JSDoc: Namespace: cna

MaiaScript Social and Complex Network Analysis library.

Source:

cna.maia, line 21

Methods

(static) createNetwork(topology, numVertices, numEdges, edgeProbability, averageDegree) → {object}

Creates an artificial network.

Parameters:

Name	Type	Description
`topology`	string	Graph topology. It can be: complete, random, small world, scale-free or hybrid.
`numVertices`	number	Number of vertices.
`numEdges`	number	Number of edges.
`edgeProbability`	number	Edge probability.
`averageDegree`	number	Average degree.

Source:

cna.maia, line 27

Returns:

An artificial network.

Type: object

(static) createPajekFile(adj, type) → {string}

Creates a Pajek file.

Parameters:

Name	Type	Description
`adj`	object	Adjascence matrix.
`type`	string	File type (edges, arcs or matrix).

Source:

cna.maia, line 46

Returns:

A Pajek file.

Type: string

(static) doShortestPathWalk(path, i, j) → {object}

Do a shortest parh walk in the network and returns the path.

Parameters:

Name	Type	Description
`path`	object	Paths matrix.
`i`	number	Element index.
`j`	number	Element index.

Source:

cna.maia, line 1006

Returns:

Returns an array containing the shortest parh walk between two vetice in the matrix.

Type: object

(static) getAverageClustering(clustering) → {number}

Calculates average clustering coefficient of the network.

Parameters:

Name	Type	Description
`clustering`	object	Array containing the clustering coefficients of the vertices.

Source:

cna.maia, line 798

Returns:

Returns the average clustering coefficient of the network.

Type: number

(static) getAverageDegree(degrees) → {number}

Calculates average degree of the network.

Parameters:

Name	Type	Description
`degrees`	object	Array containing degrees of the vertices.

Source:

cna.maia, line 721

Returns:

Returns the average degree of the network.

Type: number

(static) getAverageShortestPath(geodesic) → {number}

Calculates average shortest path of the network.

Parameters:

Name	Type	Description
`geodesic`	object	Array the shortest parh between each two vetices in the matrix.

Source:

cna.maia, line 911

Returns:

Returns the average shortest path of the network.

Type: number

(static) getBooleanOr(a, b) → {object}

Boolean OR between two matrices (A and B).

Parameters:

Name	Type	Description
`a`	object	Matrix A.
`b`	object	Matrix B.

Source:

cna.maia, line 579

Returns:

Boolean OR between two matrices.

Type: object

(static) getCentrality(adj, geodesic, directed) → {object}

Returns an array containing the centralities of each pair of the network's vertices.

Parameters:

Name	Type	Description
`adj`	object	Adjascence matrix.
`geodesic`	object	Vector including the geodesics of the network.
`directed`	boolean	True if the network is directed. False otherwise.

Source:

cna.maia, line 1065

Returns:

Returns an array containing the centralities of each pair of the network's vertices

Type: object

(static) getClustering(adj, directed) → {object}

Calculates the clustering coefficients of the vertices.

Parameters:

Name	Type	Description
`adj`	object	Adjascence matrix.
`directed`	boolean	True if the network is directed.

Source:

cna.maia, line 735

Returns:

Returns an array containing the clustering coefficients of the vertices.

Type: object

(static) getDegreeDistribution(degrees) → {object}

Calculates the degrees distribution in the network.

Parameters:

Name	Type	Description
`degrees`	object	Array containing degrees of the vertices.

Source:

cna.maia, line 668

Returns:

Returns an array containing the degrees distribution in the network.

Type: object

(static) getDegrees(adj, directed) → {object}

Calculates the degrees of the vertices of the matrix.

Parameters:

Name	Type	Description
`adj`	object	Adjascence matrix.
`directed`	boolean	True if the network is directed.

Source:

cna.maia, line 635

Returns:

Returns a array containing the degrees of the vertices.

Type: object

(static) getDensity(adj, directed) → {number}

Calculates the network density.

Parameters:

Name	Type	Description
`adj`	object	Adjascence matrix.
`directed`	boolean	True if the network is directed.

Source:

cna.maia, line 605

Returns:

The network density.

Type: number

(static) getDiameter(geodesic) → {number}

Calculates the network diameter.

Parameters:

Name	Type	Description
`geodesic`	object	Array the shortest parh between each two vetices in the matrix.

Source:

cna.maia, line 932

Returns:

Returns the network diameter.

Type: number

(static) getFloydWarshallShortestPath(adj, path) → {object}

Calculates the shortest parh between each two vetices in the matrix using Floyd Warshall method.

Parameters:

Name	Type	Description
`adj`	object	Adjascence matrix.
`path`	object	Matrix to store paths.

Source:

cna.maia, line 945

Returns:

Returns an array containing the shortest parh between each two vetice in the matrix.

Type: object

(static) getGlobalEfficiency(efficiency) → {number}

Returns the network's global efficiency.

Parameters:

Name	Type	Description
`efficiency`	object	Array containing the vertex efficiency of each vertex of the network.

Source:

cna.maia, line 1139

Returns:

Returns the network's global efficiency.

Type: number

(static) getLabels(adj) → {object}

Returns the network vertices labels.

Parameters:

Name	Type	Description
`adj`	object	Adjascence matrix.

Source:

cna.maia, line 1154

Returns:

Returns the network vertices labels.

Type: object

(static) getNumberOfGeodesics(adj, geodesic, directed) → {number}

Return the number os geodesics in the network.

Parameters:

Name	Type	Description
`adj`	object	Adjascence matrix.
`geodesic`	object	Vector including the geodesics of the network.
`directed`	boolean	True if the network is directed. False otherwise.

Source:

cna.maia, line 1028

Returns:

Returns the number os geodesics in the network.

Type: number

(static) getShortestPath(adj, useGPU) → {object}

Calculates the shortest parh between each two vetices in the matrix.

Parameters:

Name	Type	Description
`adj`	object	Adjascence matrix.
`useGPU`	boolean	Uses the GPU to speed up calculations.

Source:

cna.maia, line 813

Returns:

Returns an array containing the shortest parh between each two vetice in the matrix.

Type: object

(static) getTransitiveClosure(a, b) → {object}

Transitive closure between two matrices (A and B).

Parameters:

Name	Type	Description
`a`	object	Matrix A.
`b`	object	Matrix B.

Source:

cna.maia, line 549

Returns:

Transitive closure between two matrices.

Type: object

(static) getVertexEfficiency(geodesic) → {object}

Returns an array containing the vertex efficiency of each pair of the network's vertices.

Parameters:

Name	Type	Description
`geodesic`	object	Vector including the geodesics of the network.

Source:

cna.maia, line 1116

Returns:

Returns an array containing the vertex efficiency of each pair of the network's vertices

Type: object

(static) jsonToPajekFile(network) → {string}

Create a Pajek file from JSON.

Parameters:

Name	Type	Description
`network`	object	JSON containing the network.

Source:

cna.maia, line 478

Returns:

A Pajek file.

Type: string

(static) pajekFileToJson(fileContents, properties) → {object}

Convert a file in Pajek format to JSON.

Parameters:

Name	Type	Description
`fileContents`	string	Pajek file contents.
`properties`	object	Network properties (n, m and directed).

Source:

cna.maia, line 297

Returns:

A JSON containing the network.

Type: object

(static) parseMatrixFile(fileContents, properties, char, replaceCommas) → {object}

Parses a CSV matrix file.

Parameters:

Name	Type	Description
`fileContents`	string	Pajek file contents.
`properties`	object	Network properties (n, m and directed).
`char`	string	The separator character.
`replaceCommas`	boolean	Replace commas by dots in edges weights.

Source:

cna.maia, line 232

Returns:

An adjascence matrix.

Type: object

(static) parsePajekFile(fileContents, properties) → {object}

Parses a Pajek file.

Parameters:

Name	Type	Description
`fileContents`	string	Pajek file contents.
`properties`	object	Network properties (n, m and directed).

Source:

cna.maia, line 102

Returns:

An adjascence matrix.

Type: object

(static) removeLabels(adj) → {number}

Removes the network vertices labels.

Parameters:

Name	Type	Description
`adj`	object	Adjascence matrix.

Source:

cna.maia, line 1191

Returns:

Removes the network vertices labels.

Type: number

(static) setLabels(adj, labels) → {obj}

Sets the network vertices labels.

Parameters:

Name	Type	Description
`adj`	object	Adjascence matrix.
`labels`	object	Array containing the vertices labels.

Source:

cna.maia, line 1172

Returns:

Matrix with vertex labels set.

Type: obj