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molmod/molmod
molmod/io/cml.py
CMLMoleculeLoader._get_extra
def _get_extra(self, attrs, exclude): """Read the extra properties, taking into account an exclude list""" result = {} for key in attrs.getNames(): if key not in exclude: result[str(key)] = str(attrs[key]) return result
python
def _get_extra(self, attrs, exclude): """Read the extra properties, taking into account an exclude list""" result = {} for key in attrs.getNames(): if key not in exclude: result[str(key)] = str(attrs[key]) return result
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molmod/molmod
molmod/io/fchk.py
FCHKFile._read
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python
def _read(self, filename, field_labels=None): """Read all the requested fields Arguments: | ``filename`` -- the filename of the FCHK file | ``field_labels`` -- when given, only these fields are read """ # if fields is None, all fields are read def ...
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molmod/molmod
molmod/io/fchk.py
FCHKFile._analyze
def _analyze(self): """Convert a few elementary fields into a molecule object""" if ("Atomic numbers" in self.fields) and ("Current cartesian coordinates" in self.fields): self.molecule = Molecule( self.fields["Atomic numbers"], np.reshape(self.fields["Current...
python
def _analyze(self): """Convert a few elementary fields into a molecule object""" if ("Atomic numbers" in self.fields) and ("Current cartesian coordinates" in self.fields): self.molecule = Molecule( self.fields["Atomic numbers"], np.reshape(self.fields["Current...
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molmod/molmod
molmod/io/fchk.py
FCHKFile.get_optimization_coordinates
def get_optimization_coordinates(self): """Return the coordinates of the geometries at each point in the optimization""" coor_array = self.fields.get("Opt point 1 Geometries") if coor_array is None: return [] else: return np.reshape(coor_array, (-1, len(self...
python
def get_optimization_coordinates(self): """Return the coordinates of the geometries at each point in the optimization""" coor_array = self.fields.get("Opt point 1 Geometries") if coor_array is None: return [] else: return np.reshape(coor_array, (-1, len(self...
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molmod/molmod
molmod/io/fchk.py
FCHKFile.get_optimized_molecule
def get_optimized_molecule(self): """Return a molecule object of the optimal geometry""" opt_coor = self.get_optimization_coordinates() if len(opt_coor) == 0: return None else: return Molecule( self.molecule.numbers, opt_coor[-1], ...
python
def get_optimized_molecule(self): """Return a molecule object of the optimal geometry""" opt_coor = self.get_optimization_coordinates() if len(opt_coor) == 0: return None else: return Molecule( self.molecule.numbers, opt_coor[-1], ...
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molmod/molmod
molmod/io/fchk.py
FCHKFile.get_optimization_gradients
def get_optimization_gradients(self): """Return the energy gradients of all geometries during an optimization""" grad_array = self.fields.get("Opt point 1 Gradient at each geome") if grad_array is None: return [] else: return np.reshape(grad_array, (-1, len(...
python
def get_optimization_gradients(self): """Return the energy gradients of all geometries during an optimization""" grad_array = self.fields.get("Opt point 1 Gradient at each geome") if grad_array is None: return [] else: return np.reshape(grad_array, (-1, len(...
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molmod/molmod
molmod/io/fchk.py
FCHKFile.get_hessian
def get_hessian(self): """Return the hessian""" force_const = self.fields.get("Cartesian Force Constants") if force_const is None: return None N = len(self.molecule.numbers) result = np.zeros((3*N, 3*N), float) counter = 0 for row in range(3*N): ...
python
def get_hessian(self): """Return the hessian""" force_const = self.fields.get("Cartesian Force Constants") if force_const is None: return None N = len(self.molecule.numbers) result = np.zeros((3*N, 3*N), float) counter = 0 for row in range(3*N): ...
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Return the hessian
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molmod/molmod
molmod/utils.py
ReadOnly.copy_with
def copy_with(self, **kwargs): """Return a copy with (a few) changed attributes The keyword arguments are the attributes to be replaced by new values. All other attributes are copied (or referenced) from the original object. This only works if the constructor takes all ...
python
def copy_with(self, **kwargs): """Return a copy with (a few) changed attributes The keyword arguments are the attributes to be replaced by new values. All other attributes are copied (or referenced) from the original object. This only works if the constructor takes all ...
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molmod/molmod
molmod/io/gamess.py
PunchFile._read
def _read(self, filename): """Internal routine that reads all data from the punch file.""" data = {} parsers = [ FirstDataParser(), CoordinateParser(), EnergyGradParser(), SkipApproxHessian(), HessianParser(), MassParser(), ] with open(filename) as f: ...
python
def _read(self, filename): """Internal routine that reads all data from the punch file.""" data = {} parsers = [ FirstDataParser(), CoordinateParser(), EnergyGradParser(), SkipApproxHessian(), HessianParser(), MassParser(), ] with open(filename) as f: ...
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molmod/molmod
molmod/io/gamess.py
FirstDataParser.read
def read(self, line, f, data): """See :meth:`PunchParser.read`""" self.used = True data["title"] = f.readline().strip() data["symmetry"] = f.readline().split()[0] if data["symmetry"] != "C1": raise NotImplementedError("Only C1 symmetry is supported.") symbols ...
python
def read(self, line, f, data): """See :meth:`PunchParser.read`""" self.used = True data["title"] = f.readline().strip() data["symmetry"] = f.readline().split()[0] if data["symmetry"] != "C1": raise NotImplementedError("Only C1 symmetry is supported.") symbols ...
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molmod/molmod
molmod/io/gamess.py
CoordinateParser.read
def read(self, line, f, data): """See :meth:`PunchParser.read`""" f.readline() f.readline() N = len(data["symbols"]) # if the data are already read before, just overwrite them numbers = data.get("numbers") if numbers is None: numbers = np.zeros(N, int)...
python
def read(self, line, f, data): """See :meth:`PunchParser.read`""" f.readline() f.readline() N = len(data["symbols"]) # if the data are already read before, just overwrite them numbers = data.get("numbers") if numbers is None: numbers = np.zeros(N, int)...
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molmod/molmod
molmod/io/gamess.py
EnergyGradParser.read
def read(self, line, f, data): """See :meth:`PunchParser.read`""" data["energy"] = float(f.readline().split()[1]) N = len(data["symbols"]) # if the data are already read before, just overwrite them gradient = data.get("gradient") if gradient is None: gradient ...
python
def read(self, line, f, data): """See :meth:`PunchParser.read`""" data["energy"] = float(f.readline().split()[1]) N = len(data["symbols"]) # if the data are already read before, just overwrite them gradient = data.get("gradient") if gradient is None: gradient ...
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molmod/molmod
molmod/io/gamess.py
SkipApproxHessian.read
def read(self, line, f, data): """See :meth:`PunchParser.read`""" line = f.readline() assert(line == " $HESS\n") while line != " $END\n": line = f.readline()
python
def read(self, line, f, data): """See :meth:`PunchParser.read`""" line = f.readline() assert(line == " $HESS\n") while line != " $END\n": line = f.readline()
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molmod/molmod
molmod/io/gamess.py
HessianParser.read
def read(self, line, f, data): """See :meth:`PunchParser.read`""" assert("hessian" not in data) f.readline() N = len(data["symbols"]) hessian = np.zeros((3*N, 3*N), float) tmp = hessian.ravel() counter = 0 while True: line = f.readline() ...
python
def read(self, line, f, data): """See :meth:`PunchParser.read`""" assert("hessian" not in data) f.readline() N = len(data["symbols"]) hessian = np.zeros((3*N, 3*N), float) tmp = hessian.ravel() counter = 0 while True: line = f.readline() ...
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molmod/molmod
molmod/io/gamess.py
MassParser.read
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python
def read(self, line, f, data): """See :meth:`PunchParser.read`""" N = len(data["symbols"]) masses = np.zeros(N, float) counter = 0 while counter < N: words = f.readline().split() for word in words: masses[counter] = float(word)*amu ...
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molmod/molmod
molmod/examples/003_internal_coordinates/c_ff_hessian.py
setup_hydrocarbon_ff
def setup_hydrocarbon_ff(graph): """Create a simple ForceField object for hydrocarbons based on the graph.""" # A) Define parameters. # the bond parameters: bond_params = { (6, 1): 310*kcalmol/angstrom**2, (6, 6): 220*kcalmol/angstrom**2, } # for every (a, b), also add (b, a) ...
python
def setup_hydrocarbon_ff(graph): """Create a simple ForceField object for hydrocarbons based on the graph.""" # A) Define parameters. # the bond parameters: bond_params = { (6, 1): 310*kcalmol/angstrom**2, (6, 6): 220*kcalmol/angstrom**2, } # for every (a, b), also add (b, a) ...
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molmod/molmod
molmod/examples/003_internal_coordinates/c_ff_hessian.py
HarmonicEnergyTerm.add_to_hessian
def add_to_hessian(self, coordinates, hessian): """Add the contributions of this energy term to the Hessian Arguments: | ``coordinates`` -- A numpy array with 3N Cartesian coordinates. | ``hessian`` -- A matrix for the full Hessian to which this energy ...
python
def add_to_hessian(self, coordinates, hessian): """Add the contributions of this energy term to the Hessian Arguments: | ``coordinates`` -- A numpy array with 3N Cartesian coordinates. | ``hessian`` -- A matrix for the full Hessian to which this energy ...
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molmod/molmod
molmod/examples/003_internal_coordinates/c_ff_hessian.py
ForceField.hessian
def hessian(self, coordinates): """Compute the force-field Hessian for the given coordinates. Argument: | ``coordinates`` -- A numpy array with the Cartesian atom coordinates, with shape (N,3). Returns: | ``hessian`` -- A numpy arr...
python
def hessian(self, coordinates): """Compute the force-field Hessian for the given coordinates. Argument: | ``coordinates`` -- A numpy array with the Cartesian atom coordinates, with shape (N,3). Returns: | ``hessian`` -- A numpy arr...
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molmod/molmod
molmod/symmetry.py
compute_rotsym
def compute_rotsym(molecule, graph, threshold=1e-3*angstrom): """Compute the rotational symmetry number Arguments: | ``molecule`` -- The molecule | ``graph`` -- The corresponding bond graph Optional argument: | ``threshold`` -- only when a rotation results in an rmsd be...
python
def compute_rotsym(molecule, graph, threshold=1e-3*angstrom): """Compute the rotational symmetry number Arguments: | ``molecule`` -- The molecule | ``graph`` -- The corresponding bond graph Optional argument: | ``threshold`` -- only when a rotation results in an rmsd be...
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Compute the rotational symmetry number Arguments: | ``molecule`` -- The molecule | ``graph`` -- The corresponding bond graph Optional argument: | ``threshold`` -- only when a rotation results in an rmsd below the given threshold, the rotation is...
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molmod/molmod
molmod/quaternions.py
quaternion_product
def quaternion_product(quat1, quat2): """Return the quaternion product of the two arguments""" return np.array([ quat1[0]*quat2[0] - np.dot(quat1[1:], quat2[1:]), quat1[0]*quat2[1] + quat2[0]*quat1[1] + quat1[2]*quat2[3] - quat1[3]*quat2[2], quat1[0]*quat2[2] + quat2[0]*quat1[2] + quat1[...
python
def quaternion_product(quat1, quat2): """Return the quaternion product of the two arguments""" return np.array([ quat1[0]*quat2[0] - np.dot(quat1[1:], quat2[1:]), quat1[0]*quat2[1] + quat2[0]*quat1[1] + quat1[2]*quat2[3] - quat1[3]*quat2[2], quat1[0]*quat2[2] + quat2[0]*quat1[2] + quat1[...
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molmod/molmod
molmod/quaternions.py
quaternion_rotation
def quaternion_rotation(quat, vector): """Apply the rotation represented by the quaternion to the vector Warning: This only works correctly for normalized quaternions. """ dp = np.dot(quat[1:], vector) cos = (2*quat[0]*quat[0] - 1) return np.array([ 2 * (quat[0] * (quat[2] * vector[2...
python
def quaternion_rotation(quat, vector): """Apply the rotation represented by the quaternion to the vector Warning: This only works correctly for normalized quaternions. """ dp = np.dot(quat[1:], vector) cos = (2*quat[0]*quat[0] - 1) return np.array([ 2 * (quat[0] * (quat[2] * vector[2...
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Apply the rotation represented by the quaternion to the vector Warning: This only works correctly for normalized quaternions.
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train
https://github.com/molmod/molmod/blob/a7b5b4364ed514ad4c465856c05b5eda1cb561e0/molmod/quaternions.py#L58-L69
molmod/molmod
molmod/quaternions.py
rotation_matrix_to_quaternion
def rotation_matrix_to_quaternion(rotation_matrix): """Compute the quaternion representing the rotation given by the matrix""" invert = (np.linalg.det(rotation_matrix) < 0) if invert: factor = -1 else: factor = 1 c2 = 0.25*(factor*np.trace(rotation_matrix) + 1) if c2 < 0: ...
python
def rotation_matrix_to_quaternion(rotation_matrix): """Compute the quaternion representing the rotation given by the matrix""" invert = (np.linalg.det(rotation_matrix) < 0) if invert: factor = -1 else: factor = 1 c2 = 0.25*(factor*np.trace(rotation_matrix) + 1) if c2 < 0: ...
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Compute the quaternion representing the rotation given by the matrix
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train
https://github.com/molmod/molmod/blob/a7b5b4364ed514ad4c465856c05b5eda1cb561e0/molmod/quaternions.py#L74-L98
molmod/molmod
molmod/quaternions.py
quaternion_to_rotation_matrix
def quaternion_to_rotation_matrix(quaternion): """Compute the rotation matrix representated by the quaternion""" c, x, y, z = quaternion return np.array([ [c*c + x*x - y*y - z*z, 2*x*y - 2*c*z, 2*x*z + 2*c*y ], [2*x*y + 2*c*z, c*c - x*x + y*y - z*z, 2*y*z - 2*c*x ...
python
def quaternion_to_rotation_matrix(quaternion): """Compute the rotation matrix representated by the quaternion""" c, x, y, z = quaternion return np.array([ [c*c + x*x - y*y - z*z, 2*x*y - 2*c*z, 2*x*z + 2*c*y ], [2*x*y + 2*c*z, c*c - x*x + y*y - z*z, 2*y*z - 2*c*x ...
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Compute the rotation matrix representated by the quaternion
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train
https://github.com/molmod/molmod/blob/a7b5b4364ed514ad4c465856c05b5eda1cb561e0/molmod/quaternions.py#L101-L108
molmod/molmod
molmod/vectors.py
cosine
def cosine(a, b): """Compute the cosine between two vectors The result is clipped within the range [-1, 1] """ result = np.dot(a, b) / np.linalg.norm(a) / np.linalg.norm(b) return np.clip(result, -1, 1)
python
def cosine(a, b): """Compute the cosine between two vectors The result is clipped within the range [-1, 1] """ result = np.dot(a, b) / np.linalg.norm(a) / np.linalg.norm(b) return np.clip(result, -1, 1)
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Compute the cosine between two vectors The result is clipped within the range [-1, 1]
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train
https://github.com/molmod/molmod/blob/a7b5b4364ed514ad4c465856c05b5eda1cb561e0/molmod/vectors.py#L37-L43
molmod/molmod
molmod/vectors.py
random_unit
def random_unit(size=3): """Return a random unit vector of the given dimension Optional argument: size -- the number of dimensions of the unit vector [default=3] """ while True: result = np.random.normal(0, 1, size) length = np.linalg.norm(result) if length > 1e-3:...
python
def random_unit(size=3): """Return a random unit vector of the given dimension Optional argument: size -- the number of dimensions of the unit vector [default=3] """ while True: result = np.random.normal(0, 1, size) length = np.linalg.norm(result) if length > 1e-3:...
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Return a random unit vector of the given dimension Optional argument: size -- the number of dimensions of the unit vector [default=3]
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train
https://github.com/molmod/molmod/blob/a7b5b4364ed514ad4c465856c05b5eda1cb561e0/molmod/vectors.py#L54-L64
molmod/molmod
molmod/vectors.py
random_orthonormal
def random_orthonormal(normal): """Return a random normalized vector orthogonal to the given vector""" u = normal_fns[np.argmin(np.fabs(normal))](normal) u /= np.linalg.norm(u) v = np.cross(normal, u) v /= np.linalg.norm(v) alpha = np.random.uniform(0.0, np.pi*2) return np.cos(alpha)*u + np....
python
def random_orthonormal(normal): """Return a random normalized vector orthogonal to the given vector""" u = normal_fns[np.argmin(np.fabs(normal))](normal) u /= np.linalg.norm(u) v = np.cross(normal, u) v /= np.linalg.norm(v) alpha = np.random.uniform(0.0, np.pi*2) return np.cos(alpha)*u + np....
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Return a random normalized vector orthogonal to the given vector
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train
https://github.com/molmod/molmod/blob/a7b5b4364ed514ad4c465856c05b5eda1cb561e0/molmod/vectors.py#L73-L80
molmod/molmod
molmod/vectors.py
triangle_normal
def triangle_normal(a, b, c): """Return a vector orthogonal to the given triangle Arguments: a, b, c -- three 3D numpy vectors """ normal = np.cross(a - c, b - c) norm = np.linalg.norm(normal) return normal/norm
python
def triangle_normal(a, b, c): """Return a vector orthogonal to the given triangle Arguments: a, b, c -- three 3D numpy vectors """ normal = np.cross(a - c, b - c) norm = np.linalg.norm(normal) return normal/norm
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Return a vector orthogonal to the given triangle Arguments: a, b, c -- three 3D numpy vectors
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train
https://github.com/molmod/molmod/blob/a7b5b4364ed514ad4c465856c05b5eda1cb561e0/molmod/vectors.py#L82-L90
molmod/molmod
molmod/ic.py
dot
def dot(r1, r2): """Compute the dot product Arguments: | ``r1``, ``r2`` -- two :class:`Vector3` objects (Returns a Scalar) """ if r1.size != r2.size: raise ValueError("Both arguments must have the same input size.") if r1.deriv != r2.deriv: raise ValueError("Both...
python
def dot(r1, r2): """Compute the dot product Arguments: | ``r1``, ``r2`` -- two :class:`Vector3` objects (Returns a Scalar) """ if r1.size != r2.size: raise ValueError("Both arguments must have the same input size.") if r1.deriv != r2.deriv: raise ValueError("Both...
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Compute the dot product Arguments: | ``r1``, ``r2`` -- two :class:`Vector3` objects (Returns a Scalar)
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train
https://github.com/molmod/molmod/blob/a7b5b4364ed514ad4c465856c05b5eda1cb561e0/molmod/ic.py#L283-L295
molmod/molmod
molmod/ic.py
cross
def cross(r1, r2): """Compute the cross product Arguments: | ``r1``, ``r2`` -- two :class:`Vector3` objects (Returns a Vector3) """ if r1.size != r2.size: raise ValueError("Both arguments must have the same input size.") if r1.deriv != r2.deriv: raise ValueError(...
python
def cross(r1, r2): """Compute the cross product Arguments: | ``r1``, ``r2`` -- two :class:`Vector3` objects (Returns a Vector3) """ if r1.size != r2.size: raise ValueError("Both arguments must have the same input size.") if r1.deriv != r2.deriv: raise ValueError(...
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Compute the cross product Arguments: | ``r1``, ``r2`` -- two :class:`Vector3` objects (Returns a Vector3)
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train
https://github.com/molmod/molmod/blob/a7b5b4364ed514ad4c465856c05b5eda1cb561e0/molmod/ic.py#L298-L314
molmod/molmod
molmod/ic.py
_opbend_transform_mean
def _opbend_transform_mean(rs, fn_low, deriv=0): """Compute the mean of the 3 opbends """ v = 0.0 d = np.zeros((4,3), float) dd = np.zeros((4,3,4,3), float) #loop over the 3 cyclic permutations for p in np.array([[0,1,2], [2,0,1], [1,2,0]]): opbend = _opbend_transform([rs[p[0]], rs[p...
python
def _opbend_transform_mean(rs, fn_low, deriv=0): """Compute the mean of the 3 opbends """ v = 0.0 d = np.zeros((4,3), float) dd = np.zeros((4,3,4,3), float) #loop over the 3 cyclic permutations for p in np.array([[0,1,2], [2,0,1], [1,2,0]]): opbend = _opbend_transform([rs[p[0]], rs[p...
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Compute the mean of the 3 opbends
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train
https://github.com/molmod/molmod/blob/a7b5b4364ed514ad4c465856c05b5eda1cb561e0/molmod/ic.py#L590-L636
molmod/molmod
molmod/ic.py
_bond_length_low
def _bond_length_low(r, deriv): """Similar to bond_length, but with a relative vector""" r = Vector3(3, deriv, r, (0, 1, 2)) d = r.norm() return d.results()
python
def _bond_length_low(r, deriv): """Similar to bond_length, but with a relative vector""" r = Vector3(3, deriv, r, (0, 1, 2)) d = r.norm() return d.results()
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Similar to bond_length, but with a relative vector
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train
https://github.com/molmod/molmod/blob/a7b5b4364ed514ad4c465856c05b5eda1cb561e0/molmod/ic.py#L644-L648
molmod/molmod
molmod/ic.py
_bend_cos_low
def _bend_cos_low(a, b, deriv): """Similar to bend_cos, but with relative vectors""" a = Vector3(6, deriv, a, (0, 1, 2)) b = Vector3(6, deriv, b, (3, 4, 5)) a /= a.norm() b /= b.norm() return dot(a, b).results()
python
def _bend_cos_low(a, b, deriv): """Similar to bend_cos, but with relative vectors""" a = Vector3(6, deriv, a, (0, 1, 2)) b = Vector3(6, deriv, b, (3, 4, 5)) a /= a.norm() b /= b.norm() return dot(a, b).results()
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Similar to bend_cos, but with relative vectors
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train
https://github.com/molmod/molmod/blob/a7b5b4364ed514ad4c465856c05b5eda1cb561e0/molmod/ic.py#L651-L657
molmod/molmod
molmod/ic.py
_bend_angle_low
def _bend_angle_low(a, b, deriv): """Similar to bend_angle, but with relative vectors""" result = _bend_cos_low(a, b, deriv) return _cos_to_angle(result, deriv)
python
def _bend_angle_low(a, b, deriv): """Similar to bend_angle, but with relative vectors""" result = _bend_cos_low(a, b, deriv) return _cos_to_angle(result, deriv)
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Similar to bend_angle, but with relative vectors
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train
https://github.com/molmod/molmod/blob/a7b5b4364ed514ad4c465856c05b5eda1cb561e0/molmod/ic.py#L660-L663
molmod/molmod
molmod/ic.py
_dihed_cos_low
def _dihed_cos_low(a, b, c, deriv): """Similar to dihed_cos, but with relative vectors""" a = Vector3(9, deriv, a, (0, 1, 2)) b = Vector3(9, deriv, b, (3, 4, 5)) c = Vector3(9, deriv, c, (6, 7, 8)) b /= b.norm() tmp = b.copy() tmp *= dot(a, b) a -= tmp tmp = b.copy() tmp *= dot(c...
python
def _dihed_cos_low(a, b, c, deriv): """Similar to dihed_cos, but with relative vectors""" a = Vector3(9, deriv, a, (0, 1, 2)) b = Vector3(9, deriv, b, (3, 4, 5)) c = Vector3(9, deriv, c, (6, 7, 8)) b /= b.norm() tmp = b.copy() tmp *= dot(a, b) a -= tmp tmp = b.copy() tmp *= dot(c...
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Similar to dihed_cos, but with relative vectors
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train
https://github.com/molmod/molmod/blob/a7b5b4364ed514ad4c465856c05b5eda1cb561e0/molmod/ic.py#L666-L680
molmod/molmod
molmod/ic.py
_dihed_angle_low
def _dihed_angle_low(av, bv, cv, deriv): """Similar to dihed_cos, but with relative vectors""" a = Vector3(9, deriv, av, (0, 1, 2)) b = Vector3(9, deriv, bv, (3, 4, 5)) c = Vector3(9, deriv, cv, (6, 7, 8)) b /= b.norm() tmp = b.copy() tmp *= dot(a, b) a -= tmp tmp = b.copy() tmp ...
python
def _dihed_angle_low(av, bv, cv, deriv): """Similar to dihed_cos, but with relative vectors""" a = Vector3(9, deriv, av, (0, 1, 2)) b = Vector3(9, deriv, bv, (3, 4, 5)) c = Vector3(9, deriv, cv, (6, 7, 8)) b /= b.norm() tmp = b.copy() tmp *= dot(a, b) a -= tmp tmp = b.copy() tmp ...
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Similar to dihed_cos, but with relative vectors
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train
https://github.com/molmod/molmod/blob/a7b5b4364ed514ad4c465856c05b5eda1cb561e0/molmod/ic.py#L683-L710
molmod/molmod
molmod/ic.py
_opdist_low
def _opdist_low(av, bv, cv, deriv): """Similar to opdist, but with relative vectors""" a = Vector3(9, deriv, av, (0, 1, 2)) b = Vector3(9, deriv, bv, (3, 4, 5)) c = Vector3(9, deriv, cv, (6, 7, 8)) n = cross(a, b) n /= n.norm() dist = dot(c, n) return dist.results()
python
def _opdist_low(av, bv, cv, deriv): """Similar to opdist, but with relative vectors""" a = Vector3(9, deriv, av, (0, 1, 2)) b = Vector3(9, deriv, bv, (3, 4, 5)) c = Vector3(9, deriv, cv, (6, 7, 8)) n = cross(a, b) n /= n.norm() dist = dot(c, n) return dist.results()
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Similar to opdist, but with relative vectors
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train
https://github.com/molmod/molmod/blob/a7b5b4364ed514ad4c465856c05b5eda1cb561e0/molmod/ic.py#L713-L721
molmod/molmod
molmod/ic.py
_opbend_cos_low
def _opbend_cos_low(a, b, c, deriv): """Similar to opbend_cos, but with relative vectors""" a = Vector3(9, deriv, a, (0, 1, 2)) b = Vector3(9, deriv, b, (3, 4, 5)) c = Vector3(9, deriv, c, (6, 7, 8)) n = cross(a,b) n /= n.norm() c /= c.norm() temp = dot(n,c) result = temp.copy() ...
python
def _opbend_cos_low(a, b, c, deriv): """Similar to opbend_cos, but with relative vectors""" a = Vector3(9, deriv, a, (0, 1, 2)) b = Vector3(9, deriv, b, (3, 4, 5)) c = Vector3(9, deriv, c, (6, 7, 8)) n = cross(a,b) n /= n.norm() c /= c.norm() temp = dot(n,c) result = temp.copy() ...
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Similar to opbend_cos, but with relative vectors
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train
https://github.com/molmod/molmod/blob/a7b5b4364ed514ad4c465856c05b5eda1cb561e0/molmod/ic.py#L724-L744
molmod/molmod
molmod/ic.py
_opbend_angle_low
def _opbend_angle_low(a, b, c, deriv=0): """Similar to opbend_angle, but with relative vectors""" result = _opbend_cos_low(a, b, c, deriv) sign = np.sign(np.linalg.det([a, b, c])) return _cos_to_angle(result, deriv, sign)
python
def _opbend_angle_low(a, b, c, deriv=0): """Similar to opbend_angle, but with relative vectors""" result = _opbend_cos_low(a, b, c, deriv) sign = np.sign(np.linalg.det([a, b, c])) return _cos_to_angle(result, deriv, sign)
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Similar to opbend_angle, but with relative vectors
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train
https://github.com/molmod/molmod/blob/a7b5b4364ed514ad4c465856c05b5eda1cb561e0/molmod/ic.py#L747-L751
molmod/molmod
molmod/ic.py
_cos_to_angle
def _cos_to_angle(result, deriv, sign=1): """Convert a cosine and its derivatives to an angle and its derivatives""" v = np.arccos(np.clip(result[0], -1, 1)) if deriv == 0: return v*sign, if abs(result[0]) >= 1: factor1 = 0 else: factor1 = -1.0/np.sqrt(1-result[0]**2) d =...
python
def _cos_to_angle(result, deriv, sign=1): """Convert a cosine and its derivatives to an angle and its derivatives""" v = np.arccos(np.clip(result[0], -1, 1)) if deriv == 0: return v*sign, if abs(result[0]) >= 1: factor1 = 0 else: factor1 = -1.0/np.sqrt(1-result[0]**2) d =...
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Convert a cosine and its derivatives to an angle and its derivatives
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train
https://github.com/molmod/molmod/blob/a7b5b4364ed514ad4c465856c05b5eda1cb561e0/molmod/ic.py#L759-L775
molmod/molmod
molmod/ic.py
_sin_to_angle
def _sin_to_angle(result, deriv, side=1): """Convert a sine and its derivatives to an angle and its derivatives""" v = np.arcsin(np.clip(result[0], -1, 1)) sign = side if sign == -1: if v < 0: offset = -np.pi else: offset = np.pi else: offset = 0.0 ...
python
def _sin_to_angle(result, deriv, side=1): """Convert a sine and its derivatives to an angle and its derivatives""" v = np.arcsin(np.clip(result[0], -1, 1)) sign = side if sign == -1: if v < 0: offset = -np.pi else: offset = np.pi else: offset = 0.0 ...
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train
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molmod/molmod
molmod/ic.py
Scalar.copy
def copy(self): """Return a deep copy""" result = Scalar(self.size, self.deriv) result.v = self.v if self.deriv > 0: result.d[:] = self.d[:] if self.deriv > 1: result.dd[:] = self.dd[:] return result
python
def copy(self): """Return a deep copy""" result = Scalar(self.size, self.deriv) result.v = self.v if self.deriv > 0: result.d[:] = self.d[:] if self.deriv > 1: result.dd[:] = self.dd[:] return result
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train
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molmod/molmod
molmod/ic.py
Scalar.results
def results(self): """Return the value and optionally derivative and second order derivative""" if self.deriv == 0: return self.v, if self.deriv == 1: return self.v, self.d if self.deriv == 2: return self.v, self.d, self.dd
python
def results(self): """Return the value and optionally derivative and second order derivative""" if self.deriv == 0: return self.v, if self.deriv == 1: return self.v, self.d if self.deriv == 2: return self.v, self.d, self.dd
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molmod/molmod
molmod/ic.py
Scalar.inv
def inv(self): """In place invert""" self.v = 1/self.v tmp = self.v**2 if self.deriv > 1: self.dd[:] = tmp*(2*self.v*np.outer(self.d, self.d) - self.dd) if self.deriv > 0: self.d[:] = -tmp*self.d[:]
python
def inv(self): """In place invert""" self.v = 1/self.v tmp = self.v**2 if self.deriv > 1: self.dd[:] = tmp*(2*self.v*np.outer(self.d, self.d) - self.dd) if self.deriv > 0: self.d[:] = -tmp*self.d[:]
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molmod/molmod
molmod/ic.py
Vector3.copy
def copy(self): """Return a deep copy""" result = Vector3(self.size, self.deriv) result.x.v = self.x.v result.y.v = self.y.v result.z.v = self.z.v if self.deriv > 0: result.x.d[:] = self.x.d result.y.d[:] = self.y.d result.z.d[:] = self...
python
def copy(self): """Return a deep copy""" result = Vector3(self.size, self.deriv) result.x.v = self.x.v result.y.v = self.y.v result.z.v = self.z.v if self.deriv > 0: result.x.d[:] = self.x.d result.y.d[:] = self.y.d result.z.d[:] = self...
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train
https://github.com/molmod/molmod/blob/a7b5b4364ed514ad4c465856c05b5eda1cb561e0/molmod/ic.py#L211-L225
molmod/molmod
molmod/ic.py
Vector3.norm
def norm(self): """Return a Scalar object with the norm of this vector""" result = Scalar(self.size, self.deriv) result.v = np.sqrt(self.x.v**2 + self.y.v**2 + self.z.v**2) if self.deriv > 0: result.d += self.x.v*self.x.d result.d += self.y.v*self.y.d ...
python
def norm(self): """Return a Scalar object with the norm of this vector""" result = Scalar(self.size, self.deriv) result.v = np.sqrt(self.x.v**2 + self.y.v**2 + self.z.v**2) if self.deriv > 0: result.d += self.x.v*self.x.d result.d += self.y.v*self.y.d ...
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Return a Scalar object with the norm of this vector
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train
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molmod/molmod
molmod/io/gromacs.py
GroReader._get_line
def _get_line(self): """Get a line or raise StopIteration""" line = self._f.readline() if len(line) == 0: raise StopIteration return line
python
def _get_line(self): """Get a line or raise StopIteration""" line = self._f.readline() if len(line) == 0: raise StopIteration return line
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train
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molmod/molmod
molmod/io/gromacs.py
GroReader._read_frame
def _read_frame(self): """Read one frame""" # Read the first line, ignore the title and try to get the time. The # time field is optional. line = self._get_line() pos = line.rfind("t=") if pos >= 0: time = float(line[pos+2:])*picosecond else: ...
python
def _read_frame(self): """Read one frame""" # Read the first line, ignore the title and try to get the time. The # time field is optional. line = self._get_line() pos = line.rfind("t=") if pos >= 0: time = float(line[pos+2:])*picosecond else: ...
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train
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molmod/molmod
molmod/io/gromacs.py
GroReader._skip_frame
def _skip_frame(self): """Skip one frame""" self._get_line() num_atoms = int(self._get_line()) if self.num_atoms is not None and self.num_atoms != num_atoms: raise ValueError("The number of atoms must be the same over the entire file.") for i in range(num_atoms+1): ...
python
def _skip_frame(self): """Skip one frame""" self._get_line() num_atoms = int(self._get_line()) if self.num_atoms is not None and self.num_atoms != num_atoms: raise ValueError("The number of atoms must be the same over the entire file.") for i in range(num_atoms+1): ...
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Skip one frame
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molmod/molmod
molmod/examples/003_internal_coordinates/d_dft_hessian.py
setup_ics
def setup_ics(graph): """Make a list of internal coordinates based on the graph Argument: | ``graph`` -- A Graph instance. The list of internal coordinates will include all bond lengths, all bending angles, and all dihedral angles. """ ics = [] # A) Collect all bonds. ...
python
def setup_ics(graph): """Make a list of internal coordinates based on the graph Argument: | ``graph`` -- A Graph instance. The list of internal coordinates will include all bond lengths, all bending angles, and all dihedral angles. """ ics = [] # A) Collect all bonds. ...
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molmod/molmod
molmod/examples/003_internal_coordinates/d_dft_hessian.py
compute_jacobian
def compute_jacobian(ics, coordinates): """Construct a Jacobian for the given internal and Cartesian coordinates Arguments: | ``ics`` -- A list of internal coordinate objects. | ``coordinates`` -- A numpy array with Cartesian coordinates, shape=(N,3) The ...
python
def compute_jacobian(ics, coordinates): """Construct a Jacobian for the given internal and Cartesian coordinates Arguments: | ``ics`` -- A list of internal coordinate objects. | ``coordinates`` -- A numpy array with Cartesian coordinates, shape=(N,3) The ...
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train
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molmod/molmod
molmod/examples/003_internal_coordinates/d_dft_hessian.py
InternalCoordinate.fill_jacobian_column
def fill_jacobian_column(self, jaccol, coordinates): """Fill in a column of the Jacobian. Arguments: | ``jaccol`` -- The column of Jacobian to which the result must be added. | ``coordinates`` -- A numpy array with Cartesian coordinates, ...
python
def fill_jacobian_column(self, jaccol, coordinates): """Fill in a column of the Jacobian. Arguments: | ``jaccol`` -- The column of Jacobian to which the result must be added. | ``coordinates`` -- A numpy array with Cartesian coordinates, ...
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Fill in a column of the Jacobian. Arguments: | ``jaccol`` -- The column of Jacobian to which the result must be added. | ``coordinates`` -- A numpy array with Cartesian coordinates, shape=(N,3)
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train
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molmod/molmod
molmod/similarity.py
compute_similarity
def compute_similarity(a, b, margin=1.0, cutoff=10.0): """Compute the similarity between two molecules based on their descriptors Arguments: a -- the similarity measure of the first molecule b -- the similarity measure of the second molecule margin -- the sensitivity when co...
python
def compute_similarity(a, b, margin=1.0, cutoff=10.0): """Compute the similarity between two molecules based on their descriptors Arguments: a -- the similarity measure of the first molecule b -- the similarity measure of the second molecule margin -- the sensitivity when co...
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train
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molmod/molmod
molmod/similarity.py
SimilarityDescriptor.from_molecule
def from_molecule(cls, molecule, labels=None): """Initialize a similarity descriptor Arguments: molecule -- a Molecules object labels -- a list with integer labels used to identify atoms of the same type. When not given, the atom numbers from ...
python
def from_molecule(cls, molecule, labels=None): """Initialize a similarity descriptor Arguments: molecule -- a Molecules object labels -- a list with integer labels used to identify atoms of the same type. When not given, the atom numbers from ...
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train
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molmod/molmod
molmod/similarity.py
SimilarityDescriptor.from_molecular_graph
def from_molecular_graph(cls, molecular_graph, labels=None): """Initialize a similarity descriptor Arguments: molecular_graphs -- A MolecularGraphs object labels -- a list with integer labels used to identify atoms of the same type. When not giv...
python
def from_molecular_graph(cls, molecular_graph, labels=None): """Initialize a similarity descriptor Arguments: molecular_graphs -- A MolecularGraphs object labels -- a list with integer labels used to identify atoms of the same type. When not giv...
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train
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molmod/molmod
molmod/similarity.py
SimilarityDescriptor.from_coordinates
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 im...
python
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 im...
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train
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molmod/molmod
molmod/io/chk.py
load_chk
def load_chk(filename): '''Load a checkpoint file Argument: | filename -- the file to load from The return value is a dictionary whose keys are field labels and the values can be None, string, integer, float, boolean or an array of strings, integers, booleans or floats. ...
python
def load_chk(filename): '''Load a checkpoint file Argument: | filename -- the file to load from The return value is a dictionary whose keys are field labels and the values can be None, string, integer, float, boolean or an array of strings, integers, booleans or floats. ...
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train
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molmod/molmod
molmod/io/chk.py
dump_chk
def dump_chk(filename, data): '''Dump a checkpoint file Argument: | filename -- the file to write to | data -- a dictionary whose keys are field labels and the values can be None, string, integer, float, boolean, an array/list of strings, integers, fl...
python
def dump_chk(filename, data): '''Dump a checkpoint file Argument: | filename -- the file to write to | data -- a dictionary whose keys are field labels and the values can be None, string, integer, float, boolean, an array/list of strings, integers, fl...
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train
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molmod/molmod
molmod/io/psf.py
PSFFile.clear
def clear(self): """Clear the contents of the data structure""" self.title = None self.numbers = np.zeros(0, int) self.atom_types = [] # the atom_types in the second column, used to associate ff parameters self.charges = [] # ff charges self.names = [] # a name that is un...
python
def clear(self): """Clear the contents of the data structure""" self.title = None self.numbers = np.zeros(0, int) self.atom_types = [] # the atom_types in the second column, used to associate ff parameters self.charges = [] # ff charges self.names = [] # a name that is un...
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Clear the contents of the data structure
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train
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molmod/molmod
molmod/io/psf.py
PSFFile.read_from_file
def read_from_file(self, filename): """Load a PSF file""" self.clear() with open(filename) as f: # A) check the first line line = next(f) if not line.startswith("PSF"): raise FileFormatError("Error while reading: A PSF file must start with a li...
python
def read_from_file(self, filename): """Load a PSF file""" self.clear() with open(filename) as f: # A) check the first line line = next(f) if not line.startswith("PSF"): raise FileFormatError("Error while reading: A PSF file must start with a li...
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train
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molmod/molmod
molmod/io/psf.py
PSFFile._get_name
def _get_name(self, graph, group=None): """Convert a molecular graph into a unique name This method is not sensitive to the order of the atoms in the graph. """ if group is not None: graph = graph.get_subgraph(group, normalize=True) fingerprint = graph.fingerprin...
python
def _get_name(self, graph, group=None): """Convert a molecular graph into a unique name This method is not sensitive to the order of the atoms in the graph. """ if group is not None: graph = graph.get_subgraph(group, normalize=True) fingerprint = graph.fingerprin...
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Convert a molecular graph into a unique name This method is not sensitive to the order of the atoms in the graph.
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train
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molmod/molmod
molmod/io/psf.py
PSFFile.dump
def dump(self, f): """Dump the data structure to a file-like object""" # header print("PSF", file=f) print(file=f) # title print(" 1 !NTITLE", file=f) print(self.title, file=f) print(file=f) # atoms print("% 7i !NATOM" % len(self.num...
python
def dump(self, f): """Dump the data structure to a file-like object""" # header print("PSF", file=f) print(file=f) # title print(" 1 !NTITLE", file=f) print(self.title, file=f) print(file=f) # atoms print("% 7i !NATOM" % len(self.num...
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Dump the data structure to a file-like object
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train
https://github.com/molmod/molmod/blob/a7b5b4364ed514ad4c465856c05b5eda1cb561e0/molmod/io/psf.py#L169-L254
molmod/molmod
molmod/io/psf.py
PSFFile.add_molecule
def add_molecule(self, molecule, atom_types=None, charges=None, split=True): """Add the graph of the molecule to the data structure The molecular graph is estimated from the molecular geometry based on interatomic distances. Argument: | ``molecule`` -- a Molecule...
python
def add_molecule(self, molecule, atom_types=None, charges=None, split=True): """Add the graph of the molecule to the data structure The molecular graph is estimated from the molecular geometry based on interatomic distances. Argument: | ``molecule`` -- a Molecule...
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train
https://github.com/molmod/molmod/blob/a7b5b4364ed514ad4c465856c05b5eda1cb561e0/molmod/io/psf.py#L256-L272
molmod/molmod
molmod/io/psf.py
PSFFile.add_molecular_graph
def add_molecular_graph(self, molecular_graph, atom_types=None, charges=None, split=True, molecule=None): """Add the molecular graph to the data structure Argument: | ``molecular_graph`` -- a MolecularGraph instance Optional arguments: | ``atom_types`` -- a li...
python
def add_molecular_graph(self, molecular_graph, atom_types=None, charges=None, split=True, molecule=None): """Add the molecular graph to the data structure Argument: | ``molecular_graph`` -- a MolecularGraph instance Optional arguments: | ``atom_types`` -- a li...
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Add the molecular graph to the data structure Argument: | ``molecular_graph`` -- a MolecularGraph instance Optional arguments: | ``atom_types`` -- a list with atom type strings | ``charges`` -- The net atom charges | ``split`` -- When True,...
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train
https://github.com/molmod/molmod/blob/a7b5b4364ed514ad4c465856c05b5eda1cb561e0/molmod/io/psf.py#L274-L325
molmod/molmod
molmod/io/psf.py
PSFFile.get_groups
def get_groups(self): """Return a list of groups of atom indexes Each atom in a group belongs to the same molecule or residue. """ groups = [] for a_index, m_index in enumerate(self.molecules): if m_index >= len(groups): groups.append([a_index]) ...
python
def get_groups(self): """Return a list of groups of atom indexes Each atom in a group belongs to the same molecule or residue. """ groups = [] for a_index, m_index in enumerate(self.molecules): if m_index >= len(groups): groups.append([a_index]) ...
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Return a list of groups of atom indexes Each atom in a group belongs to the same molecule or residue.
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train
https://github.com/molmod/molmod/blob/a7b5b4364ed514ad4c465856c05b5eda1cb561e0/molmod/io/psf.py#L398-L409
molmod/molmod
molmod/randomize.py
iter_halfs_bond
def iter_halfs_bond(graph): """Select a random bond (pair of atoms) that divides the molecule in two""" for atom1, atom2 in graph.edges: try: affected_atoms1, affected_atoms2 = graph.get_halfs(atom1, atom2) yield affected_atoms1, affected_atoms2, (atom1, atom2) except Gra...
python
def iter_halfs_bond(graph): """Select a random bond (pair of atoms) that divides the molecule in two""" for atom1, atom2 in graph.edges: try: affected_atoms1, affected_atoms2 = graph.get_halfs(atom1, atom2) yield affected_atoms1, affected_atoms2, (atom1, atom2) except Gra...
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train
https://github.com/molmod/molmod/blob/a7b5b4364ed514ad4c465856c05b5eda1cb561e0/molmod/randomize.py#L205-L213
molmod/molmod
molmod/randomize.py
iter_halfs_bend
def iter_halfs_bend(graph): """Select randomly two consecutive bonds that divide the molecule in two""" for atom2 in range(graph.num_vertices): neighbors = list(graph.neighbors[atom2]) for index1, atom1 in enumerate(neighbors): for atom3 in neighbors[index1+1:]: try: ...
python
def iter_halfs_bend(graph): """Select randomly two consecutive bonds that divide the molecule in two""" for atom2 in range(graph.num_vertices): neighbors = list(graph.neighbors[atom2]) for index1, atom1 in enumerate(neighbors): for atom3 in neighbors[index1+1:]: try: ...
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Select randomly two consecutive bonds that divide the molecule in two
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train
https://github.com/molmod/molmod/blob/a7b5b4364ed514ad4c465856c05b5eda1cb561e0/molmod/randomize.py#L216-L234
molmod/molmod
molmod/randomize.py
iter_halfs_double
def iter_halfs_double(graph): """Select two random non-consecutive bonds that divide the molecule in two""" edges = graph.edges for index1, (atom_a1, atom_b1) in enumerate(edges): for atom_a2, atom_b2 in edges[:index1]: try: affected_atoms1, affected_atoms2, hinge_atoms =...
python
def iter_halfs_double(graph): """Select two random non-consecutive bonds that divide the molecule in two""" edges = graph.edges for index1, (atom_a1, atom_b1) in enumerate(edges): for atom_a2, atom_b2 in edges[:index1]: try: affected_atoms1, affected_atoms2, hinge_atoms =...
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Select two random non-consecutive bonds that divide the molecule in two
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train
https://github.com/molmod/molmod/blob/a7b5b4364ed514ad4c465856c05b5eda1cb561e0/molmod/randomize.py#L237-L246
molmod/molmod
molmod/randomize.py
generate_manipulations
def generate_manipulations( molecule, bond_stretch_factor=0.15, torsion_amplitude=np.pi, bending_amplitude=0.30 ): """Generate a (complete) set of manipulations The result can be used as input for the functions 'randomize_molecule' and 'single_random_manipulation' Arguments: ...
python
def generate_manipulations( molecule, bond_stretch_factor=0.15, torsion_amplitude=np.pi, bending_amplitude=0.30 ): """Generate a (complete) set of manipulations The result can be used as input for the functions 'randomize_molecule' and 'single_random_manipulation' Arguments: ...
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train
https://github.com/molmod/molmod/blob/a7b5b4364ed514ad4c465856c05b5eda1cb561e0/molmod/randomize.py#L250-L324
molmod/molmod
molmod/randomize.py
check_nonbond
def check_nonbond(molecule, thresholds): """Check whether all nonbonded atoms are well separated. If a nonbond atom pair is found that has an interatomic distance below the given thresholds. The thresholds dictionary has the following format: {frozenset([atom_number1, atom_number2]): distance}...
python
def check_nonbond(molecule, thresholds): """Check whether all nonbonded atoms are well separated. If a nonbond atom pair is found that has an interatomic distance below the given thresholds. The thresholds dictionary has the following format: {frozenset([atom_number1, atom_number2]): distance}...
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Check whether all nonbonded atoms are well separated. If a nonbond atom pair is found that has an interatomic distance below the given thresholds. The thresholds dictionary has the following format: {frozenset([atom_number1, atom_number2]): distance} When random geometries are generated fo...
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train
https://github.com/molmod/molmod/blob/a7b5b4364ed514ad4c465856c05b5eda1cb561e0/molmod/randomize.py#L327-L350
molmod/molmod
molmod/randomize.py
randomize_molecule
def randomize_molecule(molecule, manipulations, nonbond_thresholds, max_tries=1000): """Return a randomized copy of the molecule. If no randomized molecule can be generated that survives the nonbond check after max_tries repetitions, None is returned. In case of success, the randomized molecul...
python
def randomize_molecule(molecule, manipulations, nonbond_thresholds, max_tries=1000): """Return a randomized copy of the molecule. If no randomized molecule can be generated that survives the nonbond check after max_tries repetitions, None is returned. In case of success, the randomized molecul...
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Return a randomized copy of the molecule. If no randomized molecule can be generated that survives the nonbond check after max_tries repetitions, None is returned. In case of success, the randomized molecule is returned. The original molecule is not altered.
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train
https://github.com/molmod/molmod/blob/a7b5b4364ed514ad4c465856c05b5eda1cb561e0/molmod/randomize.py#L353-L364
molmod/molmod
molmod/randomize.py
randomize_molecule_low
def randomize_molecule_low(molecule, manipulations): """Return a randomized copy of the molecule, without the nonbond check.""" manipulations = copy.copy(manipulations) shuffle(manipulations) coordinates = molecule.coordinates.copy() for manipulation in manipulations: manipulation.apply(coo...
python
def randomize_molecule_low(molecule, manipulations): """Return a randomized copy of the molecule, without the nonbond check.""" manipulations = copy.copy(manipulations) shuffle(manipulations) coordinates = molecule.coordinates.copy() for manipulation in manipulations: manipulation.apply(coo...
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Return a randomized copy of the molecule, without the nonbond check.
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train
https://github.com/molmod/molmod/blob/a7b5b4364ed514ad4c465856c05b5eda1cb561e0/molmod/randomize.py#L367-L375
molmod/molmod
molmod/randomize.py
single_random_manipulation
def single_random_manipulation(molecule, manipulations, nonbond_thresholds, max_tries=1000): """Apply a single random manipulation. If no randomized molecule can be generated that survives the nonbond check after max_tries repetitions, None is returned. In case of success, the randomized molec...
python
def single_random_manipulation(molecule, manipulations, nonbond_thresholds, max_tries=1000): """Apply a single random manipulation. If no randomized molecule can be generated that survives the nonbond check after max_tries repetitions, None is returned. In case of success, the randomized molec...
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Apply a single random manipulation. If no randomized molecule can be generated that survives the nonbond check after max_tries repetitions, None is returned. In case of success, the randomized molecule and the corresponding transformation is returned. The original molecule is not altered.
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train
https://github.com/molmod/molmod/blob/a7b5b4364ed514ad4c465856c05b5eda1cb561e0/molmod/randomize.py#L378-L390
molmod/molmod
molmod/randomize.py
single_random_manipulation_low
def single_random_manipulation_low(molecule, manipulations): """Return a randomized copy of the molecule, without the nonbond check.""" manipulation = sample(manipulations, 1)[0] coordinates = molecule.coordinates.copy() transformation = manipulation.apply(coordinates) return molecule.copy_with(coo...
python
def single_random_manipulation_low(molecule, manipulations): """Return a randomized copy of the molecule, without the nonbond check.""" manipulation = sample(manipulations, 1)[0] coordinates = molecule.coordinates.copy() transformation = manipulation.apply(coordinates) return molecule.copy_with(coo...
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train
https://github.com/molmod/molmod/blob/a7b5b4364ed514ad4c465856c05b5eda1cb561e0/molmod/randomize.py#L393-L399
molmod/molmod
molmod/randomize.py
random_dimer
def random_dimer(molecule0, molecule1, thresholds, shoot_max): """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 approxima...
python
def random_dimer(molecule0, molecule1, thresholds, shoot_max): """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 approxima...
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train
https://github.com/molmod/molmod/blob/a7b5b4364ed514ad4c465856c05b5eda1cb561e0/molmod/randomize.py#L402-L468
molmod/molmod
molmod/randomize.py
MolecularDistortion.read_from_file
def read_from_file(cls, filename): """Construct a MolecularDistortion object from a file""" with open(filename) as f: lines = list(line for line in f if line[0] != '#') r = [] t = [] for line in lines[:3]: values = list(float(word) for word in line.split()...
python
def read_from_file(cls, filename): """Construct a MolecularDistortion object from a file""" with open(filename) as f: lines = list(line for line in f if line[0] != '#') r = [] t = [] for line in lines[:3]: values = list(float(word) for word in line.split()...
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Construct a MolecularDistortion object from a file
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train
https://github.com/molmod/molmod/blob/a7b5b4364ed514ad4c465856c05b5eda1cb561e0/molmod/randomize.py#L60-L72
molmod/molmod
molmod/randomize.py
MolecularDistortion.apply
def apply(self, coordinates): """Apply this distortion to Cartesian coordinates""" for i in self.affected_atoms: coordinates[i] = self.transformation*coordinates[i]
python
def apply(self, coordinates): """Apply this distortion to Cartesian coordinates""" for i in self.affected_atoms: coordinates[i] = self.transformation*coordinates[i]
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train
https://github.com/molmod/molmod/blob/a7b5b4364ed514ad4c465856c05b5eda1cb561e0/molmod/randomize.py#L84-L87
molmod/molmod
molmod/randomize.py
MolecularDistortion.write_to_file
def write_to_file(self, filename): """Write the object to a file""" r = self.transformation.r t = self.transformation.t with open(filename, "w") as f: print("# A (random) transformation of a part of a molecule:", file=f) print("# The translation vector is in atomi...
python
def write_to_file(self, filename): """Write the object to a file""" r = self.transformation.r t = self.transformation.t with open(filename, "w") as f: print("# A (random) transformation of a part of a molecule:", file=f) print("# The translation vector is in atomi...
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Write the object to a file
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train
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molmod/molmod
molmod/randomize.py
RandomManipulation.apply
def apply(self, coordinates): """Generate, apply and return a random manipulation""" transform = self.get_transformation(coordinates) result = MolecularDistortion(self.affected_atoms, transform) result.apply(coordinates) return result
python
def apply(self, coordinates): """Generate, apply and return a random manipulation""" transform = self.get_transformation(coordinates) result = MolecularDistortion(self.affected_atoms, transform) result.apply(coordinates) return result
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Generate, apply and return a random manipulation
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train
https://github.com/molmod/molmod/blob/a7b5b4364ed514ad4c465856c05b5eda1cb561e0/molmod/randomize.py#L127-L132
molmod/molmod
molmod/randomize.py
RandomStretch.get_transformation
def get_transformation(self, coordinates): """Construct a transformation object""" atom1, atom2 = self.hinge_atoms direction = coordinates[atom1] - coordinates[atom2] direction /= np.linalg.norm(direction) direction *= np.random.uniform(-self.max_amplitude, self.max_amplitude) ...
python
def get_transformation(self, coordinates): """Construct a transformation object""" atom1, atom2 = self.hinge_atoms direction = coordinates[atom1] - coordinates[atom2] direction /= np.linalg.norm(direction) direction *= np.random.uniform(-self.max_amplitude, self.max_amplitude) ...
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Construct a transformation object
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train
https://github.com/molmod/molmod/blob/a7b5b4364ed514ad4c465856c05b5eda1cb561e0/molmod/randomize.py#L143-L150
molmod/molmod
molmod/randomize.py
RandomTorsion.get_transformation
def get_transformation(self, coordinates): """Construct a transformation object""" atom1, atom2 = self.hinge_atoms center = coordinates[atom1] axis = coordinates[atom1] - coordinates[atom2] axis /= np.linalg.norm(axis) angle = np.random.uniform(-self.max_amplitude, self.m...
python
def get_transformation(self, coordinates): """Construct a transformation object""" atom1, atom2 = self.hinge_atoms center = coordinates[atom1] axis = coordinates[atom1] - coordinates[atom2] axis /= np.linalg.norm(axis) angle = np.random.uniform(-self.max_amplitude, self.m...
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Construct a transformation object
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train
https://github.com/molmod/molmod/blob/a7b5b4364ed514ad4c465856c05b5eda1cb561e0/molmod/randomize.py#L157-L164
molmod/molmod
molmod/randomize.py
RandomBend.get_transformation
def get_transformation(self, coordinates): """Construct a transformation object""" atom1, atom2, atom3 = self.hinge_atoms center = coordinates[atom2] a = coordinates[atom1] - coordinates[atom2] b = coordinates[atom3] - coordinates[atom2] axis = np.cross(a, b) norm...
python
def get_transformation(self, coordinates): """Construct a transformation object""" atom1, atom2, atom3 = self.hinge_atoms center = coordinates[atom2] a = coordinates[atom1] - coordinates[atom2] b = coordinates[atom3] - coordinates[atom2] axis = np.cross(a, b) norm...
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Construct a transformation object
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train
https://github.com/molmod/molmod/blob/a7b5b4364ed514ad4c465856c05b5eda1cb561e0/molmod/randomize.py#L171-L185
molmod/molmod
molmod/randomize.py
RandomDoubleStretch.get_transformation
def get_transformation(self, coordinates): """Construct a transformation object""" atom1, atom2, atom3, atom4 = self.hinge_atoms a = coordinates[atom1] - coordinates[atom2] a /= np.linalg.norm(a) b = coordinates[atom3] - coordinates[atom4] b /= np.linalg.norm(b) d...
python
def get_transformation(self, coordinates): """Construct a transformation object""" atom1, atom2, atom3, atom4 = self.hinge_atoms a = coordinates[atom1] - coordinates[atom2] a /= np.linalg.norm(a) b = coordinates[atom3] - coordinates[atom4] b /= np.linalg.norm(b) d...
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Construct a transformation object
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train
https://github.com/molmod/molmod/blob/a7b5b4364ed514ad4c465856c05b5eda1cb561e0/molmod/randomize.py#L192-L202
molmod/molmod
molmod/binning.py
Binning.iter_surrounding
def iter_surrounding(self, center_key): """Iterate over all bins surrounding the given bin""" for shift in self.neighbor_indexes: key = tuple(np.add(center_key, shift).astype(int)) if self.integer_cell is not None: key = self.wrap_key(key) bin = self._...
python
def iter_surrounding(self, center_key): """Iterate over all bins surrounding the given bin""" for shift in self.neighbor_indexes: key = tuple(np.add(center_key, shift).astype(int)) if self.integer_cell is not None: key = self.wrap_key(key) bin = self._...
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Iterate over all bins surrounding the given bin
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train
https://github.com/molmod/molmod/blob/a7b5b4364ed514ad4c465856c05b5eda1cb561e0/molmod/binning.py#L94-L102
molmod/molmod
molmod/binning.py
Binning.wrap_key
def wrap_key(self, key): """Translate the key into the central cell This method is only applicable in case of a periodic system. """ return tuple(np.round( self.integer_cell.shortest_vector(key) ).astype(int))
python
def wrap_key(self, key): """Translate the key into the central cell This method is only applicable in case of a periodic system. """ return tuple(np.round( self.integer_cell.shortest_vector(key) ).astype(int))
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Translate the key into the central cell This method is only applicable in case of a periodic system.
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train
https://github.com/molmod/molmod/blob/a7b5b4364ed514ad4c465856c05b5eda1cb561e0/molmod/binning.py#L104-L111
molmod/molmod
molmod/binning.py
PairSearchBase._setup_grid
def _setup_grid(self, cutoff, unit_cell, grid): """Choose a proper grid for the binning process""" if grid is None: # automatically choose a decent grid if unit_cell is None: grid = cutoff/2.9 else: # The following would be faster, but ...
python
def _setup_grid(self, cutoff, unit_cell, grid): """Choose a proper grid for the binning process""" if grid is None: # automatically choose a decent grid if unit_cell is None: grid = cutoff/2.9 else: # The following would be faster, but ...
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Choose a proper grid for the binning process
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train
https://github.com/molmod/molmod/blob/a7b5b4364ed514ad4c465856c05b5eda1cb561e0/molmod/binning.py#L116-L152
molmod/molmod
molmod/units.py
parse_unit
def parse_unit(expression): """Evaluate a python expression string containing constants Argument: | ``expression`` -- A string containing a numerical expressions including unit conversions. In addition to the variables in this module, also the following ...
python
def parse_unit(expression): """Evaluate a python expression string containing constants Argument: | ``expression`` -- A string containing a numerical expressions including unit conversions. In addition to the variables in this module, also the following ...
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Evaluate a python expression string containing constants Argument: | ``expression`` -- A string containing a numerical expressions including unit conversions. In addition to the variables in this module, also the following shorthands are supported:
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train
https://github.com/molmod/molmod/blob/a7b5b4364ed514ad4c465856c05b5eda1cb561e0/molmod/units.py#L66-L82
thavel/synolopy
synolopy/cgi.py
PathElement.parents
def parents(self): """ Returns an simple FIFO queue with the ancestors and itself. """ q = self.__parent__.parents() q.put(self) return q
python
def parents(self): """ Returns an simple FIFO queue with the ancestors and itself. """ q = self.__parent__.parents() q.put(self) return q
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Returns an simple FIFO queue with the ancestors and itself.
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train
https://github.com/thavel/synolopy/blob/fdb23cdde693b13a59af9873f03b2afab35cb50e/synolopy/cgi.py#L56-L62
thavel/synolopy
synolopy/cgi.py
PathElement.url
def url(self): """ Returns the whole URL from the base to this node. """ path = None nodes = self.parents() while not nodes.empty(): path = urljoin(path, nodes.get().path()) return path
python
def url(self): """ Returns the whole URL from the base to this node. """ path = None nodes = self.parents() while not nodes.empty(): path = urljoin(path, nodes.get().path()) return path
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Returns the whole URL from the base to this node.
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train
https://github.com/thavel/synolopy/blob/fdb23cdde693b13a59af9873f03b2afab35cb50e/synolopy/cgi.py#L70-L78
thavel/synolopy
synolopy/cgi.py
PathElement.auth_required
def auth_required(self): """ If any ancestor required an authentication, this node needs it too. """ if self._auth: return self._auth, self return self.__parent__.auth_required()
python
def auth_required(self): """ If any ancestor required an authentication, this node needs it too. """ if self._auth: return self._auth, self return self.__parent__.auth_required()
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If any ancestor required an authentication, this node needs it too.
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train
https://github.com/thavel/synolopy/blob/fdb23cdde693b13a59af9873f03b2afab35cb50e/synolopy/cgi.py#L80-L86
molmod/molmod
molmod/molecules.py
Molecule._check_graph
def _check_graph(self, graph): """the atomic numbers must match""" if graph.num_vertices != self.size: raise TypeError("The number of vertices in the graph does not " "match the length of the atomic numbers array.") # In practice these are typically the same arrays us...
python
def _check_graph(self, graph): """the atomic numbers must match""" if graph.num_vertices != self.size: raise TypeError("The number of vertices in the graph does not " "match the length of the atomic numbers array.") # In practice these are typically the same arrays us...
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the atomic numbers must match
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train
https://github.com/molmod/molmod/blob/a7b5b4364ed514ad4c465856c05b5eda1cb561e0/molmod/molecules.py#L64-L73
molmod/molmod
molmod/molecules.py
Molecule.from_file
def from_file(cls, filename): """Construct a molecule object read from the given file. The file format is inferred from the extensions. Currently supported formats are: ``*.cml``, ``*.fchk``, ``*.pdb``, ``*.sdf``, ``*.xyz`` If a file contains more than one molecule, only the f...
python
def from_file(cls, filename): """Construct a molecule object read from the given file. The file format is inferred from the extensions. Currently supported formats are: ``*.cml``, ``*.fchk``, ``*.pdb``, ``*.sdf``, ``*.xyz`` If a file contains more than one molecule, only the f...
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Construct a molecule object read from the given file. The file format is inferred from the extensions. Currently supported formats are: ``*.cml``, ``*.fchk``, ``*.pdb``, ``*.sdf``, ``*.xyz`` If a file contains more than one molecule, only the first one is read. ...
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train
https://github.com/molmod/molmod/blob/a7b5b4364ed514ad4c465856c05b5eda1cb561e0/molmod/molecules.py#L121-L157
molmod/molmod
molmod/molecules.py
Molecule.com
def com(self): """the center of mass of the molecule""" return (self.coordinates*self.masses.reshape((-1,1))).sum(axis=0)/self.mass
python
def com(self): """the center of mass of the molecule""" return (self.coordinates*self.masses.reshape((-1,1))).sum(axis=0)/self.mass
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the center of mass of the molecule
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train
https://github.com/molmod/molmod/blob/a7b5b4364ed514ad4c465856c05b5eda1cb561e0/molmod/molecules.py#L174-L176
molmod/molmod
molmod/molecules.py
Molecule.inertia_tensor
def inertia_tensor(self): """the intertia tensor of the molecule""" result = np.zeros((3,3), float) for i in range(self.size): r = self.coordinates[i] - self.com # the diagonal term result.ravel()[::4] += self.masses[i]*(r**2).sum() # the outer pro...
python
def inertia_tensor(self): """the intertia tensor of the molecule""" result = np.zeros((3,3), float) for i in range(self.size): r = self.coordinates[i] - self.com # the diagonal term result.ravel()[::4] += self.masses[i]*(r**2).sum() # the outer pro...
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the intertia tensor of the molecule
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train
https://github.com/molmod/molmod/blob/a7b5b4364ed514ad4c465856c05b5eda1cb561e0/molmod/molecules.py#L179-L188
molmod/molmod
molmod/molecules.py
Molecule.chemical_formula
def chemical_formula(self): """the chemical formula of the molecule""" counts = {} for number in self.numbers: counts[number] = counts.get(number, 0)+1 items = [] for number, count in sorted(counts.items(), reverse=True): if count == 1: ite...
python
def chemical_formula(self): """the chemical formula of the molecule""" counts = {} for number in self.numbers: counts[number] = counts.get(number, 0)+1 items = [] for number, count in sorted(counts.items(), reverse=True): if count == 1: ite...
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the chemical formula of the molecule
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train
https://github.com/molmod/molmod/blob/a7b5b4364ed514ad4c465856c05b5eda1cb561e0/molmod/molecules.py#L191-L202
molmod/molmod
molmod/molecules.py
Molecule.set_default_masses
def set_default_masses(self): """Set self.masses based on self.numbers and periodic table.""" self.masses = np.array([periodic[n].mass for n in self.numbers])
python
def set_default_masses(self): """Set self.masses based on self.numbers and periodic table.""" self.masses = np.array([periodic[n].mass for n in self.numbers])
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Set self.masses based on self.numbers and periodic table.
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train
https://github.com/molmod/molmod/blob/a7b5b4364ed514ad4c465856c05b5eda1cb561e0/molmod/molecules.py#L204-L206
molmod/molmod
molmod/molecules.py
Molecule.set_default_symbols
def set_default_symbols(self): """Set self.symbols based on self.numbers and the periodic table.""" self.symbols = tuple(periodic[n].symbol for n in self.numbers)
python
def set_default_symbols(self): """Set self.symbols based on self.numbers and the periodic table.""" self.symbols = tuple(periodic[n].symbol for n in self.numbers)
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Set self.symbols based on self.numbers and the periodic table.
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train
https://github.com/molmod/molmod/blob/a7b5b4364ed514ad4c465856c05b5eda1cb561e0/molmod/molecules.py#L222-L224
molmod/molmod
molmod/molecules.py
Molecule.write_to_file
def write_to_file(self, filename): """Write the molecular geometry to a file. The file format is inferred from the extensions. Currently supported formats are: ``*.xyz``, ``*.cml`` Argument: | ``filename`` -- a filename """ # TODO: give all file f...
python
def write_to_file(self, filename): """Write the molecular geometry to a file. The file format is inferred from the extensions. Currently supported formats are: ``*.xyz``, ``*.cml`` Argument: | ``filename`` -- a filename """ # TODO: give all file f...
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Write the molecular geometry to a file. The file format is inferred from the extensions. Currently supported formats are: ``*.xyz``, ``*.cml`` Argument: | ``filename`` -- a filename
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train
https://github.com/molmod/molmod/blob/a7b5b4364ed514ad4c465856c05b5eda1cb561e0/molmod/molecules.py#L226-L252
molmod/molmod
molmod/molecules.py
Molecule.rmsd
def rmsd(self, other): """Compute the RMSD between two molecules. Arguments: | ``other`` -- Another molecule with the same atom numbers Return values: | ``transformation`` -- the transformation that brings 'self' into overlap ...
python
def rmsd(self, other): """Compute the RMSD between two molecules. Arguments: | ``other`` -- Another molecule with the same atom numbers Return values: | ``transformation`` -- the transformation that brings 'self' into overlap ...
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Compute the RMSD between two molecules. Arguments: | ``other`` -- Another molecule with the same atom numbers Return values: | ``transformation`` -- the transformation that brings 'self' into overlap with 'other' | ``other...
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train
https://github.com/molmod/molmod/blob/a7b5b4364ed514ad4c465856c05b5eda1cb561e0/molmod/molecules.py#L254-L276
molmod/molmod
molmod/molecules.py
Molecule.compute_rotsym
def compute_rotsym(self, threshold=1e-3*angstrom): """Compute the rotational symmetry number. Optional argument: | ``threshold`` -- only when a rotation results in an rmsd below the given threshold, the rotation is considered to transform the ...
python
def compute_rotsym(self, threshold=1e-3*angstrom): """Compute the rotational symmetry number. Optional argument: | ``threshold`` -- only when a rotation results in an rmsd below the given threshold, the rotation is considered to transform the ...
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Compute the rotational symmetry number. Optional argument: | ``threshold`` -- only when a rotation results in an rmsd below the given threshold, the rotation is considered to transform the molecule onto itself.
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train
https://github.com/molmod/molmod/blob/a7b5b4364ed514ad4c465856c05b5eda1cb561e0/molmod/molecules.py#L278-L292
molmod/molmod
molmod/io/atrj.py
SectionFile._get_current_label
def _get_current_label(self): """Get the label from the last line read""" if len(self._last) == 0: raise StopIteration return self._last[:self._last.find(":")]
python
def _get_current_label(self): """Get the label from the last line read""" if len(self._last) == 0: raise StopIteration return self._last[:self._last.find(":")]
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Get the label from the last line read
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train
https://github.com/molmod/molmod/blob/a7b5b4364ed514ad4c465856c05b5eda1cb561e0/molmod/io/atrj.py#L45-L49