/*! * Fuzzy Search for DataTables * 2021 SpryMedia Ltd - datatables.net/license MIT license * * Damerau-Levenshtein function courtesy of https://github.com/tad-lispy/node-damerau-levenshtein * BSD 2-Clause License * Copyright (c) 2018, Tadeusz Ĺazurski * All rights reserved. */ (function( factory ){ if ( typeof define === 'function' && define.amd ) { // AMD define( ['jquery', 'datatables.net'], function ( $ ) { return factory( $, window, document ); } ); } else if ( typeof exports === 'object' ) { // CommonJS var jq = require('jquery'); var cjsRequires = function (root, $) { if ( ! $.fn.dataTable ) { require('datatables.net')(root, $); } }; if (typeof window === 'undefined') { module.exports = function (root, $) { if ( ! root ) { // CommonJS environments without a window global must pass a // root. This will give an error otherwise root = window; } if ( ! $ ) { $ = jq( root ); } cjsRequires( root, $ ); return factory( $, root, root.document ); }; } else { cjsRequires( window, jq ); module.exports = factory( jq, window, window.document ); } } else { // Browser factory( jQuery, window, document ); } }(function( $, window, document ) { 'use strict'; var DataTable = $.fn.dataTable; function levenshtein(__this, that, limit) { var thisLength = __this.length, thatLength = that.length, matrix = []; // If the limit is not defined it will be calculate from this and that args. limit = (limit || (thatLength > thisLength ? thatLength : thisLength)) + 1; for (var i = 0; i < limit; i++) { matrix[i] = [i]; matrix[i].length = limit; } for (i = 0; i < limit; i++) { matrix[0][i] = i; } if (Math.abs(thisLength - thatLength) > (limit || 100)) { return prepare(limit || 100); } if (thisLength === 0) { return prepare(thatLength); } if (thatLength === 0) { return prepare(thisLength); } // Calculate matrix. var j, this_i, that_j, cost, min, t; for (i = 1; i <= thisLength; ++i) { this_i = __this[i - 1]; // Step 4 for (j = 1; j <= thatLength; ++j) { // Check the jagged ld total so far if (i === j && matrix[i][j] > 4) return prepare(thisLength); that_j = that[j - 1]; cost = this_i === that_j ? 0 : 1; // Step 5 // Calculate the minimum (much faster than Math.min(...)). min = matrix[i - 1][j] + 1; // Devarion. if ((t = matrix[i][j - 1] + 1) < min) min = t; // Insertion. if ((t = matrix[i - 1][j - 1] + cost) < min) min = t; // Substitution. // Update matrix. matrix[i][j] = i > 1 && j > 1 && this_i === that[j - 2] && __this[i - 2] === that_j && (t = matrix[i - 2][j - 2] + cost) < min ? t : min; // Transposition. } } return prepare(matrix[thisLength][thatLength]); function prepare(steps) { var length = Math.max(thisLength, thatLength); var relative = length === 0 ? 0 : steps / length; var similarity = 1 - relative; return { steps: steps, relative: relative, similarity: similarity, }; } } function fuzzySearch(searchVal, data, initial) { // If no searchVal has been defined then return all rows. if (searchVal === undefined || searchVal.length === 0) { return { pass: true, score: '', }; } var threshold = initial.threshold !== undefined ? initial.threshold : 0.5; // Split the searchVal into individual words. var splitSearch = searchVal.split(/ /g); // Array to keep scores in var highestCollated = []; // Remove any empty words or spaces for (var x = 0; x < splitSearch.length; x++) { if (splitSearch[x].length === 0 || splitSearch[x] === ' ') { splitSearch.splice(x, 1); x--; } // Aside - Add to the score collection if not done so yet for this search word else if (highestCollated.length < splitSearch.length) { highestCollated.push({ pass: false, score: 0 }); } } // Going to check each cell for potential matches for (var i = 0; i < data.length; i++) { // Convert all data points to lower case fo insensitive sorting data[i] = data[i].toLowerCase(); // Split the data into individual words var splitData = data[i].split(/ /g); // Remove any empty words or spaces for (var y = 0; y < splitData.length; y++) { if (splitData[y].length === 0 || splitData[y] === ' ') { splitData.splice(y, 1); x--; } } // Check each search term word for (var x = 0; x < splitSearch.length; x++) { // Reset highest score var highest = { pass: undefined, score: 0, }; // Against each word in the cell for (var y = 0; y < splitData.length; y++) { // If this search Term word is the beginning of the word in the cell we want to pass this word if (splitData[y].indexOf(splitSearch[x]) === 0) { var newScore = splitSearch[x].length / splitData[y].length; highest = { pass: true, score: highest.score < newScore ? newScore : highest.score, }; } // Get the levenshtein similarity score for the two words var steps = levenshtein(splitSearch[x], splitData[y]).similarity; // If the levenshtein similarity score is better than a previous one for the search word then var's store it if (steps > highest.score) { highest.score = steps; } } // If this cell has a higher scoring word than previously found to the search term in the row, store it if (highestCollated[x].score < highest.score || highest.pass) { highestCollated[x] = { pass: highest.pass || highestCollated[x].pass ? true : highest.score > threshold, score: highest.score, }; } } } // Check that all of the search words have passed for (var i = 0; i < highestCollated.length; i++) { if (!highestCollated[i].pass) { return { pass: false, score: Math.round((highestCollated.reduce((a, b) => a + b.score, 0) / highestCollated.length) * 100) + '%', }; } } // If we get to here, all scores greater than 0.5 so display the row return { pass: true, score: Math.round((highestCollated.reduce((a, b) => a + b.score, 0) / highestCollated.length) * 100) + '%', }; } DataTable.ext.search.push(function (settings, data, dataIndex) { var initial = settings.oInit.fuzzySearch; if (!initial) { return true; } if (settings.aoData[dataIndex]) { // If fuzzy searching has not been implemented then pass all rows for this function if (settings.aoData[dataIndex]._fuzzySearch !== undefined) { // Read score to set the cell content and sort data var score = settings.aoData[dataIndex]._fuzzySearch.score; if (initial.rankColumn !== undefined) { settings.aoData[dataIndex].anCells[initial.rankColumn].innerHTML = score; // Remove '%' from the end of the score so can sort on a number settings.aoData[dataIndex]._aSortData[initial.rankColumn] = +score.substring(0, score.length - 1); } // Return the value for the pass as decided by the fuzzySearch function return settings.aoData[dataIndex]._fuzzySearch.pass; } else if (initial.rankColumn !== undefined) { settings.aoData[dataIndex].anCells[initial.rankColumn].innerHTML = ''; settings.aoData[dataIndex]._aSortData[initial.rankColumn] = ''; } } return true; }); $(document).on('init.dt', function (e, settings) { var api = new DataTable.Api(settings); var initial = api.init(); var initialFuzzy = initial.fuzzySearch; // If this is not set then fuzzy searching is not enabled on the table so return. if (!initialFuzzy) { return; } var fromPlugin = false; // Find the input element var input = $('div.dt-search input', api.table().container()); var fontBold = { 'font-weight': '600', 'background-color': 'rgba(255,255,255,0.1)', }; var fontNormal = { 'font-weight': '500', 'background-color': 'transparent', }; var toggleCSS = { border: 'none', background: 'none', 'font-size': '100%', width: '50%', display: 'inline-block', color: 'white', cursor: 'pointer', padding: '0.5em', }; // Only going to set the toggle if it is enabled var toggle, tooltip, exact, fuzzy, label; if (initialFuzzy === true || initialFuzzy.toggleSmart) { toggle = $('') .insertAfter(input) .css({ border: 'none', background: 'none', position: 'relative', right: '33px', top: '0px', cursor: 'pointer', color: '#3b5e99', 'margin-top': '1px', }); exact = $('') .insertAfter(input) .css(toggleCSS) .css(fontBold) .attr('highlighted', 'true'); fuzzy = $('') .insertAfter(input) .css(toggleCSS); input.css({ 'padding-right': '30px', }); $(input.parent()).css('right', '-33px').css('position', 'relative'); label = $('