GenPrefAttach
'''''''''''''

.. function:: GenPrefAttach(Nodes, NodesOutDeg, Rnd=TRnd)

Generates an undirected graph with a power-law degree distribution using Barabasi-Albert model of scale-free graphs.

Parameters: 

- *Nodes*: int (input)
	The number of nodes desired.

- *NodeOutDeg*: int (input)
	The out degree of each node desired.

- *Rnd*: :class:`TRnd` (input)
	Random number generator.

Return Value: 
	
- undirected graph
	A Snap.py undirected graph representing the power-law degree distribution. 

The function implements a Barabasi-Albert model of scale-free graphs and generates graphs with a power-law degree distribution. See: Emergence of scaling in random networks by Barabasi and Albert. URL: http://arxiv.org/abs/cond-mat/9910332


The following example shows how to use :func:`GenPrefAttach`::
	
    import snap 

    Rnd = snap.TRnd()
    UGraph = snap.GenPrefAttach(100, 10, Rnd)
    for EI in UGraph.Edges():
        print("edge: (%d, %d)" % (EI.GetSrcNId(), EI.GetDstNId()))