def test_gyration_tensor_no_coords(self): a = np.array([]) g_tensor = ftmd.gyration_tensor(a, diagonalize=True) self.assertTrue( all( math.isnan(g_tensor[i, j]) for i, j in it.product(range(3), repeat=2)))
def test_gyration_tensor_vs_rog(self): a1 = np.array([[1., 1., 1.], [0., 0., 0.], [-1., -1., -1.], [-2, -2, -2]]) rog = ftmd.radius_of_gyration(a1) g_tensor = ftmd.gyration_tensor(a1, diagonalize=True) print(rog, g_tensor) #the first invariant is the rog self.assertAlmostEqual( g_tensor[0, 0] + g_tensor[1, 1] + g_tensor[2, 2], rog**2)
def test_gyration_tensor_vs_rog(self): a1 = np.array([[1., 1., 1.], [0., 0., 0.], [-1., -1., -1.], [-2, -2, -2]]) rog = ftmd.radius_of_gyration(a1) g_tensor = ftmd.gyration_tensor(a1, diagonalize=True) print(rog, g_tensor) # the first invariant is the rog self.assertAlmostEqual( g_tensor[0, 0] + g_tensor[1, 1] + g_tensor[2, 2], rog**2)
def test_gyration_tensor_diagonalize(self): a1 = np.array([[1., 1., 1.], [0., 0., 0.], [-1., -1., -1.], [-2, -2, -2]]) a2 = np.array([[1., 2., 1.], [0., 0., 0.], [-1., -1., -2.], [-12, -2, -25]]) for a in [a1, a2]: g_tensor = ftmd.gyration_tensor(a1, diagonalize=True) self.assertEqual(g_tensor[0, 1], 0) self.assertEqual(g_tensor[0, 2], 0) self.assertEqual(g_tensor[1, 2], 0) self.assertEqual(g_tensor[1, 0], 0) self.assertEqual(g_tensor[2, 0], 0) self.assertEqual(g_tensor[2, 1], 0) self.assertGreaterEqual(g_tensor[0, 0], g_tensor[1, 1]) self.assertGreaterEqual(g_tensor[1, 1], g_tensor[2, 2])
def test_gyration_tensor_no_coords(self): a = np.array([]) g_tensor = ftmd.gyration_tensor(a, diagonalize=True) self.assertTrue( all(math.isnan(g_tensor[i, j]) for i, j in it.product(range(3), repeat=2)))