GenRndPowerLaw¶
-
GenRndPowerLaw
(Nodes, PowerExp, ConfModel=True, Rnd=TRnd)¶
Generates a random scale-free graph with power-law degree distribution with exponent PowerExp. The method uses either the Configuration model (fast but the result is approximate) or the Edge Rewiring method (slow but exact).
Parameters:
- Nodes: int (input)
Number of nodes.
- PowerExp: float (input)
Power exponent, which must be greater than 1.
- ConfModel: bool (input)
Whether the method uses the Configuration model.
- Rnd:
TRnd
(input) Random number generator.
- Rnd:
Return value:
- undirected graph
A Snap.py undirected, random, scale-free graph.
The following example shows how to create TUNGraph
with this function:
import snap
UGraph1 = snap.GenRndPowerLaw (9, 10)
for NI in UGraph1.Nodes():
print("node: %d, out-degree %d, in-degree %d" % (NI.GetId(), NI.GetOutDeg(), NI.GetInDeg()))
UGraph2 = snap.GenRndPowerLaw (5, 2, False)
for NI in UGraph2.Nodes():
print("node: %d, out-degree %d, in-degree %d" % (NI.GetId(), NI.GetOutDeg(), NI.GetInDeg()))