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import pytest
import torch
import torch_geometric.typing
from torch_geometric.typing import SparseTensor
from torch_geometric.utils import assortativity
def test_assortativity():
# Completely assortative graph:
edge_index = torch.tensor([[0, 0, 0, 1, 1, 1, 2, 2, 2, 3, 3, 3, 4, 5],
[1, 2, 3, 0, 2, 3, 0, 1, 3, 0, 1, 2, 5, 4]])
out = assortativity(edge_index)
assert pytest.approx(out, abs=1e-5) == 1.0
if torch_geometric.typing.WITH_TORCH_SPARSE:
adj = SparseTensor.from_edge_index(edge_index, sparse_sizes=[6, 6])
out = assortativity(adj)
assert pytest.approx(out, abs=1e-5) == 1.0
# Completely disassortative graph:
edge_index = torch.tensor([[0, 1, 2, 3, 4, 5, 5, 5, 5, 5],
[5, 5, 5, 5, 5, 0, 1, 2, 3, 4]])
out = assortativity(edge_index)
assert pytest.approx(out, abs=1e-5) == -1.0
if torch_geometric.typing.WITH_TORCH_SPARSE:
adj = SparseTensor.from_edge_index(edge_index, sparse_sizes=[6, 6])
out = assortativity(adj)
assert pytest.approx(out, abs=1e-5) == -1.0
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