diff --git a/pages/students/2016/jan_holp/pagerank.js b/pages/students/2016/jan_holp/pagerank.js deleted file mode 100644 index 056391efc8..0000000000 --- a/pages/students/2016/jan_holp/pagerank.js +++ /dev/null @@ -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