GetInEgonetSub

GetInEgonetSub(NId, H, N=2, P=- 1.0)

A graph method that returns a sampled H hop in-ego network of the node NId. A sampled H hop in-ego network includes the node NId, a sample of its in-neighbours and edges that connect them to the origin node, then samples of all their in-neighbours and edges and so on until H hop neighbours. The sampling is specified by the N and P parameters. If P is -1.0, then N determines the maximum number of neighbours added to the in-ego network for each node. If P is different than -1.0, then it determines the percentage of added neighbours. For example, if P is 0.5, then half of the neighbours will be added to the in-ego network for each node. The neighbours are selected randomly.

Parameters:

• NId: int

  Id of the center node of the ego network.

• H: int

  The number of hops for the ego network.

• (optional) N: int

  The maximum number of neighbours selected. Default value is 2. It has no effect, is P is different from -1.0.

• (optional) P: float

  The percentage of neighbours selected, between 0.0 and 1.0. Default value is -1.0, which means that the parameter has no effect.

Return value:

• graph

  A graph of the same type as the input graph, containing the in-ego network for NId.

The following example shows how to create a subgraph for nodes in TNGraph, TUNGraph, and TNEANet:

import snap

NGraph = snap.GenRndGnm(snap.TNGraph, 100, 1000)
InEgonet = NGraph.GetInEgonetSub(0, 2, 3)

UGraph = snap.GenRndGnm(snap.TUNGraph, 100, 1000)
InEgonet = UGraph.GetInEgonetSub(3, 1, 3)

Network = snap.GenRndGnm(snap.TNEANet, 100, 1000)
InEgonet = Network.GetInEgonetSub(10, 3, 0, 0.4)