import torch
from torch_geometric.data import Data
from torch_geometric.transforms import BaseTransform
from torch_geometric.utils import to_scipy_sparse_matrix
[docs]class LargestConnectedComponents(BaseTransform):
r"""Selects the subgraph that corresponds to the
largest connected components in the graph.
Args:
num_components (int, optional): Number of largest components to keep
(default: :obj:`1`)
"""
def __init__(self, num_components: int = 1):
self.num_components = num_components
def __call__(self, data: Data) -> Data:
import numpy as np
import scipy.sparse as sp
adj = to_scipy_sparse_matrix(data.edge_index, num_nodes=data.num_nodes)
num_components, component = sp.csgraph.connected_components(adj)
if num_components <= self.num_components:
return data
_, count = np.unique(component, return_counts=True)
subset = np.in1d(component, count.argsort()[-self.num_components:])
return data.subgraph(torch.from_numpy(subset).to(torch.bool))
def __repr__(self) -> str:
return f'{self.__class__.__name__}({self.num_components})'