text: /**
   * lunr - http://lunrjs.com - A bit like Solr, but much smaller and not as bright - 2.3.8
   * Copyright (C) 2019 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 = '2.3.8'
    /*!
     * lunr.utils
     * Copyright (C) 2019 Oliver Nightingale
     */
  
    /**
     * A namespace containing utils for the rest of the lunr library
     * @namespace lunr.utils
     */
    lunr.utils = {}
  
    /**
     * Print a warning message to the console.
     *
     * @param {String} message The message to be printed.
     * @memberOf lunr.utils
     * @function
     */
    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 lunr.utils
     */
    lunr.utils.asString = function (obj) {
      if (obj === void 0 || obj === null) {
        return ''
      } else {
        return obj.toString()
      }
    }
  
    /**
     * Clones an object.
     *
     * Will create a copy of an existing object such that any mutations
     * on the copy cannot affect the original.
     *
     * Only shallow objects are supported, passing a nested object to this
     * function will cause a TypeError.
     *
     * Objects with primitives, and arrays of primitives are supported.
     *
     * @param {Object} obj The object to clone.
     * @return {Object} a clone of the passed object.
     * @throws {TypeError} when a nested object is passed.
     * @memberOf Utils
     */
    lunr.utils.clone = function (obj) {
      if (obj === null || obj === undefined) {
        return obj
      }
  
      var clone = Object.create(null)
      var keys = Object.keys(obj)
  
      for (var i = 0; i < keys.length; i++) {
        var key = keys[i]
        var val = obj[key]
  
        if (Array.isArray(val)) {
          clone[key] = val.slice()
          continue
        }
  
        if (typeof val === 'string' ||
          typeof val === 'number' ||
          typeof val === 'boolean') {
          clone[key] = val
          continue
        }
  
        throw new TypeError('clone is not deep and does not support nested objects')
      }
  
      return clone
    }
    lunr.FieldRef = function (docRef, fieldName, stringValue) {
      this.docRef = docRef
      this.fieldName = fieldName
      this._stringValue = stringValue
    }
  
    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)
      var docRef = s.slice(n + 1)
  
      return new lunr.FieldRef(docRef, fieldRef, s)
    }
  
    lunr.FieldRef.prototype.toString = function () {
      if (this._stringValue == undefined) {
        this._stringValue = this.fieldName + lunr.FieldRef.joiner + this.docRef
      }
  
      return this._stringValue
    }
    /*!
     * lunr.Set
     * Copyright (C) 2019 Oliver Nightingale
     */
  
    /**
     * A lunr set.
     *
     * @constructor
     */
    lunr.Set = function (elements) {
      this.elements = Object.create(null)
  
      if (elements) {
        this.length = elements.length
  
        for (var i = 0; i < this.length; i++) {
          this.elements[elements[i]] = true
        }
      } else {
        this.length = 0
      }
    }
  
    /**
     * A complete set that contains all elements.
     *
     * @static
     * @readonly
     * @type {lunr.Set}
     */
    lunr.Set.complete = {
      intersect: function (other) {
        return other
      },
  
      union: function (other) {
        return other
      },
  
      contains: function () {
        return true
      },
    }
  
    /**
     * An empty set that contains no elements.
     *
     * @static
     * @readonly
     * @type {lunr.Set}
     */
    lunr.Set.empty = {
      intersect: function () {
        return this
      },
  
      union: function (other) {
        return other
      },
  
      contains: function () {
        return false
      },
    }
  
    /**
     * Returns true if this set contains the specified object.
     *
     * @param {object} object - Object whose presence in this set is to be tested.
     * @returns {boolean} - True if this set contains the specified object.
     */
    lunr.Set.prototype.contains = function (object) {
      return !!this.elements[object]
    }
  
    /**
     * Returns a new set containing only the elements that are present in both
     * this set and the specified set.
     *
     * @param {lunr.Set} other - set to intersect with this set.
     * @returns {lunr.Set} a new set that is the intersection of this and the specified set.
     */
  
    lunr.Set.prototype.intersect = function (other) {
      var a; var b; var elements; var intersection = []
  
      if (other === lunr.Set.complete) {
        return this
      }
  
      if (other === lunr.Set.empty) {
        return other
      }
  
      if (this.length < other.length) {
        a = this
        b = other
      } else {
        a = other
        b = this
      }
  
      elements = Object.keys(a.elements)
  
      for (var i = 0; i < elements.length; i++) {
        var element = elements[i]
        if (element in b.elements) {
          intersection.push(element)
        }
      }
  
      return new lunr.Set(intersection)
    }
  
    /**
     * Returns a new set combining the elements of this and the specified set.
     *
     * @param {lunr.Set} other - set to union with this set.
     * @return {lunr.Set} a new set that is the union of this and the specified set.
     */
  
    lunr.Set.prototype.union = function (other) {
      if (other === lunr.Set.complete) {
        return lunr.Set.complete
      }
  
      if (other === lunr.Set.empty) {
        return this
      }
  
      return new lunr.Set(Object.keys(this.elements).concat(Object.keys(other.elements)))
    }
    /**
     * 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) 2019 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.
     *
     * Optional metadata can be passed to the tokenizer, this metadata will be cloned and
     * added as metadata to every token that is created from the object to be tokenized.
     *
     * @static
     * @param {?(string|object|object[])} obj - The object to convert into tokens
     * @param {?object} metadata - Optional metadata to associate with every token
     * @returns {lunr.Token[]}
     * @see {@link lunr.Pipeline}
     */
    lunr.tokenizer = function (obj, metadata) {
      if (obj == null || obj == undefined) {
        return []
      }
  
      if (Array.isArray(obj)) {
        return obj.map(function (t) {
          return new lunr.Token(
            lunr.utils.asString(t).toLowerCase(),
            lunr.utils.clone(metadata)
          )
        })
      }
  
      var str = obj.toString().toLowerCase()
      var len = str.length
      var tokens = []
  
      for (var sliceEnd = 0, sliceStart = 0; sliceEnd <= len; sliceEnd++) {
        var char = str.charAt(sliceEnd)
        var sliceLength = sliceEnd - sliceStart
  
        if ((char.match(lunr.tokenizer.separator) || sliceEnd == len)) {
          if (sliceLength > 0) {
            var tokenMetadata = lunr.utils.clone(metadata) || {}
            tokenMetadata.position = [sliceStart, sliceLength]
            tokenMetadata.index = tokens.length
  
            tokens.push(
              new lunr.Token(
                str.slice(sliceStart, sliceEnd),
                tokenMetadata
              )
            )
          }
  
          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) 2019 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, undefined or an empty string. 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]
        var memo = []
  
        for (var j = 0; j < tokens.length; j++) {
          var result = fn(tokens[j], j, tokens)
  
          if (result === null || result === void 0 || result === '') continue
  
          if (Array.isArray(result)) {
            for (var k = 0; k < result.length; k++) {
              memo.push(result[k])
            }
          } else {
            memo.push(result)
          }
        }
  
        tokens = memo
      }
  
      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.
     * @param {?object} metadata - Optional metadata to associate with the token
     * passed to the pipeline.
     * @returns {string[]}
     */
    lunr.Pipeline.prototype.runString = function (str, metadata) {
      var token = new lunr.Token(str, metadata)
  
      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) 2019 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
      var end = this.elements.length / 2
      var sliceLength = end - start
      var pivotPoint = Math.floor(sliceLength / 2)
      var 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
      var 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
      var a = this.elements; var b = otherVector.elements
      var aLen = a.length; var bLen = b.length
      var aVal = 0; var bVal = 0
      var i = 0; var 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 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() || 0
    }
  
    /**
     * 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) 2019 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}
     * @function
     */
    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) 2019 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.
     *
     * @function
     * @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.
     *
     * @function
     * @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) 2019 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) 2019 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
          }
  
          stack.push({
            node: noEditNode,
            editsRemaining: frame.editsRemaining,
            str: frame.str.slice(1)
          })
        }
  
        if (frame.editsRemaining == 0) {
          continue
        }
  
        // insertion
        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
        }
  
        stack.push({
          node: insertionNode,
          editsRemaining: frame.editsRemaining - 1,
          str: frame.str
        })
  
        // 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.str.length > 1) {
          stack.push({
            node: frame.node,
            editsRemaining: frame.editsRemaining - 1,
            str: frame.str.slice(1)
          })
        }
  
        // deletion
        // just removing the last character from the str
        if (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.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
          }
  
          stack.push({
            node: substitutionNode,
            editsRemaining: frame.editsRemaining - 1,
            str: frame.str.slice(1)
          })
        }
  
        // transposition
        // can only do a transposition if there are edits remaining
        // and there are enough characters to transpose
        if (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
          }
  
          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
  
      /*
       * Iterates through all characters within the passed string
       * appending a node for each character.
       *
       * When 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 == "*") {
          node.edges[char] = node
          node.final = final
  
        } else {
          var next = new lunr.TokenSet
          next.final = final
  
          node.edges[char] = next
          node = next
        }
      }
  
      return root
    }
  
    /**
     * Converts this TokenSet into an array of strings
     * contained within the TokenSet.
     *
     * This is not intended to be used on a TokenSet that
     * contains wildcards, in these cases the results are
     * undefined and are likely to cause an infinite loop.
     *
     * @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) {
          /* In Safari, at this point the prefix is sometimes corrupted, see:
           * https://github.com/olivernn/lunr.js/issues/279 Calling any
           * String.prototype method forces Safari to "cast" this string to what
           * it's supposed to be, fixing the bug. */
          frame.prefix.charAt(0)
          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) 2019 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.fieldVectors - Field vectors
     * @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.
     *
     * Each term also supports a presence modifier. By default a term's presence in document is optional, however
     * this can be changed to either required or prohibited. For a term's presence to be required in a document the
     * term should be prefixed with a '+', e.g. `+foo bar` is a search for documents that must contain 'foo' and
     * optionally contain 'bar'. Conversely a leading '-' sets the terms presence to prohibited, i.e. it must not
     * appear in a document, e.g. `-foo bar` is a search for documents that do not contain 'foo' but may contain 'bar'.
     *
     * 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
     * @example <caption>terms with presence modifiers</caption>
     * -foo +bar baz
     */
  
    /**
     * 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 details on how the score is calculated, please see
     * the {@link https://lunrjs.com/guides/searching.html#scoring|guide}.
     *
     * 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),
        termFieldCache = Object.create(null),
        requiredMatches = Object.create(null),
        prohibitedMatches = Object.create(null)
  
      /*
       * To support field level boosts a query vector is created per
       * field. An empty vector is eagerly created to support negated
       * queries.
       */
      for (var i = 0; i < this.fields.length; i++) {
        queryVectors[this.fields[i]] = 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,
          clauseMatches = lunr.Set.complete
  
        if (clause.usePipeline) {
          terms = this.pipeline.runString(clause.term, {
            fields: clause.fields
          })
        } 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()
  
          /*
           * If a term marked as required does not exist in the tokenSet it is
           * impossible for the search to return any matches. We set all the field
           * scoped required matches set to empty and stop examining any further
           * clauses.
           */
          if (expandedTerms.length === 0 && clause.presence === lunr.Query.presence.REQUIRED) {
            for (var k = 0; k < clause.fields.length; k++) {
              var field = clause.fields[k]
              requiredMatches[field] = lunr.Set.empty
            }
  
            break
          }
  
          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),
                termField = expandedTerm + "/" + field,
                matchingDocumentsSet = new lunr.Set(matchingDocumentRefs)
  
              /*
               * if the presence of this term is required ensure that the matching
               * documents are added to the set of required matches for this clause.
               *
               */
              if (clause.presence == lunr.Query.presence.REQUIRED) {
                clauseMatches = clauseMatches.union(matchingDocumentsSet)
  
                if (requiredMatches[field] === undefined) {
                  requiredMatches[field] = lunr.Set.complete
                }
              }
  
              /*
               * if the presence of this term is prohibited ensure that the matching
               * documents are added to the set of prohibited matches for this field,
               * creating that set if it does not yet exist.
               */
              if (clause.presence == lunr.Query.presence.PROHIBITED) {
                if (prohibitedMatches[field] === undefined) {
                  prohibitedMatches[field] = lunr.Set.empty
                }
  
                prohibitedMatches[field] = prohibitedMatches[field].union(matchingDocumentsSet)
  
                /*
                 * Prohibited matches should not be part of the query vector used for
                 * similarity scoring and no metadata should be extracted so we continue
                 * to the next field
                 */
                continue
              }
  
              /*
               * The query field vector is populated using the termIndex found for
               * the term and a unit value with the appropriate boost applied.
               * 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, clause.boost, function (a, b) { return a + b })
  
              /**
               * If we've already seen this term, field combo then we've already collected
               * the matching documents and metadata, no need to go through all that again
               */
              if (termFieldCache[termField]) {
                continue
              }
  
              for (var l = 0; l < matchingDocumentRefs.length; l++) {
                /*
                 * 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),
                  metadata = fieldPosting[matchingDocumentRef],
                  fieldMatch
  
                if ((fieldMatch = matchingFields[matchingFieldRef]) === undefined) {
                  matchingFields[matchingFieldRef] = new lunr.MatchData (expandedTerm, field, metadata)
                } else {
                  fieldMatch.add(expandedTerm, field, metadata)
                }
  
              }
  
              termFieldCache[termField] = true
            }
          }
        }
  
        /**
         * If the presence was required we need to update the requiredMatches field sets.
         * We do this after all fields for the term have collected their matches because
         * the clause terms presence is required in _any_ of the fields not _all_ of the
         * fields.
         */
        if (clause.presence === lunr.Query.presence.REQUIRED) {
          for (var k = 0; k < clause.fields.length; k++) {
            var field = clause.fields[k]
            requiredMatches[field] = requiredMatches[field].intersect(clauseMatches)
          }
        }
      }
  
      /**
       * Need to combine the field scoped required and prohibited
       * matching documents into a global set of required and prohibited
       * matches
       */
      var allRequiredMatches = lunr.Set.complete,
        allProhibitedMatches = lunr.Set.empty
  
      for (var i = 0; i < this.fields.length; i++) {
        var field = this.fields[i]
  
        if (requiredMatches[field]) {
          allRequiredMatches = allRequiredMatches.intersect(requiredMatches[field])
        }
  
        if (prohibitedMatches[field]) {
          allProhibitedMatches = allProhibitedMatches.union(prohibitedMatches[field])
        }
      }
  
      var matchingFieldRefs = Object.keys(matchingFields),
        results = [],
        matches = Object.create(null)
  
      /*
       * If the query is negated (contains only prohibited terms)
       * we need to get _all_ fieldRefs currently existing in the
       * index. This is only done when we know that the query is
       * entirely prohibited terms to avoid any cost of getting all
       * fieldRefs unnecessarily.
       *
       * Additionally, blank MatchData must be created to correctly
       * populate the results.
       */
      if (query.isNegated()) {
        matchingFieldRefs = Object.keys(this.fieldVectors)
  
        for (var i = 0; i < matchingFieldRefs.length; i++) {
          var matchingFieldRef = matchingFieldRefs[i]
          var fieldRef = lunr.FieldRef.fromString(matchingFieldRef)
          matchingFields[matchingFieldRef] = new lunr.MatchData
        }
      }
  
      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
  
        if (!allRequiredMatches.contains(docRef)) {
          continue
        }
  
        if (allProhibitedMatches.contains(docRef)) {
          continue
        }
  
        var fieldVector = this.fieldVectors[fieldRef],
          score = queryVectors[fieldRef.fieldName].similarity(fieldVector),
          docMatch
  
        if ((docMatch = matches[docRef]) !== undefined) {
          docMatch.score += score
          docMatch.matchData.combine(matchingFields[fieldRef])
        } else {
          var match = {
            ref: docRef,
            score: score,
            matchData: matchingFields[fieldRef]
          }
          matches[docRef] = match
          results.push(match)
        }
      }
  
      /*
       * Sort the results objects by score, highest first.
       */
      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 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 = Object.create(null),
        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) 2019 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 = Object.create(null)
      this._documents = Object.create(null)
      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
    }
  
    /**
     * A function that is used to extract a field from a document.
     *
     * Lunr expects a field to be at the top level of a document, if however the field
     * is deeply nested within a document an extractor function can be used to extract
     * the right field for indexing.
     *
     * @callback fieldExtractor
     * @param {object} doc - The document being added to the index.
     * @returns {?(string|object|object[])} obj - The object that will be indexed for this field.
     * @example <caption>Extracting a nested field</caption>
     * function (doc) { return doc.nested.field }
     */
  
    /**
     * 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.
     *
     * Fields can be boosted at build time. This allows terms within that field to have more
     * importance when ranking search results. Use a field boost to specify that matches within
     * one field are more important than other fields.
     *
     * @param {string} fieldName - The name of a field to index in all documents.
     * @param {object} attributes - Optional attributes associated with this field.
     * @param {number} [attributes.boost=1] - Boost applied to all terms within this field.
     * @param {fieldExtractor} [attributes.extractor] - Function to extract a field from a document.
     * @throws {RangeError} fieldName cannot contain unsupported characters '/'
     */
    lunr.Builder.prototype.field = function (fieldName, attributes) {
      if (/\//.test(fieldName)) {
        throw new RangeError ("Field '" + fieldName + "' contains illegal character '/'")
      }
  
      this._fields[fieldName] = attributes || {}
    }
  
    /**
     * 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.
     *
     * Entire documents can be boosted at build time. Applying a boost to a document indicates that
     * this document should rank higher in search results than other documents.
     *
     * @param {object} doc - The document to add to the index.
     * @param {object} attributes - Optional attributes associated with this document.
     * @param {number} [attributes.boost=1] - Boost applied to all terms within this document.
     */
    lunr.Builder.prototype.add = function (doc, attributes) {
      var docRef = doc[this._ref],
        fields = Object.keys(this._fields)
  
      this._documents[docRef] = attributes || {}
      this.documentCount += 1
  
      for (var i = 0; i < fields.length; i++) {
        var fieldName = fields[i],
          extractor = this._fields[fieldName].extractor,
          field = extractor ? extractor(doc) : doc[fieldName],
          tokens = this.tokenizer(field, {
            fields: [fieldName]
          }),
          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 < fields.length; k++) {
              posting[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]
      }
  
      var fields = Object.keys(this._fields)
  
      for (var i = 0; i < fields.length; i++) {
        var fieldName = fields[i]
        accumulator[fieldName] = accumulator[fieldName] / documentsWithField[fieldName]
      }
  
      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,
        termIdfCache = Object.create(null)
  
      for (var i = 0; i < fieldRefsLength; i++) {
        var fieldRef = lunr.FieldRef.fromString(fieldRefs[i]),
          fieldName = fieldRef.fieldName,
          fieldLength = this.fieldLengths[fieldRef],
          fieldVector = new lunr.Vector,
          termFrequencies = this.fieldTermFrequencies[fieldRef],
          terms = Object.keys(termFrequencies),
          termsLength = terms.length
  
  
        var fieldBoost = this._fields[fieldName].boost || 1,
          docBoost = this._documents[fieldRef.docRef].boost || 1
  
        for (var j = 0; j < termsLength; j++) {
          var term = terms[j],
            tf = termFrequencies[term],
            termIndex = this.invertedIndex[term]._index,
            idf, score, scoreWithPrecision
  
          if (termIdfCache[term] === undefined) {
            idf = lunr.idf(this.invertedIndex[term], this.documentCount)
            termIdfCache[term] = idf
          } else {
            idf = termIdfCache[term]
          }
  
          score = idf * ((this._k1 + 1) * tf) / (this._k1 * (1 - this._b + this._b * (fieldLength / this.averageFieldLength[fieldName])) + tf)
          score *= fieldBoost
          score *= docBoost
          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.
     *
     * @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: Object.keys(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)
  
      if (term !== undefined) {
        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])
            }
  
          }
        }
      }
    }
  
    /**
     * Add metadata for a term/field pair to this instance of match data.
     *
     * @param {string} term - The term this match data is associated with
     * @param {string} field - The field in which the term was found
     * @param {object} metadata - The metadata recorded about this term in this field
     */
    lunr.MatchData.prototype.add = function (term, field, metadata) {
      if (!(term in this.metadata)) {
        this.metadata[term] = Object.create(null)
        this.metadata[term][field] = metadata
        return
      }
  
      if (!(field in this.metadata[term])) {
        this.metadata[term][field] = metadata
        return
      }
  
      var metadataKeys = Object.keys(metadata)
  
      for (var i = 0; i < metadataKeys.length; i++) {
        var key = metadataKeys[i]
  
        if (key in this.metadata[term][field]) {
          this.metadata[term][field][key] = this.metadata[term][field][key].concat(metadata[key])
        } else {
          this.metadata[term][field][key] = metadata[key]
        }
      }
    }
    /**
     * 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
  
    /**
     * Constants for indicating what kind of presence a term must have in matching documents.
     *
     * @constant
     * @enum {number}
     * @see lunr.Query~Clause
     * @see lunr.Query#clause
     * @see lunr.Query#term
     * @example <caption>query term with required presence</caption>
     * query.term('foo', { presence: lunr.Query.presence.REQUIRED })
     */
    lunr.Query.presence = {
      /**
       * Term's presence in a document is optional, this is the default value.
       */
      OPTIONAL: 1,
  
      /**
       * Term's presence in a document is required, documents that do not contain
       * this term will not be returned.
       */
      REQUIRED: 2,
  
      /**
       * Term's presence in a document is prohibited, documents that do contain
       * this term will not be returned.
       */
      PROHIBITED: 3
    }
  
    /**
     * 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=lunr.Query.wildcard.NONE] - Whether the term should have wildcards appended or prepended.
     * @property {number} [presence=lunr.Query.presence.OPTIONAL] - The terms presence in any matching documents.
     */
  
    /**
     * 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 + "*"
      }
  
      if (!('presence' in clause)) {
        clause.presence = lunr.Query.presence.OPTIONAL
      }
  
      this.clauses.push(clause)
  
      return this
    }
  
    /**
     * A negated query is one in which every clause has a presence of
     * prohibited. These queries require some special processing to return
     * the expected results.
     *
     * @returns boolean
     */
    lunr.Query.prototype.isNegated = function () {
      for (var i = 0; i < this.clauses.length; i++) {
        if (this.clauses[i].presence != lunr.Query.presence.PROHIBITED) {
          return false
        }
      }
  
      return true
    }
  
    /**
     * 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.
     *
     * The term is used as is, i.e. no tokenization will be performed by this method. Instead conversion
     * to a token or token-like string should be done before calling this method.
     *
     * The term will be converted to a string by calling `toString`. Multiple terms can be passed as an
     * array, each term in the array will share the same options.
     *
     * @param {object|object[]} term - The term(s) 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
     * })
     * @example <caption>using lunr.tokenizer to convert a string to tokens before using them as terms</caption>
     * query.term(lunr.tokenizer("foo bar"))
     */
    lunr.Query.prototype.term = function (term, options) {
      if (Array.isArray(term)) {
        term.forEach(function (t) { this.term(t, lunr.utils.clone(options)) }, this)
        return this
      }
  
      var clause = options || {}
      clause.term = term.toString()
  
      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.PRESENCE = 'PRESENCE'
  
    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
        }
  
        // "+" indicates term presence is required
        // checking for length to ensure that only
        // leading "+" are considered
        if (char == "+" && lexer.width() === 1) {
          lexer.emit(lunr.QueryLexer.PRESENCE)
          return lunr.QueryLexer.lexText
        }
  
        // "-" indicates term presence is prohibited
        // checking for length to ensure that only
        // leading "-" are considered
        if (char == "-" && lexer.width() === 1) {
          lexer.emit(lunr.QueryLexer.PRESENCE)
          return lunr.QueryLexer.lexText
        }
  
        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.parseClause
  
      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.parseClause = function (parser) {
      var lexeme = parser.peekLexeme()
  
      if (lexeme == undefined) {
        return
      }
  
      switch (lexeme.type) {
        case lunr.QueryLexer.PRESENCE:
          return lunr.QueryParser.parsePresence
        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.parsePresence = function (parser) {
      var lexeme = parser.consumeLexeme()
  
      if (lexeme == undefined) {
        return
      }
  
      switch (lexeme.str) {
        case "-":
          parser.currentClause.presence = lunr.Query.presence.PROHIBITED
          break
        case "+":
          parser.currentClause.presence = lunr.Query.presence.REQUIRED
          break
        default:
          var errorMessage = "unrecognised presence operator'" + lexeme.str + "'"
          throw new lunr.QueryParseError (errorMessage, lexeme.start, lexeme.end)
      }
  
      var nextLexeme = parser.peekLexeme()
  
      if (nextLexeme == undefined) {
        var errorMessage = "expecting term or field, found nothing"
        throw new lunr.QueryParseError (errorMessage, lexeme.start, lexeme.end)
      }
  
      switch (nextLexeme.type) {
        case lunr.QueryLexer.FIELD:
          return lunr.QueryParser.parseField
        case lunr.QueryLexer.TERM:
          return lunr.QueryParser.parseTerm
        default:
          var errorMessage = "expecting term or field, found '" + nextLexeme.type + "'"
          throw new lunr.QueryParseError (errorMessage, nextLexeme.start, nextLexeme.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
        case lunr.QueryLexer.PRESENCE:
          parser.nextClause()
          return lunr.QueryParser.parsePresence
        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
        case lunr.QueryLexer.PRESENCE:
          parser.nextClause()
          return lunr.QueryParser.parsePresence
        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
        case lunr.QueryLexer.PRESENCE:
          parser.nextClause()
          return lunr.QueryParser.parsePresence
        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
    }))
  })();
  