├── LICENSE ├── README.md ├── TODO.txt └── linkedin ├── d3js-linkedin.js ├── sna-js.js └── socilab-linkedin.js /LICENSE: -------------------------------------------------------------------------------- 1 | GNU GENERAL PUBLIC LICENSE 2 | Version 2, June 1991 3 | 4 | Copyright (C) 1989, 1991 Free Software Foundation, Inc., 5 | 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA 6 | Everyone is permitted to copy and distribute verbatim copies 7 | of this license document, but changing it is not allowed. 8 | 9 | Preamble 10 | 11 | The licenses for most software are designed to take away your 12 | freedom to share and change it. By contrast, the GNU General Public 13 | License is intended to guarantee your freedom to share and change free 14 | software--to make sure the software is free for all its users. This 15 | General Public License applies to most of the Free Software 16 | Foundation's software and to any other program whose authors commit to 17 | using it. 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If this is what you want to do, use the GNU Lesser General 339 | Public License instead of this License. 340 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | sna-js 2 | ====== 3 | 4 | This repository contains javascript code that interact with social network APIs, generate D3.js visualizations, and calculate relevant metrics for **social network analysis**. 5 | 6 | You can see it in use at: http://socilab.com. Socilab is a social network utility that allows users to visualize, analyze, and download data on their LinkedIn network. It has been used for in class tutorials at a number of universities - including Carnegie Mellon, Cornell, Dartmouth, London Business School, University of Sydney, among others, and is featured on datasciencemasters.org. 7 | 8 | I am actively developing this as users request more features and look forward to collaborating to anyone who shares an interest in **making network data and analysis more accessible to end users**. 9 | 10 | LinkedIn 11 | ------ 12 | ###sna-js.js: 13 | Takes in 2D adjacency matrix from socilab-linkedin.js and performs egocentric network calculations for social network analysis. 14 | 15 | ###d3js-linkedin.js: 16 | A dynamic and interactive visualization of a user's LinkedIn network using the d3js library, with options to enable/disable connections to ego and color nodes by industry. 17 | 18 | ###socilab-linkedin.js: 19 | Methods for interacting with LinkedIn API to gather network data for display, analysis, and download by user. 20 | 21 | **Note on LinkedIn API functionality**: LinkedIn's public API no longer supports the related-connections request that this script relies on. LinkedIn was courteous enough to extend socilab's access to the prior functionality while our partnership application is pending review. I do not have a timeline for when the application will be processed, but any contributions made here in the meantime can be implemented on the public site so long as they comply with the terms. 22 | 23 | ---- 24 | **Author**: *Craig Tutterow*, [@craigtutterow](https://github.com/craigtutterow) 25 | 26 | Contributors: *Lars Juel Nielsen* ([@LJNielsenDk](https://github.com/LJNielsenDk)), *Kushal Likhi* ([@kushal-likhi](https://github.com/kushal-likhi)) 27 | -------------------------------------------------------------------------------- /TODO.txt: -------------------------------------------------------------------------------- 1 | Features to add to network analysis: 2 | 3 | 1. Industry diversity index 4 | 2. Ordered list of top 5 contacts in eigenvector centrality 5 | 3. Add sharing feature for social media integration. 6 | 4. Add pdf download feature. 7 | 5. Error message once throttled. 8 | 6. Format download according to visualization option (connections to self included/excluded). 9 | 7. Add attributes file. 10 | 11 | Features to add to visualization: 12 | 13 | 1. Node sizing by ego's dependence (proportional tie strength or eigenvector centrality of a given node) 14 | 2. Coloring by community detection algorithm (detect clusters of contacts with high density - e.g. colleagues at different companies, classmates, friends from civic organization, etc.) 15 | 3. Add static sharing feature for social media integration. 16 | 4. Add option to remove names. 17 | 18 | Site functionality: 19 | 1. Prevent page from reloading after clicking tab to home page (jquery). 20 | 2. Add facebook support 21 | -------------------------------------------------------------------------------- /linkedin/d3js-linkedin.js: -------------------------------------------------------------------------------- 1 | /*D3.js code to visualize a user's LinkedIn network from 2d array. Adjacency matrix of user's contacts 2 | is received after being parsed from LinkedIn API.*/ 3 | function visualizeConnections(data, enableConnectionsToSelf, colorization) { 4 | var matrix = enableConnectionsToSelf ? data.matrix : data.reducedMatrix; 5 | var connections = data.publicConnections; 6 | var me = { firstName: "Me", lastName: "" }; 7 | var ggraph = d3.graph(); 8 | ggraph.matrix(matrix); 9 | var nodes = enableConnectionsToSelf ? [ me ].concat(connections) : connections; 10 | ggraph.nodes(nodes); 11 | var glinks = ggraph.links().filter(function(d) {return d.value > 0;}); 12 | var gnodes = ggraph.nodes(); 13 | var radius = 5; 14 | var defaultLinkStrength = 1; 15 | var myLinkStrength = 0.2; 16 | var showText = true; 17 | 18 | //console.log('nodes', ggraph.nodes()); 19 | //console.log('links', JSON.stringify(ggraph.links()); 20 | //console.log('description', ggraph.description()); 21 | 22 | var color = d3.scale.category20(); 23 | 24 | var width = 960, 25 | height = 800; 26 | 27 | 28 | 29 | var linkDistance = function(link) { 30 | var len1 = glinks.filter(function(d) {return (d.source.id == link.source.id);}).length; 31 | var len2 = glinks.filter(function(d) {return d.target.id == link.target.id;}).length; 32 | //console.log(len1, len2); 33 | return 160; 34 | }; 35 | 36 | var force = d3.layout.force() 37 | .nodes(gnodes) 38 | .links(glinks) 39 | .size([width, height]) 40 | //.linkDistance(linkDistance) 41 | .linkStrength(function(d) { return (d.source.id && d.target.id) ? d.value * defaultLinkStrength : d.value * myLinkStrength; } ) 42 | .charge(-900) 43 | .gravity(.8) 44 | //.on("tick", tick) 45 | .start(); 46 | 47 | d3.select("body").selectAll("svg").remove(); 48 | var svg = d3.select("div#d3_viewport").append("svg") 49 | .attr("width", width) 50 | .attr("height", height) 51 | .call(d3.behavior.zoom() 52 | .on("zoom", redraw)) 53 | .append("g"); 54 | 55 | function redraw() { 56 | svg.attr("transform", "translate(" + d3.event.translate + ")scale(" + d3.event.scale + ")"); 57 | } 58 | 59 | // add the links and the arrows 60 | var glink = svg.selectAll(".link") 61 | .data(force.links()); 62 | var glinkEnter = glink 63 | .enter().append("line") 64 | .attr("class", "link") 65 | .style("stroke-width", function (d) { 66 | return Math.sqrt(d.value); 67 | }); 68 | glink.exit().remove(); 69 | 70 | 71 | // define the nodes 72 | var gnode = svg.selectAll(".node") 73 | .data(force.nodes()); 74 | var gnodeEnter = gnode 75 | .enter() 76 | .append("g"); 77 | gnodeEnter 78 | .append("circle") 79 | .attr("class", "node") 80 | .attr("r", radius) 81 | .call(force.drag); 82 | 83 | console.log("Colorization now: " + colorization); 84 | gnode.selectAll(".node") 85 | .style("fill", function (d) { return color(colorization(d)); }); 86 | 87 | gnodeEnter.append("text") 88 | .text(function (d) { return d.firstName + " " + d.lastName; }) 89 | .attr("transform", "translate(7, 0)") 90 | .style("pointer-events", "none") 91 | .style("cursor", "default") 92 | .style("display", showText ? "block" : "none") 93 | .style("font-size", 8) 94 | ; 95 | glink.exit().remove(); 96 | 97 | 98 | force.on("tick", function () { 99 | glink.attr("x1", function (d) { 100 | return d.source.x; 101 | }) 102 | .attr("y1", function (d) { 103 | return d.source.y; 104 | }) 105 | .attr("x2", function (d) { 106 | return d.target.x; 107 | }) 108 | .attr("y2", function (d) { 109 | return d.target.y; 110 | }); 111 | 112 | gnode.select("circle").attr("cx", function(d) {return d.x;}); 113 | gnode.select("circle").attr("cy", function(d) {return d.y;}); 114 | gnode.select("text").attr("transform", function (d) { 115 | return "translate(" + (d.x + 6) + "," + (d.y + 4) + ")"; 116 | }); 117 | }); 118 | 119 | //add curvy lines? 120 | /*function tick() { 121 | glink.attr("d", function (d) { 122 | var dx = d.target.x - d.source.x, 123 | dy = d.target.y - d.source.y, 124 | dr = Math.sqrt(dx * dx + dy * dy); 125 | return "M" + d.source.x + "," + d.source.y + "A" + dr + "," + dr + " 0 0,1 " + d.target.x + "," + d.target.y; 126 | }); 127 | 128 | gnode.attr("transform", function (d) { 129 | return "translate(" + d.x + "," + d.y + ")"; 130 | }); 131 | } */ 132 | } -------------------------------------------------------------------------------- /linkedin/sna-js.js: -------------------------------------------------------------------------------- 1 | var num = [ 2 | /* data is parsed from LinkedIn's API to take in a 2d array like this: 3 | 4 | [0, 1, 1, 1, 1, 1, 1, 1, 1, 1], 5 | [1, 0, 1, 1, 0, 0, 0, 0, 0, 1], 6 | [1, 1, 0, 1, 0, 0, 1, 0, 0, 0], 7 | [1, 1, 1, 0, 1, 1, 0, 0, 0, 0], 8 | [1, 0, 0, 1, 0, 1, 1, 0, 0, 0], 9 | [1, 0, 0, 1, 1, 0, 1, 1, 0, 0], 10 | [1, 0, 1, 0, 1, 1, 0, 1, 1, 0], 11 | [1, 0, 0, 0, 0, 1, 1, 0, 1, 1], 12 | [1, 0, 0, 0, 0, 0, 1, 1, 0, 1], 13 | [1, 1, 0, 0, 0, 0, 0, 1, 1, 0] 14 | 15 | rows and columns representing an ordered list of one's contacts, producing 16 | an adjacency matrix. A 1 at the intersection of 2 contacts representing a 17 | mutual connection between x and y. Note that the matrix is symmetric by definition 18 | and that the diagonal is set to 0, as no ego can be connected to themselves) 19 | */ 20 | ]; 21 | 22 | /*transpose function for matrix operations*/ 23 | Array.prototype.transpose = function () { 24 | var a = this, 25 | w = a.length ? a.length : 0, 26 | h = a[0] instanceof Array ? a[0].length : 0; 27 | if (h === 0 || w === 0) { 28 | return []; 29 | } 30 | var i, j, t = []; 31 | for (i = 0; i < h; i++) { 32 | t[i] = []; 33 | for (j = 0; j < w; j++) { 34 | t[i][j] = a[j][i]; 35 | } 36 | } 37 | return t; 38 | }; 39 | 40 | var totedges = 0; 41 | 42 | /*row sum operation for matrix operations*/ 43 | function rowsums(mm) { 44 | var mmlen = mm.length; 45 | sumOfRows = new Array(mmlen); 46 | var sumR = 0; 47 | for (var row = 0; row < mmlen; row++) { 48 | for (var col = 0; col < mmlen; col++) { 49 | sumR += mm[row][col]; 50 | totedges = totedges + (mm[row][col] / 2); 51 | } 52 | sumOfRows[row] = sumR; 53 | sumR = 0; 54 | } 55 | totedges = totedges - (2 * (mmlen - 1)); 56 | return sumOfRows; 57 | } 58 | 59 | /*calculate the proportional strength of network edges (input for structural holes calculation)*/ 60 | function ptiestrength(Z) { 61 | Ztrans = Z.transpose(); 62 | zlen = Z.length; 63 | znum = new Array(zlen); 64 | for (var l = 0; l < zlen; l++) { 65 | znum[l] = new Array(zlen); 66 | } 67 | for (var x = 0; x < zlen; x++) { 68 | for (var y = 0; y < zlen; y++) { 69 | znum[x][y] = Z[x][y] + Ztrans[x][y]; 70 | } 71 | } 72 | dtemp = rowsums(znum); 73 | P = new Array(zlen); 74 | for (var k = 0; k < zlen; k++) { 75 | P[k] = new Array(zlen); 76 | } 77 | for (var i = 0; i < zlen; i++) { 78 | for (var j = 0; j < zlen; j++) { 79 | if (dtemp[i] > 0) { 80 | P[i][j] = znum[i][j] / dtemp[i]; 81 | } 82 | if (dtemp[i] <= 0) { 83 | P[i][j] = 0; 84 | } 85 | } 86 | } 87 | return P; 88 | } 89 | 90 | /*calculate the structural holes index and its components*/ 91 | function structuralholes(Z) { 92 | aa = Z; 93 | var aalen = aa.length; 94 | var i = 0; 95 | P = ptiestrength(Z); 96 | var constraint = 0; 97 | var esize = 0; 98 | var csize = 0; 99 | var density = 0; 100 | var pubdensity = 0; 101 | var hierarchy = 0; 102 | var maxedges = (aalen - 1) * (aalen - 2) * 2; 103 | for (var j = 1; j < aalen; j++) { 104 | Pij = P[i][j]; 105 | csize = csize + Math.pow(Pij, 2) 106 | var innersum = 0; 107 | for (var q = 1; q < aalen; q++) { 108 | if (q != j & q != i) { 109 | innersum = innersum + (P[i][q] * P[q][j]) 110 | } 111 | } 112 | density = density + (2 * Pij * innersum) 113 | hierarchy = hierarchy + Math.pow(innersum, 2); 114 | esize = (aalen - 1) - ((totedges * 2) / (aalen - 1)); 115 | asize = aalen - 1; 116 | } 117 | var betweenness=((aalen-1)*(aalen-2))/2; 118 | for(var i=1; i0) 142 | { 143 | betweenness=betweenness-(shared/(shared+1)); 144 | } 145 | } 146 | } 147 | } 148 | csize = csize * 100; 149 | density = density * 100; 150 | pubdensity=totedges/((aalen-1)*(aalen-2))/2*100; 151 | hierarchy = hierarchy * 100; 152 | constraint = csize + density + hierarchy; 153 | var asize = aalen - 1; 154 | var Csdhe = { constraint: constraint, csize: csize, density:density, hierarchy: hierarchy, esize: esize, asize: asize, pubdensity: pubdensity, betweenness: betweenness}; 155 | return Csdhe; 156 | } 157 | 158 | /*processes user's sociomatrix and presents results*/ 159 | function processMatrix(matrix) { 160 | num = matrix; 161 | var ntr = num.transpose(); 162 | var rsum = rowsums(num); 163 | var z = ptiestrength(num); 164 | var holes = structuralholes(num); 165 | document.getElementById('Instructions').innerHTML = 166 | "" 167 | ; 168 | document.getElementById('asize_output').innerHTML = 169 | "" + holes.asize.toString() + "" + 170 | "; This is the total number of contacts you have. It is not as informative as your unique (or 'effective') ties. The quality of your network isn't just about the total number of people you know, but the information, opportunities, and social support they provide. These factors are correlated with the structure of the ties between your contacts, not just their raw number.
" 171 | + "
" 172 | ; 173 | document.getElementById('esize_output').innerHTML = 174 | "" + holes.esize.toFixed(1) + "" + 175 | "; This is the 'effective size' of your network. Not every contact counts the same or adds the same value to your network. Some ties are 'redundant' because you both know all of the same people. They are not necessarily giving you unique information. This measure controls for that fact and gives an estimate of the unique number of clusters you are connected to.
" 176 | + "
" 177 | ; 178 | document.getElementById('constraint_output').innerHTML = 179 | "" + holes.constraint.toFixed(2) + "" + 180 | "/100; This is an index measure that describes the extent to which your network spans different groups (i.e. bridging structural holes) or is concentrated in one or two areas. As the number approaches 100, you are in a closed, or focused network. As it approaches 0, your network is more open/dispersed, indicating that you have more vision across social groups. Disconnected contacts may expose you to new information, but closure is required to develop a reputation or generate trust, among other things.
" 181 | + "
" 182 | ; 183 | document.getElementById('density_output').innerHTML = 184 | "" + holes.pubdensity.toFixed(2) + "" + 185 | "/100; This is a percentage that represents the number of ties between your contacts divided by the total number of possible ties (i.e. how 'dense' or closed your network is). As the number approaches 100, it means that all of your contacts know each other. As it approaches 0, it means all of your contacts are disconnected from each other. Having a closed network can be good or bad depending on the task and social environment.
" 186 | + "
" 187 | ; 188 | document.getElementById('hierarchy_output').innerHTML = 189 | "" + holes.hierarchy.toFixed(2) + "" + 190 | "/100; This number is a concentration index that represents how dependent you are on a few focal contacts. If all of your contacts know you through your boss or parent, then you have a 'hierarchical' network, and are dependent on them. This can work well in situations where you are considered an 'outsider' and need a strategic partner to get in the door, but is generally considered a handicap.
" 191 | + "
" 192 | ; 193 | document.getElementById('betweenness_output').innerHTML = 194 | "" + holes.betweenness.toFixed(1) + "" + 195 | "; This number represents the number of structural holes, or bridging opportunities, to which you have exclusive access. You have exclusive access to a structural hole if you lie on the shortest path between two contacts in your network. If others in your network lie on an equidistant path between the two contacts, then you each own a proportional amount. This number is typically quite large, and is presented in raw form in order to emphasize the opportunities you have to move information between people in your network who don't know each other.
" 196 | + "
" 197 | ; 198 | console.log("JSON: " + JSON.stringify(holes)); 199 | new socilabAnalysisReport(holes).save().getPercentile(function (data) { 200 | $("#percentiles").show(); 201 | $("#p_constraint span").text(data.constraint.toFixed(2) + "%"); 202 | $("#p_hierarchy span").text(data.hierarchy.toFixed(2) + "%"); 203 | $("#p_asize span").text(data.asize.toFixed(2) + "%"); 204 | $("#p_esize span").text(data.esize.toFixed(2) + "%"); 205 | $("#p_density span").text(data.density.toFixed(2) + "%"); 206 | $("#p_csize span").text(data.csize.toFixed(2) + "%"); 207 | $("#p_betweenness span").text(data.betweenness.toFixed(2) + "%"); 208 | 209 | $("#p_constraint div.bar").css({width: data.constraint.toFixed(2) + "%"}); 210 | $("#p_hierarchy div.bar").css({width: data.hierarchy.toFixed(2) + "%"}); 211 | $("#p_asize div.bar").css({width: data.asize.toFixed(2) + "%"}); 212 | $("#p_esize div.bar").css({width: data.esize.toFixed(2) + "%"}); 213 | $("#p_density div.bar").css({width: data.density.toFixed(2) + "%"}); 214 | $("#p_csize div.bar").css({width: data.csize.toFixed(2) + "%"}); 215 | $("#p_betweenness div.bar").css({width: data.betweenness.toFixed(2) + "%"}); 216 | }); 217 | try { 218 | loader.hide(); 219 | } catch (c) { 220 | } 221 | } 222 | 223 | /*database functionality to post metrics and receive percentiles*/ 224 | var socilab = { 225 | config: { 226 | urls: { 227 | saveReport: "/service/analysis/report/save", 228 | getPercentile: "/service/analysis/report/percentile" 229 | } 230 | }, 231 | constructors: { 232 | UserDataProvider: function () { 233 | var username = $("meta[name='user-name']").attr("content"); 234 | var userID = $("meta[name='user-id']").attr("content"); 235 | this.getID = function () { 236 | return userID; 237 | }; 238 | this.getUsername = function () { 239 | return username; 240 | }; 241 | }, 242 | socilabDataTransport: function (url) { 243 | this.post = function (data, callback) { 244 | $.post(url, data, callback); 245 | }; 246 | }, 247 | socilabAnalysisReport: function (holes) { 248 | var _this = this; 249 | var userDataProvider = new socilab.constructors.UserDataProvider(); 250 | var data = $.extend(holes, { 251 | user_id: userDataProvider.getID(), 252 | user_login: userDataProvider.getUsername() 253 | }); 254 | this.save = function (callback) { 255 | new socilab.constructors.socilabDataTransport(socilab.config.urls.saveReport).post(data, function () { 256 | try { 257 | console.log("Data Saved!"); 258 | if (typeof(callback) != 'undefined') callback(); 259 | } catch (c) { 260 | } 261 | }); 262 | return _this; 263 | }; 264 | this.getPercentile = function (callback) { 265 | new socilab.constructors.socilabDataTransport(socilab.config.urls.getPercentile).post(data, function (data) { 266 | callback(data); 267 | }); 268 | return _this; 269 | }; 270 | } 271 | }, 272 | init: new function () { 273 | $(function () { 274 | socilab.constructor(); 275 | }); 276 | }, 277 | constructor: function () { 278 | window.socilabAnalysisReport = socilab.constructors.socilabAnalysisReport; 279 | } 280 | }; -------------------------------------------------------------------------------- /linkedin/socilab-linkedin.js: -------------------------------------------------------------------------------- 1 | //d3js option 2 | var enableConnectionsToSelf = false; 3 | var currentData; 4 | 5 | //utilities for d3js visualization options 6 | var byName = function (d) { 7 | return d.firstName + " " + d.lastName; 8 | }; 9 | var byIndustry = function (d) { 10 | return d.industry; 11 | }; 12 | var byCountryCode = function (d) { 13 | return d.location.country.code; 14 | }; 15 | var byLocation = function (d) { 16 | var result = ""; 17 | if (d.location.country.code !== 'undefined') { 18 | result = d.location.name + ", " + d.location.country.code; 19 | } else { 20 | result = d.location.name; 21 | } 22 | return result; 23 | }; 24 | var colorization = byIndustry; 25 | 26 | //test data can be uploaded for debugging 27 | var testMode = false; 28 | if (window.location.search.indexOf("test") >= 0) { 29 | testMode = true; 30 | } 31 | 32 | Object.size = function (obj) { 33 | var size = 0, key; 34 | for (key in obj) { 35 | if (obj.hasOwnProperty(key)) size++; 36 | } 37 | return size; 38 | }; 39 | 40 | //linkedin authorization for api access 41 | function onLinkedInLoad() { 42 | if (testMode) { 43 | setConnections(sampleData.connections); 44 | dataReady(sampleData); 45 | } else { 46 | IN.Event.on(IN, "auth", function () { 47 | onLinkedInLogin(); 48 | }); 49 | IN.Event.on(IN, "logout", function () { 50 | onLinkedInLogout(); 51 | }); 52 | } 53 | } 54 | 55 | function onLinkedInLogout() { 56 | setConnections({}, {total: 0}); 57 | } 58 | 59 | function onLinkedInLogin() { 60 | //Get my info and also set the meta tags 61 | try{ 62 | loader.show(); 63 | }catch(c){} 64 | IN.API.Profile("me").result(function (result) { 65 | if(result.values.length){ 66 | $("meta[name='user-name']").attr("content", result.values[0].firstName + " " +result.values[0].lastName); 67 | $("meta[name='user-id']").attr("content", result.values[0].id); 68 | } 69 | // pass the fields as individual string parameters 70 | IN.API.Connections("me") 71 | .fields("id", "firstName", "lastName", "pictureUrl", "publicProfileUrl", "industry") 72 | .result(function (result, metadata) { 73 | setConnections(result.values, metadata); 74 | }); 75 | }); 76 | } 77 | 78 | //process data and produce csv file of adjacency matrix for user download 79 | function dataReady(resultData) { 80 | console.log(JSON.stringify(resultData)); 81 | console.log(JSON.stringify(resultData.connections[2].firstName + " " + resultData.connections[2].lastName)); 82 | var myData='"",'+ '"Me",'; 83 | console.log(resultData.connections.length); 84 | var nverts=resultData.connections.length+1; 85 | var myPajData='*Vertices '+ nverts.toString() + "\n" + '1 "Me"' + "\n"; 86 | for (var i=0; i 0) { 195 | console.warn("Querying contacts has produced " + errorCount + " error" + (errorCount == 1 ? "" : "s")); 196 | } 197 | 198 | var sociomat = mutualConnectsToMatrix(mutualconnects); 199 | var reducedSociomat = mutualConnectsToReducedMatrix(mutualconnects); 200 | var resultData = { 201 | connections: connections, 202 | publicConnections: publicConnections, 203 | matrix: sociomat, 204 | reducedMatrix: reducedSociomat 205 | }; 206 | console.log("SOCIOMAT", sociomat); 207 | try { 208 | console.log('saving to local storage'); 209 | localStorage.setItem(inId, JSON.stringify(resultData)); 210 | } catch (c) { 211 | 212 | } 213 | dataReady(resultData); 214 | }); 215 | } 216 | 217 | //converts mutual connections array to adjacency matrix 218 | function mutualConnectsToMatrix(mutualconnects) { 219 | var len = mutualconnects.length; 220 | var result = []; 221 | 222 | for (var i = 0; i < len + 1; i++) { 223 | result.push(new Array(len + 1)); 224 | result[i][i] = 0; 225 | for (var j = 0; j < i; j++) { 226 | var value = (i == 0 || j == 0 || (mutualconnects[i - 1] && mutualconnects[i - 1].indexOf(j - 1) >= 0)) ? 1 : 0; 227 | result[i][j] = result[j][i] = value; 228 | } 229 | } 230 | 231 | return result; 232 | } 233 | 234 | //reduces network by removing ego node - used in the 'disable links to self' d3js option to 235 | //make internal structure of contacts more visible. 236 | function mutualConnectsToReducedMatrix(mutualconnects) { 237 | var len = mutualconnects.length; 238 | var result = []; 239 | 240 | for (var i = 0; i < len; i++) { 241 | result.push(new Array(len)); 242 | result[i][i] = 0; 243 | for (var j = 0; j < i; j++) { 244 | var value = 0; 245 | if (mutualconnects[i] && mutualconnects[i].indexOf(j) >= 0) { 246 | value = 1; 247 | } 248 | result[i][j] = result[j][i] = value; 249 | } 250 | } 251 | 252 | return result; 253 | } 254 | 255 | 256 | $(function () { 257 | $("input[name=radio1]").click(function () { 258 | switch (this.value) { 259 | case "industry": 260 | colorization = byIndustry; 261 | break; 262 | case "name": 263 | colorization = byName; 264 | break; 265 | case "countryCode": 266 | colorization = byCountryCode; 267 | break; 268 | case "location": colorization = byLocation; 269 | break; 270 | default: 271 | colorization = byIndustry; 272 | } 273 | visualizeConnections(currentData, enableConnectionsToSelf, colorization); 274 | }); 275 | 276 | $("input[name=radio2]").click(function () { 277 | enableConnectionsToSelf = (this.value == "self"); 278 | visualizeConnections(currentData, enableConnectionsToSelf, colorization); 279 | }); 280 | }); 281 | --------------------------------------------------------------------------------