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- """
- Threshold Graphs
- ================
- """
- import pytest
- import networkx as nx
- import networkx.algorithms.threshold as nxt
- from networkx.algorithms.isomorphism.isomorph import graph_could_be_isomorphic
- cnlti = nx.convert_node_labels_to_integers
- class TestGeneratorThreshold:
- def test_threshold_sequence_graph_test(self):
- G = nx.star_graph(10)
- assert nxt.is_threshold_graph(G)
- assert nxt.is_threshold_sequence([d for n, d in G.degree()])
- G = nx.complete_graph(10)
- assert nxt.is_threshold_graph(G)
- assert nxt.is_threshold_sequence([d for n, d in G.degree()])
- deg = [3, 2, 2, 1, 1, 1]
- assert not nxt.is_threshold_sequence(deg)
- deg = [3, 2, 2, 1]
- assert nxt.is_threshold_sequence(deg)
- G = nx.generators.havel_hakimi_graph(deg)
- assert nxt.is_threshold_graph(G)
- def test_creation_sequences(self):
- deg = [3, 2, 2, 1]
- G = nx.generators.havel_hakimi_graph(deg)
- with pytest.raises(ValueError):
- nxt.creation_sequence(deg, with_labels=True, compact=True)
- cs0 = nxt.creation_sequence(deg)
- H0 = nxt.threshold_graph(cs0)
- assert "".join(cs0) == "ddid"
- cs1 = nxt.creation_sequence(deg, with_labels=True)
- H1 = nxt.threshold_graph(cs1)
- assert cs1 == [(1, "d"), (2, "d"), (3, "i"), (0, "d")]
- cs2 = nxt.creation_sequence(deg, compact=True)
- H2 = nxt.threshold_graph(cs2)
- assert cs2 == [2, 1, 1]
- assert "".join(nxt.uncompact(cs2)) == "ddid"
- assert graph_could_be_isomorphic(H0, G)
- assert graph_could_be_isomorphic(H0, H1)
- assert graph_could_be_isomorphic(H0, H2)
- def test_make_compact(self):
- assert nxt.make_compact(["d", "d", "d", "i", "d", "d"]) == [3, 1, 2]
- assert nxt.make_compact([3, 1, 2]) == [3, 1, 2]
- assert pytest.raises(TypeError, nxt.make_compact, [3.0, 1.0, 2.0])
- def test_uncompact(self):
- assert nxt.uncompact([3, 1, 2]) == ["d", "d", "d", "i", "d", "d"]
- assert nxt.uncompact(["d", "d", "i", "d"]) == ["d", "d", "i", "d"]
- assert nxt.uncompact(
- nxt.uncompact([(1, "d"), (2, "d"), (3, "i"), (0, "d")])
- ) == nxt.uncompact([(1, "d"), (2, "d"), (3, "i"), (0, "d")])
- assert pytest.raises(TypeError, nxt.uncompact, [3.0, 1.0, 2.0])
- def test_creation_sequence_to_weights(self):
- assert nxt.creation_sequence_to_weights([3, 1, 2]) == [
- 0.5,
- 0.5,
- 0.5,
- 0.25,
- 0.75,
- 0.75,
- ]
- assert pytest.raises(
- TypeError, nxt.creation_sequence_to_weights, [3.0, 1.0, 2.0]
- )
- def test_weights_to_creation_sequence(self):
- deg = [3, 2, 2, 1]
- with pytest.raises(ValueError):
- nxt.weights_to_creation_sequence(deg, with_labels=True, compact=True)
- assert nxt.weights_to_creation_sequence(deg, with_labels=True) == [
- (3, "d"),
- (1, "d"),
- (2, "d"),
- (0, "d"),
- ]
- assert nxt.weights_to_creation_sequence(deg, compact=True) == [4]
- def test_find_alternating_4_cycle(self):
- G = nx.Graph()
- G.add_edge(1, 2)
- assert not nxt.find_alternating_4_cycle(G)
- def test_shortest_path(self):
- deg = [3, 2, 2, 1]
- G = nx.generators.havel_hakimi_graph(deg)
- cs1 = nxt.creation_sequence(deg, with_labels=True)
- for n, m in [(3, 0), (0, 3), (0, 2), (0, 1), (1, 3), (3, 1), (1, 2), (2, 3)]:
- assert nxt.shortest_path(cs1, n, m) == nx.shortest_path(G, n, m)
- spl = nxt.shortest_path_length(cs1, 3)
- spl2 = nxt.shortest_path_length([t for v, t in cs1], 2)
- assert spl == spl2
- spld = {}
- for j, pl in enumerate(spl):
- n = cs1[j][0]
- spld[n] = pl
- assert spld == nx.single_source_shortest_path_length(G, 3)
- assert nxt.shortest_path(["d", "d", "d", "i", "d", "d"], 1, 2) == [1, 2]
- assert nxt.shortest_path([3, 1, 2], 1, 2) == [1, 2]
- assert pytest.raises(TypeError, nxt.shortest_path, [3.0, 1.0, 2.0], 1, 2)
- assert pytest.raises(ValueError, nxt.shortest_path, [3, 1, 2], "a", 2)
- assert pytest.raises(ValueError, nxt.shortest_path, [3, 1, 2], 1, "b")
- assert nxt.shortest_path([3, 1, 2], 1, 1) == [1]
- def test_shortest_path_length(self):
- assert nxt.shortest_path_length([3, 1, 2], 1) == [1, 0, 1, 2, 1, 1]
- assert nxt.shortest_path_length(["d", "d", "d", "i", "d", "d"], 1) == [
- 1,
- 0,
- 1,
- 2,
- 1,
- 1,
- ]
- assert nxt.shortest_path_length(("d", "d", "d", "i", "d", "d"), 1) == [
- 1,
- 0,
- 1,
- 2,
- 1,
- 1,
- ]
- assert pytest.raises(TypeError, nxt.shortest_path, [3.0, 1.0, 2.0], 1)
- def test_random_threshold_sequence(self):
- assert len(nxt.random_threshold_sequence(10, 0.5)) == 10
- assert nxt.random_threshold_sequence(10, 0.5, seed=42) == [
- "d",
- "i",
- "d",
- "d",
- "d",
- "i",
- "i",
- "i",
- "d",
- "d",
- ]
- assert pytest.raises(ValueError, nxt.random_threshold_sequence, 10, 1.5)
- def test_right_d_threshold_sequence(self):
- assert nxt.right_d_threshold_sequence(3, 2) == ["d", "i", "d"]
- assert pytest.raises(ValueError, nxt.right_d_threshold_sequence, 2, 3)
- def test_left_d_threshold_sequence(self):
- assert nxt.left_d_threshold_sequence(3, 2) == ["d", "i", "d"]
- assert pytest.raises(ValueError, nxt.left_d_threshold_sequence, 2, 3)
- def test_weights_thresholds(self):
- wseq = [3, 4, 3, 3, 5, 6, 5, 4, 5, 6]
- cs = nxt.weights_to_creation_sequence(wseq, threshold=10)
- wseq = nxt.creation_sequence_to_weights(cs)
- cs2 = nxt.weights_to_creation_sequence(wseq)
- assert cs == cs2
- wseq = nxt.creation_sequence_to_weights(nxt.uncompact([3, 1, 2, 3, 3, 2, 3]))
- assert wseq == [
- s * 0.125 for s in [4, 4, 4, 3, 5, 5, 2, 2, 2, 6, 6, 6, 1, 1, 7, 7, 7]
- ]
- wseq = nxt.creation_sequence_to_weights([3, 1, 2, 3, 3, 2, 3])
- assert wseq == [
- s * 0.125 for s in [4, 4, 4, 3, 5, 5, 2, 2, 2, 6, 6, 6, 1, 1, 7, 7, 7]
- ]
- wseq = nxt.creation_sequence_to_weights(list(enumerate("ddidiiidididi")))
- assert wseq == [s * 0.1 for s in [5, 5, 4, 6, 3, 3, 3, 7, 2, 8, 1, 9, 0]]
- wseq = nxt.creation_sequence_to_weights("ddidiiidididi")
- assert wseq == [s * 0.1 for s in [5, 5, 4, 6, 3, 3, 3, 7, 2, 8, 1, 9, 0]]
- wseq = nxt.creation_sequence_to_weights("ddidiiidididid")
- ws = [s / 12 for s in [6, 6, 5, 7, 4, 4, 4, 8, 3, 9, 2, 10, 1, 11]]
- assert sum(abs(c - d) for c, d in zip(wseq, ws)) < 1e-14
- def test_finding_routines(self):
- G = nx.Graph({1: [2], 2: [3], 3: [4], 4: [5], 5: [6]})
- G.add_edge(2, 4)
- G.add_edge(2, 5)
- G.add_edge(2, 7)
- G.add_edge(3, 6)
- G.add_edge(4, 6)
- # Alternating 4 cycle
- assert nxt.find_alternating_4_cycle(G) == [1, 2, 3, 6]
- # Threshold graph
- TG = nxt.find_threshold_graph(G)
- assert nxt.is_threshold_graph(TG)
- assert sorted(TG.nodes()) == [1, 2, 3, 4, 5, 7]
- cs = nxt.creation_sequence(dict(TG.degree()), with_labels=True)
- assert nxt.find_creation_sequence(G) == cs
- def test_fast_versions_properties_threshold_graphs(self):
- cs = "ddiiddid"
- G = nxt.threshold_graph(cs)
- assert nxt.density("ddiiddid") == nx.density(G)
- assert sorted(nxt.degree_sequence(cs)) == sorted(d for n, d in G.degree())
- ts = nxt.triangle_sequence(cs)
- assert ts == list(nx.triangles(G).values())
- assert sum(ts) // 3 == nxt.triangles(cs)
- c1 = nxt.cluster_sequence(cs)
- c2 = list(nx.clustering(G).values())
- assert sum(abs(c - d) for c, d in zip(c1, c2)) == pytest.approx(0, abs=1e-7)
- b1 = nx.betweenness_centrality(G).values()
- b2 = nxt.betweenness_sequence(cs)
- assert sum(abs(c - d) for c, d in zip(b1, b2)) < 1e-14
- assert nxt.eigenvalues(cs) == [0, 1, 3, 3, 5, 7, 7, 8]
- # Degree Correlation
- assert abs(nxt.degree_correlation(cs) + 0.593038821954) < 1e-12
- assert nxt.degree_correlation("diiiddi") == -0.8
- assert nxt.degree_correlation("did") == -1.0
- assert nxt.degree_correlation("ddd") == 1.0
- assert nxt.eigenvalues("dddiii") == [0, 0, 0, 0, 3, 3]
- assert nxt.eigenvalues("dddiiid") == [0, 1, 1, 1, 4, 4, 7]
- def test_tg_creation_routines(self):
- s = nxt.left_d_threshold_sequence(5, 7)
- s = nxt.right_d_threshold_sequence(5, 7)
- s1 = nxt.swap_d(s, 1.0, 1.0)
- s1 = nxt.swap_d(s, 1.0, 1.0, seed=1)
- def test_eigenvectors(self):
- np = pytest.importorskip("numpy")
- eigenval = np.linalg.eigvals
- pytest.importorskip("scipy")
- cs = "ddiiddid"
- G = nxt.threshold_graph(cs)
- (tgeval, tgevec) = nxt.eigenvectors(cs)
- np.testing.assert_allclose([np.dot(lv, lv) for lv in tgevec], 1.0, rtol=1e-9)
- lapl = nx.laplacian_matrix(G)
- def test_create_using(self):
- cs = "ddiiddid"
- G = nxt.threshold_graph(cs)
- assert pytest.raises(
- nx.exception.NetworkXError,
- nxt.threshold_graph,
- cs,
- create_using=nx.DiGraph(),
- )
- MG = nxt.threshold_graph(cs, create_using=nx.MultiGraph())
- assert sorted(MG.edges()) == sorted(G.edges())
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