def get_structures_from_trajectory(self):
"""
Convert the coordinates in each time step to a structure(boxed molecule).
Used to construct DiffusionAnalyzer object.
Returns:
list of Structure objects
"""
structures = []
mass_to_symbol = dict(
(round(y["Atomic mass"], 1), x) for x, y in _pt_data.items())
unique_atomic_masses = np.array(self.lammps_data.atomic_masses)[:, 1]
for step in range(self.timesteps.size):
begin = step * self.natoms
end = (step + 1) * self.natoms
mol_vector_structured = \
self.trajectory[begin:end][:][["x", "y", "z"]]
new_shape = mol_vector_structured.shape + (-1, )
mol_vector = mol_vector_structured.view(
np.float64).reshape(new_shape)
coords = mol_vector.copy()
species = [
mass_to_symbol[round(unique_atomic_masses[atype - 1], 1)]
for atype in self.trajectory[begin:end][:]["atom_type"]
]
mol = Molecule(species, coords)
try:
boxed_mol = mol.get_boxed_structure(*self.box_lengths)
except ValueError as error:
print("Error: '{}' at timestep {} in the trajectory".format(
error, int(self.timesteps[step])))
structures.append(boxed_mol)
return structures
def get_structures_from_trajectory(self):
"""
Convert the coordinates in each time step to a structure(boxed molecule).
Used to construct DiffusionAnalyzer object.
Returns:
list of Structure objects
"""
lattice = Lattice([[self.box_lengths[0], 0, 0],
[0, self.box_lengths[1], 0],
[0, 0, self.box_lengths[2]]])
structures = []
mass_to_symbol = dict(
(round(y["Atomic mass"], 1), x) for x, y in _pt_data.items())
unique_atomic_masses = self.lammps_data.masses["mass"].values
for step in range(self.timesteps.size):
begin = step * self.natoms
end = (step + 1) * self.natoms
mol_vector_structured = \
self.trajectory[begin:end][:][["x", "y", "z"]]
mol_vector = np.array(mol_vector_structured.tolist())
coords = mol_vector.copy()
species = [mass_to_symbol[round(unique_atomic_masses[atype - 1], 1)]
for atype in self.trajectory[begin:end][:]["atom_type"]]
try:
structure = Structure(lattice, species, coords,
coords_are_cartesian=True)
except ValueError as error:
print("Error: '{}' at timestep {} in the trajectory".format(
error,
int(self.timesteps[step])))
structures.append(structure)
return structures
def get_structures_from_trajectory(self):
"""
Convert the coordinates in each time step to a structure(boxed molecule).
Used to construct DiffusionAnalyzer object.
Returns:
list of Structure objects
"""
structures = []
mass_to_symbol = dict(
(round(y["Atomic mass"], 1), x) for x, y in _pt_data.items())
unique_atomic_masses = np.array(self.lammps_data.atomic_masses)[:, 1]
for step in range(self.timesteps.size):
begin = step * self.natoms
end = (step + 1) * self.natoms
mol_vector_structured = \
self.trajectory[begin:end][:][["x", "y", "z"]]
new_shape = mol_vector_structured.shape + (-1,)
mol_vector = mol_vector_structured.view(np.float64).reshape(
new_shape)
coords = mol_vector.copy()
species = [mass_to_symbol[round(unique_atomic_masses[atype - 1], 1)]
for atype in self.trajectory[begin:end][:]["atom_type"]]
mol = Molecule(species, coords)
try:
boxed_mol = mol.get_boxed_structure(*self.box_lengths)
except ValueError as error:
print("Error: '{}' at timestep {} in the trajectory".format(
error,
int(self.timesteps[step])))
structures.append(boxed_mol)
return structures
def get_displacements(self):
"""
Return the initial structure and displacements for each time step.
Used to interface with the DiffusionAnalyzer.
Returns:
Structure object, numpy array of displacements
"""
lattice = Lattice([[self.box_lengths[0], 0, 0],
[0, self.box_lengths[1], 0],
[0, 0, self.box_lengths[2]]])
mass_to_symbol = dict(
(round(y["Atomic mass"], 1), x) for x, y in _pt_data.items())
unique_atomic_masses = np.array(self.lammps_data.atomic_masses)[:, 1]
frac_coords = []
for step in range(self.timesteps.size):
begin = step * self.natoms
end = (step + 1) * self.natoms
mol_vector_structured = \
self.trajectory[begin:end][:][["x", "y", "z"]]
new_shape = mol_vector_structured.shape + (-1, )
mol_vector = mol_vector_structured.view(
np.float64).reshape(new_shape)
coords = mol_vector.copy()
if step == 0:
species = [
mass_to_symbol[round(unique_atomic_masses[atype - 1], 1)]
for atype in self.trajectory[begin:end][:]["atom_type"]
]
structure = Structure(lattice,
species,
coords,
coords_are_cartesian=True)
step_frac_coords = [
lattice.get_fractional_coords(crd) for crd in coords
]
frac_coords.append(np.array(step_frac_coords)[:, None])
frac_coords = np.concatenate(frac_coords, axis=1)
dp = frac_coords[:, 1:] - frac_coords[:, :-1]
dp = dp - np.round(dp)
f_disp = np.cumsum(dp, axis=1)
disp = lattice.get_cartesian_coords(f_disp)
return structure, disp
def get_displacements(self):
"""
Return the initial structure and displacements for each time step.
Used to interface with the DiffusionAnalyzer.
Returns:
Structure object, numpy array of displacements
"""
lattice = Lattice([[self.box_lengths[0], 0, 0],
[0, self.box_lengths[1], 0],
[0, 0, self.box_lengths[2]]])
mass_to_symbol = dict(
(round(y["Atomic mass"], 1), x) for x, y in _pt_data.items())
unique_atomic_masses = np.array([d["mass"] for d in self.lammps_data.masses])
frac_coords = []
for step in range(self.timesteps.size):
begin = step * self.natoms
end = (step + 1) * self.natoms
mol_vector_structured = \
self.trajectory[begin:end][:][["x", "y", "z"]]
new_shape = mol_vector_structured.shape + (-1,)
mol_vector = mol_vector_structured.view(np.float64).reshape(
new_shape)
coords = mol_vector.copy()
if step == 0:
species = [
mass_to_symbol[round(unique_atomic_masses[atype - 1], 1)]
for atype in self.trajectory[begin:end][:]["atom_type"]]
structure = Structure(lattice, species, coords,
coords_are_cartesian=True)
step_frac_coords = [lattice.get_fractional_coords(crd)
for crd in coords]
frac_coords.append(np.array(step_frac_coords)[:, None])
frac_coords = np.concatenate(frac_coords, axis=1)
dp = frac_coords[:, 1:] - frac_coords[:, :-1]
dp = dp - np.round(dp)
f_disp = np.cumsum(dp, axis=1)
disp = lattice.get_cartesian_coords(f_disp)
return structure, disp