def get_transformation(self, molecule):
atom1, atom2 = self.hinge_atoms
center = molecule.coordinates[atom1]
axis = molecule.coordinates[atom1] - molecule.coordinates[atom2]
axis /= numpy.linalg.norm(axis)
angle = numpy.random.uniform(-self.max_amplitude, self.max_amplitude)
return rotation_around_center(center, angle, axis)
def get_transformation(self, molecule):
atom1, atom2 = self.hinge_atoms
center = molecule.coordinates[atom1]
axis = molecule.coordinates[atom1] - molecule.coordinates[atom2]
axis /= numpy.linalg.norm(axis)
angle = numpy.random.uniform(-self.max_amplitude, self.max_amplitude)
return rotation_around_center(center, angle, axis)
def do(self):
transformation = rotation_around_center(
self.parameters.center,
math.pi,
self.parameters.normal,
True
)
for victim in context.application.cache.translated_nodes:
primitive.Transform(victim, transformation)
def test_center_ses2(self):
from molmod.ext import center_ses2
for i in xrange(1000):
close1 = numpy.random.uniform(0, 5, 3)
close1_radius = numpy.random.uniform(0, 5)
close2 = numpy.random.uniform(0, 5, 3)
close2_radius = numpy.random.uniform(0, 5)
probe = numpy.random.uniform(0, 5, 3)
center = numpy.zeros(3, float)
result = bool(
center_ses2(probe, close1, close1_radius, close2,
close2_radius, center))
check_result = ((numpy.linalg.norm(close1 - close2) >
close1_radius + close2_radius)
or (numpy.linalg.norm(close1 - close2) <
abs(close1_radius - close2_radius)))
self.assertEqual(result, check_result)
if result == False:
# test distances
self.assertAlmostEqual(numpy.linalg.norm(center - close1),
close1_radius)
self.assertAlmostEqual(numpy.linalg.norm(center - close2),
close2_radius)
# test coplanarity
mat = numpy.array([
probe - center,
probe - close1,
probe - close2,
])
self.assertAlmostEqual(numpy.linalg.det(mat), 0)
# define a rotation of 180 degrees about the close1-close2 axis
rotation = rotation_around_center(close1, numpy.pi,
close2 - close1)
new_center = rotation.vector_apply(center)
# test if the rotated center also satisfies the distances and the coplanarity
self.assertAlmostEqual(numpy.linalg.norm(new_center - close1),
close1_radius)
self.assertAlmostEqual(numpy.linalg.norm(new_center - close2),
close2_radius)
# test coplanarity
mat = numpy.array([
probe - new_center,
probe - close1,
probe - close2,
])
self.assertAlmostEqual(numpy.linalg.det(mat), 0)
# test if the center is closes to the probe than new_center
self.assert_(
numpy.linalg.norm(center -
probe) < numpy.linalg.norm(new_center -
probe))
def get_transformation(self, molecule):
atom1, atom2, atom3 = self.hinge_atoms
center = molecule.coordinates[atom2]
a = molecule.coordinates[atom1] - molecule.coordinates[atom2]
b = molecule.coordinates[atom3] - molecule.coordinates[atom2]
axis = numpy.cross(a, b)
norm = numpy.linalg.norm(axis)
if norm < 1e-5:
# We suppose that atom3 is part of the affected atoms
axis = random_orthonormal(a)
else:
axis /= numpy.linalg.norm(axis)
angle = numpy.random.uniform(-self.max_amplitude, self.max_amplitude)
return rotation_around_center(center, angle, axis)
def get_transformation(self, molecule):
atom1, atom2, atom3 = self.hinge_atoms
center = molecule.coordinates[atom2]
a = molecule.coordinates[atom1] - molecule.coordinates[atom2]
b = molecule.coordinates[atom3] - molecule.coordinates[atom2]
axis = numpy.cross(a, b)
norm = numpy.linalg.norm(axis)
if norm < 1e-5:
# We suppose that atom3 is part of the affected atoms
axis = random_orthonormal(a)
else:
axis /= numpy.linalg.norm(axis)
angle = numpy.random.uniform(-self.max_amplitude, self.max_amplitude)
return rotation_around_center(center, angle, axis)
def test_center_ses2(self):
from molmod.ext import center_ses2
for i in xrange(1000):
close1 = numpy.random.uniform(0, 5, 3)
close1_radius = numpy.random.uniform(0, 5)
close2 = numpy.random.uniform(0, 5, 3)
close2_radius = numpy.random.uniform(0, 5)
probe = numpy.random.uniform(0, 5, 3)
center = numpy.zeros(3, float)
result = bool(center_ses2(probe, close1, close1_radius, close2, close2_radius, center))
check_result = (
(numpy.linalg.norm(close1 - close2) > close1_radius + close2_radius) or
(numpy.linalg.norm(close1 - close2) < abs(close1_radius - close2_radius))
)
self.assertEqual(result, check_result)
if result == False:
# test distances
self.assertAlmostEqual(numpy.linalg.norm(center-close1), close1_radius)
self.assertAlmostEqual(numpy.linalg.norm(center-close2), close2_radius)
# test coplanarity
mat = numpy.array([
probe - center,
probe - close1,
probe - close2,
])
self.assertAlmostEqual(numpy.linalg.det(mat), 0)
# define a rotation of 180 degrees about the close1-close2 axis
rotation = rotation_around_center(close1, numpy.pi, close2-close1)
new_center = rotation.vector_apply(center)
# test if the rotated center also satisfies the distances and the coplanarity
self.assertAlmostEqual(numpy.linalg.norm(new_center-close1), close1_radius)
self.assertAlmostEqual(numpy.linalg.norm(new_center-close2), close2_radius)
# test coplanarity
mat = numpy.array([
probe - new_center,
probe - close1,
probe - close2,
])
self.assertAlmostEqual(numpy.linalg.det(mat), 0)
# test if the center is closes to the probe than new_center
self.assert_(numpy.linalg.norm(center - probe) < numpy.linalg.norm(new_center - probe))
def random_dimer(molecule0, molecule1, thresholds, shoot_max, max_tries=1000):
"""Create a random dimer.
molecule0 and molecule1 are placed in one reference frame at random relative
positions. Interatomic distances are above the thresholds. Initially a dimer
is created where one interatomic distance approximates the threshold value.
Then the molecules are given an additional separation in the range
[0,shoot_max].
thresholds has the following format:
{frozenset([atom_number1, atom_number2]): distance}
"""
# apply a random rotation to molecule1
center = numpy.zeros(3, float)
angle = numpy.random.uniform(0, 2*numpy.pi)
axis = random_unit(3)
rotation = rotation_around_center(center, angle, axis)
cor1 = numpy.dot(molecule1.coordinates, rotation.r)
# select a random atom in each molecule
atom0 = numpy.random.randint(len(molecule0.numbers))
atom1 = numpy.random.randint(len(molecule1.numbers))
# define a translation of molecule1 that brings both atoms in overlap
delta = molecule0.coordinates[atom0] - cor1[atom1]
cor1 += delta
# define a random direction
direction = random_unit(3)
cor1 += 1*direction
# move molecule1 along this direction until all intermolecular atomic
# distances are above the threshold values
threshold_mat = numpy.zeros((len(molecule0.numbers), len(molecule1.numbers)), float)
distance_mat = numpy.zeros((len(molecule0.numbers), len(molecule1.numbers)), float)
for i1, n1 in enumerate(molecule0.numbers):
for i2, n2 in enumerate(molecule1.numbers):
threshold = thresholds.get(frozenset([n1,n2]))
threshold_mat[i1,i2] = threshold**2
while True:
cor1 += 0.1*direction
distance_mat[:] = 0
for i in 0,1,2:
distance_mat += numpy.subtract.outer(molecule0.coordinates[:,i], cor1[:,i])**2
if (distance_mat > threshold_mat).all():
break
# translate over a random distance [0,shoot] along the same direction
# (if necessary repeat until no overlap is found)
while True:
cor1 += direction*numpy.random.uniform(0,shoot_max)
distance_mat[:] = 0
for i in 0,1,2:
distance_mat += numpy.subtract.outer(molecule0.coordinates[:,i], cor1[:,i])**2
if (distance_mat > threshold_mat).all():
break
# done
dimer = Molecule(
numpy.concatenate([molecule0.numbers, molecule1.numbers]),
numpy.concatenate([molecule0.coordinates, cor1])
)
dimer.direction = direction
dimer.atom0 = atom0
dimer.atom1 = atom1
return dimer
def random_dimer(molecule0, molecule1, thresholds, shoot_max, max_tries=1000):
"""Create a random dimer.
molecule0 and molecule1 are placed in one reference frame at random relative
positions. Interatomic distances are above the thresholds. Initially a dimer
is created where one interatomic distance approximates the threshold value.
Then the molecules are given an additional separation in the range
[0,shoot_max].
thresholds has the following format:
{frozenset([atom_number1, atom_number2]): distance}
"""
# apply a random rotation to molecule1
center = numpy.zeros(3, float)
angle = numpy.random.uniform(0, 2 * numpy.pi)
axis = random_unit(3)
rotation = rotation_around_center(center, angle, axis)
cor1 = numpy.dot(molecule1.coordinates, rotation.r)
# select a random atom in each molecule
atom0 = numpy.random.randint(len(molecule0.numbers))
atom1 = numpy.random.randint(len(molecule1.numbers))
# define a translation of molecule1 that brings both atoms in overlap
delta = molecule0.coordinates[atom0] - cor1[atom1]
cor1 += delta
# define a random direction
direction = random_unit(3)
cor1 += 1 * direction
# move molecule1 along this direction until all intermolecular atomic
# distances are above the threshold values
threshold_mat = numpy.zeros(
(len(molecule0.numbers), len(molecule1.numbers)), float)
distance_mat = numpy.zeros(
(len(molecule0.numbers), len(molecule1.numbers)), float)
for i1, n1 in enumerate(molecule0.numbers):
for i2, n2 in enumerate(molecule1.numbers):
threshold = thresholds.get(frozenset([n1, n2]))
threshold_mat[i1, i2] = threshold**2
while True:
cor1 += 0.1 * direction
distance_mat[:] = 0
for i in 0, 1, 2:
distance_mat += numpy.subtract.outer(molecule0.coordinates[:, i],
cor1[:, i])**2
if (distance_mat > threshold_mat).all():
break
# translate over a random distance [0,shoot] along the same direction
# (if necessary repeat until no overlap is found)
while True:
cor1 += direction * numpy.random.uniform(0, shoot_max)
distance_mat[:] = 0
for i in 0, 1, 2:
distance_mat += numpy.subtract.outer(molecule0.coordinates[:, i],
cor1[:, i])**2
if (distance_mat > threshold_mat).all():
break
# done
dimer = Molecule(numpy.concatenate([molecule0.numbers, molecule1.numbers]),
numpy.concatenate([molecule0.coordinates, cor1]))
dimer.direction = direction
dimer.atom0 = atom0
dimer.atom1 = atom1
return dimer
