diff --git a/typedoc/assets/css/main.css b/typedoc/assets/css/main.css deleted file mode 100644 index ca83efe..0000000 --- a/typedoc/assets/css/main.css +++ /dev/null @@ -1,2638 +0,0 @@ -/*! normalize.css v1.1.3 | MIT License | git.io/normalize */ -/* ========================================================================== - * * HTML5 display definitions - * * ========================================================================== */ -/** - * * Correct `block` display not defined in IE 6/7/8/9 and Firefox 3. */ -article, aside, details, figcaption, figure, footer, header, hgroup, main, nav, section, summary { - display: block; -} - -/** - * * Correct `inline-block` display not defined in IE 6/7/8/9 and Firefox 3. */ -audio, canvas, video { - display: inline-block; - *display: inline; - *zoom: 1; -} - -/** - * * Prevent modern browsers from displaying `audio` without controls. - * * Remove excess height in iOS 5 devices. */ -audio:not([controls]) { - display: none; - height: 0; -} - -/** - * * Address styling not present in IE 7/8/9, Firefox 3, and Safari 4. - * * Known issue: no IE 6 support. */ -[hidden] { - display: none; -} - -/* ========================================================================== - * * Base - * * ========================================================================== */ -/** - * * 1. 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translate(100%, 0); - } - to { - transform: translate(0, 0); - } -} -@keyframes pop-out-to-right { - from { - transform: translate(0, 0); - visibility: visible; - } - to { - transform: translate(100%, 0); - } -} -body { - background: #fdfdfd; - font-family: "Segoe UI", sans-serif; - font-size: 16px; - color: #222; -} - -a { - color: #4da6ff; - text-decoration: none; -} -a:hover { - text-decoration: underline; -} - -code, pre { - font-family: Menlo, Monaco, Consolas, "Courier New", monospace; - padding: 0.2em; - margin: 0; - font-size: 14px; - background-color: rgba(0, 0, 0, 0.04); -} - -pre { - padding: 10px; -} -pre code { - padding: 0; - font-size: 100%; - background-color: transparent; -} - -blockquote { - margin: 1em 0; - padding-left: 1em; - border-left: 4px solid gray; -} - -.tsd-typography { - line-height: 1.333em; -} -.tsd-typography ul { - list-style: square; - padding: 0 0 0 20px; - margin: 0; -} -.tsd-typography h4, .tsd-typography .tsd-index-panel h3, .tsd-index-panel .tsd-typography h3, .tsd-typography h5, .tsd-typography h6 { - font-size: 1em; - margin: 0; -} -.tsd-typography h5, .tsd-typography h6 { - font-weight: normal; -} -.tsd-typography p, .tsd-typography ul, .tsd-typography ol { - margin: 1em 0; -} - -@media (min-width: 901px) and (max-width: 1024px) { - html.default .col-content { - width: 72%; - } - html.default .col-menu { - width: 28%; - } - html.default .tsd-navigation { - padding-left: 10px; - } -} -@media (max-width: 900px) { - html.default .col-content { - float: none; - width: 100%; - } - html.default .col-menu { - position: fixed !important; - overflow: auto; - -webkit-overflow-scrolling: touch; - z-index: 1024; - top: 0 !important; - bottom: 0 !important; - left: auto !important; - right: 0 !important; - width: 100%; - padding: 20px 20px 0 0; - max-width: 450px; - visibility: hidden; - background-color: #fff; - transform: translate(100%, 0); - } - html.default .col-menu > *:last-child { - padding-bottom: 20px; - } - html.default .overlay { - content: ""; - display: block; - position: fixed; - z-index: 1023; - top: 0; - left: 0; - right: 0; - bottom: 0; - background-color: rgba(0, 0, 0, 0.75); - visibility: hidden; - } - html.default.to-has-menu .overlay { - animation: fade-in 0.4s; - } - html.default.to-has-menu header, -html.default.to-has-menu footer, -html.default.to-has-menu .col-content { - animation: shift-to-left 0.4s; - } - html.default.to-has-menu .col-menu { - animation: pop-in-from-right 0.4s; - } - html.default.from-has-menu .overlay { - animation: fade-out 0.4s; - } - html.default.from-has-menu header, -html.default.from-has-menu footer, -html.default.from-has-menu .col-content { - animation: unshift-to-left 0.4s; - } - html.default.from-has-menu .col-menu { - animation: pop-out-to-right 0.4s; - } - html.default.has-menu body { - overflow: hidden; - } - html.default.has-menu .overlay { - visibility: visible; - } - html.default.has-menu header, -html.default.has-menu footer, -html.default.has-menu .col-content { - transform: translate(-25%, 0); - } - html.default.has-menu .col-menu { - visibility: visible; - transform: translate(0, 0); - } -} - -.tsd-page-title { - padding: 70px 0 20px 0; - margin: 0 0 40px 0; - background: #fff; - box-shadow: 0 0 5px rgba(0, 0, 0, 0.35); -} -.tsd-page-title h1 { - margin: 0; -} - -.tsd-breadcrumb { - margin: 0; - padding: 0; - color: #707070; -} -.tsd-breadcrumb a { - color: #707070; - text-decoration: none; -} -.tsd-breadcrumb a:hover { - text-decoration: underline; -} -.tsd-breadcrumb li { - display: inline; -} -.tsd-breadcrumb li:after { - content: " / "; -} - -html.minimal .container { - margin: 0; -} -html.minimal .container-main { - padding-top: 50px; - padding-bottom: 0; -} -html.minimal .content-wrap { - padding-left: 300px; -} -html.minimal .tsd-navigation { - position: fixed !important; - overflow: auto; - -webkit-overflow-scrolling: touch; - box-sizing: border-box; - z-index: 1; - left: 0; - top: 40px; - bottom: 0; - width: 300px; - padding: 20px; - margin: 0; -} -html.minimal .tsd-member .tsd-member { - margin-left: 0; -} -html.minimal .tsd-page-toolbar { - position: fixed; - z-index: 2; -} -html.minimal #tsd-filter .tsd-filter-group { - right: 0; - transform: none; -} -html.minimal footer { - background-color: transparent; -} -html.minimal footer .container { - padding: 0; -} -html.minimal .tsd-generator { - padding: 0; -} -@media (max-width: 900px) { - html.minimal .tsd-navigation { - display: none; - } - html.minimal .content-wrap { - padding-left: 0; - } -} - -dl.tsd-comment-tags { - overflow: hidden; -} -dl.tsd-comment-tags dt { - float: left; - padding: 1px 5px; - margin: 0 10px 0 0; - border-radius: 4px; - border: 1px solid #707070; - color: #707070; - font-size: 0.8em; - font-weight: normal; -} -dl.tsd-comment-tags dd { - margin: 0 0 10px 0; -} -dl.tsd-comment-tags dd:before, dl.tsd-comment-tags dd:after { - display: table; - content: " "; -} -dl.tsd-comment-tags dd pre, dl.tsd-comment-tags dd:after { - clear: both; -} -dl.tsd-comment-tags p { - margin: 0; -} - -.tsd-panel.tsd-comment .lead { - font-size: 1.1em; - line-height: 1.333em; - margin-bottom: 2em; -} -.tsd-panel.tsd-comment .lead:last-child { - margin-bottom: 0; -} - -.toggle-protected .tsd-is-private { - display: none; -} - -.toggle-public .tsd-is-private, -.toggle-public .tsd-is-protected, -.toggle-public .tsd-is-private-protected { - display: none; -} - -.toggle-inherited .tsd-is-inherited { - display: none; -} - -.toggle-externals .tsd-is-external { - display: none; -} - -#tsd-filter { - position: relative; - display: inline-block; - height: 40px; - vertical-align: bottom; -} -.no-filter #tsd-filter { - display: none; -} -#tsd-filter .tsd-filter-group { - display: inline-block; - height: 40px; - vertical-align: bottom; - white-space: nowrap; -} -#tsd-filter input { - display: none; -} -@media (max-width: 900px) { - #tsd-filter .tsd-filter-group { - display: block; - position: absolute; - top: 40px; - right: 20px; - height: auto; - background-color: #fff; - visibility: hidden; - transform: translate(50%, 0); - box-shadow: 0 0 4px rgba(0, 0, 0, 0.25); - } - .has-options #tsd-filter .tsd-filter-group { - visibility: visible; - } - .to-has-options #tsd-filter .tsd-filter-group { - animation: fade-in 0.2s; - } - .from-has-options #tsd-filter .tsd-filter-group { - animation: fade-out 0.2s; - } - #tsd-filter label, -#tsd-filter .tsd-select { - display: block; - padding-right: 20px; - } -} - -footer { - border-top: 1px solid #eee; - background-color: #fff; -} -footer.with-border-bottom { - border-bottom: 1px solid #eee; -} -footer .tsd-legend-group { - font-size: 0; -} -footer .tsd-legend { - display: inline-block; - width: 25%; - padding: 0; - font-size: 16px; - list-style: none; - line-height: 1.333em; - vertical-align: top; -} -@media (max-width: 900px) { - footer .tsd-legend { - width: 50%; - } -} - -.tsd-hierarchy { - list-style: square; - padding: 0 0 0 20px; - margin: 0; -} -.tsd-hierarchy .target { - font-weight: bold; -} - -.tsd-index-panel .tsd-index-content { - margin-bottom: -30px !important; -} -.tsd-index-panel .tsd-index-section { - margin-bottom: 30px !important; -} -.tsd-index-panel h3 { - margin: 0 -20px 10px -20px; - padding: 0 20px 10px 20px; - border-bottom: 1px solid #eee; -} -.tsd-index-panel ul.tsd-index-list { - -webkit-column-count: 3; - -moz-column-count: 3; - -ms-column-count: 3; - -o-column-count: 3; - column-count: 3; - -webkit-column-gap: 20px; - -moz-column-gap: 20px; - -ms-column-gap: 20px; - -o-column-gap: 20px; - column-gap: 20px; - padding: 0; - list-style: none; - line-height: 1.333em; -} -@media (max-width: 900px) { - .tsd-index-panel ul.tsd-index-list { - -webkit-column-count: 1; - -moz-column-count: 1; - -ms-column-count: 1; - -o-column-count: 1; - column-count: 1; - } -} -@media (min-width: 901px) and (max-width: 1024px) { - .tsd-index-panel ul.tsd-index-list { - -webkit-column-count: 2; - -moz-column-count: 2; - -ms-column-count: 2; - -o-column-count: 2; - column-count: 2; - } -} -.tsd-index-panel ul.tsd-index-list li { - -webkit-page-break-inside: avoid; - -moz-page-break-inside: avoid; - -ms-page-break-inside: avoid; - -o-page-break-inside: avoid; - page-break-inside: avoid; -} -.tsd-index-panel a, -.tsd-index-panel .tsd-parent-kind-module a { - color: #9600ff; -} -.tsd-index-panel .tsd-parent-kind-interface a { - color: #647F1B; -} -.tsd-index-panel .tsd-parent-kind-enum a { - color: #937210; -} -.tsd-index-panel .tsd-parent-kind-class a { - color: #0672DE; -} -.tsd-index-panel .tsd-kind-module a { - color: #9600ff; -} -.tsd-index-panel .tsd-kind-interface a { - color: #647F1B; -} -.tsd-index-panel .tsd-kind-enum a { - color: #937210; -} -.tsd-index-panel .tsd-kind-class a { - color: #0672DE; -} -.tsd-index-panel .tsd-is-private a { - color: #707070; -} - -.tsd-flag { - display: inline-block; - padding: 1px 5px; - border-radius: 4px; - color: #fff; - background-color: #707070; - text-indent: 0; - font-size: 14px; - font-weight: normal; -} - -.tsd-anchor { - position: absolute; - top: -100px; -} - -.tsd-member { - position: relative; -} -.tsd-member .tsd-anchor + h3 { - margin-top: 0; - margin-bottom: 0; - border-bottom: none; -} -.tsd-member a[data-tsd-kind] { - color: #9600ff; -} -.tsd-member a[data-tsd-kind=Interface] { - color: #647F1B; -} -.tsd-member a[data-tsd-kind=Enum] { - color: #937210; -} -.tsd-member a[data-tsd-kind=Class] { - color: #0672DE; -} -.tsd-member a[data-tsd-kind=Private] { - color: #707070; -} - -.tsd-navigation { - margin: 0 0 0 40px; -} -.tsd-navigation a { - display: block; - padding-top: 2px; - padding-bottom: 2px; - border-left: 2px solid transparent; - color: #222; - text-decoration: none; - transition: border-left-color 0.1s; -} -.tsd-navigation a:hover { - text-decoration: underline; -} -.tsd-navigation ul { - margin: 0; - padding: 0; - list-style: none; -} -.tsd-navigation li { - padding: 0; -} - -.tsd-navigation.primary { - padding-bottom: 40px; -} -.tsd-navigation.primary a { - display: block; - padding-top: 6px; - padding-bottom: 6px; -} -.tsd-navigation.primary ul li a { - padding-left: 5px; -} -.tsd-navigation.primary ul li li a { - padding-left: 25px; -} -.tsd-navigation.primary ul li li li a { - padding-left: 45px; -} -.tsd-navigation.primary ul li li li li a { - padding-left: 65px; -} -.tsd-navigation.primary ul li li li li li a { - padding-left: 85px; -} -.tsd-navigation.primary ul li li li li li li a { - padding-left: 105px; -} -.tsd-navigation.primary > ul { - border-bottom: 1px solid #eee; -} -.tsd-navigation.primary li { - border-top: 1px solid #eee; -} -.tsd-navigation.primary li.current > a { - font-weight: bold; -} -.tsd-navigation.primary li.label span { - display: block; - padding: 20px 0 6px 5px; - color: #707070; -} -.tsd-navigation.primary li.globals + li > span, .tsd-navigation.primary li.globals + li > a { - padding-top: 20px; -} - -.tsd-navigation.secondary { - max-height: calc(100vh - 1rem - 40px); - overflow: auto; - position: -webkit-sticky; - position: sticky; - top: calc(.5rem + 40px); - transition: 0.3s; -} -.tsd-navigation.secondary.tsd-navigation--toolbar-hide { - max-height: calc(100vh - 1rem); - top: 0.5rem; -} -.tsd-navigation.secondary ul { - transition: opacity 0.2s; -} -.tsd-navigation.secondary ul li a { - padding-left: 25px; -} -.tsd-navigation.secondary ul li li a { - padding-left: 45px; -} -.tsd-navigation.secondary ul li li li a { - padding-left: 65px; -} -.tsd-navigation.secondary ul li li li li a { - padding-left: 85px; -} -.tsd-navigation.secondary ul li li li li li a { - padding-left: 105px; -} -.tsd-navigation.secondary ul li li li li li li a { - padding-left: 125px; -} -.tsd-navigation.secondary ul.current a { - border-left-color: #eee; -} -.tsd-navigation.secondary li.focus > a, -.tsd-navigation.secondary ul.current li.focus > a { - border-left-color: #000; -} -.tsd-navigation.secondary li.current { - margin-top: 20px; - margin-bottom: 20px; - 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solid #ccc; -} -.tsd-panel table tr:nth-child(2n) { - background-color: #f8f8f8; -} - -.tsd-panel-group { - margin: 60px 0; -} -.tsd-panel-group > h1, .tsd-panel-group > h2, .tsd-panel-group > h3 { - padding-left: 20px; - padding-right: 20px; -} - -#tsd-search { - transition: background-color 0.2s; -} -#tsd-search .title { - position: relative; - z-index: 2; -} -#tsd-search .field { - position: absolute; - left: 0; - top: 0; - right: 40px; - height: 40px; -} -#tsd-search .field input { - box-sizing: border-box; - position: relative; - top: -50px; - z-index: 1; - width: 100%; - padding: 0 10px; - opacity: 0; - outline: 0; - border: 0; - background: transparent; - color: #222; -} -#tsd-search .field label { - position: absolute; - overflow: hidden; - right: -40px; -} -#tsd-search .field input, -#tsd-search .title { - transition: opacity 0.2s; -} -#tsd-search .results { - position: absolute; - visibility: hidden; - top: 40px; - width: 100%; - margin: 0; - padding: 0; - list-style: none; - 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files a/typedoc/assets/images/widgets.png and /dev/null differ diff --git a/typedoc/assets/images/widgets@2x.png b/typedoc/assets/images/widgets@2x.png deleted file mode 100644 index 4bbbd57..0000000 Binary files a/typedoc/assets/images/widgets@2x.png and /dev/null differ diff --git a/typedoc/assets/js/main.js b/typedoc/assets/js/main.js deleted file mode 100644 index 715fdab..0000000 --- a/typedoc/assets/js/main.js +++ /dev/null @@ -1,248 +0,0 @@ -/* - * ATTENTION: The "eval" devtool has been used (maybe by default in mode: "development"). - * This devtool is not neither made for production nor for readable output files. - * It uses "eval()" calls to create a separate source file in the browser devtools. - * If you are trying to read the output file, select a different devtool (https://webpack.js.org/configuration/devtool/) - * or disable the default devtool with "devtool: false". - * If you are looking for production-ready output files, see mode: "production" (https://webpack.js.org/configuration/mode/). - */ -/******/ (() => { // webpackBootstrap -/******/ var __webpack_modules__ = ({ - -/***/ "../node_modules/lunr/lunr.js": -/*!************************************!*\ - !*** ../node_modules/lunr/lunr.js ***! - \************************************/ -/***/ ((module, exports, __webpack_require__) => { - -eval("var __WEBPACK_AMD_DEFINE_FACTORY__, __WEBPACK_AMD_DEFINE_RESULT__;/**\n * lunr - http://lunrjs.com - A bit like Solr, but much smaller and not as bright - 2.3.9\n * Copyright (C) 2020 Oliver Nightingale\n * @license MIT\n */\n\n;(function(){\n\n/**\n * A convenience function for configuring and constructing\n * a new lunr Index.\n *\n * A lunr.Builder instance is created and the pipeline setup\n * with a trimmer, stop word filter and stemmer.\n *\n * This builder object is yielded to the configuration function\n * that is passed as a parameter, allowing the list of fields\n * and other builder parameters to be customised.\n *\n * All documents _must_ be added within the passed config function.\n *\n * @example\n * var idx = lunr(function () {\n * this.field('title')\n * this.field('body')\n * this.ref('id')\n *\n * documents.forEach(function (doc) {\n * this.add(doc)\n * }, this)\n * })\n *\n * @see {@link lunr.Builder}\n * @see {@link lunr.Pipeline}\n * @see {@link lunr.trimmer}\n * @see {@link lunr.stopWordFilter}\n * @see {@link lunr.stemmer}\n * @namespace {function} lunr\n */\nvar lunr = function (config) {\n var builder = new lunr.Builder\n\n builder.pipeline.add(\n lunr.trimmer,\n lunr.stopWordFilter,\n lunr.stemmer\n )\n\n builder.searchPipeline.add(\n lunr.stemmer\n )\n\n config.call(builder, builder)\n return builder.build()\n}\n\nlunr.version = \"2.3.9\"\n/*!\n * lunr.utils\n * Copyright (C) 2020 Oliver Nightingale\n */\n\n/**\n * A namespace containing utils for the rest of the lunr library\n * @namespace lunr.utils\n */\nlunr.utils = {}\n\n/**\n * Print a warning message to the console.\n *\n * @param {String} message The message to be printed.\n * @memberOf lunr.utils\n * @function\n */\nlunr.utils.warn = (function (global) {\n /* eslint-disable no-console */\n return function (message) {\n if (global.console && console.warn) {\n console.warn(message)\n }\n }\n /* eslint-enable no-console */\n})(this)\n\n/**\n * Convert an object to a string.\n *\n * In the case of `null` and `undefined` the function returns\n * the empty string, in all other cases the result of calling\n * `toString` on the passed object is returned.\n *\n * @param {Any} obj The object to convert to a string.\n * @return {String} string representation of the passed object.\n * @memberOf lunr.utils\n */\nlunr.utils.asString = function (obj) {\n if (obj === void 0 || obj === null) {\n return \"\"\n } else {\n return obj.toString()\n }\n}\n\n/**\n * Clones an object.\n *\n * Will create a copy of an existing object such that any mutations\n * on the copy cannot affect the original.\n *\n * Only shallow objects are supported, passing a nested object to this\n * function will cause a TypeError.\n *\n * Objects with primitives, and arrays of primitives are supported.\n *\n * @param {Object} obj The object to clone.\n * @return {Object} a clone of the passed object.\n * @throws {TypeError} when a nested object is passed.\n * @memberOf Utils\n */\nlunr.utils.clone = function (obj) {\n if (obj === null || obj === undefined) {\n return obj\n }\n\n var clone = Object.create(null),\n keys = Object.keys(obj)\n\n for (var i = 0; i < keys.length; i++) {\n var key = keys[i],\n val = obj[key]\n\n if (Array.isArray(val)) {\n clone[key] = val.slice()\n continue\n }\n\n if (typeof val === 'string' ||\n typeof val === 'number' ||\n typeof val === 'boolean') {\n clone[key] = val\n continue\n }\n\n throw new TypeError(\"clone is not deep and does not support nested objects\")\n }\n\n return clone\n}\nlunr.FieldRef = function (docRef, fieldName, stringValue) {\n this.docRef = docRef\n this.fieldName = fieldName\n this._stringValue = stringValue\n}\n\nlunr.FieldRef.joiner = \"/\"\n\nlunr.FieldRef.fromString = function (s) {\n var n = s.indexOf(lunr.FieldRef.joiner)\n\n if (n === -1) {\n throw \"malformed field ref string\"\n }\n\n var fieldRef = s.slice(0, n),\n docRef = s.slice(n + 1)\n\n return new lunr.FieldRef (docRef, fieldRef, s)\n}\n\nlunr.FieldRef.prototype.toString = function () {\n if (this._stringValue == undefined) {\n this._stringValue = this.fieldName + lunr.FieldRef.joiner + this.docRef\n }\n\n return this._stringValue\n}\n/*!\n * lunr.Set\n * Copyright (C) 2020 Oliver Nightingale\n */\n\n/**\n * A lunr set.\n *\n * @constructor\n */\nlunr.Set = function (elements) {\n this.elements = Object.create(null)\n\n if (elements) {\n this.length = elements.length\n\n for (var i = 0; i < this.length; i++) {\n this.elements[elements[i]] = true\n }\n } else {\n this.length = 0\n }\n}\n\n/**\n * A complete set that contains all elements.\n *\n * @static\n * @readonly\n * @type {lunr.Set}\n */\nlunr.Set.complete = {\n intersect: function (other) {\n return other\n },\n\n union: function () {\n return this\n },\n\n contains: function () {\n return true\n }\n}\n\n/**\n * An empty set that contains no elements.\n *\n * @static\n * @readonly\n * @type {lunr.Set}\n */\nlunr.Set.empty = {\n intersect: function () {\n return this\n },\n\n union: function (other) {\n return other\n },\n\n contains: function () {\n return false\n }\n}\n\n/**\n * Returns true if this set contains the specified object.\n *\n * @param {object} object - Object whose presence in this set is to be tested.\n * @returns {boolean} - True if this set contains the specified object.\n */\nlunr.Set.prototype.contains = function (object) {\n return !!this.elements[object]\n}\n\n/**\n * Returns a new set containing only the elements that are present in both\n * this set and the specified set.\n *\n * @param {lunr.Set} other - set to intersect with this set.\n * @returns {lunr.Set} a new set that is the intersection of this and the specified set.\n */\n\nlunr.Set.prototype.intersect = function (other) {\n var a, b, elements, intersection = []\n\n if (other === lunr.Set.complete) {\n return this\n }\n\n if (other === lunr.Set.empty) {\n return other\n }\n\n if (this.length < other.length) {\n a = this\n b = other\n } else {\n a = other\n b = this\n }\n\n elements = Object.keys(a.elements)\n\n for (var i = 0; i < elements.length; i++) {\n var element = elements[i]\n if (element in b.elements) {\n intersection.push(element)\n }\n }\n\n return new lunr.Set (intersection)\n}\n\n/**\n * Returns a new set combining the elements of this and the specified set.\n *\n * @param {lunr.Set} other - set to union with this set.\n * @return {lunr.Set} a new set that is the union of this and the specified set.\n */\n\nlunr.Set.prototype.union = function (other) {\n if (other === lunr.Set.complete) {\n return lunr.Set.complete\n }\n\n if (other === lunr.Set.empty) {\n return this\n }\n\n return new lunr.Set(Object.keys(this.elements).concat(Object.keys(other.elements)))\n}\n/**\n * A function to calculate the inverse document frequency for\n * a posting. This is shared between the builder and the index\n *\n * @private\n * @param {object} posting - The posting for a given term\n * @param {number} documentCount - The total number of documents.\n */\nlunr.idf = function (posting, documentCount) {\n var documentsWithTerm = 0\n\n for (var fieldName in posting) {\n if (fieldName == '_index') continue // Ignore the term index, its not a field\n documentsWithTerm += Object.keys(posting[fieldName]).length\n }\n\n var x = (documentCount - documentsWithTerm + 0.5) / (documentsWithTerm + 0.5)\n\n return Math.log(1 + Math.abs(x))\n}\n\n/**\n * A token wraps a string representation of a token\n * as it is passed through the text processing pipeline.\n *\n * @constructor\n * @param {string} [str=''] - The string token being wrapped.\n * @param {object} [metadata={}] - Metadata associated with this token.\n */\nlunr.Token = function (str, metadata) {\n this.str = str || \"\"\n this.metadata = metadata || {}\n}\n\n/**\n * Returns the token string that is being wrapped by this object.\n *\n * @returns {string}\n */\nlunr.Token.prototype.toString = function () {\n return this.str\n}\n\n/**\n * A token update function is used when updating or optionally\n * when cloning a token.\n *\n * @callback lunr.Token~updateFunction\n * @param {string} str - The string representation of the token.\n * @param {Object} metadata - All metadata associated with this token.\n */\n\n/**\n * Applies the given function to the wrapped string token.\n *\n * @example\n * token.update(function (str, metadata) {\n * return str.toUpperCase()\n * })\n *\n * @param {lunr.Token~updateFunction} fn - A function to apply to the token string.\n * @returns {lunr.Token}\n */\nlunr.Token.prototype.update = function (fn) {\n this.str = fn(this.str, this.metadata)\n return this\n}\n\n/**\n * Creates a clone of this token. Optionally a function can be\n * applied to the cloned token.\n *\n * @param {lunr.Token~updateFunction} [fn] - An optional function to apply to the cloned token.\n * @returns {lunr.Token}\n */\nlunr.Token.prototype.clone = function (fn) {\n fn = fn || function (s) { return s }\n return new lunr.Token (fn(this.str, this.metadata), this.metadata)\n}\n/*!\n * lunr.tokenizer\n * Copyright (C) 2020 Oliver Nightingale\n */\n\n/**\n * A function for splitting a string into tokens ready to be inserted into\n * the search index. Uses `lunr.tokenizer.separator` to split strings, change\n * the value of this property to change how strings are split into tokens.\n *\n * This tokenizer will convert its parameter to a string by calling `toString` and\n * then will split this string on the character in `lunr.tokenizer.separator`.\n * Arrays will have their elements converted to strings and wrapped in a lunr.Token.\n *\n * Optional metadata can be passed to the tokenizer, this metadata will be cloned and\n * added as metadata to every token that is created from the object to be tokenized.\n *\n * @static\n * @param {?(string|object|object[])} obj - The object to convert into tokens\n * @param {?object} metadata - Optional metadata to associate with every token\n * @returns {lunr.Token[]}\n * @see {@link lunr.Pipeline}\n */\nlunr.tokenizer = function (obj, metadata) {\n if (obj == null || obj == undefined) {\n return []\n }\n\n if (Array.isArray(obj)) {\n return obj.map(function (t) {\n return new lunr.Token(\n lunr.utils.asString(t).toLowerCase(),\n lunr.utils.clone(metadata)\n )\n })\n }\n\n var str = obj.toString().toLowerCase(),\n len = str.length,\n tokens = []\n\n for (var sliceEnd = 0, sliceStart = 0; sliceEnd <= len; sliceEnd++) {\n var char = str.charAt(sliceEnd),\n sliceLength = sliceEnd - sliceStart\n\n if ((char.match(lunr.tokenizer.separator) || sliceEnd == len)) {\n\n if (sliceLength > 0) {\n var tokenMetadata = lunr.utils.clone(metadata) || {}\n tokenMetadata[\"position\"] = [sliceStart, sliceLength]\n tokenMetadata[\"index\"] = tokens.length\n\n tokens.push(\n new lunr.Token (\n str.slice(sliceStart, sliceEnd),\n tokenMetadata\n )\n )\n }\n\n sliceStart = sliceEnd + 1\n }\n\n }\n\n return tokens\n}\n\n/**\n * The separator used to split a string into tokens. Override this property to change the behaviour of\n * `lunr.tokenizer` behaviour when tokenizing strings. By default this splits on whitespace and hyphens.\n *\n * @static\n * @see lunr.tokenizer\n */\nlunr.tokenizer.separator = /[\\s\\-]+/\n/*!\n * lunr.Pipeline\n * Copyright (C) 2020 Oliver Nightingale\n */\n\n/**\n * lunr.Pipelines maintain an ordered list of functions to be applied to all\n * tokens in documents entering the search index and queries being ran against\n * the index.\n *\n * An instance of lunr.Index created with the lunr shortcut will contain a\n * pipeline with a stop word filter and an English language stemmer. Extra\n * functions can be added before or after either of these functions or these\n * default functions can be removed.\n *\n * When run the pipeline will call each function in turn, passing a token, the\n * index of that token in the original list of all tokens and finally a list of\n * all the original tokens.\n *\n * The output of functions in the pipeline will be passed to the next function\n * in the pipeline. To exclude a token from entering the index the function\n * should return undefined, the rest of the pipeline will not be called with\n * this token.\n *\n * For serialisation of pipelines to work, all functions used in an instance of\n * a pipeline should be registered with lunr.Pipeline. Registered functions can\n * then be loaded. If trying to load a serialised pipeline that uses functions\n * that are not registered an error will be thrown.\n *\n * If not planning on serialising the pipeline then registering pipeline functions\n * is not necessary.\n *\n * @constructor\n */\nlunr.Pipeline = function () {\n this._stack = []\n}\n\nlunr.Pipeline.registeredFunctions = Object.create(null)\n\n/**\n * A pipeline function maps lunr.Token to lunr.Token. A lunr.Token contains the token\n * string as well as all known metadata. A pipeline function can mutate the token string\n * or mutate (or add) metadata for a given token.\n *\n * A pipeline function can indicate that the passed token should be discarded by returning\n * null, undefined or an empty string. This token will not be passed to any downstream pipeline\n * functions and will not be added to the index.\n *\n * Multiple tokens can be returned by returning an array of tokens. Each token will be passed\n * to any downstream pipeline functions and all will returned tokens will be added to the index.\n *\n * Any number of pipeline functions may be chained together using a lunr.Pipeline.\n *\n * @interface lunr.PipelineFunction\n * @param {lunr.Token} token - A token from the document being processed.\n * @param {number} i - The index of this token in the complete list of tokens for this document/field.\n * @param {lunr.Token[]} tokens - All tokens for this document/field.\n * @returns {(?lunr.Token|lunr.Token[])}\n */\n\n/**\n * Register a function with the pipeline.\n *\n * Functions that are used in the pipeline should be registered if the pipeline\n * needs to be serialised, or a serialised pipeline needs to be loaded.\n *\n * Registering a function does not add it to a pipeline, functions must still be\n * added to instances of the pipeline for them to be used when running a pipeline.\n *\n * @param {lunr.PipelineFunction} fn - The function to check for.\n * @param {String} label - The label to register this function with\n */\nlunr.Pipeline.registerFunction = function (fn, label) {\n if (label in this.registeredFunctions) {\n lunr.utils.warn('Overwriting existing registered function: ' + label)\n }\n\n fn.label = label\n lunr.Pipeline.registeredFunctions[fn.label] = fn\n}\n\n/**\n * Warns if the function is not registered as a Pipeline function.\n *\n * @param {lunr.PipelineFunction} fn - The function to check for.\n * @private\n */\nlunr.Pipeline.warnIfFunctionNotRegistered = function (fn) {\n var isRegistered = fn.label && (fn.label in this.registeredFunctions)\n\n if (!isRegistered) {\n lunr.utils.warn('Function is not registered with pipeline. This may cause problems when serialising the index.\\n', fn)\n }\n}\n\n/**\n * Loads a previously serialised pipeline.\n *\n * All functions to be loaded must already be registered with lunr.Pipeline.\n * If any function from the serialised data has not been registered then an\n * error will be thrown.\n *\n * @param {Object} serialised - The serialised pipeline to load.\n * @returns {lunr.Pipeline}\n */\nlunr.Pipeline.load = function (serialised) {\n var pipeline = new lunr.Pipeline\n\n serialised.forEach(function (fnName) {\n var fn = lunr.Pipeline.registeredFunctions[fnName]\n\n if (fn) {\n pipeline.add(fn)\n } else {\n throw new Error('Cannot load unregistered function: ' + fnName)\n }\n })\n\n return pipeline\n}\n\n/**\n * Adds new functions to the end of the pipeline.\n *\n * Logs a warning if the function has not been registered.\n *\n * @param {lunr.PipelineFunction[]} functions - Any number of functions to add to the pipeline.\n */\nlunr.Pipeline.prototype.add = function () {\n var fns = Array.prototype.slice.call(arguments)\n\n fns.forEach(function (fn) {\n lunr.Pipeline.warnIfFunctionNotRegistered(fn)\n this._stack.push(fn)\n }, this)\n}\n\n/**\n * Adds a single function after a function that already exists in the\n * pipeline.\n *\n * Logs a warning if the function has not been registered.\n *\n * @param {lunr.PipelineFunction} existingFn - A function that already exists in the pipeline.\n * @param {lunr.PipelineFunction} newFn - The new function to add to the pipeline.\n */\nlunr.Pipeline.prototype.after = function (existingFn, newFn) {\n lunr.Pipeline.warnIfFunctionNotRegistered(newFn)\n\n var pos = this._stack.indexOf(existingFn)\n if (pos == -1) {\n throw new Error('Cannot find existingFn')\n }\n\n pos = pos + 1\n this._stack.splice(pos, 0, newFn)\n}\n\n/**\n * Adds a single function before a function that already exists in the\n * pipeline.\n *\n * Logs a warning if the function has not been registered.\n *\n * @param {lunr.PipelineFunction} existingFn - A function that already exists in the pipeline.\n * @param {lunr.PipelineFunction} newFn - The new function to add to the pipeline.\n */\nlunr.Pipeline.prototype.before = function (existingFn, newFn) {\n lunr.Pipeline.warnIfFunctionNotRegistered(newFn)\n\n var pos = this._stack.indexOf(existingFn)\n if (pos == -1) {\n throw new Error('Cannot find existingFn')\n }\n\n this._stack.splice(pos, 0, newFn)\n}\n\n/**\n * Removes a function from the pipeline.\n *\n * @param {lunr.PipelineFunction} fn The function to remove from the pipeline.\n */\nlunr.Pipeline.prototype.remove = function (fn) {\n var pos = this._stack.indexOf(fn)\n if (pos == -1) {\n return\n }\n\n this._stack.splice(pos, 1)\n}\n\n/**\n * Runs the current list of functions that make up the pipeline against the\n * passed tokens.\n *\n * @param {Array} tokens The tokens to run through the pipeline.\n * @returns {Array}\n */\nlunr.Pipeline.prototype.run = function (tokens) {\n var stackLength = this._stack.length\n\n for (var i = 0; i < stackLength; i++) {\n var fn = this._stack[i]\n var memo = []\n\n for (var j = 0; j < tokens.length; j++) {\n var result = fn(tokens[j], j, tokens)\n\n if (result === null || result === void 0 || result === '') continue\n\n if (Array.isArray(result)) {\n for (var k = 0; k < result.length; k++) {\n memo.push(result[k])\n }\n } else {\n memo.push(result)\n }\n }\n\n tokens = memo\n }\n\n return tokens\n}\n\n/**\n * Convenience method for passing a string through a pipeline and getting\n * strings out. This method takes care of wrapping the passed string in a\n * token and mapping the resulting tokens back to strings.\n *\n * @param {string} str - The string to pass through the pipeline.\n * @param {?object} metadata - Optional metadata to associate with the token\n * passed to the pipeline.\n * @returns {string[]}\n */\nlunr.Pipeline.prototype.runString = function (str, metadata) {\n var token = new lunr.Token (str, metadata)\n\n return this.run([token]).map(function (t) {\n return t.toString()\n })\n}\n\n/**\n * Resets the pipeline by removing any existing processors.\n *\n */\nlunr.Pipeline.prototype.reset = function () {\n this._stack = []\n}\n\n/**\n * Returns a representation of the pipeline ready for serialisation.\n *\n * Logs a warning if the function has not been registered.\n *\n * @returns {Array}\n */\nlunr.Pipeline.prototype.toJSON = function () {\n return this._stack.map(function (fn) {\n lunr.Pipeline.warnIfFunctionNotRegistered(fn)\n\n return fn.label\n })\n}\n/*!\n * lunr.Vector\n * Copyright (C) 2020 Oliver Nightingale\n */\n\n/**\n * A vector is used to construct the vector space of documents and queries. These\n * vectors support operations to determine the similarity between two documents or\n * a document and a query.\n *\n * Normally no parameters are required for initializing a vector, but in the case of\n * loading a previously dumped vector the raw elements can be provided to the constructor.\n *\n * For performance reasons vectors are implemented with a flat array, where an elements\n * index is immediately followed by its value. E.g. [index, value, index, value]. This\n * allows the underlying array to be as sparse as possible and still offer decent\n * performance when being used for vector calculations.\n *\n * @constructor\n * @param {Number[]} [elements] - The flat list of element index and element value pairs.\n */\nlunr.Vector = function (elements) {\n this._magnitude = 0\n this.elements = elements || []\n}\n\n\n/**\n * Calculates the position within the vector to insert a given index.\n *\n * This is used internally by insert and upsert. If there are duplicate indexes then\n * the position is returned as if the value for that index were to be updated, but it\n * is the callers responsibility to check whether there is a duplicate at that index\n *\n * @param {Number} insertIdx - The index at which the element should be inserted.\n * @returns {Number}\n */\nlunr.Vector.prototype.positionForIndex = function (index) {\n // For an empty vector the tuple can be inserted at the beginning\n if (this.elements.length == 0) {\n return 0\n }\n\n var start = 0,\n end = this.elements.length / 2,\n sliceLength = end - start,\n pivotPoint = Math.floor(sliceLength / 2),\n pivotIndex = this.elements[pivotPoint * 2]\n\n while (sliceLength > 1) {\n if (pivotIndex < index) {\n start = pivotPoint\n }\n\n if (pivotIndex > index) {\n end = pivotPoint\n }\n\n if (pivotIndex == index) {\n break\n }\n\n sliceLength = end - start\n pivotPoint = start + Math.floor(sliceLength / 2)\n pivotIndex = this.elements[pivotPoint * 2]\n }\n\n if (pivotIndex == index) {\n return pivotPoint * 2\n }\n\n if (pivotIndex > index) {\n return pivotPoint * 2\n }\n\n if (pivotIndex < index) {\n return (pivotPoint + 1) * 2\n }\n}\n\n/**\n * Inserts an element at an index within the vector.\n *\n * Does not allow duplicates, will throw an error if there is already an entry\n * for this index.\n *\n * @param {Number} insertIdx - The index at which the element should be inserted.\n * @param {Number} val - The value to be inserted into the vector.\n */\nlunr.Vector.prototype.insert = function (insertIdx, val) {\n this.upsert(insertIdx, val, function () {\n throw \"duplicate index\"\n })\n}\n\n/**\n * Inserts or updates an existing index within the vector.\n *\n * @param {Number} insertIdx - The index at which the element should be inserted.\n * @param {Number} val - The value to be inserted into the vector.\n * @param {function} fn - A function that is called for updates, the existing value and the\n * requested value are passed as arguments\n */\nlunr.Vector.prototype.upsert = function (insertIdx, val, fn) {\n this._magnitude = 0\n var position = this.positionForIndex(insertIdx)\n\n if (this.elements[position] == insertIdx) {\n this.elements[position + 1] = fn(this.elements[position + 1], val)\n } else {\n this.elements.splice(position, 0, insertIdx, val)\n }\n}\n\n/**\n * Calculates the magnitude of this vector.\n *\n * @returns {Number}\n */\nlunr.Vector.prototype.magnitude = function () {\n if (this._magnitude) return this._magnitude\n\n var sumOfSquares = 0,\n elementsLength = this.elements.length\n\n for (var i = 1; i < elementsLength; i += 2) {\n var val = this.elements[i]\n sumOfSquares += val * val\n }\n\n return this._magnitude = Math.sqrt(sumOfSquares)\n}\n\n/**\n * Calculates the dot product of this vector and another vector.\n *\n * @param {lunr.Vector} otherVector - The vector to compute the dot product with.\n * @returns {Number}\n */\nlunr.Vector.prototype.dot = function (otherVector) {\n var dotProduct = 0,\n a = this.elements, b = otherVector.elements,\n aLen = a.length, bLen = b.length,\n aVal = 0, bVal = 0,\n i = 0, j = 0\n\n while (i < aLen && j < bLen) {\n aVal = a[i], bVal = b[j]\n if (aVal < bVal) {\n i += 2\n } else if (aVal > bVal) {\n j += 2\n } else if (aVal == bVal) {\n dotProduct += a[i + 1] * b[j + 1]\n i += 2\n j += 2\n }\n }\n\n return dotProduct\n}\n\n/**\n * Calculates the similarity between this vector and another vector.\n *\n * @param {lunr.Vector} otherVector - The other vector to calculate the\n * similarity with.\n * @returns {Number}\n */\nlunr.Vector.prototype.similarity = function (otherVector) {\n return this.dot(otherVector) / this.magnitude() || 0\n}\n\n/**\n * Converts the vector to an array of the elements within the vector.\n *\n * @returns {Number[]}\n */\nlunr.Vector.prototype.toArray = function () {\n var output = new Array (this.elements.length / 2)\n\n for (var i = 1, j = 0; i < this.elements.length; i += 2, j++) {\n output[j] = this.elements[i]\n }\n\n return output\n}\n\n/**\n * A JSON serializable representation of the vector.\n *\n * @returns {Number[]}\n */\nlunr.Vector.prototype.toJSON = function () {\n return this.elements\n}\n/* eslint-disable */\n/*!\n * lunr.stemmer\n * Copyright (C) 2020 Oliver Nightingale\n * Includes code from - http://tartarus.org/~martin/PorterStemmer/js.txt\n */\n\n/**\n * lunr.stemmer is an english language stemmer, this is a JavaScript\n * implementation of the PorterStemmer taken from http://tartarus.org/~martin\n *\n * @static\n * @implements {lunr.PipelineFunction}\n * @param {lunr.Token} token - The string to stem\n * @returns {lunr.Token}\n * @see {@link lunr.Pipeline}\n * @function\n */\nlunr.stemmer = (function(){\n var step2list = {\n \"ational\" : \"ate\",\n \"tional\" : \"tion\",\n \"enci\" : \"ence\",\n \"anci\" : \"ance\",\n \"izer\" : \"ize\",\n \"bli\" : \"ble\",\n \"alli\" : \"al\",\n \"entli\" : \"ent\",\n \"eli\" : \"e\",\n \"ousli\" : \"ous\",\n \"ization\" : \"ize\",\n \"ation\" : \"ate\",\n \"ator\" : \"ate\",\n \"alism\" : \"al\",\n \"iveness\" : \"ive\",\n \"fulness\" : \"ful\",\n \"ousness\" : \"ous\",\n \"aliti\" : \"al\",\n \"iviti\" : \"ive\",\n \"biliti\" : \"ble\",\n \"logi\" : \"log\"\n },\n\n step3list = {\n \"icate\" : \"ic\",\n \"ative\" : \"\",\n \"alize\" : \"al\",\n \"iciti\" : \"ic\",\n \"ical\" : \"ic\",\n \"ful\" : \"\",\n \"ness\" : \"\"\n },\n\n c = \"[^aeiou]\", // consonant\n v = \"[aeiouy]\", // vowel\n C = c + \"[^aeiouy]*\", // consonant sequence\n V = v + \"[aeiou]*\", // vowel sequence\n\n mgr0 = \"^(\" + C + \")?\" + V + C, // [C]VC... is m>0\n meq1 = \"^(\" + C + \")?\" + V + C + \"(\" + V + \")?$\", // [C]VC[V] is m=1\n mgr1 = \"^(\" + C + \")?\" + V + C + V + C, // [C]VCVC... is m>1\n s_v = \"^(\" + C + \")?\" + v; // vowel in stem\n\n var re_mgr0 = new RegExp(mgr0);\n var re_mgr1 = new RegExp(mgr1);\n var re_meq1 = new RegExp(meq1);\n var re_s_v = new RegExp(s_v);\n\n var re_1a = /^(.+?)(ss|i)es$/;\n var re2_1a = /^(.+?)([^s])s$/;\n var re_1b = /^(.+?)eed$/;\n var re2_1b = /^(.+?)(ed|ing)$/;\n var re_1b_2 = /.$/;\n var re2_1b_2 = /(at|bl|iz)$/;\n var re3_1b_2 = new RegExp(\"([^aeiouylsz])\\\\1$\");\n var re4_1b_2 = new RegExp(\"^\" + C + v + \"[^aeiouwxy]$\");\n\n var re_1c = /^(.+?[^aeiou])y$/;\n var re_2 = /^(.+?)(ational|tional|enci|anci|izer|bli|alli|entli|eli|ousli|ization|ation|ator|alism|iveness|fulness|ousness|aliti|iviti|biliti|logi)$/;\n\n var re_3 = /^(.+?)(icate|ative|alize|iciti|ical|ful|ness)$/;\n\n var re_4 = /^(.+?)(al|ance|ence|er|ic|able|ible|ant|ement|ment|ent|ou|ism|ate|iti|ous|ive|ize)$/;\n var re2_4 = /^(.+?)(s|t)(ion)$/;\n\n var re_5 = /^(.+?)e$/;\n var re_5_1 = /ll$/;\n var re3_5 = new RegExp(\"^\" + C + v + \"[^aeiouwxy]$\");\n\n var porterStemmer = function porterStemmer(w) {\n var stem,\n suffix,\n firstch,\n re,\n re2,\n re3,\n re4;\n\n if (w.length < 3) { return w; }\n\n firstch = w.substr(0,1);\n if (firstch == \"y\") {\n w = firstch.toUpperCase() + w.substr(1);\n }\n\n // Step 1a\n re = re_1a\n re2 = re2_1a;\n\n if (re.test(w)) { w = w.replace(re,\"$1$2\"); }\n else if (re2.test(w)) { w = w.replace(re2,\"$1$2\"); }\n\n // Step 1b\n re = re_1b;\n re2 = re2_1b;\n if (re.test(w)) {\n var fp = re.exec(w);\n re = re_mgr0;\n if (re.test(fp[1])) {\n re = re_1b_2;\n w = w.replace(re,\"\");\n }\n } else if (re2.test(w)) {\n var fp = re2.exec(w);\n stem = fp[1];\n re2 = re_s_v;\n if (re2.test(stem)) {\n w = stem;\n re2 = re2_1b_2;\n re3 = re3_1b_2;\n re4 = re4_1b_2;\n if (re2.test(w)) { w = w + \"e\"; }\n else if (re3.test(w)) { re = re_1b_2; w = w.replace(re,\"\"); }\n else if (re4.test(w)) { w = w + \"e\"; }\n }\n }\n\n // 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)\n re = re_1c;\n if (re.test(w)) {\n var fp = re.exec(w);\n stem = fp[1];\n w = stem + \"i\";\n }\n\n // Step 2\n re = re_2;\n if (re.test(w)) {\n var fp = re.exec(w);\n stem = fp[1];\n suffix = fp[2];\n re = re_mgr0;\n if (re.test(stem)) {\n w = stem + step2list[suffix];\n }\n }\n\n // Step 3\n re = re_3;\n if (re.test(w)) {\n var fp = re.exec(w);\n stem = fp[1];\n suffix = fp[2];\n re = re_mgr0;\n if (re.test(stem)) {\n w = stem + step3list[suffix];\n }\n }\n\n // Step 4\n re = re_4;\n re2 = re2_4;\n if (re.test(w)) {\n var fp = re.exec(w);\n stem = fp[1];\n re = re_mgr1;\n if (re.test(stem)) {\n w = stem;\n }\n } else if (re2.test(w)) {\n var fp = re2.exec(w);\n stem = fp[1] + fp[2];\n re2 = re_mgr1;\n if (re2.test(stem)) {\n w = stem;\n }\n }\n\n // Step 5\n re = re_5;\n if (re.test(w)) {\n var fp = re.exec(w);\n stem = fp[1];\n re = re_mgr1;\n re2 = re_meq1;\n re3 = re3_5;\n if (re.test(stem) || (re2.test(stem) && !(re3.test(stem)))) {\n w = stem;\n }\n }\n\n re = re_5_1;\n re2 = re_mgr1;\n if (re.test(w) && re2.test(w)) {\n re = re_1b_2;\n w = w.replace(re,\"\");\n }\n\n // and turn initial Y back to y\n\n if (firstch == \"y\") {\n w = firstch.toLowerCase() + w.substr(1);\n }\n\n return w;\n };\n\n return function (token) {\n return token.update(porterStemmer);\n }\n})();\n\nlunr.Pipeline.registerFunction(lunr.stemmer, 'stemmer')\n/*!\n * lunr.stopWordFilter\n * Copyright (C) 2020 Oliver Nightingale\n */\n\n/**\n * lunr.generateStopWordFilter builds a stopWordFilter function from the provided\n * list of stop words.\n *\n * The built in lunr.stopWordFilter is built using this generator and can be used\n * to generate custom stopWordFilters for applications or non English languages.\n *\n * @function\n * @param {Array} token The token to pass through the filter\n * @returns {lunr.PipelineFunction}\n * @see lunr.Pipeline\n * @see lunr.stopWordFilter\n */\nlunr.generateStopWordFilter = function (stopWords) {\n var words = stopWords.reduce(function (memo, stopWord) {\n memo[stopWord] = stopWord\n return memo\n }, {})\n\n return function (token) {\n if (token && words[token.toString()] !== token.toString()) return token\n }\n}\n\n/**\n * lunr.stopWordFilter is an English language stop word list filter, any words\n * contained in the list will not be passed through the filter.\n *\n * This is intended to be used in the Pipeline. If the token does not pass the\n * filter then undefined will be returned.\n *\n * @function\n * @implements {lunr.PipelineFunction}\n * @params {lunr.Token} token - A token to check for being a stop word.\n * @returns {lunr.Token}\n * @see {@link lunr.Pipeline}\n */\nlunr.stopWordFilter = lunr.generateStopWordFilter([\n 'a',\n 'able',\n 'about',\n 'across',\n 'after',\n 'all',\n 'almost',\n 'also',\n 'am',\n 'among',\n 'an',\n 'and',\n 'any',\n 'are',\n 'as',\n 'at',\n 'be',\n 'because',\n 'been',\n 'but',\n 'by',\n 'can',\n 'cannot',\n 'could',\n 'dear',\n 'did',\n 'do',\n 'does',\n 'either',\n 'else',\n 'ever',\n 'every',\n 'for',\n 'from',\n 'get',\n 'got',\n 'had',\n 'has',\n 'have',\n 'he',\n 'her',\n 'hers',\n 'him',\n 'his',\n 'how',\n 'however',\n 'i',\n 'if',\n 'in',\n 'into',\n 'is',\n 'it',\n 'its',\n 'just',\n 'least',\n 'let',\n 'like',\n 'likely',\n 'may',\n 'me',\n 'might',\n 'most',\n 'must',\n 'my',\n 'neither',\n 'no',\n 'nor',\n 'not',\n 'of',\n 'off',\n 'often',\n 'on',\n 'only',\n 'or',\n 'other',\n 'our',\n 'own',\n 'rather',\n 'said',\n 'say',\n 'says',\n 'she',\n 'should',\n 'since',\n 'so',\n 'some',\n 'than',\n 'that',\n 'the',\n 'their',\n 'them',\n 'then',\n 'there',\n 'these',\n 'they',\n 'this',\n 'tis',\n 'to',\n 'too',\n 'twas',\n 'us',\n 'wants',\n 'was',\n 'we',\n 'were',\n 'what',\n 'when',\n 'where',\n 'which',\n 'while',\n 'who',\n 'whom',\n 'why',\n 'will',\n 'with',\n 'would',\n 'yet',\n 'you',\n 'your'\n])\n\nlunr.Pipeline.registerFunction(lunr.stopWordFilter, 'stopWordFilter')\n/*!\n * lunr.trimmer\n * Copyright (C) 2020 Oliver Nightingale\n */\n\n/**\n * lunr.trimmer is a pipeline function for trimming non word\n * characters from the beginning and end of tokens before they\n * enter the index.\n *\n * This implementation may not work correctly for non latin\n * characters and should either be removed or adapted for use\n * with languages with non-latin characters.\n *\n * @static\n * @implements {lunr.PipelineFunction}\n * @param {lunr.Token} token The token to pass through the filter\n * @returns {lunr.Token}\n * @see lunr.Pipeline\n */\nlunr.trimmer = function (token) {\n return token.update(function (s) {\n return s.replace(/^\\W+/, '').replace(/\\W+$/, '')\n })\n}\n\nlunr.Pipeline.registerFunction(lunr.trimmer, 'trimmer')\n/*!\n * lunr.TokenSet\n * Copyright (C) 2020 Oliver Nightingale\n */\n\n/**\n * A token set is used to store the unique list of all tokens\n * within an index. Token sets are also used to represent an\n * incoming query to the index, this query token set and index\n * token set are then intersected to find which tokens to look\n * up in the inverted index.\n *\n * A token set can hold multiple tokens, as in the case of the\n * index token set, or it can hold a single token as in the\n * case of a simple query token set.\n *\n * Additionally token sets are used to perform wildcard matching.\n * Leading, contained and trailing wildcards are supported, and\n * from this edit distance matching can also be provided.\n *\n * Token sets are implemented as a minimal finite state automata,\n * where both common prefixes and suffixes are shared between tokens.\n * This helps to reduce the space used for storing the token set.\n *\n * @constructor\n */\nlunr.TokenSet = function () {\n this.final = false\n this.edges = {}\n this.id = lunr.TokenSet._nextId\n lunr.TokenSet._nextId += 1\n}\n\n/**\n * Keeps track of the next, auto increment, identifier to assign\n * to a new tokenSet.\n *\n * TokenSets require a unique identifier to be correctly minimised.\n *\n * @private\n */\nlunr.TokenSet._nextId = 1\n\n/**\n * Creates a TokenSet instance from the given sorted array of words.\n *\n * @param {String[]} arr - A sorted array of strings to create the set from.\n * @returns {lunr.TokenSet}\n * @throws Will throw an error if the input array is not sorted.\n */\nlunr.TokenSet.fromArray = function (arr) {\n var builder = new lunr.TokenSet.Builder\n\n for (var i = 0, len = arr.length; i < len; i++) {\n builder.insert(arr[i])\n }\n\n builder.finish()\n return builder.root\n}\n\n/**\n * Creates a token set from a query clause.\n *\n * @private\n * @param {Object} clause - A single clause from lunr.Query.\n * @param {string} clause.term - The query clause term.\n * @param {number} [clause.editDistance] - The optional edit distance for the term.\n * @returns {lunr.TokenSet}\n */\nlunr.TokenSet.fromClause = function (clause) {\n if ('editDistance' in clause) {\n return lunr.TokenSet.fromFuzzyString(clause.term, clause.editDistance)\n } else {\n return lunr.TokenSet.fromString(clause.term)\n }\n}\n\n/**\n * Creates a token set representing a single string with a specified\n * edit distance.\n *\n * Insertions, deletions, substitutions and transpositions are each\n * treated as an edit distance of 1.\n *\n * Increasing the allowed edit distance will have a dramatic impact\n * on the performance of both creating and intersecting these TokenSets.\n * It is advised to keep the edit distance less than 3.\n *\n * @param {string} str - The string to create the token set from.\n * @param {number} editDistance - The allowed edit distance to match.\n * @returns {lunr.Vector}\n */\nlunr.TokenSet.fromFuzzyString = function (str, editDistance) {\n var root = new lunr.TokenSet\n\n var stack = [{\n node: root,\n editsRemaining: editDistance,\n str: str\n }]\n\n while (stack.length) {\n var frame = stack.pop()\n\n // no edit\n if (frame.str.length > 0) {\n var char = frame.str.charAt(0),\n noEditNode\n\n if (char in frame.node.edges) {\n noEditNode = frame.node.edges[char]\n } else {\n noEditNode = new lunr.TokenSet\n frame.node.edges[char] = noEditNode\n }\n\n if (frame.str.length == 1) {\n noEditNode.final = true\n }\n\n stack.push({\n node: noEditNode,\n editsRemaining: frame.editsRemaining,\n str: frame.str.slice(1)\n })\n }\n\n if (frame.editsRemaining == 0) {\n continue\n }\n\n // insertion\n if (\"*\" in frame.node.edges) {\n var insertionNode = frame.node.edges[\"*\"]\n } else {\n var insertionNode = new lunr.TokenSet\n frame.node.edges[\"*\"] = insertionNode\n }\n\n if (frame.str.length == 0) {\n insertionNode.final = true\n }\n\n stack.push({\n node: insertionNode,\n editsRemaining: frame.editsRemaining - 1,\n str: frame.str\n })\n\n // deletion\n // can only do a deletion if we have enough edits remaining\n // and if there are characters left to delete in the string\n if (frame.str.length > 1) {\n stack.push({\n node: frame.node,\n editsRemaining: frame.editsRemaining - 1,\n str: frame.str.slice(1)\n })\n }\n\n // deletion\n // just removing the last character from the str\n if (frame.str.length == 1) {\n frame.node.final = true\n }\n\n // substitution\n // can only do a substitution if we have enough edits remaining\n // and if there are characters left to substitute\n if (frame.str.length >= 1) {\n if (\"*\" in frame.node.edges) {\n var substitutionNode = frame.node.edges[\"*\"]\n } else {\n var substitutionNode = new lunr.TokenSet\n frame.node.edges[\"*\"] = substitutionNode\n }\n\n if (frame.str.length == 1) {\n substitutionNode.final = true\n }\n\n stack.push({\n node: substitutionNode,\n editsRemaining: frame.editsRemaining - 1,\n str: frame.str.slice(1)\n })\n }\n\n // transposition\n // can only do a transposition if there are edits remaining\n // and there are enough characters to transpose\n if (frame.str.length > 1) {\n var charA = frame.str.charAt(0),\n charB = frame.str.charAt(1),\n transposeNode\n\n if (charB in frame.node.edges) {\n transposeNode = frame.node.edges[charB]\n } else {\n transposeNode = new lunr.TokenSet\n frame.node.edges[charB] = transposeNode\n }\n\n if (frame.str.length == 1) {\n transposeNode.final = true\n }\n\n stack.push({\n node: transposeNode,\n editsRemaining: frame.editsRemaining - 1,\n str: charA + frame.str.slice(2)\n })\n }\n }\n\n return root\n}\n\n/**\n * Creates a TokenSet from a string.\n *\n * The string may contain one or more wildcard characters (*)\n * that will allow wildcard matching when intersecting with\n * another TokenSet.\n *\n * @param {string} str - The string to create a TokenSet from.\n * @returns {lunr.TokenSet}\n */\nlunr.TokenSet.fromString = function (str) {\n var node = new lunr.TokenSet,\n root = node\n\n /*\n * Iterates through all characters within the passed string\n * appending a node for each character.\n *\n * When a wildcard character is found then a self\n * referencing edge is introduced to continually match\n * any number of any characters.\n */\n for (var i = 0, len = str.length; i < len; i++) {\n var char = str[i],\n final = (i == len - 1)\n\n if (char == \"*\") {\n node.edges[char] = node\n node.final = final\n\n } else {\n var next = new lunr.TokenSet\n next.final = final\n\n node.edges[char] = next\n node = next\n }\n }\n\n return root\n}\n\n/**\n * Converts this TokenSet into an array of strings\n * contained within the TokenSet.\n *\n * This is not intended to be used on a TokenSet that\n * contains wildcards, in these cases the results are\n * undefined and are likely to cause an infinite loop.\n *\n * @returns {string[]}\n */\nlunr.TokenSet.prototype.toArray = function () {\n var words = []\n\n var stack = [{\n prefix: \"\",\n node: this\n }]\n\n while (stack.length) {\n var frame = stack.pop(),\n edges = Object.keys(frame.node.edges),\n len = edges.length\n\n if (frame.node.final) {\n /* In Safari, at this point the prefix is sometimes corrupted, see:\n * https://github.com/olivernn/lunr.js/issues/279 Calling any\n * String.prototype method forces Safari to \"cast\" this string to what\n * it's supposed to be, fixing the bug. */\n frame.prefix.charAt(0)\n words.push(frame.prefix)\n }\n\n for (var i = 0; i < len; i++) {\n var edge = edges[i]\n\n stack.push({\n prefix: frame.prefix.concat(edge),\n node: frame.node.edges[edge]\n })\n }\n }\n\n return words\n}\n\n/**\n * Generates a string representation of a TokenSet.\n *\n * This is intended to allow TokenSets to be used as keys\n * in objects, largely to aid the construction and minimisation\n * of a TokenSet. As such it is not designed to be a human\n * friendly representation of the TokenSet.\n *\n * @returns {string}\n */\nlunr.TokenSet.prototype.toString = function () {\n // NOTE: Using Object.keys here as this.edges is very likely\n // to enter 'hash-mode' with many keys being added\n //\n // avoiding a for-in loop here as it leads to the function\n // being de-optimised (at least in V8). From some simple\n // benchmarks the performance is comparable, but allowing\n // V8 to optimize may mean easy performance wins in the future.\n\n if (this._str) {\n return this._str\n }\n\n var str = this.final ? '1' : '0',\n labels = Object.keys(this.edges).sort(),\n len = labels.length\n\n for (var i = 0; i < len; i++) {\n var label = labels[i],\n node = this.edges[label]\n\n str = str + label + node.id\n }\n\n return str\n}\n\n/**\n * Returns a new TokenSet that is the intersection of\n * this TokenSet and the passed TokenSet.\n *\n * This intersection will take into account any wildcards\n * contained within the TokenSet.\n *\n * @param {lunr.TokenSet} b - An other TokenSet to intersect with.\n * @returns {lunr.TokenSet}\n */\nlunr.TokenSet.prototype.intersect = function (b) {\n var output = new lunr.TokenSet,\n frame = undefined\n\n var stack = [{\n qNode: b,\n output: output,\n node: this\n }]\n\n while (stack.length) {\n frame = stack.pop()\n\n // NOTE: As with the #toString method, we are using\n // Object.keys and a for loop instead of a for-in loop\n // as both of these objects enter 'hash' mode, causing\n // the function to be de-optimised in V8\n var qEdges = Object.keys(frame.qNode.edges),\n qLen = qEdges.length,\n nEdges = Object.keys(frame.node.edges),\n nLen = nEdges.length\n\n for (var q = 0; q < qLen; q++) {\n var qEdge = qEdges[q]\n\n for (var n = 0; n < nLen; n++) {\n var nEdge = nEdges[n]\n\n if (nEdge == qEdge || qEdge == '*') {\n var node = frame.node.edges[nEdge],\n qNode = frame.qNode.edges[qEdge],\n final = node.final && qNode.final,\n next = undefined\n\n if (nEdge in frame.output.edges) {\n // an edge already exists for this character\n // no need to create a new node, just set the finality\n // bit unless this node is already final\n next = frame.output.edges[nEdge]\n next.final = next.final || final\n\n } else {\n // no edge exists yet, must create one\n // set the finality bit and insert it\n // into the output\n next = new lunr.TokenSet\n next.final = final\n frame.output.edges[nEdge] = next\n }\n\n stack.push({\n qNode: qNode,\n output: next,\n node: node\n })\n }\n }\n }\n }\n\n return output\n}\nlunr.TokenSet.Builder = function () {\n this.previousWord = \"\"\n this.root = new lunr.TokenSet\n this.uncheckedNodes = []\n this.minimizedNodes = {}\n}\n\nlunr.TokenSet.Builder.prototype.insert = function (word) {\n var node,\n commonPrefix = 0\n\n if (word < this.previousWord) {\n throw new Error (\"Out of order word insertion\")\n }\n\n for (var i = 0; i < word.length && i < this.previousWord.length; i++) {\n if (word[i] != this.previousWord[i]) break\n commonPrefix++\n }\n\n this.minimize(commonPrefix)\n\n if (this.uncheckedNodes.length == 0) {\n node = this.root\n } else {\n node = this.uncheckedNodes[this.uncheckedNodes.length - 1].child\n }\n\n for (var i = commonPrefix; i < word.length; i++) {\n var nextNode = new lunr.TokenSet,\n char = word[i]\n\n node.edges[char] = nextNode\n\n this.uncheckedNodes.push({\n parent: node,\n char: char,\n child: nextNode\n })\n\n node = nextNode\n }\n\n node.final = true\n this.previousWord = word\n}\n\nlunr.TokenSet.Builder.prototype.finish = function () {\n this.minimize(0)\n}\n\nlunr.TokenSet.Builder.prototype.minimize = function (downTo) {\n for (var i = this.uncheckedNodes.length - 1; i >= downTo; i--) {\n var node = this.uncheckedNodes[i],\n childKey = node.child.toString()\n\n if (childKey in this.minimizedNodes) {\n node.parent.edges[node.char] = this.minimizedNodes[childKey]\n } else {\n // Cache the key for this node since\n // we know it can't change anymore\n node.child._str = childKey\n\n this.minimizedNodes[childKey] = node.child\n }\n\n this.uncheckedNodes.pop()\n }\n}\n/*!\n * lunr.Index\n * Copyright (C) 2020 Oliver Nightingale\n */\n\n/**\n * An index contains the built index of all documents and provides a query interface\n * to the index.\n *\n * Usually instances of lunr.Index will not be created using this constructor, instead\n * lunr.Builder should be used to construct new indexes, or lunr.Index.load should be\n * used to load previously built and serialized indexes.\n *\n * @constructor\n * @param {Object} attrs - The attributes of the built search index.\n * @param {Object} attrs.invertedIndex - An index of term/field to document reference.\n * @param {Object} attrs.fieldVectors - Field vectors\n * @param {lunr.TokenSet} attrs.tokenSet - An set of all corpus tokens.\n * @param {string[]} attrs.fields - The names of indexed document fields.\n * @param {lunr.Pipeline} attrs.pipeline - The pipeline to use for search terms.\n */\nlunr.Index = function (attrs) {\n this.invertedIndex = attrs.invertedIndex\n this.fieldVectors = attrs.fieldVectors\n this.tokenSet = attrs.tokenSet\n this.fields = attrs.fields\n this.pipeline = attrs.pipeline\n}\n\n/**\n * A result contains details of a document matching a search query.\n * @typedef {Object} lunr.Index~Result\n * @property {string} ref - The reference of the document this result represents.\n * @property {number} score - A number between 0 and 1 representing how similar this document is to the query.\n * @property {lunr.MatchData} matchData - Contains metadata about this match including which term(s) caused the match.\n */\n\n/**\n * Although lunr provides the ability to create queries using lunr.Query, it also provides a simple\n * query language which itself is parsed into an instance of lunr.Query.\n *\n * For programmatically building queries it is advised to directly use lunr.Query, the query language\n * is best used for human entered text rather than program generated text.\n *\n * At its simplest queries can just be a single term, e.g. `hello`, multiple terms are also supported\n * and will be combined with OR, e.g `hello world` will match documents that contain either 'hello'\n * or 'world', though those that contain both will rank higher in the results.\n *\n * Wildcards can be included in terms to match one or more unspecified characters, these wildcards can\n * be inserted anywhere within the term, and more than one wildcard can exist in a single term. Adding\n * wildcards will increase the number of documents that will be found but can also have a negative\n * impact on query performance, especially with wildcards at the beginning of a term.\n *\n * Terms can be restricted to specific fields, e.g. `title:hello`, only documents with the term\n * hello in the title field will match this query. Using a field not present in the index will lead\n * to an error being thrown.\n *\n * Modifiers can also be added to terms, lunr supports edit distance and boost modifiers on terms. A term\n * boost will make documents matching that term score higher, e.g. `foo^5`. Edit distance is also supported\n * to provide fuzzy matching, e.g. 'hello~2' will match documents with hello with an edit distance of 2.\n * Avoid large values for edit distance to improve query performance.\n *\n * Each term also supports a presence modifier. By default a term's presence in document is optional, however\n * this can be changed to either required or prohibited. For a term's presence to be required in a document the\n * term should be prefixed with a '+', e.g. `+foo bar` is a search for documents that must contain 'foo' and\n * optionally contain 'bar'. Conversely a leading '-' sets the terms presence to prohibited, i.e. it must not\n * appear in a document, e.g. `-foo bar` is a search for documents that do not contain 'foo' but may contain 'bar'.\n *\n * To escape special characters the backslash character '\\' can be used, this allows searches to include\n * characters that would normally be considered modifiers, e.g. `foo\\~2` will search for a term \"foo~2\" instead\n * of attempting to apply a boost of 2 to the search term \"foo\".\n *\n * @typedef {string} lunr.Index~QueryString\n * @example Simple single term query\n * hello\n * @example Multiple term query\n * hello world\n * @example term scoped to a field\n * title:hello\n * @example term with a boost of 10\n * hello^10\n * @example term with an edit distance of 2\n * hello~2\n * @example terms with presence modifiers\n * -foo +bar baz\n */\n\n/**\n * Performs a search against the index using lunr query syntax.\n *\n * Results will be returned sorted by their score, the most relevant results\n * will be returned first. For details on how the score is calculated, please see\n * the {@link https://lunrjs.com/guides/searching.html#scoring|guide}.\n *\n * For more programmatic querying use lunr.Index#query.\n *\n * @param {lunr.Index~QueryString} queryString - A string containing a lunr query.\n * @throws {lunr.QueryParseError} If the passed query string cannot be parsed.\n * @returns {lunr.Index~Result[]}\n */\nlunr.Index.prototype.search = function (queryString) {\n return this.query(function (query) {\n var parser = new lunr.QueryParser(queryString, query)\n parser.parse()\n })\n}\n\n/**\n * A query builder callback provides a query object to be used to express\n * the query to perform on the index.\n *\n * @callback lunr.Index~queryBuilder\n * @param {lunr.Query} query - The query object to build up.\n * @this lunr.Query\n */\n\n/**\n * Performs a query against the index using the yielded lunr.Query object.\n *\n * If performing programmatic queries against the index, this method is preferred\n * over lunr.Index#search so as to avoid the additional query parsing overhead.\n *\n * A query object is yielded to the supplied function which should be used to\n * express the query to be run against the index.\n *\n * Note that although this function takes a callback parameter it is _not_ an\n * asynchronous operation, the callback is just yielded a query object to be\n * customized.\n *\n * @param {lunr.Index~queryBuilder} fn - A function that is used to build the query.\n * @returns {lunr.Index~Result[]}\n */\nlunr.Index.prototype.query = function (fn) {\n // for each query clause\n // * process terms\n // * expand terms from token set\n // * find matching documents and metadata\n // * get document vectors\n // * score documents\n\n var query = new lunr.Query(this.fields),\n matchingFields = Object.create(null),\n queryVectors = Object.create(null),\n termFieldCache = Object.create(null),\n requiredMatches = Object.create(null),\n prohibitedMatches = Object.create(null)\n\n /*\n * To support field level boosts a query vector is created per\n * field. An empty vector is eagerly created to support negated\n * queries.\n */\n for (var i = 0; i < this.fields.length; i++) {\n queryVectors[this.fields[i]] = new lunr.Vector\n }\n\n fn.call(query, query)\n\n for (var i = 0; i < query.clauses.length; i++) {\n /*\n * Unless the pipeline has been disabled for this term, which is\n * the case for terms with wildcards, we need to pass the clause\n * term through the search pipeline. A pipeline returns an array\n * of processed terms. Pipeline functions may expand the passed\n * term, which means we may end up performing multiple index lookups\n * for a single query term.\n */\n var clause = query.clauses[i],\n terms = null,\n clauseMatches = lunr.Set.empty\n\n if (clause.usePipeline) {\n terms = this.pipeline.runString(clause.term, {\n fields: clause.fields\n })\n } else {\n terms = [clause.term]\n }\n\n for (var m = 0; m < terms.length; m++) {\n var term = terms[m]\n\n /*\n * Each term returned from the pipeline needs to use the same query\n * clause object, e.g. the same boost and or edit distance. The\n * simplest way to do this is to re-use the clause object but mutate\n * its term property.\n */\n clause.term = term\n\n /*\n * From the term in the clause we create a token set which will then\n * be used to intersect the indexes token set to get a list of terms\n * to lookup in the inverted index\n */\n var termTokenSet = lunr.TokenSet.fromClause(clause),\n expandedTerms = this.tokenSet.intersect(termTokenSet).toArray()\n\n /*\n * If a term marked as required does not exist in the tokenSet it is\n * impossible for the search to return any matches. We set all the field\n * scoped required matches set to empty and stop examining any further\n * clauses.\n */\n if (expandedTerms.length === 0 && clause.presence === lunr.Query.presence.REQUIRED) {\n for (var k = 0; k < clause.fields.length; k++) {\n var field = clause.fields[k]\n requiredMatches[field] = lunr.Set.empty\n }\n\n break\n }\n\n for (var j = 0; j < expandedTerms.length; j++) {\n /*\n * For each term get the posting and termIndex, this is required for\n * building the query vector.\n */\n var expandedTerm = expandedTerms[j],\n posting = this.invertedIndex[expandedTerm],\n termIndex = posting._index\n\n for (var k = 0; k < clause.fields.length; k++) {\n /*\n * For each field that this query term is scoped by (by default\n * all fields are in scope) we need to get all the document refs\n * that have this term in that field.\n *\n * The posting is the entry in the invertedIndex for the matching\n * term from above.\n */\n var field = clause.fields[k],\n fieldPosting = posting[field],\n matchingDocumentRefs = Object.keys(fieldPosting),\n termField = expandedTerm + \"/\" + field,\n matchingDocumentsSet = new lunr.Set(matchingDocumentRefs)\n\n /*\n * if the presence of this term is required ensure that the matching\n * documents are added to the set of required matches for this clause.\n *\n */\n if (clause.presence == lunr.Query.presence.REQUIRED) {\n clauseMatches = clauseMatches.union(matchingDocumentsSet)\n\n if (requiredMatches[field] === undefined) {\n requiredMatches[field] = lunr.Set.complete\n }\n }\n\n /*\n * if the presence of this term is prohibited ensure that the matching\n * documents are added to the set of prohibited matches for this field,\n * creating that set if it does not yet exist.\n */\n if (clause.presence == lunr.Query.presence.PROHIBITED) {\n if (prohibitedMatches[field] === undefined) {\n prohibitedMatches[field] = lunr.Set.empty\n }\n\n prohibitedMatches[field] = prohibitedMatches[field].union(matchingDocumentsSet)\n\n /*\n * Prohibited matches should not be part of the query vector used for\n * similarity scoring and no metadata should be extracted so we continue\n * to the next field\n */\n continue\n }\n\n /*\n * The query field vector is populated using the termIndex found for\n * the term and a unit value with the appropriate boost applied.\n * Using upsert because there could already be an entry in the vector\n * for the term we are working with. In that case we just add the scores\n * together.\n */\n queryVectors[field].upsert(termIndex, clause.boost, function (a, b) { return a + b })\n\n /**\n * If we've already seen this term, field combo then we've already collected\n * the matching documents and metadata, no need to go through all that again\n */\n if (termFieldCache[termField]) {\n continue\n }\n\n for (var l = 0; l < matchingDocumentRefs.length; l++) {\n /*\n * All metadata for this term/field/document triple\n * are then extracted and collected into an instance\n * of lunr.MatchData ready to be returned in the query\n * results\n */\n var matchingDocumentRef = matchingDocumentRefs[l],\n matchingFieldRef = new lunr.FieldRef (matchingDocumentRef, field),\n metadata = fieldPosting[matchingDocumentRef],\n fieldMatch\n\n if ((fieldMatch = matchingFields[matchingFieldRef]) === undefined) {\n matchingFields[matchingFieldRef] = new lunr.MatchData (expandedTerm, field, metadata)\n } else {\n fieldMatch.add(expandedTerm, field, metadata)\n }\n\n }\n\n termFieldCache[termField] = true\n }\n }\n }\n\n /**\n * If the presence was required we need to update the requiredMatches field sets.\n * We do this after all fields for the term have collected their matches because\n * the clause terms presence is required in _any_ of the fields not _all_ of the\n * fields.\n */\n if (clause.presence === lunr.Query.presence.REQUIRED) {\n for (var k = 0; k < clause.fields.length; k++) {\n var field = clause.fields[k]\n requiredMatches[field] = requiredMatches[field].intersect(clauseMatches)\n }\n }\n }\n\n /**\n * Need to combine the field scoped required and prohibited\n * matching documents into a global set of required and prohibited\n * matches\n */\n var allRequiredMatches = lunr.Set.complete,\n allProhibitedMatches = lunr.Set.empty\n\n for (var i = 0; i < this.fields.length; i++) {\n var field = this.fields[i]\n\n if (requiredMatches[field]) {\n allRequiredMatches = allRequiredMatches.intersect(requiredMatches[field])\n }\n\n if (prohibitedMatches[field]) {\n allProhibitedMatches = allProhibitedMatches.union(prohibitedMatches[field])\n }\n }\n\n var matchingFieldRefs = Object.keys(matchingFields),\n results = [],\n matches = Object.create(null)\n\n /*\n * If the query is negated (contains only prohibited terms)\n * we need to get _all_ fieldRefs currently existing in the\n * index. This is only done when we know that the query is\n * entirely prohibited terms to avoid any cost of getting all\n * fieldRefs unnecessarily.\n *\n * Additionally, blank MatchData must be created to correctly\n * populate the results.\n */\n if (query.isNegated()) {\n matchingFieldRefs = Object.keys(this.fieldVectors)\n\n for (var i = 0; i < matchingFieldRefs.length; i++) {\n var matchingFieldRef = matchingFieldRefs[i]\n var fieldRef = lunr.FieldRef.fromString(matchingFieldRef)\n matchingFields[matchingFieldRef] = new lunr.MatchData\n }\n }\n\n for (var i = 0; i < matchingFieldRefs.length; i++) {\n /*\n * Currently we have document fields that match the query, but we\n * need to return documents. The matchData and scores are combined\n * from multiple fields belonging to the same document.\n *\n * Scores are calculated by field, using the query vectors created\n * above, and combined into a final document score using addition.\n */\n var fieldRef = lunr.FieldRef.fromString(matchingFieldRefs[i]),\n docRef = fieldRef.docRef\n\n if (!allRequiredMatches.contains(docRef)) {\n continue\n }\n\n if (allProhibitedMatches.contains(docRef)) {\n continue\n }\n\n var fieldVector = this.fieldVectors[fieldRef],\n score = queryVectors[fieldRef.fieldName].similarity(fieldVector),\n docMatch\n\n if ((docMatch = matches[docRef]) !== undefined) {\n docMatch.score += score\n docMatch.matchData.combine(matchingFields[fieldRef])\n } else {\n var match = {\n ref: docRef,\n score: score,\n matchData: matchingFields[fieldRef]\n }\n matches[docRef] = match\n results.push(match)\n }\n }\n\n /*\n * Sort the results objects by score, highest first.\n */\n return results.sort(function (a, b) {\n return b.score - a.score\n })\n}\n\n/**\n * Prepares the index for JSON serialization.\n *\n * The schema for this JSON blob will be described in a\n * separate JSON schema file.\n *\n * @returns {Object}\n */\nlunr.Index.prototype.toJSON = function () {\n var invertedIndex = Object.keys(this.invertedIndex)\n .sort()\n .map(function (term) {\n return [term, this.invertedIndex[term]]\n }, this)\n\n var fieldVectors = Object.keys(this.fieldVectors)\n .map(function (ref) {\n return [ref, this.fieldVectors[ref].toJSON()]\n }, this)\n\n return {\n version: lunr.version,\n fields: this.fields,\n fieldVectors: fieldVectors,\n invertedIndex: invertedIndex,\n pipeline: this.pipeline.toJSON()\n }\n}\n\n/**\n * Loads a previously serialized lunr.Index\n *\n * @param {Object} serializedIndex - A previously serialized lunr.Index\n * @returns {lunr.Index}\n */\nlunr.Index.load = function (serializedIndex) {\n var attrs = {},\n fieldVectors = {},\n serializedVectors = serializedIndex.fieldVectors,\n invertedIndex = Object.create(null),\n serializedInvertedIndex = serializedIndex.invertedIndex,\n tokenSetBuilder = new lunr.TokenSet.Builder,\n pipeline = lunr.Pipeline.load(serializedIndex.pipeline)\n\n if (serializedIndex.version != lunr.version) {\n lunr.utils.warn(\"Version mismatch when loading serialised index. Current version of lunr '\" + lunr.version + \"' does not match serialized index '\" + serializedIndex.version + \"'\")\n }\n\n for (var i = 0; i < serializedVectors.length; i++) {\n var tuple = serializedVectors[i],\n ref = tuple[0],\n elements = tuple[1]\n\n fieldVectors[ref] = new lunr.Vector(elements)\n }\n\n for (var i = 0; i < serializedInvertedIndex.length; i++) {\n var tuple = serializedInvertedIndex[i],\n term = tuple[0],\n posting = tuple[1]\n\n tokenSetBuilder.insert(term)\n invertedIndex[term] = posting\n }\n\n tokenSetBuilder.finish()\n\n attrs.fields = serializedIndex.fields\n\n attrs.fieldVectors = fieldVectors\n attrs.invertedIndex = invertedIndex\n attrs.tokenSet = tokenSetBuilder.root\n attrs.pipeline = pipeline\n\n return new lunr.Index(attrs)\n}\n/*!\n * lunr.Builder\n * Copyright (C) 2020 Oliver Nightingale\n */\n\n/**\n * lunr.Builder performs indexing on a set of documents and\n * returns instances of lunr.Index ready for querying.\n *\n * All configuration of the index is done via the builder, the\n * fields to index, the document reference, the text processing\n * pipeline and document scoring parameters are all set on the\n * builder before indexing.\n *\n * @constructor\n * @property {string} _ref - Internal reference to the document reference field.\n * @property {string[]} _fields - Internal reference to the document fields to index.\n * @property {object} invertedIndex - The inverted index maps terms to document fields.\n * @property {object} documentTermFrequencies - Keeps track of document term frequencies.\n * @property {object} documentLengths - Keeps track of the length of documents added to the index.\n * @property {lunr.tokenizer} tokenizer - Function for splitting strings into tokens for indexing.\n * @property {lunr.Pipeline} pipeline - The pipeline performs text processing on tokens before indexing.\n * @property {lunr.Pipeline} searchPipeline - A pipeline for processing search terms before querying the index.\n * @property {number} documentCount - Keeps track of the total number of documents indexed.\n * @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.\n * @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.\n * @property {number} termIndex - A counter incremented for each unique term, used to identify a terms position in the vector space.\n * @property {array} metadataWhitelist - A list of metadata keys that have been whitelisted for entry in the index.\n */\nlunr.Builder = function () {\n this._ref = \"id\"\n this._fields = Object.create(null)\n this._documents = Object.create(null)\n this.invertedIndex = Object.create(null)\n this.fieldTermFrequencies = {}\n this.fieldLengths = {}\n this.tokenizer = lunr.tokenizer\n this.pipeline = new lunr.Pipeline\n this.searchPipeline = new lunr.Pipeline\n this.documentCount = 0\n this._b = 0.75\n this._k1 = 1.2\n this.termIndex = 0\n this.metadataWhitelist = []\n}\n\n/**\n * Sets the document field used as the document reference. Every document must have this field.\n * The type of this field in the document should be a string, if it is not a string it will be\n * coerced into a string by calling toString.\n *\n * The default ref is 'id'.\n *\n * The ref should _not_ be changed during indexing, it should be set before any documents are\n * added to the index. Changing it during indexing can lead to inconsistent results.\n *\n * @param {string} ref - The name of the reference field in the document.\n */\nlunr.Builder.prototype.ref = function (ref) {\n this._ref = ref\n}\n\n/**\n * A function that is used to extract a field from a document.\n *\n * Lunr expects a field to be at the top level of a document, if however the field\n * is deeply nested within a document an extractor function can be used to extract\n * the right field for indexing.\n *\n * @callback fieldExtractor\n * @param {object} doc - The document being added to the index.\n * @returns {?(string|object|object[])} obj - The object that will be indexed for this field.\n * @example Extracting a nested field\n * function (doc) { return doc.nested.field }\n */\n\n/**\n * Adds a field to the list of document fields that will be indexed. Every document being\n * indexed should have this field. Null values for this field in indexed documents will\n * not cause errors but will limit the chance of that document being retrieved by searches.\n *\n * All fields should be added before adding documents to the index. Adding fields after\n * a document has been indexed will have no effect on already indexed documents.\n *\n * Fields can be boosted at build time. This allows terms within that field to have more\n * importance when ranking search results. Use a field boost to specify that matches within\n * one field are more important than other fields.\n *\n * @param {string} fieldName - The name of a field to index in all documents.\n * @param {object} attributes - Optional attributes associated with this field.\n * @param {number} [attributes.boost=1] - Boost applied to all terms within this field.\n * @param {fieldExtractor} [attributes.extractor] - Function to extract a field from a document.\n * @throws {RangeError} fieldName cannot contain unsupported characters '/'\n */\nlunr.Builder.prototype.field = function (fieldName, attributes) {\n if (/\\//.test(fieldName)) {\n throw new RangeError (\"Field '\" + fieldName + \"' contains illegal character '/'\")\n }\n\n this._fields[fieldName] = attributes || {}\n}\n\n/**\n * A parameter to tune the amount of field length normalisation that is applied when\n * calculating relevance scores. A value of 0 will completely disable any normalisation\n * and a value of 1 will fully normalise field lengths. The default is 0.75. Values of b\n * will be clamped to the range 0 - 1.\n *\n * @param {number} number - The value to set for this tuning parameter.\n */\nlunr.Builder.prototype.b = function (number) {\n if (number < 0) {\n this._b = 0\n } else if (number > 1) {\n this._b = 1\n } else {\n this._b = number\n }\n}\n\n/**\n * A parameter that controls the speed at which a rise in term frequency results in term\n * frequency saturation. The default value is 1.2. Setting this to a higher value will give\n * slower saturation levels, a lower value will result in quicker saturation.\n *\n * @param {number} number - The value to set for this tuning parameter.\n */\nlunr.Builder.prototype.k1 = function (number) {\n this._k1 = number\n}\n\n/**\n * Adds a document to the index.\n *\n * Before adding fields to the index the index should have been fully setup, with the document\n * ref and all fields to index already having been specified.\n *\n * The document must have a field name as specified by the ref (by default this is 'id') and\n * it should have all fields defined for indexing, though null or undefined values will not\n * cause errors.\n *\n * Entire documents can be boosted at build time. Applying a boost to a document indicates that\n * this document should rank higher in search results than other documents.\n *\n * @param {object} doc - The document to add to the index.\n * @param {object} attributes - Optional attributes associated with this document.\n * @param {number} [attributes.boost=1] - Boost applied to all terms within this document.\n */\nlunr.Builder.prototype.add = function (doc, attributes) {\n var docRef = doc[this._ref],\n fields = Object.keys(this._fields)\n\n this._documents[docRef] = attributes || {}\n this.documentCount += 1\n\n for (var i = 0; i < fields.length; i++) {\n var fieldName = fields[i],\n extractor = this._fields[fieldName].extractor,\n field = extractor ? extractor(doc) : doc[fieldName],\n tokens = this.tokenizer(field, {\n fields: [fieldName]\n }),\n terms = this.pipeline.run(tokens),\n fieldRef = new lunr.FieldRef (docRef, fieldName),\n fieldTerms = Object.create(null)\n\n this.fieldTermFrequencies[fieldRef] = fieldTerms\n this.fieldLengths[fieldRef] = 0\n\n // store the length of this field for this document\n this.fieldLengths[fieldRef] += terms.length\n\n // calculate term frequencies for this field\n for (var j = 0; j < terms.length; j++) {\n var term = terms[j]\n\n if (fieldTerms[term] == undefined) {\n fieldTerms[term] = 0\n }\n\n fieldTerms[term] += 1\n\n // add to inverted index\n // create an initial posting if one doesn't exist\n if (this.invertedIndex[term] == undefined) {\n var posting = Object.create(null)\n posting[\"_index\"] = this.termIndex\n this.termIndex += 1\n\n for (var k = 0; k < fields.length; k++) {\n posting[fields[k]] = Object.create(null)\n }\n\n this.invertedIndex[term] = posting\n }\n\n // add an entry for this term/fieldName/docRef to the invertedIndex\n if (this.invertedIndex[term][fieldName][docRef] == undefined) {\n this.invertedIndex[term][fieldName][docRef] = Object.create(null)\n }\n\n // store all whitelisted metadata about this token in the\n // inverted index\n for (var l = 0; l < this.metadataWhitelist.length; l++) {\n var metadataKey = this.metadataWhitelist[l],\n metadata = term.metadata[metadataKey]\n\n if (this.invertedIndex[term][fieldName][docRef][metadataKey] == undefined) {\n this.invertedIndex[term][fieldName][docRef][metadataKey] = []\n }\n\n this.invertedIndex[term][fieldName][docRef][metadataKey].push(metadata)\n }\n }\n\n }\n}\n\n/**\n * Calculates the average document length for this index\n *\n * @private\n */\nlunr.Builder.prototype.calculateAverageFieldLengths = function () {\n\n var fieldRefs = Object.keys(this.fieldLengths),\n numberOfFields = fieldRefs.length,\n accumulator = {},\n documentsWithField = {}\n\n for (var i = 0; i < numberOfFields; i++) {\n var fieldRef = lunr.FieldRef.fromString(fieldRefs[i]),\n field = fieldRef.fieldName\n\n documentsWithField[field] || (documentsWithField[field] = 0)\n documentsWithField[field] += 1\n\n accumulator[field] || (accumulator[field] = 0)\n accumulator[field] += this.fieldLengths[fieldRef]\n }\n\n var fields = Object.keys(this._fields)\n\n for (var i = 0; i < fields.length; i++) {\n var fieldName = fields[i]\n accumulator[fieldName] = accumulator[fieldName] / documentsWithField[fieldName]\n }\n\n this.averageFieldLength = accumulator\n}\n\n/**\n * Builds a vector space model of every document using lunr.Vector\n *\n * @private\n */\nlunr.Builder.prototype.createFieldVectors = function () {\n var fieldVectors = {},\n fieldRefs = Object.keys(this.fieldTermFrequencies),\n fieldRefsLength = fieldRefs.length,\n termIdfCache = Object.create(null)\n\n for (var i = 0; i < fieldRefsLength; i++) {\n var fieldRef = lunr.FieldRef.fromString(fieldRefs[i]),\n fieldName = fieldRef.fieldName,\n fieldLength = this.fieldLengths[fieldRef],\n fieldVector = new lunr.Vector,\n termFrequencies = this.fieldTermFrequencies[fieldRef],\n terms = Object.keys(termFrequencies),\n termsLength = terms.length\n\n\n var fieldBoost = this._fields[fieldName].boost || 1,\n docBoost = this._documents[fieldRef.docRef].boost || 1\n\n for (var j = 0; j < termsLength; j++) {\n var term = terms[j],\n tf = termFrequencies[term],\n termIndex = this.invertedIndex[term]._index,\n idf, score, scoreWithPrecision\n\n if (termIdfCache[term] === undefined) {\n idf = lunr.idf(this.invertedIndex[term], this.documentCount)\n termIdfCache[term] = idf\n } else {\n idf = termIdfCache[term]\n }\n\n score = idf * ((this._k1 + 1) * tf) / (this._k1 * (1 - this._b + this._b * (fieldLength / this.averageFieldLength[fieldName])) + tf)\n score *= fieldBoost\n score *= docBoost\n scoreWithPrecision = Math.round(score * 1000) / 1000\n // Converts 1.23456789 to 1.234.\n // Reducing the precision so that the vectors take up less\n // space when serialised. Doing it now so that they behave\n // the same before and after serialisation. Also, this is\n // the fastest approach to reducing a number's precision in\n // JavaScript.\n\n fieldVector.insert(termIndex, scoreWithPrecision)\n }\n\n fieldVectors[fieldRef] = fieldVector\n }\n\n this.fieldVectors = fieldVectors\n}\n\n/**\n * Creates a token set of all tokens in the index using lunr.TokenSet\n *\n * @private\n */\nlunr.Builder.prototype.createTokenSet = function () {\n this.tokenSet = lunr.TokenSet.fromArray(\n Object.keys(this.invertedIndex).sort()\n )\n}\n\n/**\n * Builds the index, creating an instance of lunr.Index.\n *\n * This completes the indexing process and should only be called\n * once all documents have been added to the index.\n *\n * @returns {lunr.Index}\n */\nlunr.Builder.prototype.build = function () {\n this.calculateAverageFieldLengths()\n this.createFieldVectors()\n this.createTokenSet()\n\n return new lunr.Index({\n invertedIndex: this.invertedIndex,\n fieldVectors: this.fieldVectors,\n tokenSet: this.tokenSet,\n fields: Object.keys(this._fields),\n pipeline: this.searchPipeline\n })\n}\n\n/**\n * Applies a plugin to the index builder.\n *\n * A plugin is a function that is called with the index builder as its context.\n * Plugins can be used to customise or extend the behaviour of the index\n * in some way. A plugin is just a function, that encapsulated the custom\n * behaviour that should be applied when building the index.\n *\n * The plugin function will be called with the index builder as its argument, additional\n * arguments can also be passed when calling use. The function will be called\n * with the index builder as its context.\n *\n * @param {Function} plugin The plugin to apply.\n */\nlunr.Builder.prototype.use = function (fn) {\n var args = Array.prototype.slice.call(arguments, 1)\n args.unshift(this)\n fn.apply(this, args)\n}\n/**\n * Contains and collects metadata about a matching document.\n * A single instance of lunr.MatchData is returned as part of every\n * lunr.Index~Result.\n *\n * @constructor\n * @param {string} term - The term this match data is associated with\n * @param {string} field - The field in which the term was found\n * @param {object} metadata - The metadata recorded about this term in this field\n * @property {object} metadata - A cloned collection of metadata associated with this document.\n * @see {@link lunr.Index~Result}\n */\nlunr.MatchData = function (term, field, metadata) {\n var clonedMetadata = Object.create(null),\n metadataKeys = Object.keys(metadata || {})\n\n // Cloning the metadata to prevent the original\n // being mutated during match data combination.\n // Metadata is kept in an array within the inverted\n // index so cloning the data can be done with\n // Array#slice\n for (var i = 0; i < metadataKeys.length; i++) {\n var key = metadataKeys[i]\n clonedMetadata[key] = metadata[key].slice()\n }\n\n this.metadata = Object.create(null)\n\n if (term !== undefined) {\n this.metadata[term] = Object.create(null)\n this.metadata[term][field] = clonedMetadata\n }\n}\n\n/**\n * An instance of lunr.MatchData will be created for every term that matches a\n * document. However only one instance is required in a lunr.Index~Result. This\n * method combines metadata from another instance of lunr.MatchData with this\n * objects metadata.\n *\n * @param {lunr.MatchData} otherMatchData - Another instance of match data to merge with this one.\n * @see {@link lunr.Index~Result}\n */\nlunr.MatchData.prototype.combine = function (otherMatchData) {\n var terms = Object.keys(otherMatchData.metadata)\n\n for (var i = 0; i < terms.length; i++) {\n var term = terms[i],\n fields = Object.keys(otherMatchData.metadata[term])\n\n if (this.metadata[term] == undefined) {\n this.metadata[term] = Object.create(null)\n }\n\n for (var j = 0; j < fields.length; j++) {\n var field = fields[j],\n keys = Object.keys(otherMatchData.metadata[term][field])\n\n if (this.metadata[term][field] == undefined) {\n this.metadata[term][field] = Object.create(null)\n }\n\n for (var k = 0; k < keys.length; k++) {\n var key = keys[k]\n\n if (this.metadata[term][field][key] == undefined) {\n this.metadata[term][field][key] = otherMatchData.metadata[term][field][key]\n } else {\n this.metadata[term][field][key] = this.metadata[term][field][key].concat(otherMatchData.metadata[term][field][key])\n }\n\n }\n }\n }\n}\n\n/**\n * Add metadata for a term/field pair to this instance of match data.\n *\n * @param {string} term - The term this match data is associated with\n * @param {string} field - The field in which the term was found\n * @param {object} metadata - The metadata recorded about this term in this field\n */\nlunr.MatchData.prototype.add = function (term, field, metadata) {\n if (!(term in this.metadata)) {\n this.metadata[term] = Object.create(null)\n this.metadata[term][field] = metadata\n return\n }\n\n if (!(field in this.metadata[term])) {\n this.metadata[term][field] = metadata\n return\n }\n\n var metadataKeys = Object.keys(metadata)\n\n for (var i = 0; i < metadataKeys.length; i++) {\n var key = metadataKeys[i]\n\n if (key in this.metadata[term][field]) {\n this.metadata[term][field][key] = this.metadata[term][field][key].concat(metadata[key])\n } else {\n this.metadata[term][field][key] = metadata[key]\n }\n }\n}\n/**\n * A lunr.Query provides a programmatic way of defining queries to be performed\n * against a {@link lunr.Index}.\n *\n * Prefer constructing a lunr.Query using the {@link lunr.Index#query} method\n * so the query object is pre-initialized with the right index fields.\n *\n * @constructor\n * @property {lunr.Query~Clause[]} clauses - An array of query clauses.\n * @property {string[]} allFields - An array of all available fields in a lunr.Index.\n */\nlunr.Query = function (allFields) {\n this.clauses = []\n this.allFields = allFields\n}\n\n/**\n * Constants for indicating what kind of automatic wildcard insertion will be used when constructing a query clause.\n *\n * This allows wildcards to be added to the beginning and end of a term without having to manually do any string\n * concatenation.\n *\n * The wildcard constants can be bitwise combined to select both leading and trailing wildcards.\n *\n * @constant\n * @default\n * @property {number} wildcard.NONE - The term will have no wildcards inserted, this is the default behaviour\n * @property {number} wildcard.LEADING - Prepend the term with a wildcard, unless a leading wildcard already exists\n * @property {number} wildcard.TRAILING - Append a wildcard to the term, unless a trailing wildcard already exists\n * @see lunr.Query~Clause\n * @see lunr.Query#clause\n * @see lunr.Query#term\n * @example query term with trailing wildcard\n * query.term('foo', { wildcard: lunr.Query.wildcard.TRAILING })\n * @example query term with leading and trailing wildcard\n * query.term('foo', {\n * wildcard: lunr.Query.wildcard.LEADING | lunr.Query.wildcard.TRAILING\n * })\n */\n\nlunr.Query.wildcard = new String (\"*\")\nlunr.Query.wildcard.NONE = 0\nlunr.Query.wildcard.LEADING = 1\nlunr.Query.wildcard.TRAILING = 2\n\n/**\n * Constants for indicating what kind of presence a term must have in matching documents.\n *\n * @constant\n * @enum {number}\n * @see lunr.Query~Clause\n * @see lunr.Query#clause\n * @see lunr.Query#term\n * @example query term with required presence\n * query.term('foo', { presence: lunr.Query.presence.REQUIRED })\n */\nlunr.Query.presence = {\n /**\n * Term's presence in a document is optional, this is the default value.\n */\n OPTIONAL: 1,\n\n /**\n * Term's presence in a document is required, documents that do not contain\n * this term will not be returned.\n */\n REQUIRED: 2,\n\n /**\n * Term's presence in a document is prohibited, documents that do contain\n * this term will not be returned.\n */\n PROHIBITED: 3\n}\n\n/**\n * A single clause in a {@link lunr.Query} contains a term and details on how to\n * match that term against a {@link lunr.Index}.\n *\n * @typedef {Object} lunr.Query~Clause\n * @property {string[]} fields - The fields in an index this clause should be matched against.\n * @property {number} [boost=1] - Any boost that should be applied when matching this clause.\n * @property {number} [editDistance] - Whether the term should have fuzzy matching applied, and how fuzzy the match should be.\n * @property {boolean} [usePipeline] - Whether the term should be passed through the search pipeline.\n * @property {number} [wildcard=lunr.Query.wildcard.NONE] - Whether the term should have wildcards appended or prepended.\n * @property {number} [presence=lunr.Query.presence.OPTIONAL] - The terms presence in any matching documents.\n */\n\n/**\n * Adds a {@link lunr.Query~Clause} to this query.\n *\n * Unless the clause contains the fields to be matched all fields will be matched. In addition\n * a default boost of 1 is applied to the clause.\n *\n * @param {lunr.Query~Clause} clause - The clause to add to this query.\n * @see lunr.Query~Clause\n * @returns {lunr.Query}\n */\nlunr.Query.prototype.clause = function (clause) {\n if (!('fields' in clause)) {\n clause.fields = this.allFields\n }\n\n if (!('boost' in clause)) {\n clause.boost = 1\n }\n\n if (!('usePipeline' in clause)) {\n clause.usePipeline = true\n }\n\n if (!('wildcard' in clause)) {\n clause.wildcard = lunr.Query.wildcard.NONE\n }\n\n if ((clause.wildcard & lunr.Query.wildcard.LEADING) && (clause.term.charAt(0) != lunr.Query.wildcard)) {\n clause.term = \"*\" + clause.term\n }\n\n if ((clause.wildcard & lunr.Query.wildcard.TRAILING) && (clause.term.slice(-1) != lunr.Query.wildcard)) {\n clause.term = \"\" + clause.term + \"*\"\n }\n\n if (!('presence' in clause)) {\n clause.presence = lunr.Query.presence.OPTIONAL\n }\n\n this.clauses.push(clause)\n\n return this\n}\n\n/**\n * A negated query is one in which every clause has a presence of\n * prohibited. These queries require some special processing to return\n * the expected results.\n *\n * @returns boolean\n */\nlunr.Query.prototype.isNegated = function () {\n for (var i = 0; i < this.clauses.length; i++) {\n if (this.clauses[i].presence != lunr.Query.presence.PROHIBITED) {\n return false\n }\n }\n\n return true\n}\n\n/**\n * Adds a term to the current query, under the covers this will create a {@link lunr.Query~Clause}\n * to the list of clauses that make up this query.\n *\n * The term is used as is, i.e. no tokenization will be performed by this method. Instead conversion\n * to a token or token-like string should be done before calling this method.\n *\n * The term will be converted to a string by calling `toString`. Multiple terms can be passed as an\n * array, each term in the array will share the same options.\n *\n * @param {object|object[]} term - The term(s) to add to the query.\n * @param {object} [options] - Any additional properties to add to the query clause.\n * @returns {lunr.Query}\n * @see lunr.Query#clause\n * @see lunr.Query~Clause\n * @example adding a single term to a query\n * query.term(\"foo\")\n * @example adding a single term to a query and specifying search fields, term boost and automatic trailing wildcard\n * query.term(\"foo\", {\n * fields: [\"title\"],\n * boost: 10,\n * wildcard: lunr.Query.wildcard.TRAILING\n * })\n * @example using lunr.tokenizer to convert a string to tokens before using them as terms\n * query.term(lunr.tokenizer(\"foo bar\"))\n */\nlunr.Query.prototype.term = function (term, options) {\n if (Array.isArray(term)) {\n term.forEach(function (t) { this.term(t, lunr.utils.clone(options)) }, this)\n return this\n }\n\n var clause = options || {}\n clause.term = term.toString()\n\n this.clause(clause)\n\n return this\n}\nlunr.QueryParseError = function (message, start, end) {\n this.name = \"QueryParseError\"\n this.message = message\n this.start = start\n this.end = end\n}\n\nlunr.QueryParseError.prototype = new Error\nlunr.QueryLexer = function (str) {\n this.lexemes = []\n this.str = str\n this.length = str.length\n this.pos = 0\n this.start = 0\n this.escapeCharPositions = []\n}\n\nlunr.QueryLexer.prototype.run = function () {\n var state = lunr.QueryLexer.lexText\n\n while (state) {\n state = state(this)\n }\n}\n\nlunr.QueryLexer.prototype.sliceString = function () {\n var subSlices = [],\n sliceStart = this.start,\n sliceEnd = this.pos\n\n for (var i = 0; i < this.escapeCharPositions.length; i++) {\n sliceEnd = this.escapeCharPositions[i]\n subSlices.push(this.str.slice(sliceStart, sliceEnd))\n sliceStart = sliceEnd + 1\n }\n\n subSlices.push(this.str.slice(sliceStart, this.pos))\n this.escapeCharPositions.length = 0\n\n return subSlices.join('')\n}\n\nlunr.QueryLexer.prototype.emit = function (type) {\n this.lexemes.push({\n type: type,\n str: this.sliceString(),\n start: this.start,\n end: this.pos\n })\n\n this.start = this.pos\n}\n\nlunr.QueryLexer.prototype.escapeCharacter = function () {\n this.escapeCharPositions.push(this.pos - 1)\n this.pos += 1\n}\n\nlunr.QueryLexer.prototype.next = function () {\n if (this.pos >= this.length) {\n return lunr.QueryLexer.EOS\n }\n\n var char = this.str.charAt(this.pos)\n this.pos += 1\n return char\n}\n\nlunr.QueryLexer.prototype.width = function () {\n return this.pos - this.start\n}\n\nlunr.QueryLexer.prototype.ignore = function () {\n if (this.start == this.pos) {\n this.pos += 1\n }\n\n this.start = this.pos\n}\n\nlunr.QueryLexer.prototype.backup = function () {\n this.pos -= 1\n}\n\nlunr.QueryLexer.prototype.acceptDigitRun = function () {\n var char, charCode\n\n do {\n char = this.next()\n charCode = char.charCodeAt(0)\n } while (charCode > 47 && charCode < 58)\n\n if (char != lunr.QueryLexer.EOS) {\n this.backup()\n }\n}\n\nlunr.QueryLexer.prototype.more = function () {\n return this.pos < this.length\n}\n\nlunr.QueryLexer.EOS = 'EOS'\nlunr.QueryLexer.FIELD = 'FIELD'\nlunr.QueryLexer.TERM = 'TERM'\nlunr.QueryLexer.EDIT_DISTANCE = 'EDIT_DISTANCE'\nlunr.QueryLexer.BOOST = 'BOOST'\nlunr.QueryLexer.PRESENCE = 'PRESENCE'\n\nlunr.QueryLexer.lexField = function (lexer) {\n lexer.backup()\n lexer.emit(lunr.QueryLexer.FIELD)\n lexer.ignore()\n return lunr.QueryLexer.lexText\n}\n\nlunr.QueryLexer.lexTerm = function (lexer) {\n if (lexer.width() > 1) {\n lexer.backup()\n lexer.emit(lunr.QueryLexer.TERM)\n }\n\n lexer.ignore()\n\n if (lexer.more()) {\n return lunr.QueryLexer.lexText\n }\n}\n\nlunr.QueryLexer.lexEditDistance = function (lexer) {\n lexer.ignore()\n lexer.acceptDigitRun()\n lexer.emit(lunr.QueryLexer.EDIT_DISTANCE)\n return lunr.QueryLexer.lexText\n}\n\nlunr.QueryLexer.lexBoost = function (lexer) {\n lexer.ignore()\n lexer.acceptDigitRun()\n lexer.emit(lunr.QueryLexer.BOOST)\n return lunr.QueryLexer.lexText\n}\n\nlunr.QueryLexer.lexEOS = function (lexer) {\n if (lexer.width() > 0) {\n lexer.emit(lunr.QueryLexer.TERM)\n }\n}\n\n// This matches the separator used when tokenising fields\n// within a document. These should match otherwise it is\n// not possible to search for some tokens within a document.\n//\n// It is possible for the user to change the separator on the\n// tokenizer so it _might_ clash with any other of the special\n// characters already used within the search string, e.g. :.\n//\n// This means that it is possible to change the separator in\n// such a way that makes some words unsearchable using a search\n// string.\nlunr.QueryLexer.termSeparator = lunr.tokenizer.separator\n\nlunr.QueryLexer.lexText = function (lexer) {\n while (true) {\n var char = lexer.next()\n\n if (char == lunr.QueryLexer.EOS) {\n return lunr.QueryLexer.lexEOS\n }\n\n // Escape character is '\\'\n if (char.charCodeAt(0) == 92) {\n lexer.escapeCharacter()\n continue\n }\n\n if (char == \":\") {\n return lunr.QueryLexer.lexField\n }\n\n if (char == \"~\") {\n lexer.backup()\n if (lexer.width() > 0) {\n lexer.emit(lunr.QueryLexer.TERM)\n }\n return lunr.QueryLexer.lexEditDistance\n }\n\n if (char == \"^\") {\n lexer.backup()\n if (lexer.width() > 0) {\n lexer.emit(lunr.QueryLexer.TERM)\n }\n return lunr.QueryLexer.lexBoost\n }\n\n // \"+\" indicates term presence is required\n // checking for length to ensure that only\n // leading \"+\" are considered\n if (char == \"+\" && lexer.width() === 1) {\n lexer.emit(lunr.QueryLexer.PRESENCE)\n return lunr.QueryLexer.lexText\n }\n\n // \"-\" indicates term presence is prohibited\n // checking for length to ensure that only\n // leading \"-\" are considered\n if (char == \"-\" && lexer.width() === 1) {\n lexer.emit(lunr.QueryLexer.PRESENCE)\n return lunr.QueryLexer.lexText\n }\n\n if (char.match(lunr.QueryLexer.termSeparator)) {\n return lunr.QueryLexer.lexTerm\n }\n }\n}\n\nlunr.QueryParser = function (str, query) {\n this.lexer = new lunr.QueryLexer (str)\n this.query = query\n this.currentClause = {}\n this.lexemeIdx = 0\n}\n\nlunr.QueryParser.prototype.parse = function () {\n this.lexer.run()\n this.lexemes = this.lexer.lexemes\n\n var state = lunr.QueryParser.parseClause\n\n while (state) {\n state = state(this)\n }\n\n return this.query\n}\n\nlunr.QueryParser.prototype.peekLexeme = function () {\n return this.lexemes[this.lexemeIdx]\n}\n\nlunr.QueryParser.prototype.consumeLexeme = function () {\n var lexeme = this.peekLexeme()\n this.lexemeIdx += 1\n return lexeme\n}\n\nlunr.QueryParser.prototype.nextClause = function () {\n var completedClause = this.currentClause\n this.query.clause(completedClause)\n this.currentClause = {}\n}\n\nlunr.QueryParser.parseClause = function (parser) {\n var lexeme = parser.peekLexeme()\n\n if (lexeme == undefined) {\n return\n }\n\n switch (lexeme.type) {\n case lunr.QueryLexer.PRESENCE:\n return lunr.QueryParser.parsePresence\n case lunr.QueryLexer.FIELD:\n return lunr.QueryParser.parseField\n case lunr.QueryLexer.TERM:\n return lunr.QueryParser.parseTerm\n default:\n var errorMessage = \"expected either a field or a term, found \" + lexeme.type\n\n if (lexeme.str.length >= 1) {\n errorMessage += \" with value '\" + lexeme.str + \"'\"\n }\n\n throw new lunr.QueryParseError (errorMessage, lexeme.start, lexeme.end)\n }\n}\n\nlunr.QueryParser.parsePresence = function (parser) {\n var lexeme = parser.consumeLexeme()\n\n if (lexeme == undefined) {\n return\n }\n\n switch (lexeme.str) {\n case \"-\":\n parser.currentClause.presence = lunr.Query.presence.PROHIBITED\n break\n case \"+\":\n parser.currentClause.presence = lunr.Query.presence.REQUIRED\n break\n default:\n var errorMessage = \"unrecognised presence operator'\" + lexeme.str + \"'\"\n throw new lunr.QueryParseError (errorMessage, lexeme.start, lexeme.end)\n }\n\n var nextLexeme = parser.peekLexeme()\n\n if (nextLexeme == undefined) {\n var errorMessage = \"expecting term or field, found nothing\"\n throw new lunr.QueryParseError (errorMessage, lexeme.start, lexeme.end)\n }\n\n switch (nextLexeme.type) {\n case lunr.QueryLexer.FIELD:\n return lunr.QueryParser.parseField\n case lunr.QueryLexer.TERM:\n return lunr.QueryParser.parseTerm\n default:\n var errorMessage = \"expecting term or field, found '\" + nextLexeme.type + \"'\"\n throw new lunr.QueryParseError (errorMessage, nextLexeme.start, nextLexeme.end)\n }\n}\n\nlunr.QueryParser.parseField = function (parser) {\n var lexeme = parser.consumeLexeme()\n\n if (lexeme == undefined) {\n return\n }\n\n if (parser.query.allFields.indexOf(lexeme.str) == -1) {\n var possibleFields = parser.query.allFields.map(function (f) { return \"'\" + f + \"'\" }).join(', '),\n errorMessage = \"unrecognised field '\" + lexeme.str + \"', possible fields: \" + possibleFields\n\n throw new lunr.QueryParseError (errorMessage, lexeme.start, lexeme.end)\n }\n\n parser.currentClause.fields = [lexeme.str]\n\n var nextLexeme = parser.peekLexeme()\n\n if (nextLexeme == undefined) {\n var errorMessage = \"expecting term, found nothing\"\n throw new lunr.QueryParseError (errorMessage, lexeme.start, lexeme.end)\n }\n\n switch (nextLexeme.type) {\n case lunr.QueryLexer.TERM:\n return lunr.QueryParser.parseTerm\n default:\n var errorMessage = \"expecting term, found '\" + nextLexeme.type + \"'\"\n throw new lunr.QueryParseError (errorMessage, nextLexeme.start, nextLexeme.end)\n }\n}\n\nlunr.QueryParser.parseTerm = function (parser) {\n var lexeme = parser.consumeLexeme()\n\n if (lexeme == undefined) {\n return\n }\n\n parser.currentClause.term = lexeme.str.toLowerCase()\n\n if (lexeme.str.indexOf(\"*\") != -1) {\n parser.currentClause.usePipeline = false\n }\n\n var nextLexeme = parser.peekLexeme()\n\n if (nextLexeme == undefined) {\n parser.nextClause()\n return\n }\n\n switch (nextLexeme.type) {\n case lunr.QueryLexer.TERM:\n parser.nextClause()\n return lunr.QueryParser.parseTerm\n case lunr.QueryLexer.FIELD:\n parser.nextClause()\n return lunr.QueryParser.parseField\n case lunr.QueryLexer.EDIT_DISTANCE:\n return lunr.QueryParser.parseEditDistance\n case lunr.QueryLexer.BOOST:\n return lunr.QueryParser.parseBoost\n case lunr.QueryLexer.PRESENCE:\n parser.nextClause()\n return lunr.QueryParser.parsePresence\n default:\n var errorMessage = \"Unexpected lexeme type '\" + nextLexeme.type + \"'\"\n throw new lunr.QueryParseError (errorMessage, nextLexeme.start, nextLexeme.end)\n }\n}\n\nlunr.QueryParser.parseEditDistance = function (parser) {\n var lexeme = parser.consumeLexeme()\n\n if (lexeme == undefined) {\n return\n }\n\n var editDistance = parseInt(lexeme.str, 10)\n\n if (isNaN(editDistance)) {\n var errorMessage = \"edit distance must be numeric\"\n throw new lunr.QueryParseError (errorMessage, lexeme.start, lexeme.end)\n }\n\n parser.currentClause.editDistance = editDistance\n\n var nextLexeme = parser.peekLexeme()\n\n if (nextLexeme == undefined) {\n parser.nextClause()\n return\n }\n\n switch (nextLexeme.type) {\n case lunr.QueryLexer.TERM:\n parser.nextClause()\n return lunr.QueryParser.parseTerm\n case lunr.QueryLexer.FIELD:\n parser.nextClause()\n return lunr.QueryParser.parseField\n case lunr.QueryLexer.EDIT_DISTANCE:\n return lunr.QueryParser.parseEditDistance\n case lunr.QueryLexer.BOOST:\n return lunr.QueryParser.parseBoost\n case lunr.QueryLexer.PRESENCE:\n parser.nextClause()\n return lunr.QueryParser.parsePresence\n default:\n var errorMessage = \"Unexpected lexeme type '\" + nextLexeme.type + \"'\"\n throw new lunr.QueryParseError (errorMessage, nextLexeme.start, nextLexeme.end)\n }\n}\n\nlunr.QueryParser.parseBoost = function (parser) {\n var lexeme = parser.consumeLexeme()\n\n if (lexeme == undefined) {\n return\n }\n\n var boost = parseInt(lexeme.str, 10)\n\n if (isNaN(boost)) {\n var errorMessage = \"boost must be numeric\"\n throw new lunr.QueryParseError (errorMessage, lexeme.start, lexeme.end)\n }\n\n parser.currentClause.boost = boost\n\n var nextLexeme = parser.peekLexeme()\n\n if (nextLexeme == undefined) {\n parser.nextClause()\n return\n }\n\n switch (nextLexeme.type) {\n case lunr.QueryLexer.TERM:\n parser.nextClause()\n return lunr.QueryParser.parseTerm\n case lunr.QueryLexer.FIELD:\n parser.nextClause()\n return lunr.QueryParser.parseField\n case lunr.QueryLexer.EDIT_DISTANCE:\n return lunr.QueryParser.parseEditDistance\n case lunr.QueryLexer.BOOST:\n return lunr.QueryParser.parseBoost\n case lunr.QueryLexer.PRESENCE:\n parser.nextClause()\n return lunr.QueryParser.parsePresence\n default:\n var errorMessage = \"Unexpected lexeme type '\" + nextLexeme.type + \"'\"\n throw new lunr.QueryParseError (errorMessage, nextLexeme.start, nextLexeme.end)\n }\n}\n\n /**\n * export the module via AMD, CommonJS or as a browser global\n * Export code from https://github.com/umdjs/umd/blob/master/returnExports.js\n */\n ;(function (root, factory) {\n if (true) {\n // AMD. Register as an anonymous module.\n !(__WEBPACK_AMD_DEFINE_FACTORY__ = (factory),\n\t\t__WEBPACK_AMD_DEFINE_RESULT__ = (typeof __WEBPACK_AMD_DEFINE_FACTORY__ === 'function' ?\n\t\t(__WEBPACK_AMD_DEFINE_FACTORY__.call(exports, __webpack_require__, exports, module)) :\n\t\t__WEBPACK_AMD_DEFINE_FACTORY__),\n\t\t__WEBPACK_AMD_DEFINE_RESULT__ !== undefined && (module.exports = __WEBPACK_AMD_DEFINE_RESULT__))\n } else {}\n }(this, function () {\n /**\n * Just return a value to define the module export.\n * This example returns an object, but the module\n * can return a function as the exported value.\n */\n return lunr\n }))\n})();\n\n\n//# sourceURL=webpack:///../node_modules/lunr/lunr.js?"); - -/***/ }), - -/***/ "./default/assets/css/main.sass": -/*!**************************************!*\ - !*** ./default/assets/css/main.sass ***! - \**************************************/ -/***/ ((__unused_webpack_module, __webpack_exports__, __webpack_require__) => { - -"use strict"; -eval("__webpack_require__.r(__webpack_exports__);\n// extracted by mini-css-extract-plugin\n\n\n//# sourceURL=webpack:///./default/assets/css/main.sass?"); - -/***/ }), - -/***/ "./default/assets/js/src/bootstrap.ts": -/*!********************************************!*\ - !*** ./default/assets/js/src/bootstrap.ts ***! - \********************************************/ -/***/ ((__unused_webpack_module, __webpack_exports__, __webpack_require__) => { - -"use strict"; -eval("__webpack_require__.r(__webpack_exports__);\n/* harmony import */ var _typedoc_Application__WEBPACK_IMPORTED_MODULE_0__ = __webpack_require__(/*! ./typedoc/Application */ \"./default/assets/js/src/typedoc/Application.ts\");\n/* harmony import */ var _typedoc_components_MenuHighlight__WEBPACK_IMPORTED_MODULE_1__ = __webpack_require__(/*! ./typedoc/components/MenuHighlight */ \"./default/assets/js/src/typedoc/components/MenuHighlight.ts\");\n/* harmony import */ var _typedoc_components_Search__WEBPACK_IMPORTED_MODULE_2__ = __webpack_require__(/*! ./typedoc/components/Search */ \"./default/assets/js/src/typedoc/components/Search.ts\");\n/* harmony import */ var _typedoc_components_Signature__WEBPACK_IMPORTED_MODULE_3__ = __webpack_require__(/*! ./typedoc/components/Signature */ \"./default/assets/js/src/typedoc/components/Signature.ts\");\n/* harmony import */ var _typedoc_components_Toggle__WEBPACK_IMPORTED_MODULE_4__ = __webpack_require__(/*! 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Object.create(b) : (__.prototype = b.prototype, new __());\n };\n})();\n\n\nvar FilterItem = /** @class */ (function () {\n function FilterItem(key, value) {\n this.key = key;\n this.value = value;\n this.defaultValue = value;\n this.initialize();\n if (window.localStorage[this.key]) {\n this.setValue(this.fromLocalStorage(window.localStorage[this.key]));\n }\n }\n FilterItem.prototype.initialize = function () { };\n FilterItem.prototype.setValue = function (value) {\n if (this.value == value)\n return;\n var oldValue = this.value;\n this.value = value;\n window.localStorage[this.key] = this.toLocalStorage(value);\n this.handleValueChange(oldValue, value);\n };\n return FilterItem;\n}());\nvar FilterItemCheckbox = /** @class */ (function (_super) {\n __extends(FilterItemCheckbox, _super);\n function FilterItemCheckbox() {\n return _super !== null && _super.apply(this, arguments) || this;\n }\n FilterItemCheckbox.prototype.initialize = function () {\n var _this = this;\n var checkbox = document.querySelector(\"#tsd-filter-\" + this.key);\n if (!checkbox)\n return;\n this.checkbox = checkbox;\n this.checkbox.addEventListener(\"change\", function () {\n _this.setValue(_this.checkbox.checked);\n });\n };\n FilterItemCheckbox.prototype.handleValueChange = function (oldValue, newValue) {\n if (!this.checkbox)\n return;\n this.checkbox.checked = this.value;\n document.documentElement.classList.toggle(\"toggle-\" + this.key, this.value != this.defaultValue);\n };\n FilterItemCheckbox.prototype.fromLocalStorage = function (value) {\n return value == \"true\";\n };\n FilterItemCheckbox.prototype.toLocalStorage = function (value) {\n return value ? 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index < count; index++) {\n anchor = this.anchors[index];\n var rect = anchor.anchor.getBoundingClientRect();\n anchor.position = rect.top + document.body.scrollTop;\n }\n this.anchors.sort(function (a, b) {\n return a.position - b.position;\n });\n var event = new CustomEvent(\"scroll\", {\n detail: {\n scrollTop: _services_Viewport__WEBPACK_IMPORTED_MODULE_1__.Viewport.instance.scrollTop,\n },\n });\n this.onScroll(event);\n };\n /**\n * Triggered after the viewport was scrolled.\n *\n * @param event The custom event with the current vertical scroll position.\n */\n MenuHighlight.prototype.onScroll = function (event) {\n var scrollTop = event.detail.scrollTop + 5;\n var anchors = this.anchors;\n var count = anchors.length - 1;\n var index = this.index;\n while (index > -1 && anchors[index].position > scrollTop) {\n index -= 1;\n }\n while (index < count && anchors[index + 1].position < scrollTop) {\n index += 1;\n }\n if (this.index != index) {\n if (this.index > -1)\n this.anchors[this.index].link.classList.remove(\"focus\");\n this.index = index;\n if (this.index > -1)\n this.anchors[this.index].link.classList.add(\"focus\");\n }\n };\n return MenuHighlight;\n}(_Component__WEBPACK_IMPORTED_MODULE_0__.Component));\n\n\n\n//# sourceURL=webpack:///./default/assets/js/src/typedoc/components/MenuHighlight.ts?"); 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});\n}\n\n\n//# sourceURL=webpack:///./default/assets/js/src/typedoc/components/Search.ts?"); - -/***/ }), - -/***/ "./default/assets/js/src/typedoc/components/Signature.ts": -/*!***************************************************************!*\ - !*** ./default/assets/js/src/typedoc/components/Signature.ts ***! - \***************************************************************/ -/***/ ((__unused_webpack_module, __webpack_exports__, __webpack_require__) => { - -"use strict"; -eval("__webpack_require__.r(__webpack_exports__);\n/* harmony export */ __webpack_require__.d(__webpack_exports__, {\n/* harmony export */ \"Signature\": () => /* binding */ Signature\n/* harmony export */ });\n/* harmony import */ var _Component__WEBPACK_IMPORTED_MODULE_0__ = __webpack_require__(/*! ../Component */ \"./default/assets/js/src/typedoc/Component.ts\");\n/* harmony import */ var _services_Viewport__WEBPACK_IMPORTED_MODULE_1__ = __webpack_require__(/*! ../services/Viewport */ \"./default/assets/js/src/typedoc/services/Viewport.ts\");\nvar __extends = (undefined && undefined.__extends) || (function () {\n var extendStatics = function (d, b) {\n extendStatics = Object.setPrototypeOf ||\n ({ __proto__: [] } instanceof Array && function (d, b) { d.__proto__ = b; 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window.addEventListener(\"resize\", (0,_utils_trottle__WEBPACK_IMPORTED_MODULE_1__.throttle)(function () { return _this.onResize(); }, 10));\n _this.onResize();\n _this.onScroll();\n return _this;\n }\n /**\n * Trigger a resize event.\n */\n Viewport.prototype.triggerResize = function () {\n var event = new CustomEvent(\"resize\", {\n detail: {\n width: this.width,\n height: this.height,\n },\n });\n this.dispatchEvent(event);\n };\n /**\n * Triggered when the size of the window has changed.\n */\n Viewport.prototype.onResize = function () {\n this.width = window.innerWidth || 0;\n this.height = window.innerHeight || 0;\n var event = new CustomEvent(\"resize\", {\n detail: {\n width: this.width,\n height: this.height,\n },\n });\n this.dispatchEvent(event);\n };\n /**\n * Triggered when the user scrolled the viewport.\n */\n Viewport.prototype.onScroll = function () {\n this.scrollTop = window.scrollY || 0;\n var event = new CustomEvent(\"scroll\", {\n detail: {\n scrollTop: 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Class Human

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Hierarchy

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Constructors

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Constructors

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constructor

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  • new Human(userConfig?: {}): Human
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    Parameters

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      userConfig: {} = ...
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    Returns Human

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Properties

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classes

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classes: { age: __module; body: __module | __module; emotion: __module; facemesh: __module; gender: __module; hand: __module }
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Type declaration

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    age: __module
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    body: __module | __module
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    emotion: __module
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    facemesh: __module
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    gender: __module
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    hand: __module
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config

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config: { async: boolean; backend: string; body: { enabled: boolean; maxDetections: number; modelPath: string; nmsRadius: number; scoreThreshold: number }; deallocate: boolean; debug: boolean; face: { age: { enabled: boolean; modelPath: string; skipFrames: number }; detector: { iouThreshold: number; maxFaces: number; minConfidence: number; modelPath: string; return: boolean; rotation: boolean; scoreThreshold: number; skipFrames: number; skipInitial: boolean }; embedding: { enabled: boolean; modelPath: string }; emotion: { enabled: boolean; minConfidence: number; modelPath: string; skipFrames: number }; enabled: boolean; gender: { enabled: boolean; minConfidence: number; modelPath: string; skipFrames: number }; iris: { enabled: boolean; modelPath: string }; mesh: { enabled: boolean; modelPath: string } }; filter: { blur: number; brightness: number; contrast: number; enabled: boolean; height: number; hue: number; kodachrome: boolean; negative: boolean; pixelate: number; polaroid: boolean; return: boolean; saturation: number; sepia: boolean; sharpness: number; technicolor: boolean; vintage: boolean; width: number }; gesture: { enabled: boolean }; hand: { detector: { modelPath: string }; enabled: boolean; iouThreshold: number; landmarks: boolean; maxHands: number; minConfidence: number; rotation: boolean; scoreThreshold: number; skeleton: { modelPath: string }; skipFrames: number; skipInitial: boolean }; profile: boolean; scoped: boolean; videoOptimized: boolean; warmup: string; wasmPath: string }
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Type declaration

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    async: boolean
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    backend: string
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    body: { enabled: boolean; maxDetections: number; modelPath: string; nmsRadius: number; scoreThreshold: number }
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      enabled: boolean
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      maxDetections: number
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      modelPath: string
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      nmsRadius: number
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      scoreThreshold: number
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    deallocate: boolean
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    debug: boolean
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    face: { age: { enabled: boolean; modelPath: string; skipFrames: number }; detector: { iouThreshold: number; maxFaces: number; minConfidence: number; modelPath: string; return: boolean; rotation: boolean; scoreThreshold: number; skipFrames: number; skipInitial: boolean }; embedding: { enabled: boolean; modelPath: string }; emotion: { enabled: boolean; minConfidence: number; modelPath: string; skipFrames: number }; enabled: boolean; gender: { enabled: boolean; minConfidence: number; modelPath: string; skipFrames: number }; iris: { enabled: boolean; modelPath: string }; mesh: { enabled: boolean; modelPath: string } }
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      age: { enabled: boolean; modelPath: string; skipFrames: number }
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        enabled: boolean
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        modelPath: string
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      detector: { iouThreshold: number; maxFaces: number; minConfidence: number; modelPath: string; return: boolean; rotation: boolean; scoreThreshold: number; skipFrames: number; skipInitial: boolean }
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        iouThreshold: number
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        maxFaces: number
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        minConfidence: number
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        modelPath: string
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        return: boolean
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        rotation: boolean
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        scoreThreshold: number
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        skipFrames: number
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        skipInitial: boolean
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      embedding: { enabled: boolean; modelPath: string }
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        enabled: boolean
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        modelPath: string
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      emotion: { enabled: boolean; minConfidence: number; modelPath: string; skipFrames: number }
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        enabled: boolean
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        minConfidence: number
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        modelPath: string
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      enabled: boolean
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      gender: { enabled: boolean; minConfidence: number; modelPath: string; skipFrames: number }
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        minConfidence: number
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        modelPath: string
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        skipFrames: number
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      iris: { enabled: boolean; modelPath: string }
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        modelPath: string
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      mesh: { enabled: boolean; modelPath: string }
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        enabled: boolean
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        modelPath: string
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    filter: { blur: number; brightness: number; contrast: number; enabled: boolean; height: number; hue: number; kodachrome: boolean; negative: boolean; pixelate: number; polaroid: boolean; return: boolean; saturation: number; sepia: boolean; sharpness: number; technicolor: boolean; vintage: boolean; width: number }
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      blur: number
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      brightness: number
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      contrast: number
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      enabled: boolean
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      height: number
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      hue: number
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      kodachrome: boolean
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      negative: boolean
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      pixelate: number
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      polaroid: boolean
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      return: boolean
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      saturation: number
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      sepia: boolean
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      sharpness: number
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      technicolor: boolean
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      vintage: boolean
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      width: number
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    gesture: { enabled: boolean }
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      enabled: boolean
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    hand: { detector: { modelPath: string }; enabled: boolean; iouThreshold: number; landmarks: boolean; maxHands: number; minConfidence: number; rotation: boolean; scoreThreshold: number; skeleton: { modelPath: string }; skipFrames: number; skipInitial: boolean }
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      detector: { modelPath: string }
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      enabled: boolean
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      iouThreshold: number
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      landmarks: boolean
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      maxHands: number
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      minConfidence: number
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      rotation: boolean
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      scoreThreshold: number
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      skeleton: { modelPath: string }
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        modelPath: string
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      skipFrames: number
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      skipInitial: boolean
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    profile: boolean
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    scoped: boolean
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    videoOptimized: boolean
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    warmup: string
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    wasmPath: string
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draw

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draw: { all: Function; body: Function; canvas: Function; face: Function; gesture: Function; hand: Function; options?: { bufferedOutput: Boolean; color: string; drawBoxes: Boolean; drawLabels: Boolean; drawPoints: Boolean; drawPolygons: Boolean; fillPolygons: Boolean; font: string; labelColor: string; lineHeight: number; lineWidth: number; pointSize: number; roundRect: number; shadowColor: string; useCurves: Boolean; useDepth: Boolean } }
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Type declaration

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    all: Function
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    body: Function
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    canvas: Function
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    face: Function
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    Optional options?: { bufferedOutput: Boolean; color: string; drawBoxes: Boolean; drawLabels: Boolean; drawPoints: Boolean; drawPolygons: Boolean; fillPolygons: Boolean; font: string; labelColor: string; lineHeight: number; lineWidth: number; pointSize: number; roundRect: number; shadowColor: string; useCurves: Boolean; useDepth: Boolean }
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      color: string
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      drawBoxes: Boolean
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      drawLabels: Boolean
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      drawPoints: Boolean
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      drawPolygons: Boolean
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      fillPolygons: Boolean
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      font: string
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      labelColor: string
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      lineHeight: number
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      pointSize: number
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      roundRect: number
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      shadowColor: string
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      useDepth: Boolean
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image

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image: { canvas: OffscreenCanvas | HTMLCanvasElement; tensor: Tensor }
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Type declaration

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    canvas: OffscreenCanvas | HTMLCanvasElement
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    tensor: Tensor
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models

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models: { age: null | Model; blazepose: null | Model; embedding: null | Model; emotion: null | Model; face: null | MediaPipeFaceMesh; gender: null | Model; handpose: null | HandPose; iris: null | Model; posenet: null | PoseNet }
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    age: null | Model
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    blazepose: null | Model
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    embedding: null | Model
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    emotion: null | Model
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    face: null | MediaPipeFaceMesh
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    gender: null | Model
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    handpose: null | HandPose
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    iris: null | Model
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    posenet: null | PoseNet
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state

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state: String
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sysinfo

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sysinfo: { agent: String; platform: String }
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    agent: String
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    platform: String
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version

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Methods

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detect

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  • detect(input: OffscreenCanvas | HTMLCanvasElement | Tensor | ImageData | HTMLVideoElement, userConfig?: Object): Promise<Result | { error: String }>
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      input: OffscreenCanvas | HTMLCanvasElement | Tensor | ImageData | HTMLVideoElement
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    Returns Promise<Result | { error: String }>

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enhance

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  • enhance(input: Tensor): null | Tensor
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      input: Tensor
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    Returns null | Tensor

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load

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  • load(userConfig?: Object): Promise<void>
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profileData

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  • profileData(): {} | { largestKernelOps: any; newBytes: any; newTensors: any; numKernelOps: any; peakBytes: any; slowestKernelOps: any; timeKernelOps: any }
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    Returns {} | { largestKernelOps: any; newBytes: any; newTensors: any; numKernelOps: any; peakBytes: any; slowestKernelOps: any; timeKernelOps: any }

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simmilarity

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  • simmilarity(embedding1: Number[], embedding2: Number[]): Number
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      embedding1: Number[]
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    Returns Number

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warmup

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  • warmup(userConfig?: Object): Promise<Result | { error: any }>
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@vladmandic/human

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Result

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Result: { body: { id: Number; part: String; position: { x: Number; y: Number; z: Number }; presence: Number; score: Number }[]; canvas: OffscreenCanvas | HTMLCanvasElement; face: { age: Number; angle: { pitch: Number | null; roll: Number | null; yaw: Number | null }; annotations: any; box: [Number, Number, Number, Number]; boxConfidence: Number; boxRaw: [Number, Number, Number, Number]; confidence: Number; embedding: any; emotion: String; faceConfidence: Number; gender: String; genderConfidence: Number; iris: Number; mesh: [Number, Number, Number][]; meshRaw: [Number, Number, Number][] }[]; gesture: { gesture: String; part: String }[]; hand: { annotations: any; box: any; confidence: Number; landmarks: any }[]; performance: { any: any } }
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    body: { id: Number; part: String; position: { x: Number; y: Number; z: Number }; presence: Number; score: Number }[]
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    canvas: OffscreenCanvas | HTMLCanvasElement
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    face: { age: Number; angle: { pitch: Number | null; roll: Number | null; yaw: Number | null }; annotations: any; box: [Number, Number, Number, Number]; boxConfidence: Number; boxRaw: [Number, Number, Number, Number]; confidence: Number; embedding: any; emotion: String; faceConfidence: Number; gender: String; genderConfidence: Number; iris: Number; mesh: [Number, Number, Number][]; meshRaw: [Number, Number, Number][] }[]
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    gesture: { gesture: String; part: String }[]
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Config

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Config: { async: boolean; backend: string; body: { enabled: boolean; maxDetections: number; modelPath: string; nmsRadius: number; scoreThreshold: number }; deallocate: boolean; debug: boolean; face: { age: { enabled: boolean; modelPath: string; skipFrames: number }; detector: { iouThreshold: number; maxFaces: number; minConfidence: number; modelPath: string; return: boolean; rotation: boolean; scoreThreshold: number; skipFrames: number; skipInitial: boolean }; embedding: { enabled: boolean; modelPath: string }; emotion: { enabled: boolean; minConfidence: number; modelPath: string; skipFrames: number }; enabled: boolean; gender: { enabled: boolean; minConfidence: number; modelPath: string; skipFrames: number }; iris: { enabled: boolean; modelPath: string }; mesh: { enabled: boolean; modelPath: string } }; filter: { blur: number; brightness: number; contrast: number; enabled: boolean; height: number; hue: number; kodachrome: boolean; negative: boolean; pixelate: number; polaroid: boolean; return: boolean; saturation: number; sepia: boolean; sharpness: number; technicolor: boolean; vintage: boolean; width: number }; gesture: { enabled: boolean }; hand: { detector: { modelPath: string }; enabled: boolean; iouThreshold: number; landmarks: boolean; maxHands: number; minConfidence: number; rotation: boolean; scoreThreshold: number; skeleton: { modelPath: string }; skipFrames: number; skipInitial: boolean }; profile: boolean; scoped: boolean; videoOptimized: boolean; warmup: string; wasmPath: string }
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    async: boolean
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    backend: string
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    body: { enabled: boolean; maxDetections: number; modelPath: string; nmsRadius: number; scoreThreshold: number }
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    deallocate: boolean
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    face: { age: { enabled: boolean; modelPath: string; skipFrames: number }; detector: { iouThreshold: number; maxFaces: number; minConfidence: number; modelPath: string; return: boolean; rotation: boolean; scoreThreshold: number; skipFrames: number; skipInitial: boolean }; embedding: { enabled: boolean; modelPath: string }; emotion: { enabled: boolean; minConfidence: number; modelPath: string; skipFrames: number }; enabled: boolean; gender: { enabled: boolean; minConfidence: number; modelPath: string; skipFrames: number }; iris: { enabled: boolean; modelPath: string }; mesh: { enabled: boolean; modelPath: string } }
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      age: { enabled: boolean; modelPath: string; skipFrames: number }
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      detector: { iouThreshold: number; maxFaces: number; minConfidence: number; modelPath: string; return: boolean; rotation: boolean; scoreThreshold: number; skipFrames: number; skipInitial: boolean }
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        return: boolean
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      embedding: { enabled: boolean; modelPath: string }
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      emotion: { enabled: boolean; minConfidence: number; modelPath: string; skipFrames: number }
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      gender: { enabled: boolean; minConfidence: number; modelPath: string; skipFrames: number }
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        modelPath: string
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      iris: { enabled: boolean; modelPath: string }
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      mesh: { enabled: boolean; modelPath: string }
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    filter: { blur: number; brightness: number; contrast: number; enabled: boolean; height: number; hue: number; kodachrome: boolean; negative: boolean; pixelate: number; polaroid: boolean; return: boolean; saturation: number; sepia: boolean; sharpness: number; technicolor: boolean; vintage: boolean; width: number }
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      enabled: boolean
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      height: number
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      hue: number
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      kodachrome: boolean
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      negative: boolean
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      pixelate: number
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      polaroid: boolean
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      return: boolean
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      saturation: number
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      sepia: boolean
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      sharpness: number
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      technicolor: boolean
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      vintage: boolean
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      width: number
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  • -
    gesture: { enabled: boolean }
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      enabled: boolean
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  • -
    hand: { detector: { modelPath: string }; enabled: boolean; iouThreshold: number; landmarks: boolean; maxHands: number; minConfidence: number; rotation: boolean; scoreThreshold: number; skeleton: { modelPath: string }; skipFrames: number; skipInitial: boolean }
    -
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    • -
      detector: { modelPath: string }
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        -
      • -
        modelPath: string
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    • -
      enabled: boolean
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      iouThreshold: number
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      landmarks: boolean
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    • -
      maxHands: number
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    • -
      minConfidence: number
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      rotation: boolean
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    • -
      scoreThreshold: number
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    • -
      skeleton: { modelPath: string }
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        modelPath: string
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      skipFrames: number
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      skipInitial: boolean
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  • -
    profile: boolean
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  • -
    scoped: boolean
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    videoOptimized: boolean
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  • -
    warmup: string
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  • -
    wasmPath: string
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    • -
-
-
-
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- - -
-
-
- -
- - - \ No newline at end of file