.edges["*"] = insertionNode
}
if (frame.str.length == 0) {
insertionNode.final = true
} else {
stack.push({
node: insertionNode,
editsRemaining: frame.editsRemaining - 1,
str: frame.str
})
}
}
// transposition
// can only do a transposition if there are edits remaining
// and there are enough characters to transpose
if (frame.editsRemaining > 0 && frame.str.length > 1) {
var charA = frame.str.charAt(0),
charB = frame.str.charAt(1),
transposeNode
if (charB in frame.node.edges) {
transposeNode = frame.node.edges[charB]
} else {
transposeNode = new lunr.TokenSet
frame.node.edges[charB] = transposeNode
}
if (frame.str.length == 1) {
transposeNode.final = true
} else {
stack.push({
node: transposeNode,
editsRemaining: frame.editsRemaining - 1,
str: charA + frame.str.slice(2)
})
}
}
}
return root
}
/**
* Creates a TokenSet from a string.
*
* The string may contain one or more wildcard characters (*)
* that will allow wildcard matching when intersecting with
* another TokenSet.
*
* @param {string} str - The string to create a TokenSet from.
* @returns {lunr.TokenSet}
*/
lunr.TokenSet.fromString = function (str) {
var node = new lunr.TokenSet,
root = node,
wildcardFound = false
/*
* Iterates through all characters within the passed string
* appending a node for each character.
*
* As soon as a wildcard character is found then a self
* referencing edge is introduced to continually match
* any number of any characters.
*/
for (var i = 0, len = str.length; i < len; i++) {
var char = str[i],
final = (i == len - 1)
if (char == "*") {
wildcardFound = true
node.edges[char] = node
node.final = final
} else {
var next = new lunr.TokenSet
next.final = final
node.edges[char] = next
node = next
// TODO: is this needed anymore?
if (wildcardFound) {
node.edges["*"] = root
}
}
}
return root
}
/**
* Converts this TokenSet into an array of strings
* contained within the TokenSet.
*
* @returns {string[]}
*/
lunr.TokenSet.prototype.toArray = function () {
var words = []
var stack = [{
prefix: "",
node: this
}]
while (stack.length) {
var frame = stack.pop(),
edges = Object.keys(frame.node.edges),
len = edges.length
if (frame.node.final) {
words.push(frame.prefix)
}
for (var i = 0; i < len; i++) {
var edge = edges[i]
stack.push({
prefix: frame.prefix.concat(edge),
node: frame.node.edges[edge]
})
}
}
return words
}
/**
* Generates a string representation of a TokenSet.
*
* This is intended to allow TokenSets to be used as keys
* in objects, largely to aid the construction and minimisation
* of a TokenSet. As such it is not designed to be a human
* friendly representation of the TokenSet.
*
* @returns {string}
*/
lunr.TokenSet.prototype.toString = function () {
// NOTE: Using Object.keys here as this.edges is very likely
// to enter 'hash-mode' with many keys being added
//
// avoiding a for-in loop here as it leads to the function
// being de-optimised (at least in V8). From some simple
// benchmarks the performance is comparable, but allowing
// V8 to optimize may mean easy performance wins in the future.
if (this._str) {
return this._str
}
var str = this.final ? '1' : '0',
labels = Object.keys(this.edges).sort(),
len = labels.length
for (var i = 0; i < len; i++) {
var label = labels[i],
node = this.edges[label]
str = str + label + node.id
}
return str
}
/**
* Returns a new TokenSet that is the intersection of
* this TokenSet and the passed TokenSet.
*
* This intersection will take into account any wildcards
* contained within the TokenSet.
*
* @param {lunr.TokenSet} b - An other TokenSet to intersect with.
* @returns {lunr.TokenSet}
*/
lunr.TokenSet.prototype.intersect = function (b) {
var output = new lunr.TokenSet,
frame = undefined
var stack = [{
qNode: b,
output: output,
node: this
}]
while (stack.length) {
frame = stack.pop()
// NOTE: As with the #toString method, we are using
// Object.keys and a for loop instead of a for-in loop
// as both of these objects enter 'hash' mode, causing
// the function to be de-optimised in V8
var qEdges = Object.keys(frame.qNode.edges),
qLen = qEdges.length,
nEdges = Object.keys(frame.node.edges),
nLen = nEdges.length
for (var q = 0; q < qLen; q++) {
var qEdge = qEdges[q]
for (var n = 0; n < nLen; n++) {
var nEdge = nEdges[n]
if (nEdge == qEdge || qEdge == '*') {
var node = frame.node.edges[nEdge],
qNode = frame.qNode.edges[qEdge],
final = node.final && qNode.final,
next = undefined
if (nEdge in frame.output.edges) {
// an edge already exists for this character
// no need to create a new node, just set the finality
// bit unless this node is already final
next = frame.output.edges[nEdge]
next.final = next.final || final
} else {
// no edge exists yet, must create one
// set the finality bit and insert it
// into the output
next = new lunr.TokenSet
next.final = final
frame.output.edges[nEdge] = next
}
stack.push({
qNode: qNode,
output: next,
node: node
})
}
}
}
}
return output
}
lunr.TokenSet.Builder = function () {
this.previousWord = ""
this.root = new lunr.TokenSet
this.uncheckedNodes = []
this.minimizedNodes = {}
}
lunr.TokenSet.Builder.prototype.insert = function (word) {
var node,
commonPrefix = 0
if (word < this.previousWord) {
throw new Error ("Out of order word insertion")
}
for (var i = 0; i < word.length && i < this.previousWord.length; i++) {
if (word[i] != this.previousWord[i]) break
commonPrefix++
}
this.minimize(commonPrefix)
if (this.uncheckedNodes.length == 0) {
node = this.root
} else {
node = this.uncheckedNodes[this.uncheckedNodes.length - 1].child
}
for (var i = commonPrefix; i < word.length; i++) {
var nextNode = new lunr.TokenSet,
char = word[i]
node.edges[char] = nextNode
this.uncheckedNodes.push({
parent: node,
char: char,
child: nextNode
})
node = nextNode
}
node.final = true
this.previousWord = word
}
lunr.TokenSet.Builder.prototype.finish = function () {
this.minimize(0)
}
lunr.TokenSet.Builder.prototype.minimize = function (downTo) {
for (var i = this.uncheckedNodes.length - 1; i >= downTo; i--) {
var node = this.uncheckedNodes[i],
childKey = node.child.toString()
if (childKey in this.minimizedNodes) {
node.parent.edges[node.char] = this.minimizedNodes[childKey]
} else {
// Cache the key for this node since
// we know it can't change anymore
node.child._str = childKey
this.minimizedNodes[childKey] = node.child
}
this.uncheckedNodes.pop()
}
}
/*!
* lunr.Index
* Copyright (C) 2017 Oliver Nightingale
*/
/**
* An index contains the built index of all documents and provides a query interface
* to the index.
*
* Usually instances of lunr.Index will not be created using this constructor, instead
* lunr.Builder should be used to construct new indexes, or lunr.Index.load should be
* used to load previously built and serialized indexes.
*
* @constructor
* @param {Object} attrs - The attributes of the built search index.
* @param {Object} attrs.invertedIndex - An index of term/field to document reference.
* @param {Object<string, lunr.Vector>} attrs.documentVectors - Document vectors keyed by document reference.
* @param {lunr.TokenSet} attrs.tokenSet - An set of all corpus tokens.
* @param {string[]} attrs.fields - The names of indexed document fields.
* @param {lunr.Pipeline} attrs.pipeline - The pipeline to use for search terms.
*/
lunr.Index = function (attrs) {
this.invertedIndex = attrs.invertedIndex
this.fieldVectors = attrs.fieldVectors
this.tokenSet = attrs.tokenSet
this.fields = attrs.fields
this.pipeline = attrs.pipeline
}
/**
* A result contains details of a document matching a search query.
* @typedef {Object} lunr.Index~Result
* @property {string} ref - The reference of the document this result represents.
* @property {number} score - A number between 0 and 1 representing how similar this document is to the query.
* @property {lunr.MatchData} matchData - Contains metadata about this match including which term(s) caused the match.
*/
/**
* Although lunr provides the ability to create queries using lunr.Query, it also provides a simple
* query language which itself is parsed into an instance of lunr.Query.
*
* For programmatically building queries it is advised to directly use lunr.Query, the query language
* is best used for human entered text rather than program generated text.
*
* At its simplest queries can just be a single term, e.g. `hello`, multiple terms are also supported
* and will be combined with OR, e.g `hello world` will match documents that contain either 'hello'
* or 'world', though those that contain both will rank higher in the results.
*
* Wildcards can be included in terms to match one or more unspecified characters, these wildcards can
* be inserted anywhere within the term, and more than one wildcard can exist in a single term. Adding
* wildcards will increase the number of documents that will be found but can also have a negative
* impact on query performance, especially with wildcards at the beginning of a term.
*
* Terms can be restricted to specific fields, e.g. `title:hello`, only documents with the term
* hello in the title field will match this query. Using a field not present in the index will lead
* to an error being thrown.
*
* Modifiers can also be added to terms, lunr supports edit distance and boost modifiers on terms. A term
* boost will make documents matching that term score higher, e.g. `foo^5`. Edit distance is also supported
* to provide fuzzy matching, e.g. 'hello~2' will match documents with hello with an edit distance of 2.
* Avoid large values for edit distance to improve query performance.
*
* To escape special characters the backslash character '\' can be used, this allows searches to include
* characters that would normally be considered modifiers, e.g. `foo\~2` will search for a term "foo~2" instead
* of attempting to apply a boost of 2 to the search term "foo".
*
* @typedef {string} lunr.Index~QueryString
* @example <caption>Simple single term query</caption>
* hello
* @example <caption>Multiple term query</caption>
* hello world
* @example <caption>term scoped to a field</caption>
* title:hello
* @example <caption>term with a boost of 10</caption>
* hello^10
* @example <caption>term with an edit distance of 2</caption>
* hello~2
*/
/**
* Performs a search against the index using lunr query syntax.
*
* Results will be returned sorted by their score, the most relevant results
* will be returned first.
*
* For more programmatic querying use lunr.Index#query.
*
* @param {lunr.Index~QueryString} queryString - A string containing a lunr query.
* @throws {lunr.QueryParseError} If the passed query string cannot be parsed.
* @returns {lunr.Index~Result[]}
*/
lunr.Index.prototype.search = function (queryString) {
return this.query(function (query) {
var parser = new lunr.QueryParser(queryString, query)
parser.parse()
})
}
/**
* A query builder callback provides a query object to be used to express
* the query to perform on the index.
*
* @callback lunr.Index~queryBuilder
* @param {lunr.Query} query - The query object to build up.
* @this lunr.Query
*/
/**
* Performs a query against the index using the yielded lunr.Query object.
*
* If performing programmatic queries against the index, this method is preferred
* over lunr.Index#search so as to avoid the additional query parsing overhead.
*
* A query object is yielded to the supplied function which should be used to
* express the query to be run against the index.
*
* Note that although this function takes a callback parameter it is _not_ an
* asynchronous operation, the callback is just yielded a query object to be
* customized.
*
* @param {lunr.Index~queryBuilder} fn - A function that is used to build the query.
* @returns {lunr.Index~Result[]}
*/
lunr.Index.prototype.query = function (fn) {
// for each query clause
// * process terms
// * expand terms from token set
// * find matching documents and metadata
// * get document vectors
// * score documents
var query = new lunr.Query(this.fields),
matchingFields = Object.create(null),
queryVectors = Object.create(null)
fn.call(query, query)
for (var i = 0; i < query.clauses.length; i++) {
/*
* Unless the pipeline has been disabled for this term, which is
* the case for terms with wildcards, we need to pass the clause
* term through the search pipeline. A pipeline returns an array
* of processed terms. Pipeline functions may expand the passed
* term, which means we may end up performing multiple index lookups
* for a single query term.
*/
var clause = query.clauses[i],
terms = null
if (clause.usePipeline) {
terms = this.pipeline.runString(clause.term)
} else {
terms = [clause.term]
}
for (var m = 0; m < terms.length; m++) {
var term = terms[m]
/*
* Each term returned from the pipeline needs to use the same query
* clause object, e.g. the same boost and or edit distance. The
* simplest way to do this is to re-use the clause object but mutate
* its term property.
*/
clause.term = term
/*
* From the term in the clause we create a token set which will then
* be used to intersect the indexes token set to get a list of terms
* to lookup in the inverted index
*/
var termTokenSet = lunr.TokenSet.fromClause(clause),
expandedTerms = this.tokenSet.intersect(termTokenSet).toArray()
for (var j = 0; j < expandedTerms.length; j++) {
/*
* For each term get the posting and termIndex, this is required for
* building the query vector.
*/
var expandedTerm = expandedTerms[j],
posting = this.invertedIndex[expandedTerm],
termIndex = posting._index
for (var k = 0; k < clause.fields.length; k++) {
/*
* For each field that this query term is scoped by (by default
* all fields are in scope) we need to get all the document refs
* that have this term in that field.
*
* The posting is the entry in the invertedIndex for the matching
* term from above.
*/
var field = clause.fields[k],
fieldPosting = posting[field],
matchingDocumentRefs = Object.keys(fieldPosting)
/*
* To support field level boosts a query vector is created per
* field. This vector is populated using the termIndex found for
* the term and a unit value with the appropriate boost applied.
*
* If the query vector for this field does not exist yet it needs
* to be created.
*/
if (!(field in queryVectors)) {
queryVectors[field] = new lunr.Vector
}
/*
* Using upsert because there could already be an entry in the vector
* for the term we are working with. In that case we just add the scores
* together.
*/
queryVectors[field].upsert(termIndex, 1 * clause.boost, function (a, b) { return a + b })
for (var l = 0; l < matchingDocumentRefs.length; l++) {
/*
* All metadata for this term/field/document triple
* are then extracted and collected into an instance
* of lunr.MatchData ready to be returned in the query
* results
*/
var matchingDocumentRef = matchingDocumentRefs[l],
matchingFieldRef = new lunr.FieldRef (matchingDocumentRef, field),
documentMetadata, matchData
documentMetadata = fieldPosting[matchingDocumentRef]
matchData = new lunr.MatchData (expandedTerm, field, documentMetadata)
if (matchingFieldRef in matchingFields) {
matchingFields[matchingFieldRef].combine(matchData)
} else {
matchingFields[matchingFieldRef] = matchData
}
}
}
}
}
}
var matchingFieldRefs = Object.keys(matchingFields),
results = {}
for (var i = 0; i < matchingFieldRefs.length; i++) {
/*
* Currently we have document fields that match the query, but we
* need to return documents. The matchData and scores are combined
* from multiple fields belonging to the same document.
*
* Scores are calculated by field, using the query vectors created
* above, and combined into a final document score using addition.
*/
var fieldRef = lunr.FieldRef.fromString(matchingFieldRefs[i]),
docRef = fieldRef.docRef,
fieldVector = this.fieldVectors[fieldRef],
score = queryVectors[fieldRef.fieldName].similarity(fieldVector)
if (docRef in results) {
results[docRef].score += score
results[docRef].matchData.combine(matchingFields[fieldRef])
} else {
results[docRef] = {
ref: docRef,
score: score,
matchData: matchingFields[fieldRef]
}
}
}
/*
* The results object needs to be converted into a list
* of results, sorted by score before being returned.
*/
return Object.keys(results)
.map(function (key) {
return results[key]
})
.sort(function (a, b) {
return b.score - a.score
})
}
/**
* Prepares the index for JSON serialization.
*
* The schema for this JSON blob will be described in a
* separate JSON schema file.
*
* @returns {Object}
*/
lunr.Index.prototype.toJSON = function () {
var invertedIndex = Object.keys(this.invertedIndex)
.sort()
.map(function (term) {
return [term, this.invertedIndex[term]]
}, this)
var fieldVectors = Object.keys(this.fieldVectors)
.map(function (ref) {
return [ref, this.fieldVectors[ref].toJSON()]
}, this)
return {
version: lunr.version,
fields: this.fields,
fieldVectors: fieldVectors,
invertedIndex: invertedIndex,
pipeline: this.pipeline.toJSON()
}
}
/**
* Loads a previously serialized lunr.Index
*
* @param {Object} serializedIndex - A previously serialized lunr.Index
* @returns {lunr.Index}
*/
lunr.Index.load = function (serializedIndex) {
var attrs = {},
fieldVectors = {},
serializedVectors = serializedIndex.fieldVectors,
invertedIndex = {},
serializedInvertedIndex = serializedIndex.invertedIndex,
tokenSetBuilder = new lunr.TokenSet.Builder,
pipeline = lunr.Pipeline.load(serializedIndex.pipeline)
if (serializedIndex.version != lunr.version) {
lunr.utils.warn("Version mismatch when loading serialised index. Current version of lunr '" + lunr.version + "' does not match serialized index '" + serializedIndex.version + "'")
}
for (var i = 0; i < serializedVectors.length; i++) {
var tuple = serializedVectors[i],
ref = tuple[0],
elements = tuple[1]
fieldVectors[ref] = new lunr.Vector(elements)
}
for (var i = 0; i < serializedInvertedIndex.length; i++) {
var tuple = serializedInvertedIndex[i],
term = tuple[0],
posting = tuple[1]
tokenSetBuilder.insert(term)
invertedIndex[term] = posting
}
tokenSetBuilder.finish()
attrs.fields = serializedIndex.fields
attrs.fieldVectors = fieldVectors
attrs.invertedIndex = invertedIndex
attrs.tokenSet = tokenSetBuilder.root
attrs.pipeline = pipeline
return new lunr.Index(attrs)
}
/*!
* lunr.Builder
* Copyright (C) 2017 Oliver Nightingale
*/
/**
* lunr.Builder performs indexing on a set of documents and
* returns instances of lunr.Index ready for querying.
*
* All configuration of the index is done via the builder, the
* fields to index, the document reference, the text processing
* pipeline and document scoring parameters are all set on the
* builder before indexing.
*
* @constructor
* @property {string} _ref - Internal reference to the document reference field.
* @property {string[]} _fields - Internal reference to the document fields to index.
* @property {object} invertedIndex - The inverted index maps terms to document fields.
* @property {object} documentTermFrequencies - Keeps track of document term frequencies.
* @property {object} documentLengths - Keeps track of the length of documents added to the index.
* @property {lunr.tokenizer} tokenizer - Function for splitting strings into tokens for indexing.
* @property {lunr.Pipeline} pipeline - The pipeline performs text processing on tokens before indexing.
* @property {lunr.Pipeline} searchPipeline - A pipeline for processing search terms before querying the index.
* @property {number} documentCount - Keeps track of the total number of documents indexed.
* @property {number} _b - A parameter to control field length normalization, setting this to 0 disabled normalization, 1 fully normalizes field lengths, the default value is 0.75.
* @property {number} _k1 - A parameter to control how quickly an increase in term frequency results in term frequency saturation, the default value is 1.2.
* @property {number} termIndex - A counter incremented for each unique term, used to identify a terms position in the vector space.
* @property {array} metadataWhitelist - A list of metadata keys that have been whitelisted for entry in the index.
*/
lunr.Builder = function () {
this._ref = "id"
this._fields = []
this.invertedIndex = Object.create(null)
this.fieldTermFrequencies = {}
this.fieldLengths = {}
this.tokenizer = lunr.tokenizer
this.pipeline = new lunr.Pipeline
this.searchPipeline = new lunr.Pipeline
this.documentCount = 0
this._b = 0.75
this._k1 = 1.2
this.termIndex = 0
this.metadataWhitelist = []
}
/**
* Sets the document field used as the document reference. Every document must have this field.
* The type of this field in the document should be a string, if it is not a string it will be
* coerced into a string by calling toString.
*
* The default ref is 'id'.
*
* The ref should _not_ be changed during indexing, it should be set before any documents are
* added to the index. Changing it during indexing can lead to inconsistent results.
*
* @param {string} ref - The name of the reference field in the document.
*/
lunr.Builder.prototype.ref = function (ref) {
this._ref = ref
}
/**
* Adds a field to the list of document fields that will be indexed. Every document being
* indexed should have this field. Null values for this field in indexed documents will
* not cause errors but will limit the chance of that document being retrieved by searches.
*
* All fields should be added before adding documents to the index. Adding fields after
* a document has been indexed will have no effect on already indexed documents.
*
* @param {string} field - The name of a field to index in all documents.
*/
lunr.Builder.prototype.field = function (field) {
this._fields.push(field)
}
/**
* A parameter to tune the amount of field length normalisation that is applied when
* calculating relevance scores. A value of 0 will completely disable any normalisation
* and a value of 1 will fully normalise field lengths. The default is 0.75. Values of b
* will be clamped to the range 0 - 1.
*
* @param {number} number - The value to set for this tuning parameter.
*/
lunr.Builder.prototype.b = function (number) {
if (number < 0) {
this._b = 0
} else if (number > 1) {
this._b = 1
} else {
this._b = number
}
}
/**
* A parameter that controls the speed at which a rise in term frequency results in term
* frequency saturation. The default value is 1.2. Setting this to a higher value will give
* slower saturation levels, a lower value will result in quicker saturation.
*
* @param {number} number - The value to set for this tuning parameter.
*/
lunr.Builder.prototype.k1 = function (number) {
this._k1 = number
}
/**
* Adds a document to the index.
*
* Before adding fields to the index the index should have been fully setup, with the document
* ref and all fields to index already having been specified.
*
* The document must have a field name as specified by the ref (by default this is 'id') and
* it should have all fields defined for indexing, though null or undefined values will not
* cause errors.
*
* @param {object} doc - The document to add to the index.
*/
lunr.Builder.prototype.add = function (doc) {
var docRef = doc[this._ref]
this.documentCount += 1
for (var i = 0; i < this._fields.length; i++) {
var fieldName = this._fields[i],
field = doc[fieldName],
tokens = this.tokenizer(field),
terms = this.pipeline.run(tokens),
fieldRef = new lunr.FieldRef (docRef, fieldName),
fieldTerms = Object.create(null)
this.fieldTermFrequencies[fieldRef] = fieldTerms
this.fieldLengths[fieldRef] = 0
// store the length of this field for this document
this.fieldLengths[fieldRef] += terms.length
// calculate term frequencies for this field
for (var j = 0; j < terms.length; j++) {
var term = terms[j]
if (fieldTerms[term] == undefined) {
fieldTerms[term] = 0
}
fieldTerms[term] += 1
// add to inverted index
// create an initial posting if one doesn't exist
if (this.invertedIndex[term] == undefined) {
var posting = Object.create(null)
posting["_index"] = this.termIndex
this.termIndex += 1
for (var k = 0; k < this._fields.length; k++) {
posting[this._fields[k]] = Object.create(null)
}
this.invertedIndex[term] = posting
}
// add an entry for this term/fieldName/docRef to the invertedIndex
if (this.invertedIndex[term][fieldName][docRef] == undefined) {
this.invertedIndex[term][fieldName][docRef] = Object.create(null)
}
// store all whitelisted metadata about this token in the
// inverted index
for (var l = 0; l < this.metadataWhitelist.length; l++) {
var metadataKey = this.metadataWhitelist[l],
metadata = term.metadata[metadataKey]
if (this.invertedIndex[term][fieldName][docRef][metadataKey] == undefined) {
this.invertedIndex[term][fieldName][docRef][metadataKey] = []
}
this.invertedIndex[term][fieldName][docRef][metadataKey].push(metadata)
}
}
}
}
/**
* Calculates the average document length for this index
*
* @private
*/
lunr.Builder.prototype.calculateAverageFieldLengths = function () {
var fieldRefs = Object.keys(this.fieldLengths),
numberOfFields = fieldRefs.length,
accumulator = {},
documentsWithField = {}
for (var i = 0; i < numberOfFields; i++) {
var fieldRef = lunr.FieldRef.fromString(fieldRefs[i]),
field = fieldRef.fieldName
documentsWithField[field] || (documentsWithField[field] = 0)
documentsWithField[field] += 1
accumulator[field] || (accumulator[field] = 0)
accumulator[field] += this.fieldLengths[fieldRef]
}
for (var i = 0; i < this._fields.length; i++) {
var field = this._fields[i]
accumulator[field] = accumulator[field] / documentsWithField[field]
}
this.averageFieldLength = accumulator
}
/**
* Builds a vector space model of every document using lunr.Vector
*
* @private
*/
lunr.Builder.prototype.createFieldVectors = function () {
var fieldVectors = {},
fieldRefs = Object.keys(this.fieldTermFrequencies),
fieldRefsLength = fieldRefs.length
for (var i = 0; i < fieldRefsLength; i++) {
var fieldRef = lunr.FieldRef.fromString(fieldRefs[i]),
field = fieldRef.fieldName,
fieldLength = this.fieldLengths[fieldRef],
fieldVector = new lunr.Vector,
termFrequencies = this.fieldTermFrequencies[fieldRef],
terms = Object.keys(termFrequencies),
termsLength = terms.length
for (var j = 0; j < termsLength; j++) {
var term = terms[j],
tf = termFrequencies[term],
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.
fieldVector.insert(termIndex, scoreWithPrecision)
}
fieldVectors[fieldRef] = fieldVector
}
this.fieldVectors = fieldVectors
}
/**
* Creates a token set of all tokens in the index using lunr.TokenSet
*
* @private
*/
lunr.Builder.prototype.createTokenSet = function () {
this.tokenSet = lunr.TokenSet.fromArray(
Object.keys(this.invertedIndex).sort()
)
}
/**
* Builds the index, creating an instance of lunr.Index.
*
* This completes the indexing process and should only be called
* once all documents have been added to the index.
*
* @private
* @returns {lunr.Index}
*/
lunr.Builder.prototype.build = function () {
this.calculateAverageFieldLengths()
this.createFieldVectors()
this.createTokenSet()
return new lunr.Index({
invertedIndex: this.invertedIndex,
fieldVectors: this.fieldVectors,
tokenSet: this.tokenSet,
fields: this._fields,
pipeline: this.searchPipeline
})
}
/**
* Applies a plugin to the index builder.
*
* A plugin is a function that is called with the index builder as its context.
* Plugins can be used to customise or extend the behaviour of the index
* in some way. A plugin is just a function, that encapsulated the custom
* behaviour that should be applied when building the index.
*
* The plugin function will be called with the index builder as its argument, additional
* arguments can also be passed when calling use. The function will be called
* with the index builder as its context.
*
* @param {Function} plugin The plugin to apply.
*/
lunr.Builder.prototype.use = function (fn) {
var args = Array.prototype.slice.call(arguments, 1)
args.unshift(this)
fn.apply(this, args)
}
/**
* Contains and collects metadata about a matching document.
* A single instance of lunr.MatchData is returned as part of every
* lunr.Index~Result.
*
* @constructor
* @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
* @property {object} metadata - A cloned collection of metadata associated with this document.
* @see {@link lunr.Index~Result}
*/
lunr.MatchData = function (term, field, metadata) {
var clonedMetadata = Object.create(null),
metadataKeys = Object.keys(metadata)
// Cloning the metadata to prevent the original
// being mutated during match data combination.
// Metadata is kept in an array within the inverted
// index so cloning the data can be done with
// Array#slice
for (var i = 0; i < metadataKeys.length; i++) {
var key = metadataKeys[i]
clonedMetadata[key] = metadata[key].slice()
}
this.metadata = Object.create(null)
this.metadata[term] = Object.create(null)
this.metadata[term][field] = clonedMetadata
}
/**
* An instance of lunr.MatchData will be created for every term that matches a
* document. However only one instance is required in a lunr.Index~Result. This
* method combines metadata from another instance of lunr.MatchData with this
* objects metadata.
*
* @param {lunr.MatchData} otherMatchData - Another instance of match data to merge with this one.
* @see {@link lunr.Index~Result}
*/
lunr.MatchData.prototype.combine = function (otherMatchData) {
var terms = Object.keys(otherMatchData.metadata)
for (var i = 0; i < terms.length; i++) {
var term = terms[i],
fields = Object.keys(otherMatchData.metadata[term])
if (this.metadata[term] == undefined) {
this.metadata[term] = Object.create(null)
}
for (var j = 0; j < fields.length; j++) {
var field = fields[j],
keys = Object.keys(otherMatchData.metadata[term][field])
if (this.metadata[term][field] == undefined) {
this.metadata[term][field] = Object.create(null)
}
for (var k = 0; k < keys.length; k++) {
var key = keys[k]
if (this.metadata[term][field][key] == undefined) {
this.metadata[term][field][key] = otherMatchData.metadata[term][field][key]
} else {
this.metadata[term][field][key] = this.metadata[term][field][key].concat(otherMatchData.metadata[term][field][key])
}
}
}
}
}
/**
* A lunr.Query provides a programmatic way of defining queries to be performed
* against a {@link lunr.Index}.
*
* Prefer constructing a lunr.Query using the {@link lunr.Index#query} method
* so the query object is pre-initialized with the right index fields.
*
* @constructor
* @property {lunr.Query~Clause[]} clauses - An array of query clauses.
* @property {string[]} allFields - An array of all available fields in a lunr.Index.
*/
lunr.Query = function (allFields) {
this.clauses = []
this.allFields = allFields
}
/**
* Constants for indicating what kind of automatic wildcard insertion will be used when constructing a query clause.
*
* This allows wildcards to be added to the beginning and end of a term without having to manually do any string
* concatenation.
*
* The wildcard constants can be bitwise combined to select both leading and trailing wildcards.
*
* @constant
* @default
* @property {number} wildcard.NONE - The term will have no wildcards inserted, this is the default behaviour
* @property {number} wildcard.LEADING - Prepend the term with a wildcard, unless a leading wildcard already exists
* @property {number} wildcard.TRAILING - Append a wildcard to the term, unless a trailing wildcard already exists
* @see lunr.Query~Clause
* @see lunr.Query#clause
* @see lunr.Query#term
* @example <caption>query term with trailing wildcard</caption>
* query.term('foo', { wildcard: lunr.Query.wildcard.TRAILING })
* @example <caption>query term with leading and trailing wildcard</caption>
* query.term('foo', {
* wildcard: lunr.Query.wildcard.LEADING | lunr.Query.wildcard.TRAILING
* })
*/
lunr.Query.wildcard = new String ("*")
lunr.Query.wildcard.NONE = 0
lunr.Query.wildcard.LEADING = 1
lunr.Query.wildcard.TRAILING = 2
/**
* A single clause in a {@link lunr.Query} contains a term and details on how to
* match that term against a {@link lunr.Index}.
*
* @typedef {Object} lunr.Query~Clause
* @property {string[]} fields - The fields in an index this clause should be matched against.
* @property {number} [boost=1] - Any boost that should be applied when matching this clause.
* @property {number} [editDistance] - Whether the term should have fuzzy matching applied, and how fuzzy the match should be.
* @property {boolean} [usePipeline] - Whether the term should be passed through the search pipeline.
* @property {number} [wildcard=0] - Whether the term should have wildcards appended or prepended.
*/
/**
* Adds a {@link lunr.Query~Clause} to this query.
*
* Unless the clause contains the fields to be matched all fields will be matched. In addition
* a default boost of 1 is applied to the clause.
*
* @param {lunr.Query~Clause} clause - The clause to add to this query.
* @see lunr.Query~Clause
* @returns {lunr.Query}
*/
lunr.Query.prototype.clause = function (clause) {
if (!('fields' in clause)) {
clause.fields = this.allFields
}
if (!('boost' in clause)) {
clause.boost = 1
}
if (!('usePipeline' in clause)) {
clause.usePipeline = true
}
if (!('wildcard' in clause)) {
clause.wildcard = lunr.Query.wildcard.NONE
}
if ((clause.wildcard & lunr.Query.wildcard.LEADING) && (clause.term.charAt(0) != lunr.Query.wildcard)) {
clause.term = "*" + clause.term
}
if ((clause.wildcard & lunr.Query.wildcard.TRAILING) && (clause.term.slice(-1) != lunr.Query.wildcard)) {
clause.term = "" + clause.term + "*"
}
this.clauses.push(clause)
return this
}
/**
* Adds a term to the current query, under the covers this will create a {@link lunr.Query~Clause}
* to the list of clauses that make up this query.
*
* @param {string} term - The term to add to the query.
* @param {Object} [options] - Any additional properties to add to the query clause.
* @returns {lunr.Query}
* @see lunr.Query#clause
* @see lunr.Query~Clause
* @example <caption>adding a single term to a query</caption>
* query.term("foo")
* @example <caption>adding a single term to a query and specifying search fields, term boost and automatic trailing wildcard</caption>
* query.term("foo", {
* fields: ["title"],
* boost: 10,
* wildcard: lunr.Query.wildcard.TRAILING
* })
*/
lunr.Query.prototype.term = function (term, options) {
var clause = options || {}
clause.term = term
this.clause(clause)
return this
}
lunr.QueryParseError = function (message, start, end) {
this.name = "QueryParseError"
this.message = message
this.start = start
this.end = end
}
lunr.QueryParseError.prototype = new Error
lunr.QueryLexer = function (str) {
this.lexemes = []
this.str = str
this.length = str.length
this.pos = 0
this.start = 0
this.escapeCharPositions = []
}
lunr.QueryLexer.prototype.run = function () {
var state = lunr.QueryLexer.lexText
while (state) {
state = state(this)
}
}
lunr.QueryLexer.prototype.sliceString = function () {
var subSlices = [],
sliceStart = this.start,
sliceEnd = this.pos
for (var i = 0; i < this.escapeCharPositions.length; i++) {
sliceEnd = this.escapeCharPositions[i]
subSlices.push(this.str.slice(sliceStart, sliceEnd))
sliceStart = sliceEnd + 1
}
subSlices.push(this.str.slice(sliceStart, this.pos))
this.escapeCharPositions.length = 0
return subSlices.join('')
}
lunr.QueryLexer.prototype.emit = function (type) {
this.lexemes.push({
type: type,
str: this.sliceString(),
start: this.start,
end: this.pos
})
this.start = this.pos
}
lunr.QueryLexer.prototype.escapeCharacter = function () {
this.escapeCharPositions.push(this.pos - 1)
this.pos += 1
}
lunr.QueryLexer.prototype.next = function () {
if (this.pos >= this.length) {
return lunr.QueryLexer.EOS
}
var char = this.str.charAt(this.pos)
this.pos += 1
return char
}
lunr.QueryLexer.prototype.width = function () {
return this.pos - this.start
}
lunr.QueryLexer.prototype.ignore = function () {
if (this.start == this.pos) {
this.pos += 1
}
this.start = this.pos
}
lunr.QueryLexer.prototype.backup = function () {
this.pos -= 1
}
lunr.QueryLexer.prototype.acceptDigitRun = function () {
var char, charCode
do {
char = this.next()
charCode = char.charCodeAt(0)
} while (charCode > 47 && charCode < 58)
if (char != lunr.QueryLexer.EOS) {
this.backup()
}
}
lunr.QueryLexer.prototype.more = function () {
return this.pos < this.length
}
lunr.QueryLexer.EOS = 'EOS'
lunr.QueryLexer.FIELD = 'FIELD'
lunr.QueryLexer.TERM = 'TERM'
lunr.QueryLexer.EDIT_DISTANCE = 'EDIT_DISTANCE'
lunr.QueryLexer.BOOST = 'BOOST'
lunr.QueryLexer.lexField = function (lexer) {
lexer.backup()
lexer.emit(lunr.QueryLexer.FIELD)
lexer.ignore()
return lunr.QueryLexer.lexText
}
lunr.QueryLexer.lexTerm = function (lexer) {
if (lexer.width() > 1) {
lexer.backup()
lexer.emit(lunr.QueryLexer.TERM)
}
lexer.ignore()
if (lexer.more()) {
return lunr.QueryLexer.lexText
}
}
lunr.QueryLexer.lexEditDistance = function (lexer) {
lexer.ignore()
lexer.acceptDigitRun()
lexer.emit(lunr.QueryLexer.EDIT_DISTANCE)
return lunr.QueryLexer.lexText
}
lunr.QueryLexer.lexBoost = function (lexer) {
lexer.ignore()
lexer.acceptDigitRun()
lexer.emit(lunr.QueryLexer.BOOST)
return lunr.QueryLexer.lexText
}
lunr.QueryLexer.lexEOS = function (lexer) {
if (lexer.width() > 0) {
lexer.emit(lunr.QueryLexer.TERM)
}
}
// This matches the separator used when tokenising fields
// within a document. These should match otherwise it is
// not possible to search for some tokens within a document.
//
// It is possible for the user to change the separator on the
// tokenizer so it _might_ clash with any other of the special
// characters already used within the search string, e.g. :.
//
// This means that it is possible to change the separator in
// such a way that makes some words unsearchable using a search
// string.
lunr.QueryLexer.termSeparator = lunr.tokenizer.separator
lunr.QueryLexer.lexText = function (lexer) {
while (true) {
var char = lexer.next()
if (char == lunr.QueryLexer.EOS) {
return lunr.QueryLexer.lexEOS
}
// Escape character is '\'
if (char.charCodeAt(0) == 92) {
lexer.escapeCharacter()
continue
}
if (char == ":") {
return lunr.QueryLexer.lexField
}
if (char == "~") {
lexer.backup()
if (lexer.width() > 0) {
lexer.emit(lunr.QueryLexer.TERM)
}
return lunr.QueryLexer.lexEditDistance
}
if (char == "^") {
lexer.backup()
if (lexer.width() > 0) {
lexer.emit(lunr.QueryLexer.TERM)
}
return lunr.QueryLexer.lexBoost
}
if (char.match(lunr.QueryLexer.termSeparator)) {
return lunr.QueryLexer.lexTerm
}
}
}
lunr.QueryParser = function (str, query) {
this.lexer = new lunr.QueryLexer (str)
this.query = query
this.currentClause = {}
this.lexemeIdx = 0
}
lunr.QueryParser.prototype.parse = function () {
this.lexer.run()
this.lexemes = this.lexer.lexemes
var state = lunr.QueryParser.parseFieldOrTerm
while (state) {
state = state(this)
}
return this.query
}
lunr.QueryParser.prototype.peekLexeme = function () {
return this.lexemes[this.lexemeIdx]
}
lunr.QueryParser.prototype.consumeLexeme = function () {
var lexeme = this.peekLexeme()
this.lexemeIdx += 1
return lexeme
}
lunr.QueryParser.prototype.nextClause = function () {
var completedClause = this.currentClause
this.query.clause(completedClause)
this.currentClause = {}
}
lunr.QueryParser.parseFieldOrTerm = function (parser) {
var lexeme = parser.peekLexeme()
if (lexeme == undefined) {
return
}
switch (lexeme.type) {
case lunr.QueryLexer.FIELD:
return lunr.QueryParser.parseField
case lunr.QueryLexer.TERM:
return lunr.QueryParser.parseTerm
default:
var errorMessage = "expected either a field or a term, found " + lexeme.type
if (lexeme.str.length >= 1) {
errorMessage += " with value '" + lexeme.str + "'"
}
throw new lunr.QueryParseError (errorMessage, lexeme.start, lexeme.end)
}
}
lunr.QueryParser.parseField = function (parser) {
var lexeme = parser.consumeLexeme()
if (lexeme == undefined) {
return
}
if (parser.query.allFields.indexOf(lexeme.str) == -1) {
var possibleFields = parser.query.allFields.map(function (f) { return "'" + f + "'" }).join(', '),
errorMessage = "unrecognised field '" + lexeme.str + "', possible fields: " + possibleFields
throw new lunr.QueryParseError (errorMessage, lexeme.start, lexeme.end)
}
parser.currentClause.fields = [lexeme.str]
var nextLexeme = parser.peekLexeme()
if (nextLexeme == undefined) {
var errorMessage = "expecting term, found nothing"
throw new lunr.QueryParseError (errorMessage, lexeme.start, lexeme.end)
}
switch (nextLexeme.type) {
case lunr.QueryLexer.TERM:
return lunr.QueryParser.parseTerm
default:
var errorMessage = "expecting term, found '" + nextLexeme.type + "'"
throw new lunr.QueryParseError (errorMessage, nextLexeme.start, nextLexeme.end)
}
}
lunr.QueryParser.parseTerm = function (parser) {
var lexeme = parser.consumeLexeme()
if (lexeme == undefined) {
return
}
parser.currentClause.term = lexeme.str.toLowerCase()
if (lexeme.str.indexOf("*") != -1) {
parser.currentClause.usePipeline = false
}
var nextLexeme = parser.peekLexeme()
if (nextLexeme == undefined) {
parser.nextClause()
return
}
switch (nextLexeme.type) {
case lunr.QueryLexer.TERM:
parser.nextClause()
return lunr.QueryParser.parseTerm
case lunr.QueryLexer.FIELD:
parser.nextClause()
return lunr.QueryParser.parseField
case lunr.QueryLexer.EDIT_DISTANCE:
return lunr.QueryParser.parseEditDistance
case lunr.QueryLexer.BOOST:
return lunr.QueryParser.parseBoost
default:
var errorMessage = "Unexpected lexeme type '" + nextLexeme.type + "'"
throw new lunr.QueryParseError (errorMessage, nextLexeme.start, nextLexeme.end)
}
}
lunr.QueryParser.parseEditDistance = function (parser) {
var lexeme = parser.consumeLexeme()
if (lexeme == undefined) {
return
}
var editDistance = parseInt(lexeme.str, 10)
if (isNaN(editDistance)) {
var errorMessage = "edit distance must be numeric"
throw new lunr.QueryParseError (errorMessage, lexeme.start, lexeme.end)
}
parser.currentClause.editDistance = editDistance
var nextLexeme = parser.peekLexeme()
if (nextLexeme == undefined) {
parser.nextClause()
return
}
switch (nextLexeme.type) {
case lunr.QueryLexer.TERM:
parser.nextClause()
return lunr.QueryParser.parseTerm
case lunr.QueryLexer.FIELD:
parser.nextClause()
return lunr.QueryParser.parseField
case lunr.QueryLexer.EDIT_DISTANCE:
return lunr.QueryParser.parseEditDistance
case lunr.QueryLexer.BOOST:
return lunr.QueryParser.parseBoost
default:
var errorMessage = "Unexpected lexeme type '" + nextLexeme.type + "'"
throw new lunr.QueryParseError (errorMessage, nextLexeme.start, nextLexeme.end)
}
}
lunr.QueryParser.parseBoost = function (parser) {
var lexeme = parser.consumeLexeme()
if (lexeme == undefined) {
return
}
var boost = parseInt(lexeme.str, 10)
if (isNaN(boost)) {
var errorMessage = "boost must be numeric"
throw new lunr.QueryParseError (errorMessage, lexeme.start, lexeme.end)
}
parser.currentClause.boost = boost
var nextLexeme = parser.peekLexeme()
if (nextLexeme == undefined) {
parser.nextClause()
return
}
switch (nextLexeme.type) {
case lunr.QueryLexer.TERM:
parser.nextClause()
return lunr.QueryParser.parseTerm
case lunr.QueryLexer.FIELD:
parser.nextClause()
return lunr.QueryParser.parseField
case lunr.QueryLexer.EDIT_DISTANCE:
return lunr.QueryParser.parseEditDistance
case lunr.QueryLexer.BOOST:
return lunr.QueryParser.parseBoost
default:
var errorMessage = "Unexpected lexeme type '" + nextLexeme.type + "'"
throw new lunr.QueryParseError (errorMessage, nextLexeme.start, nextLexeme.end)
}
}
/**
* export the module via AMD, CommonJS or as a browser global
* Export code from https://github.com/umdjs/umd/blob/master/returnExports.js
*/
;(function (root, factory) {
if (typeof define === 'function' && define.amd) {
// AMD. Register as an anonymous module.
define(factory)
} else if (typeof exports === 'object') {
/**
* Node. Does not work with strict CommonJS, but
* only CommonJS-like enviroments that support module.exports,
* like Node.
*/
module.exports = factory()
} else {
// Browser globals (root is window)
root.lunr = factory()
}
}(this, function () {
/**
* Just return a value to define the module export.
* This example returns an object, but the module
* can return a function as the exported value.
*/
return lunr
}))
})();