def test_attribute_assortativity_coefficient(self):
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]])
r=mixing.attribute_assortativity_coefficient(a)
npt.assert_almost_equal(r,0.68,decmial=2)
def test_attribute_assortativity_coefficient(self):
# from "Mixing patterns in networks"
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]])
r=mixing.attribute_assortativity_coefficient(a)
npt.assert_almost_equal(r,0.623,decimal=3)
def test_attribute_assortativity_coefficient(self):
# from "Mixing patterns in networks"
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]])
r = mixing.attribute_assortativity_coefficient(a)
npt.assert_almost_equal(r, 0.623, decimal=3)
def test_attribute_assortativity_coefficient(self):
a=np.array([[50,50,0],[50,50,0],[0,0,2]])
r=mixing.attribute_assortativity_coefficient(a)
npt.assert_almost_equal(r,0.029,decimal=3)
def test_attribute_assortativity_coefficient(self):
a = np.array([[50, 50, 0], [50, 50, 0], [0, 0, 2]])
r = mixing.attribute_assortativity_coefficient(a)
npt.assert_almost_equal(r, 0.029, decimal=3)
def test_attribute_assortativity_coefficient(self):
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]])
r = mixing.attribute_assortativity_coefficient(a)
npt.assert_almost_equal(r, 0.68, decmial=2)
