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import * as is from '../../is';
import * as util from '../../util';
const defaults = util.defaults({
harmonic: true,
weight: () => 1,
directed: false,
root: null
});
const elesfn = ({
closenessCentralityNormalized: function( options ){
let { harmonic, weight, directed } = defaults(options);
let cy = this.cy();
let closenesses = {};
let maxCloseness = 0;
let nodes = this.nodes();
let fw = this.floydWarshall({ weight, directed });
// Compute closeness for every node and find the maximum closeness
for( let i = 0; i < nodes.length; i++ ){
let currCloseness = 0;
let node_i = nodes[i];
for( let j = 0; j < nodes.length; j++ ){
if( i !== j ){
let d = fw.distance( node_i, nodes[j] );
if( harmonic ){
currCloseness += 1 / d;
} else {
currCloseness += d;
}
}
}
if( !harmonic ){
currCloseness = 1 / currCloseness;
}
if( maxCloseness < currCloseness ){
maxCloseness = currCloseness;
}
closenesses[ node_i.id() ] = currCloseness;
}
return {
closeness: function( node ){
if( maxCloseness == 0 ){ return 0; }
if( is.string( node ) ){
// from is a selector string
node = (cy.filter( node )[0]).id();
} else {
// from is a node
node = node.id();
}
return closenesses[ node ] / maxCloseness;
}
};
},
// Implemented from pseudocode from wikipedia
closenessCentrality: function( options ){
let { root, weight, directed, harmonic } = defaults(options);
root = this.filter(root)[0];
// we need distance from this node to every other node
let dijkstra = this.dijkstra({ root, weight, directed });
let totalDistance = 0;
let nodes = this.nodes();
for( let i = 0; i < nodes.length; i++ ){
let n = nodes[i];
if( !n.same(root) ){
let d = dijkstra.distanceTo(n);
if( harmonic ){
totalDistance += 1 / d;
} else {
totalDistance += d;
}
}
}
return harmonic ? totalDistance : 1 / totalDistance;
} // closenessCentrality
}); // elesfn
// nice, short mathematical alias
elesfn.cc = elesfn.closenessCentrality;
elesfn.ccn = elesfn.closenessCentralityNormalised = elesfn.closenessCentralityNormalized;
export default elesfn;
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