denise-is-complex

module to measure the complexity of a graph

Install

npm install --save denise-graph-complex-js

Usage

const {allPath, }
const data = [1, 1, 1, 1,
              0, 1, 0, 0,
              1, 0, 0, 0,
              0, 1, 0, 0];
const vertices = 4;
const result = [11, 21, 7, 7, 
                0, 4, 0, 0, 
                7, 10, 4, 4, 
                0, 4, 0, 0];
const all = allPath(data, vertices);
assert.deepEqual(all, result);

const data = [1, 1, 1, 1,
              0, 1, 0, 0,
              1, 0, 0, 0,
              0, 1, 0, 0];
const vertices = 4;
const result = [2.1818181818181817,2.3333333333333335,2.142857142857143,2.142857142857143,
                Infinity,1.75,Infinity,Infinity,
                2.142857142857143,2.5,2.25, 2.25,
                Infinity,1.75,Infinity,Infinity];
const all = meanPath(data, vertices);
assert.deepEqual(all, result);

const data = [1, 1, 1, 1,
              0, 1, 0, 0,
              1, 0, 0, 0,
              0, 1, 0, 0];
const dim = 4;
const result = [
                1,1,1,1,
                Infinity,1,Infinity,Infinity,
                1,2,2,2,
                Infinity,1,Infinity,Infinity 
                ];
result._isDistance = true
describe('distance ', () => {
  it('should return the matrix of distanceMin path possibles', () => {
    const distanceMin = distance(data, dim);
    assert.deepEqual(distanceMin, result);

API

meanPath(graph = [], vertices = 0) -> Array

return the mean path matrix for the graph given without passing twice by the same vertice.

allPath(graph = [], vertices = 0) -> Array

return the matrix with all paths possibles without passing twice by the same vertice.

getDistance(graph = [], vertices = 0) -> Array

return the matrix with distances between vertices without passing twice by the same vertice.

getEfficiency(graphDistance = [], vertices = 0)

return the graph efficiency of graph, the graphDistance must be the array returned by getDistance.

getLocalClustering(graph = [], vertices = 0) -> Array

return a array with local clustering.

getGlobalClustering(graphLocalClustering = [], vertices = 0)

return average of local clustering,the graphLocalClustering must be the array returned by getLocalClustering.

graph = [x_1, x_2, ... , x_vertXvert] where vert = #Vertices

She is Denise, my love, my wife, my world: