randomgraph.js

A small library for generating, well, random graphs. Not that many models at the moment, feel free to jump in and add some more. The algorithms were partly ported and double-checked with the Gephi implementations (thx @jacomyal for the link).

#Documentation Members

• randomgraph
  • randomgraph.BalancedTree(r, h)
  • randomgraph.BarabasiAlbert(N, m0, M)
  • randomgraph.ErdosRenyi
    • ErdosRenyi.np(n, p)
    • ErdosRenyi.nm(n, M)
  • randomgraph.WattsStrogatz
    • WattsStrogatz.alpha(n, K, alpha)
    • WattsStrogatz.beta(n, K, beta)

##randomgraph.BalancedTree(r, h) Simple balanced tree

Params

• r Number - number of children each node has
• h Number - height of the tree

##randomgraph.BarabasiAlbert(N, m0, M) Barabási–Albert

Params

• N Number - total number of nodes N > 0
• m0 Number - m0 > 0 && m0 < N
• M Number - M > 0 && M <= m0

##randomgraph.ErdosRenyi Members

• randomgraph.ErdosRenyi
  • ErdosRenyi.np(n, p)
  • ErdosRenyi.nm(n, M)

###ErdosRenyi.np(n, p) Erdős–Rényi aka Gilbert

Params

• n Number - number of nodes
• p Number - probability of a edge between any two nodes

###ErdosRenyi.nm(n, M) Erdős–Rényi

Params

• n Number - number of nodes
• M Number - number of edges

##randomgraph.WattsStrogatz Members

• randomgraph.WattsStrogatz
  • WattsStrogatz.alpha(n, K, alpha)
  • WattsStrogatz.beta(n, K, beta)

###WattsStrogatz.alpha(n, K, alpha) Watts-Strogatz Small World model Alpha

Params

• n Number - number of nodes
• K Number - mean degree (even integer)
• alpha Number - rewiring probability [0..1]

###WattsStrogatz.beta(n, K, beta) Watts-Strogatz Small World model Beta

Params

• n Number - number of nodes
• K Number - mean degree (even integer)
• beta Number - rewiring probability [0..1]