diff env/lib/python3.9/site-packages/networkx/algorithms/assortativity/tests/test_correlation.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/assortativity/tests/test_correlation.py	Mon Mar 22 18:12:50 2021 +0000
@@ -0,0 +1,76 @@
+import pytest
+
+np = pytest.importorskip("numpy")
+npt = pytest.importorskip("numpy.testing")
+scipy = pytest.importorskip("scipy")
+
+
+import networkx as nx
+from .base_test import BaseTestAttributeMixing, BaseTestDegreeMixing
+from networkx.algorithms.assortativity.correlation import attribute_ac
+
+
+class TestDegreeMixingCorrelation(BaseTestDegreeMixing):
+    def test_degree_assortativity_undirected(self):
+        r = nx.degree_assortativity_coefficient(self.P4)
+        npt.assert_almost_equal(r, -1.0 / 2, decimal=4)
+
+    def test_degree_assortativity_directed(self):
+        r = nx.degree_assortativity_coefficient(self.D)
+        npt.assert_almost_equal(r, -0.57735, decimal=4)
+
+    def test_degree_assortativity_multigraph(self):
+        r = nx.degree_assortativity_coefficient(self.M)
+        npt.assert_almost_equal(r, -1.0 / 7.0, decimal=4)
+
+    def test_degree_pearson_assortativity_undirected(self):
+        r = nx.degree_pearson_correlation_coefficient(self.P4)
+        npt.assert_almost_equal(r, -1.0 / 2, decimal=4)
+
+    def test_degree_pearson_assortativity_directed(self):
+        r = nx.degree_pearson_correlation_coefficient(self.D)
+        npt.assert_almost_equal(r, -0.57735, decimal=4)
+
+    def test_degree_pearson_assortativity_multigraph(self):
+        r = nx.degree_pearson_correlation_coefficient(self.M)
+        npt.assert_almost_equal(r, -1.0 / 7.0, decimal=4)
+
+
+class TestAttributeMixingCorrelation(BaseTestAttributeMixing):
+    def test_attribute_assortativity_undirected(self):
+        r = nx.attribute_assortativity_coefficient(self.G, "fish")
+        assert r == 6.0 / 22.0
+
+    def test_attribute_assortativity_directed(self):
+        r = nx.attribute_assortativity_coefficient(self.D, "fish")
+        assert r == 1.0 / 3.0
+
+    def test_attribute_assortativity_multigraph(self):
+        r = nx.attribute_assortativity_coefficient(self.M, "fish")
+        assert r == 1.0
+
+    def test_attribute_assortativity_coefficient(self):
+        # from "Mixing patterns in networks"
+        # fmt: off
+        a = np.array([[0.258, 0.016, 0.035, 0.013],
+                      [0.012, 0.157, 0.058, 0.019],
+                      [0.013, 0.023, 0.306, 0.035],
+                      [0.005, 0.007, 0.024, 0.016]])
+        # fmt: on
+        r = attribute_ac(a)
+        npt.assert_almost_equal(r, 0.623, decimal=3)
+
+    def test_attribute_assortativity_coefficient2(self):
+        # fmt: off
+        a = np.array([[0.18, 0.02, 0.01, 0.03],
+                      [0.02, 0.20, 0.03, 0.02],
+                      [0.01, 0.03, 0.16, 0.01],
+                      [0.03, 0.02, 0.01, 0.22]])
+        # fmt: on
+        r = attribute_ac(a)
+        npt.assert_almost_equal(r, 0.68, decimal=2)
+
+    def test_attribute_assortativity(self):
+        a = np.array([[50, 50, 0], [50, 50, 0], [0, 0, 2]])
+        r = attribute_ac(a)
+        npt.assert_almost_equal(r, 0.029, decimal=3)