diff env/lib/python3.9/site-packages/networkx/algorithms/centrality/tests/test_eigenvector_centrality.py @ 0:4f3585e2f14b draft default tip

"planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"

--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/env/lib/python3.9/site-packages/networkx/algorithms/centrality/tests/test_eigenvector_centrality.py	Mon Mar 22 18:12:50 2021 +0000
@@ -0,0 +1,168 @@
+import math
+import pytest
+
+np = pytest.importorskip("numpy")
+scipy = pytest.importorskip("scipy")
+
+
+import networkx as nx
+from networkx.testing import almost_equal
+
+
+class TestEigenvectorCentrality:
+    def test_K5(self):
+        """Eigenvector centrality: K5"""
+        G = nx.complete_graph(5)
+        b = nx.eigenvector_centrality(G)
+        v = math.sqrt(1 / 5.0)
+        b_answer = dict.fromkeys(G, v)
+        for n in sorted(G):
+            assert almost_equal(b[n], b_answer[n])
+        nstart = {n: 1 for n in G}
+        b = nx.eigenvector_centrality(G, nstart=nstart)
+        for n in sorted(G):
+            assert almost_equal(b[n], b_answer[n])
+
+        b = nx.eigenvector_centrality_numpy(G)
+        for n in sorted(G):
+            assert almost_equal(b[n], b_answer[n], places=3)
+
+    def test_P3(self):
+        """Eigenvector centrality: P3"""
+        G = nx.path_graph(3)
+        b_answer = {0: 0.5, 1: 0.7071, 2: 0.5}
+        b = nx.eigenvector_centrality_numpy(G)
+        for n in sorted(G):
+            assert almost_equal(b[n], b_answer[n], places=4)
+        b = nx.eigenvector_centrality(G)
+        for n in sorted(G):
+            assert almost_equal(b[n], b_answer[n], places=4)
+
+    def test_P3_unweighted(self):
+        """Eigenvector centrality: P3"""
+        G = nx.path_graph(3)
+        b_answer = {0: 0.5, 1: 0.7071, 2: 0.5}
+        b = nx.eigenvector_centrality_numpy(G, weight=None)
+        for n in sorted(G):
+            assert almost_equal(b[n], b_answer[n], places=4)
+
+    def test_maxiter(self):
+        with pytest.raises(nx.PowerIterationFailedConvergence):
+            G = nx.path_graph(3)
+            b = nx.eigenvector_centrality(G, max_iter=0)
+
+
+class TestEigenvectorCentralityDirected:
+    @classmethod
+    def setup_class(cls):
+        G = nx.DiGraph()
+
+        edges = [
+            (1, 2),
+            (1, 3),
+            (2, 4),
+            (3, 2),
+            (3, 5),
+            (4, 2),
+            (4, 5),
+            (4, 6),
+            (5, 6),
+            (5, 7),
+            (5, 8),
+            (6, 8),
+            (7, 1),
+            (7, 5),
+            (7, 8),
+            (8, 6),
+            (8, 7),
+        ]
+
+        G.add_edges_from(edges, weight=2.0)
+        cls.G = G.reverse()
+        cls.G.evc = [
+            0.25368793,
+            0.19576478,
+            0.32817092,
+            0.40430835,
+            0.48199885,
+            0.15724483,
+            0.51346196,
+            0.32475403,
+        ]
+
+        H = nx.DiGraph()
+
+        edges = [
+            (1, 2),
+            (1, 3),
+            (2, 4),
+            (3, 2),
+            (3, 5),
+            (4, 2),
+            (4, 5),
+            (4, 6),
+            (5, 6),
+            (5, 7),
+            (5, 8),
+            (6, 8),
+            (7, 1),
+            (7, 5),
+            (7, 8),
+            (8, 6),
+            (8, 7),
+        ]
+
+        G.add_edges_from(edges)
+        cls.H = G.reverse()
+        cls.H.evc = [
+            0.25368793,
+            0.19576478,
+            0.32817092,
+            0.40430835,
+            0.48199885,
+            0.15724483,
+            0.51346196,
+            0.32475403,
+        ]
+
+    def test_eigenvector_centrality_weighted(self):
+        G = self.G
+        p = nx.eigenvector_centrality(G)
+        for (a, b) in zip(list(p.values()), self.G.evc):
+            assert almost_equal(a, b, places=4)
+
+    def test_eigenvector_centrality_weighted_numpy(self):
+        G = self.G
+        p = nx.eigenvector_centrality_numpy(G)
+        for (a, b) in zip(list(p.values()), self.G.evc):
+            assert almost_equal(a, b)
+
+    def test_eigenvector_centrality_unweighted(self):
+        G = self.H
+        p = nx.eigenvector_centrality(G)
+        for (a, b) in zip(list(p.values()), self.G.evc):
+            assert almost_equal(a, b, places=4)
+
+    def test_eigenvector_centrality_unweighted_numpy(self):
+        G = self.H
+        p = nx.eigenvector_centrality_numpy(G)
+        for (a, b) in zip(list(p.values()), self.G.evc):
+            assert almost_equal(a, b)
+
+
+class TestEigenvectorCentralityExceptions:
+    def test_multigraph(self):
+        with pytest.raises(nx.NetworkXException):
+            e = nx.eigenvector_centrality(nx.MultiGraph())
+
+    def test_multigraph_numpy(self):
+        with pytest.raises(nx.NetworkXException):
+            e = nx.eigenvector_centrality_numpy(nx.MultiGraph())
+
+    def test_empty(self):
+        with pytest.raises(nx.NetworkXException):
+            e = nx.eigenvector_centrality(nx.Graph())
+
+    def test_empty_numpy(self):
+        with pytest.raises(nx.NetworkXException):
+            e = nx.eigenvector_centrality_numpy(nx.Graph())