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- import pytest
- np = pytest.importorskip("numpy")
- pytest.importorskip("scipy")
- import networkx as nx
- from networkx.generators.degree_seq import havel_hakimi_graph
- class TestBetheHessian:
- @classmethod
- def setup_class(cls):
- deg = [3, 2, 2, 1, 0]
- cls.G = havel_hakimi_graph(deg)
- cls.P = nx.path_graph(3)
- def test_bethe_hessian(self):
- "Bethe Hessian matrix"
- # fmt: off
- H = np.array([[4, -2, 0],
- [-2, 5, -2],
- [0, -2, 4]])
- # fmt: on
- permutation = [2, 0, 1]
- # Bethe Hessian gives expected form
- np.testing.assert_equal(nx.bethe_hessian_matrix(self.P, r=2).todense(), H)
- # nodelist is correctly implemented
- np.testing.assert_equal(
- nx.bethe_hessian_matrix(self.P, r=2, nodelist=permutation).todense(),
- H[np.ix_(permutation, permutation)],
- )
- # Equal to Laplacian matrix when r=1
- np.testing.assert_equal(
- nx.bethe_hessian_matrix(self.G, r=1).todense(),
- nx.laplacian_matrix(self.G).todense(),
- )
- # Correct default for the regularizer r
- np.testing.assert_equal(
- nx.bethe_hessian_matrix(self.G).todense(),
- nx.bethe_hessian_matrix(self.G, r=1.25).todense(),
- )
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