def from_coordinates(cls, coordinates, labels):
"""Initialize a similarity descriptor
Arguments:
coordinates -- a Nx3 numpy array
labels -- a list with integer labels used to identify atoms of
the same type
"""
from molmod.ext import molecules_distance_matrix
distance_matrix = molecules_distance_matrix(coordinates)
return cls(distance_matrix, labels)
def from_coordinates(cls, coordinates, labels):
"""Initialize a similarity descriptor
Arguments:
coordinates -- a Nx3 numpy array
labels -- a list with integer labels used to identify atoms of
the same type
"""
from molmod.ext import molecules_distance_matrix
distance_matrix = molecules_distance_matrix(coordinates)
return cls(distance_matrix, labels)
def get_random_ff(self):
N = 6
mask = numpy.zeros((N, N), bool)
for i in xrange(N):
for j in xrange(i):
mask[i, j] = True
from molmod.ext import molecules_distance_matrix
while True:
unit_cell = UnitCell(
numpy.random.uniform(0, 3, (3, 3)),
numpy.random.randint(0, 2, 3).astype(bool),
)
fractional = numpy.random.uniform(0, 1, (N, 3))
coordinates = unit_cell.to_cartesian(fractional)
if numpy.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 = numpy.random.randint(N)
while True:
v2 = numpy.random.randint(N)
if v2 != v1:
break
edges.add(frozenset([v1, v2]))
edges = tuple(edges)
numbers = numpy.random.randint(6, 10, N)
graph = MolecularGraph(edges, numbers)
ff = ToyFF(graph, unit_cell)
return ff, coordinates, dm, mask, unit_cell
def get_random_ff(self):
N = 6
mask = numpy.zeros((N,N), bool)
for i in xrange(N):
for j in xrange(i):
mask[i,j] = True
from molmod.ext import molecules_distance_matrix
while True:
unit_cell = UnitCell(
numpy.random.uniform(0,3,(3,3)),
numpy.random.randint(0,2,3).astype(bool),
)
fractional = numpy.random.uniform(0,1,(N,3))
coordinates = unit_cell.to_cartesian(fractional)
if numpy.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 = numpy.random.randint(N)
while True:
v2 = numpy.random.randint(N)
if v2 != v1:
break
edges.add(frozenset([v1,v2]))
edges = tuple(edges)
numbers = numpy.random.randint(6, 10, N)
graph = MolecularGraph(edges, numbers)
ff = ToyFF(graph, unit_cell)
return ff, coordinates, dm, mask, unit_cell
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_distance_matrix_periodic(self):
for i in xrange(1000):
N = 6
unit_cell = UnitCell(
numpy.random.uniform(0,1,(3,3)),
numpy.random.randint(0,2,3).astype(bool),
)
fractional = numpy.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 xrange(N):
for j in xrange(i,N):
delta = coordinates[j]-coordinates[i]
delta = unit_cell.shortest_vector(delta)
distance = numpy.linalg.norm(delta)
self.assertAlmostEqual(dm[i,j], distance)
def test_distance_matrix_periodic(self):
for i in xrange(1000):
N = 6
unit_cell = UnitCell(
numpy.random.uniform(0, 1, (3, 3)),
numpy.random.randint(0, 2, 3).astype(bool),
)
fractional = numpy.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 xrange(N):
for j in xrange(i, N):
delta = coordinates[j] - coordinates[i]
delta = unit_cell.shortest_vector(delta)
distance = numpy.linalg.norm(delta)
self.assertAlmostEqual(dm[i, j], distance)
def distance_matrix(self):
"""the matrix with all atom pair distances"""
from molmod.ext import molecules_distance_matrix
return molecules_distance_matrix(self.coordinates)
def distance_matrix(self):
"""the matrix with all atom pair distances"""
from molmod.ext import molecules_distance_matrix
return molecules_distance_matrix(self.coordinates)
def distance_matrix(self):
from molmod.ext import molecules_distance_matrix
return molecules_distance_matrix(self.coordinates)
def distance_matrix(self):
from molmod.ext import molecules_distance_matrix
return molecules_distance_matrix(self.coordinates)
