Delete 'pages/students/2016/jan_holp/pagerank.js'

pages/students/2016/jan_holp/pagerank.js

@@ -1,149 +0,0 @@
-//"use strict";
-// pagerank.js 0.0.1
-
-//Use a random surfer algorithm to determine the relative 
-//rank of nodes. The importance of each node is determined
-//by the number of incoming links as well as the importance 
-//of those incoming links. 
-
-// Expose
-// ----------
-
-//Expose our library to be called externally
-module.exports = function (nodeMatrix, linkProb, tolerance, callback, debug) {
-    if (!nodeMatrix || !linkProb || !tolerance || !callback) {
-        throw new Error("Provide 4 arguments: "+
-            "nodeMatrix, link probability, tolerance, callback");
-    }
-    //If debug is unset set it to false
-    if (!debug) { 
-        debug=false;
-    }
-    return new Pagerank(nodeMatrix, linkProb, tolerance, callback, debug);
-};
-
-// Initialize
-// ----------
-function Pagerank(nodeMatrix, linkProb, tolerance, callback, debug) {
-    //**OutgoingNodes:** represents an array of nodes. Each node in this 
-    //array contains an array of nodes to which the corresponding node has
-    //outgoing links.
-    this.outgoingNodes = nodeMatrix;
-
-    //console.log(this.outgoingNodes);
-    //**LinkProb:** a value ??
-    this.linkProb = linkProb;
-    //**Tolerance:** the point at which a solution is deemed optimal. 
-    //Higher values are more accurate, lower values are faster to computer. 
-    this.tolerance = tolerance;
-    this.callback = callback;
-
-    //Number of outgoing nodes
-    this.pageCount = Object.keys(this.outgoingNodes).length;
-    //console.log(this.pageCount);
-    //**Coeff:** coefficient for the likelihood that a page will be visited.
-    this.coeff = (1-linkProb)/this.pageCount;
-    
-    this.probabilityNodes = !(nodeMatrix instanceof Array) ? {} : [];
-    this.incomingNodes = !(nodeMatrix instanceof Array) ? {} : [];
-    //console.log(this.incomingNodes);
-    this.debug=debug;
-    
-    this.startRanking();
-}
-
-//Start ranking 
-// ----------
-Pagerank.prototype.startRanking = function () {
-
-    //we initialize all of our probabilities
-    var initialProbability = 1/this.pageCount, 
-        outgoingNodes = this.outgoingNodes, i, a, index;
-    
-    //rearray the graph and generate initial probability
-    for (i in outgoingNodes) {
-        this.probabilityNodes[i]=initialProbability;
-        for (a in outgoingNodes[i]) {
-            index = outgoingNodes[i][a];
-            if (!this.incomingNodes[index]) {
-                this.incomingNodes[index]=[]; 
-            }
-            this.incomingNodes[index].push(i);
-               // console.log(this.incomingNodes);
-
-        }
-    }
-
-    //if debug is set, print each iteration
-    if (this.debug) this.reportDebug(1)
-    
-    this.iterate(1);
-};
-
-//Log iteration to console 
-// ----------
-Pagerank.prototype.reportDebug = function (count) {
-    //console.log("____ITERATION "+count+"____");
-    //console.log("Pages: " + Object.keys(this.outgoingNodes).length);
-    //console.log("outgoing %j", this.outgoingNodes);
-    //console.log("incoming %j",this.incomingNodes);
-    //console.log("probability %j",this.probabilityNodes);
-};
-
-
-//Calculate new weights 
-// ----------
-Pagerank.prototype.iterate = function(count) {
-    var result = [];
-    var resultHash={};
-    var prob, ct, b, a, sum, res, max, min;
-
-    //For each node, we look at the incoming edges and 
-    //the weight of the node connected via each edge. 
-    //This weight is divided by the total number of 
-    //outgoing edges from each weighted node and summed to 
-    //determine the new weight of the original node.
-    for (b in this.probabilityNodes) {
-
-        sum = 0;
-        if( this.incomingNodes[b] ) {
-            for ( a=0; a<this.incomingNodes[b].length; a++) {
-                prob = this.probabilityNodes[ this.incomingNodes[b][a] ];
-                ct = this.outgoingNodes[ this.incomingNodes[b][a] ].length;
-                sum += (prob/ct) ;
-            }
-        }
-
-        //determine if the new probability is within tolerance.
-        res = this.coeff+this.linkProb*sum;
-        max = this.probabilityNodes[b]+this.tolerance;
-        min = this.probabilityNodes[b]-this.tolerance;   
-
-        //if the result has changed push that result
-        if (min <= res && res<= max) {
-            resultHash[b]=res;
-            result.push(res);
-        }
-    
-        //update the probability for node *b*
-        this.probabilityNodes[b]=res;
-        //console.log(this.probabilityNodes[b]);
-        //console.log(res);
-    }
-
-    //When we have all results (no weights are changing) we return via callback
-    if (result.length == this.pageCount) {
-        if( !(this.outgoingNodes instanceof Array)) {
-            return this.callback(null, resultHash);
-        }
-        return this.callback(null, result);
-    }
-    
-    //if debug is set, print each iteration
-    if (this.debug) {
-        this.reportDebug(count); 
-    }
-    
-    ++count;
-    return this.iterate(count);
-};