torch_geometric_signed_directed.data.general.SDSBM

Functions

SDSBM(→ Tuple[scipy.sparse.spmatrix, numpy.array])

A signed directed stochastic block model graph generator from the

Module Contents

SDSBM(N: int, K: int, p: float, F: numpy.array, size_ratio: float = 1, eta: float = 0.1) → Tuple[scipy.sparse.spmatrix, numpy.array]

A signed directed stochastic block model graph generator from the MSGNN: A Spectral Graph Neural Network Based on a Novel Magnetic Signed Laplacian paper.

Arg types:

  • N (int) - Number of nodes.

  • K (int) - Number of clusters.

  • p (float) - Sparsity value, edge probability.

  • F (np.array) - The meta-graph adjacency matrix to generate edges.

  • size_ratio (float) - The communities have number of nodes multiples of each other, with the largest size_ratio times the number of nodes of the smallest. A geometric sequence is generated to denote the node size of each cluster based on the size_ratio.

  • eta (float) - Sign flip probability.

Return types:

  • a (sp.csr_matrix) - a is a sparse N by N matrix of the edges.

  • c (np.array) - c is an array of cluster membership.