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import pytest
import torch
import torch_geometric.typing
from torch_geometric.typing import SparseTensor
from torch_geometric.utils import homophily
def test_homophily():
edge_index = torch.tensor([[0, 1, 2, 3], [1, 2, 0, 4]])
y = torch.tensor([0, 0, 0, 0, 1])
batch = torch.tensor([0, 0, 0, 1, 1])
row, col = edge_index
if torch_geometric.typing.WITH_TORCH_SPARSE:
adj = SparseTensor(row=row, col=col, sparse_sizes=(5, 5))
method = 'edge'
assert pytest.approx(homophily(edge_index, y, method=method)) == 0.75
if torch_geometric.typing.WITH_TORCH_SPARSE:
assert pytest.approx(homophily(adj, y, method=method)) == 0.75
assert homophily(edge_index, y, batch, method).tolist() == [1., 0.]
method = 'node'
assert pytest.approx(homophily(edge_index, y, method=method)) == 0.6
if torch_geometric.typing.WITH_TORCH_SPARSE:
assert pytest.approx(homophily(adj, y, method=method)) == 0.6
assert homophily(edge_index, y, batch, method).tolist() == [1., 0.]
method = 'edge_insensitive'
assert pytest.approx(homophily(edge_index, y, method=method)) == 0.1999999
if torch_geometric.typing.WITH_TORCH_SPARSE:
assert pytest.approx(homophily(adj, y, method=method)) == 0.1999999
assert homophily(edge_index, y, batch, method).tolist() == [0., 0.]
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