def setUp(self):
np.random.seed(0)
self.nmol = 5
self.boxvec = np.array([5,5,5])
self.rcut = 2.5
self.system = OTPBulk(self.nmol, self.boxvec, self.rcut)
pot = self.system.get_potential()
self.db = self.system.create_database()
self.m1 = self.db.addMinimum(pot.getEnergy(_x1), _x1)
self.m2 = self.db.addMinimum(pot.getEnergy(_x2), _x2)
self.m3 = self.db.addMinimum(pot.getEnergy(_x3), _x3)
self.m4 = self.db.addMinimum(pot.getEnergy(_x4), _x4)
class TestOTPBulk(unittest.TestCase):
def setUp(self):
np.random.seed(0)
self.nmol = 5
self.boxvec = np.array([5,5,5])
self.rcut = 2.5
self.system = OTPBulk(self.nmol, self.boxvec, self.rcut)
pot = self.system.get_potential()
self.db = self.system.create_database()
self.m1 = self.db.addMinimum(pot.getEnergy(_x1), _x1)
self.m2 = self.db.addMinimum(pot.getEnergy(_x2), _x2)
self.m3 = self.db.addMinimum(pot.getEnergy(_x3), _x3)
self.m4 = self.db.addMinimum(pot.getEnergy(_x4), _x4)
def test_energy(self):
self.assertAlmostEqual(self.m3.energy, -34.6758148083, 5)
self.assertAlmostEqual(self.m4.energy, -33.7606288716, 5)
def test_periodic_distance(self):
x0 = self.system.get_random_configuration()
shift = np.zeros(self.nmol*6)
for i in range(3*self.nmol):
shift[i] = self.boxvec[i%3]/2+1
x1 = x0 + shift
self.assertLess(sqrt(self.system.aatopology.distance_squared(x0,x1)),
np.linalg.norm((self.boxvec//2+1))*len(self.system.aatopology.sites))
shift = np.zeros(self.nmol*6)
for i in range(3*self.nmol):
shift[i] = -self.boxvec[i%3]
x1 = x0 + shift
self.assertLess(self.system.aatopology.distance_squared(x0,x1), 1e-8)
def test1(self):
pot = self.system.get_potential()
self.assertLess(np.linalg.norm(pot.getGradient(self.m1.coords)), .1)
self.assertLess(np.linalg.norm(pot.getGradient(self.m2.coords)), .1)
def test_random_configuration(self):
n_tests = 100
fail_count = 0
x = []
for i in range(n_tests):
x.append(self.system.get_random_configuration())
for j in range(i):
if(i == j):
continue
if (np.linalg.norm(x[i]-x[j]) < 1e-10):
fail_count += 1
print("Failing configurations:")
print(x[i])
print(x[j])
print("Difference")
print(x[i]-x[j])
print("Norm")
print(np.linalg.norm(x[i]-x[j]))
if fail_count > 0:
print("Failed {} times".format(fail_count))
self.assertEqual(fail_count, 0)
def test_distance_measure(self):
n_tests = 100
fail_count = 0
for i in range(n_tests):
x1 = self.system.get_random_configuration()
x2 = self.system.get_random_configuration()
dist1 = sqrt(self.system.aatopology.distance_squared(x1, x2))
x1at = self.system.aatopology.to_atomistic(x1)
x2at = self.system.aatopology.to_atomistic(x2)
dist2 = np.linalg.norm(x1at - x2at)
if(dist1-dist2>1e-13):
fail_count+=1
print("Failed.")
print("distance measure:", dist1)
print("atomistic cartesian distance:", dist2)
self.assertEqual(fail_count, 0)
def test_basinhopping(self):
db = self.system.create_database()
bh = self.system.get_basinhopping(db)
bh.setPrinting(ostream=None)
bh.run(5)
self.assertGreaterEqual(db.number_of_minima(), 1)
def test_double_ended_connect(self):
connect = self.system.get_double_ended_connect(self.m3, self.m4, self.db)
connect.connect()
self.assertTrue(connect.success())
