def test_distance_matrix_periodic(self):
for i in range(1000):
N = 6
unit_cell = get_random_uc(1.0, np.random.randint(0, 4))
fractional = np.random.uniform(0,1,(N,3))
coordinates = unit_cell.to_cartesian(fractional)
from molmod.ext import molecules_distance_matrix
dm = molecules_distance_matrix(coordinates, unit_cell.matrix,
unit_cell.reciprocal)
for i in range(N):
for j in range(i,N):
delta = coordinates[j]-coordinates[i]
delta = unit_cell.shortest_vector(delta)
distance = np.linalg.norm(delta)
self.assertAlmostEqual(dm[i,j], distance)
def test_distances_intra_random_periodic(self):
for i in range(10):
coordinates = np.random.uniform(0, 1, (20, 3))
unit_cell = get_random_uc(5.0, np.random.randint(0, 4), 0.5)
coordinates = unit_cell.to_cartesian(
coordinates) * 3 - unit_cell.matrix.sum(axis=1)
cutoff = np.random.uniform(1, 6)
pair_search = PairSearchIntra(coordinates, cutoff, unit_cell)
self.verify_bins_intra_periodic(pair_search.bins)
distances = [(frozenset([i0, i1]), distance)
for i0, i1, delta, distance in pair_search]
self.verify_distances_intra(coordinates, cutoff, distances,
unit_cell)
def test_distances_inter_random_periodic(self):
raise SkipTest
for i in range(10):
fractional0 = np.random.uniform(0,1,(20,3))
fractional1 = np.random.uniform(0,1,(20,3))
unit_cell = get_random_uc(5.0, np.random.randint(0, 4), 0.5)
coordinates0 = unit_cell.to_cartesian(fractional0)*3-unit_cell.matrix.sum(axis=1)
coordinates1 = unit_cell.to_cartesian(fractional1)*3-unit_cell.matrix.sum(axis=1)
cutoff = np.random.uniform(1, 6)
pair_search = PairSearchInter(coordinates0, coordinates1, cutoff, unit_cell)
self.verify_bins_inter_periodic(pair_search.bins0, pair_search.bins1)
distances = [
((i0, i1), distance)
for i0, i1, delta, distance
in pair_search
]
self.verify_distances_inter(coordinates0, coordinates1, cutoff, distances, unit_cell)
def get_random_ff(self):
N = 6
mask = np.zeros((N, N), bool)
for i in range(N):
for j in range(i):
mask[i, j] = True
from molmod.ext import molecules_distance_matrix
while True:
unit_cell = get_random_uc(3.0, np.random.randint(0, 4), 0.2)
fractional = np.random.uniform(0, 1, (N, 3))
coordinates = unit_cell.to_cartesian(fractional)
if np.random.randint(0, 2):
unit_cell = None
dm = molecules_distance_matrix(coordinates)
else:
dm = molecules_distance_matrix(coordinates, unit_cell.matrix,
unit_cell.reciprocal)
if dm[mask].min() > 1.0:
break
edges = set([])
while len(edges) < 2 * N:
v1 = np.random.randint(N)
while True:
v2 = np.random.randint(N)
if v2 != v1:
break
edges.add(frozenset([v1, v2]))
edges = tuple(edges)
numbers = np.random.randint(6, 10, N)
graph = MolecularGraph(edges, numbers)
ff = ToyFF(graph, unit_cell)
return ff, coordinates, dm, mask, unit_cell