lunr.js

/**
 * lunr - http://lunrjs.com - A bit like Solr, but much smaller and not as bright - 2.0.0-alpha.1+1474820138
 * Copyright (C) 2016 Oliver Nightingale
 * MIT Licensed
 * @license
 */

;(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)
  return builder.build()
}
/*!
 * lunr.utils
 * Copyright (C) 2016 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()
  }
}
/**
 * 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
  }

  return (documentCount - documentsWithTerm + 0.5) / (documentsWithTerm + 0.5)
}

/**
 * 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) 2016 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) 2016 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 = {}

/**
 * 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) 2016 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 || []
}

/**
 * Inserts an element at an 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.
 */
lunr.Vector.prototype.insert = function (insertIdx, val) {
  this._magnitude = 0

  if (this.elements.length == 0) {
    this.elements.push(insertIdx, val)
    return
  }

  var start = 0,
      end = this.elements.length,
      sliceLength = end - start,
      pivot = Math.floor((sliceLength / 2) / 2) * 2,
      pivotIdx = this.elements[pivot]

  while (sliceLength > 2) {
    if (pivotIdx == insertIdx) {
      throw "duplicate index"
    }

    if (insertIdx > pivotIdx) {
      start = pivot
    }

    if (insertIdx < pivotIdx) {
      end = pivot
    }

    sliceLength = end - start
    pivot = start + Math.floor((sliceLength / 2) / 2) * 2
    pivotIdx = this.elements[pivot]
  }

  if (pivotIdx > insertIdx) {
    this.elements.splice(pivot, 0, insertIdx, val)
  }

  if (pivotIdx < insertIdx) {
    this.elements.splice(pivot + 2, 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) 2016 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) 2016 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) 2016 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) 2016 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 = {}
}

/**
 * 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),
      len = labels.length

  for (var i = 0; i < len; i++) {
    var label = labels[i],
        node = this.edges[label]

    str = str + label + node.toString()
  }

  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) 2016 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 {number} attrs.documentCount - The total number of documents held in the index.
 * @param {number} attrs.averageDocumentLength - The average length of all documents in the index.
 * @param {number} attrs.b - A parameter for the document scoring algorithm.
 * @param {number} attrs.k1 - A parameter for the document scoring algorithm.
 * @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.documentVectors = attrs.documentVectors
  this.tokenSet = attrs.tokenSet
  this.documentCount = attrs.documentCount
  this.averageDocumentLength = attrs.averageDocumentLength
  this.b = attrs.b
  this.k1 = attrs.k1
  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.
 *
 * @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),
      matchingDocuments = {},
      queryVector = new lunr.Vector

  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 calculate the score as the term relates to the
         * query using the same calculation used to score documents during
         * indexing. This score will be used to build a vector space
         * representation  of the query.
         *
         * Also need to discover the terms index to insert into the query
         * vector at the right position
         */
        var expandedTerm = expandedTerms[j],
            posting = this.invertedIndex[expandedTerm],
            termIndex = posting._index,
            idf = lunr.idf(posting, this.documentCount),
            tf = 1,
            score = idf * ((this.k1 + 1) * tf) / (this.k1 * (1 - this.b + this.b * (query.clauses.length / this.averageDocumentLength)) + tf)

        /*
         * Inserting the found query term, along with its term index
         * into the vector representing the query. It is here that
         * any boosts are applied to the score. They could have been
         * applied when calculating the score above, but that expression
         * is already quite busy.
         */
        queryVector.insert(termIndex, score * clause.boost)

        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)

          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],
                documentMetadata, matchData

            documentMetadata = fieldPosting[matchingDocumentRef]
            matchData = new lunr.MatchData (expandedTerm, field, documentMetadata)

            if (matchingDocumentRef in matchingDocuments) {
              matchingDocuments[matchingDocumentRef].combine(matchData)
            } else {
              matchingDocuments[matchingDocumentRef] = matchData
            }

          }
        }
      }
    }
  }

  var matchingDocumentRefs = Object.keys(matchingDocuments),
      results = []

  for (var i = 0; i < matchingDocumentRefs.length; i++) {
    /*
     * With all the matching documents found they now need
     * to be sorted by their relevance to the query. This
     * is done by retrieving the documents vector representation
     * and then finding its similarity with the query vector
     * that was constructed earlier.
     *
     * This score, along with the document ref and any metadata
     * we collected into a lunr.MatchData instance are stored
     * in the results array ready for returning to the caller
     */
    var ref = matchingDocumentRefs[i],
        documentVector = this.documentVectors[ref],
        score = queryVector.similarity(documentVector)

    results.push({
      ref: ref,
      score: score,
      matchData: matchingDocuments[ref]
    })
  }

  return results.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 documentVectors = Object.keys(this.documentVectors)
    .map(function (ref) {
      return [ref, this.documentVectors[ref].toJSON()]
    }, this)

  return {
    version: lunr.version,
    averageDocumentLength: this.averageDocumentLength,
    b: this.b,
    k1: this.k1,
    fields: this.fields,
    documentVectors: documentVectors,
    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 = {},
      documentVectors = {},
      serializedVectors = serializedIndex.documentVectors,
      documentCount = 0,
      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++, documentCount++) {
    var tuple = serializedVectors[i],
        ref = tuple[0],
        elements = tuple[1]

    documentVectors[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.b = serializedIndex.b
  attrs.k1 = serializedIndex.k1
  attrs.fields = serializedIndex.fields
  attrs.averageDocumentLength = serializedIndex.averageDocumentLength

  attrs.documentCount = documentCount
  attrs.documentVectors = documentVectors
  attrs.invertedIndex = invertedIndex
  attrs.tokenSet = tokenSetBuilder.root
  attrs.pipeline = pipeline

  return new lunr.Index(attrs)
}
/*!
 * lunr.Builder
 * Copyright (C) 2016 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 - ???
 * @property {object} documentLengths - ???
 * @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 - ???
 */
lunr.Builder = function () {
  this._ref = "id"
  this._fields = []
  this.invertedIndex = {}
  this.documentTermFrequencies = {}
  this.documentLengths = {}
  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],
      documentTerms = {}

  this.documentCount += 1
  this.documentTermFrequencies[docRef] = documentTerms
  this.documentLengths[docRef] = 0

  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)

    // store the length of this field for this document
    this.documentLengths[docRef] += terms.length

    // calculate term frequencies for this field
    for (var j = 0; j < terms.length; j++) {
      var term = terms[j]

      if (documentTerms[term] == undefined) {
        documentTerms[term] = 0
      }

      documentTerms[term] += 1

      // add to inverted index
      // create an initial posting if one doesn't exist
      if (this.invertedIndex[term] == undefined) {
        var posting = { "_index": this.termIndex }
        this.termIndex += 1

        for (var k = 0; k < this._fields.length; k++) {
          posting[this._fields[k]] = {}
        }

        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] = {}
      }

      // 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.calculateAverageDocumentLengths = function () {

  var documentRefs = Object.keys(this.documentLengths),
      numberOfDocuments = documentRefs.length,
      allDocumentsLength = 0

  for (var i = 0; i < numberOfDocuments; i++) {
    var documentRef = documentRefs[i]
    allDocumentsLength += this.documentLengths[documentRef]
  }

  this.averageDocumentLength = allDocumentsLength / numberOfDocuments
}

/**
 * Builds a vector space model of every document using lunr.Vector
 *
 * @private
 */
lunr.Builder.prototype.createDocumentVectors = function () {
  var documentVectors = {},
      docRefs = Object.keys(this.documentTermFrequencies),
      docRefsLength = docRefs.length

  for (var i = 0; i < docRefsLength; i++) {
    var docRef = docRefs[i],
        documentLength = this.documentLengths[docRef],
        documentVector = new lunr.Vector,
        termFrequencies = this.documentTermFrequencies[docRef],
        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 * (documentLength / this.averageDocumentLength)) + tf)

      documentVector.insert(termIndex, score)
    }

    documentVectors[docRef] = documentVector
  }

  this.documentVectors = documentVectors
}

/**
 * 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.calculateAverageDocumentLengths()
  this.createDocumentVectors()
  this.createTokenSet()

  return new lunr.Index({
    invertedIndex: this.invertedIndex,
    documentVectors: this.documentVectors,
    tokenSet: this.tokenSet,
    averageDocumentLength: this.averageDocumentLength,
    documentCount: this.documentCount,
    fields: this._fields,
    pipeline: this.searchPipeline,
    b: this._b,
    k1: this._k1
  })
}
/**
 * Contains and collects metadata about a matching document.
 * A single instance of lunr.MatchData is returned as part of every
 * lunr.Index~Result.
 *
 * @constructor
 * @property {string[]} terms - All the query terms that the document matched.
 * @property {object} metadata - A collection of metadata associated with this document.
 * @see {@link lunr.Index~Result}
 */
lunr.MatchData = function (term, field, metadata) {
  this.terms = [term]

  this.metadata = {}
  this.metadata[field] = metadata
}

/**
 * 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) {
  this.terms = this.terms.concat(otherMatchData.terms)

  var otherMatchDataFields = Object.keys(otherMatchData.metadata)

  for (var i = 0; i < otherMatchDataFields.length; i++) {
    var field = otherMatchDataFields[i],
        fieldMetadata = otherMatchData.metadata[field],
        fieldMetadataKeys = Object.keys(fieldMetadata)

    if (this.metadata[field] == undefined) {
      this.metadata[field] = {}
    }

    for (var j = 0; j < fieldMetadataKeys.length; j++) {
      var metadataKey = fieldMetadataKeys[j]

      if (this.metadata[field][metadataKey] == undefined) {
        this.metadata[field][metadataKey] = fieldMetadata[metadataKey]
      } else {
        this.metadata[field][metadataKey] = this.metadata[field][metadataKey].concat(fieldMetadata[metadataKey])
      }
    }
  }
}
/**
 * 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
}

/**
 * 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 - 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.
 */

/**
 * 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.
 * @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
  }

  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}
 */
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
}

lunr.QueryLexer.prototype.run = function () {
  var state = lunr.QueryLexer.lexText

  while (state) {
    state = state(this)
  }
}

lunr.QueryLexer.prototype.emit = function (type) {
  this.lexemes.push({
    type: type,
    str: this.str.slice(this.start, this.pos),
    start: this.start,
    end: this.pos
  })

  this.start = this.pos
}

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)
  }
}

lunr.QueryLexer.lexText = function (lexer) {
  while (true) {
    var char = lexer.next()

    if (char == lunr.QueryLexer.EOS) {
      return lunr.QueryLexer.lexEOS
    }

    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
    }

    // TODO: there may be more separators we want to consider
    if (char == " ") {
      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 + " 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 a field, 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

  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, found '" + lexeme.str + "'"
    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, found '" + lexeme.str + "'"
    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
  }))
})();