def collect_h5md_file(self, file_name="dump.h5", cwd=None):
"""
Args:
file_name:
cwd:
Returns:
"""
prism = UnfoldingPrism(self.structure.cell, digits=15)
if np.matrix.trace(prism.R) != 3:
raise RuntimeError("The Lammps output will not be mapped back to pyiron correctly.")
file_name = self.job_file_name(file_name=file_name, cwd=cwd)
with h5py.File(file_name, mode="r", libver="latest", swmr=True) as h5md:
positions = [
pos_i.tolist() for pos_i in h5md["/particles/all/position/value"]
]
time = [time_i.tolist() for time_i in h5md["/particles/all/position/step"]]
forces = [for_i.tolist() for for_i in h5md["/particles/all/force/value"]]
# following the explanation at: http://nongnu.org/h5md/h5md.html
cell = [
np.eye(3) * np.array(cell_i.tolist())
for cell_i in h5md["/particles/all/box/edges/value"]
]
indices = [indices_i.tolist() for indices_i in h5md["/particles/all/indices/value"]]
with self.project_hdf5.open("output/generic") as h5_file:
h5_file["forces"] = np.array(forces)
h5_file["positions"] = np.array(positions)
h5_file["time"] = np.array(time)
h5_file["cells"] = cell
h5_file["indices"] = self.remap_indices(indices)
def _get_rotation_matrix(self, pressure):
"""
Args:
pressure:
Returns:
"""
if self.structure is not None:
if self._prism is None:
self._prism = UnfoldingPrism(self.structure.cell)
self.structure = self._modify_structure_to_allow_requested_deformation(
pressure=pressure,
structure=self.structure,
prism=self._prism
)
rotation_matrix = self._prism.R
else:
warnings.warn(
"No structure set, can not validate the simulation cell!"
)
rotation_matrix = None
return rotation_matrix
def _get_steinhardt_parameter(cell,
positions,
cutoff=3.50,
n_clusters=2,
q=[4, 6]):
sys = pc.System()
prism = UnfoldingPrism(cell, digits=15)
xhi, yhi, zhi, xy, xz, yz = prism.get_lammps_prism_str()
coords = [prism.pos_to_lammps(position) for position in positions]
sys.box = [[0.0, float(xhi)], [0.0, float(yhi)], [0.0, float(zhi)]]
sys.atoms = [pc.Atom(pos=p, id=i) for i, p in enumerate(coords)]
sys.find_neighbors(method='cutoff', cutoff=cutoff)
sys.calculate_q(q, averaged=True)
sysq = sys.get_qvals(q, averaged=True)
cl = cluster.KMeans(n_clusters=n_clusters)
ind = cl.fit(list(zip(*sysq))).labels_ == 0
return sysq, ind
def interactive_structure_setter(self, structure):
self._interactive_lib_command('clear')
self._set_selective_dynamics()
self._interactive_lib_command('units ' + self.input.control['units'])
self._interactive_lib_command('dimension ' + str(self.input.control['dimension']))
self._interactive_lib_command('boundary ' + self.input.control['boundary'])
self._interactive_lib_command('atom_style ' + self.input.control['atom_style'])
self._interactive_lib_command("atom_modify map array")
self._interactive_prism = UnfoldingPrism(structure.cell)
if np.matrix.trace(self._interactive_prism.R) != 3:
print('Warning: setting upper trangular matrix might slow down the calculation')
xhi, yhi, zhi, xy, xz, yz = self._interactive_prism.get_lammps_prism()
if self._interactive_prism.is_skewed():
self._interactive_lib_command('region 1 prism' +
' 0.0 ' + str(xhi) + ' 0.0 ' + str(yhi) + ' 0.0 ' + str(zhi) +
' ' + str(xy) + ' ' + str(xz) + ' ' + str(yz) + ' units box')
else:
self._interactive_lib_command('region 1 block' +
' 0.0 ' + str(xhi) + ' 0.0 ' + str(yhi) + ' 0.0 ' + str(zhi) + ' units box')
el_struct_lst = self.structure.get_species_symbols()
el_obj_lst = self.structure.get_species_objects()
el_eam_lst = self.input.potential.get_element_lst()
self._interactive_lib_command('create_box ' + str(len(el_eam_lst)) + ' 1')
el_dict = {}
for id_eam, el_eam in enumerate(el_eam_lst):
if el_eam in el_struct_lst:
id_el = list(el_struct_lst).index(el_eam)
el = el_obj_lst[id_el]
el_dict[el] = id_eam + 1
self._interactive_lib_command('mass {0:3d} {1:f}'.format(id_eam + 1, el.AtomicMass))
else:
self._interactive_lib_command('mass {0:3d} {1:f}'.format(id_eam + 1, 1.00))
self._interactive_lib_command('create_atoms 1 random ' + str(len(structure)) + ' 12345 1')
positions = structure.positions.flatten()
elem_all = np.array([el_dict[el] for el in structure.get_chemical_elements()])
if self.server.run_mode.interactive_non_modal:
self._interactive_library.scatter_atoms("x", 1, 3, positions)
self._interactive_library.scatter_atoms('type', 0, 1, elem_all)
else:
self._interactive_library.scatter_atoms("x", 1, 3, (len(positions) * c_double)(*positions))
self._interactive_library.scatter_atoms('type', 0, 1, (len(elem_all) * c_int)(*elem_all))
self._interactive_lib_command('change_box all remap')
self._interactive_lammps_input()
self._interactive_set_potential()
def interactive_cells_setter(self, cell):
self._interactive_prism = UnfoldingPrism(cell)
lx, ly, lz, xy, xz, yz = self._interactive_prism.get_lammps_prism()
if np.matrix.trace(self._interactive_prism.R) != 3:
print('Warning: setting upper trangular matrix might slow down the calculation')
if abs(xy) + abs(xz) + abs(yz) > 1.0e-6:
if self.structure._is_scaled:
self._interactive_lib_command(
'change_box all x final 0 %f y final 0 %f z final 0 %f \
xy final %f xz final %f yz final %f triclinic remap units box' % (lx, ly, lz, xy, xz, yz))
else:
self._interactive_lib_command(
'change_box all x final 0 %f y final 0 %f z final 0 %f \
xy final %f xz final %f yz final %f triclinic units box' % (lx, ly, lz, xy, xz, yz))
else:
if self.structure._is_scaled:
self._interactive_lib_command(
'change_box all x final 0 %f y final 0 %f z final 0 %f remap units box' % (lx, ly, lz))
else:
self._interactive_lib_command(
'change_box all x final 0 %f y final 0 %f z final 0 %f units box' % (lx, ly, lz))
def structure_to_lammps(structure):
"""
Converts a structure to the Lammps coordinate frame
Args:
structure (pyiron.atomistics.structure.atoms.Atoms): Structure to convert.
Returns:
pyiron.atomistics.structure.atoms.Atoms: Structure with the LAMMPS coordinate frame.
"""
prism = UnfoldingPrism(structure.cell)
lammps_structure = structure.copy()
lammps_structure.set_cell(prism.A)
lammps_structure.positions = np.matmul(structure.positions, prism.R)
return lammps_structure
def get_steinhardt_parameter_structure(structure,
neighbor_method="cutoff",
cutoff=0,
n_clusters=2,
q=(4, 6),
averaged=False,
clustering=True):
"""
Calculate Steinhardts parameters
Args:
job (job): pyiron job
neighbor_method (str) : can be ['cutoff', 'voronoi']
cutoff (float) : can be 0 for adaptive cutoff or any other value
n_clusters (int) : number of clusters for K means clustering
q (list) : can be from 2-12, the required q values to be calculated
averaged (bool) : If True, calculates the averaged versions of the parameter
clustering (bool) : If True, cluster based on the q values
Returns:
q (list) : calculated q parameters
"""
sys = pc.System()
sys.read_inputfile(
pyiron_to_ase(structure),
format='ase',
is_triclinic=not UnfoldingPrism(structure.cell, digits=15).is_skewed())
sys.find_neighbors(method=neighbor_method, cutoff=cutoff)
sys.calculate_q(q, averaged=averaged)
sysq = sys.get_qvals(q, averaged=averaged)
if clustering:
cl = cluster.KMeans(n_clusters=n_clusters)
ind = cl.fit(list(zip(*sysq))).labels_ == 0
return sysq, ind
else:
return sysq
def get_steinhardt_parameter_structure(structure, cutoff=3.50, n_clusters=2, q=[4, 6]):
sys = pc.System()
sys.read_inputfile(
pyiron_to_ase(structure),
format='ase',
is_triclinic=not UnfoldingPrism(structure.cell, digits=15).is_skewed()
)
sys.find_neighbors(
method='cutoff',
cutoff=cutoff
)
sys.calculate_q(
q,
averaged=True
)
sysq = sys.get_qvals(
q,
averaged=True
)
cl = cluster.KMeans(
n_clusters=n_clusters
)
ind = cl.fit(list(zip(*sysq))).labels_ == 0
return sysq, ind
def structure(self, structure):
self._prism = UnfoldingPrism(structure.cell)
GenericInteractive.structure.fset(self, structure)
def interactive_structure_setter(self, structure):
self._interactive_lib_command("clear")
self._set_selective_dynamics()
self._interactive_lib_command("units " + self.input.control["units"])
self._interactive_lib_command("dimension " +
str(self.input.control["dimension"]))
self._interactive_lib_command("boundary " +
self.input.control["boundary"])
self._interactive_lib_command("atom_style " +
self.input.control["atom_style"])
self._interactive_lib_command("atom_modify map array")
self._prism = UnfoldingPrism(structure.cell)
if np.matrix.trace(self._prism.R) != 3:
warnings.warn(
"Warning: setting upper trangular matrix might slow down the calculation"
)
xhi, yhi, zhi, xy, xz, yz = self._prism.get_lammps_prism()
if self._prism.is_skewed():
self._interactive_lib_command("region 1 prism" + " 0.0 " +
str(xhi) + " 0.0 " + str(yhi) +
" 0.0 " + str(zhi) + " " + str(xy) +
" " + str(xz) + " " + str(yz) +
" units box")
else:
self._interactive_lib_command("region 1 block" + " 0.0 " +
str(xhi) + " 0.0 " + str(yhi) +
" 0.0 " + str(zhi) + " units box")
el_struct_lst = self.structure.get_species_symbols()
el_obj_lst = self.structure.get_species_objects()
el_eam_lst = self.input.potential.get_element_lst()
if self.input.control["atom_style"] == "full":
self._interactive_lib_command("create_box " +
str(len(el_eam_lst)) + " 1 " +
"bond/types 1 " + "angle/types 1 " +
"extra/bond/per/atom 2 " +
"extra/angle/per/atom 2 ")
else:
self._interactive_lib_command("create_box " +
str(len(el_eam_lst)) + " 1")
el_dict = {}
for id_eam, el_eam in enumerate(el_eam_lst):
if el_eam in el_struct_lst:
id_el = list(el_struct_lst).index(el_eam)
el = el_obj_lst[id_el]
el_dict[el] = id_eam + 1
self._interactive_lib_command("mass {0:3d} {1:f}".format(
id_eam + 1, el.AtomicMass))
else:
self._interactive_lib_command("mass {0:3d} {1:f}".format(
id_eam + 1, 1.00))
self._interactive_lib_command("create_atoms 1 random " +
str(len(structure)) + " 12345 1")
positions = structure.positions.flatten()
if np.matrix.trace(self._prism.R) != 3:
positions = np.array(positions).reshape(-1, 3)
positions = np.matmul(positions, self._prism.R)
positions = positions.flatten()
elem_all = np.array(
[el_dict[el] for el in structure.get_chemical_elements()])
if self.server.run_mode.interactive and self.server.cores == 1:
self._interactive_library.scatter_atoms(
"x", 1, 3, (len(positions) * c_double)(*positions))
self._interactive_library.scatter_atoms(
"type", 0, 1, (len(elem_all) * c_int)(*elem_all))
else:
self._interactive_library.scatter_atoms("x", 1, 3, positions)
self._interactive_library.scatter_atoms("type", 0, 1, elem_all)
self._interactive_lib_command("change_box all remap")
# if self.input.control['atom_style'] == "full":
# Do not scatter or manipulate when you have water/ use atom_style full in your system
# self._interactive_water_setter()
self._interactive_lammps_input()
self._interactive_set_potential()
class LammpsInteractive(LammpsBase, GenericInteractive):
def __init__(self, project, job_name):
super(LammpsInteractive, self).__init__(project, job_name)
self._check_opened = False
self._interactive_run_command = None
self._interactive_grand_canonical = True
if "stress" in self.interactive_output_functions.keys():
del self.interactive_output_functions["stress"]
@property
def structure(self):
return GenericInteractive.structure.fget(self)
@structure.setter
def structure(self, structure):
self._prism = UnfoldingPrism(structure.cell)
GenericInteractive.structure.fset(self, structure)
def get_structure(self, iteration_step=-1, wrap_atoms=True):
return GenericInteractive.get_structure(self,
iteration_step=iteration_step,
wrap_atoms=wrap_atoms)
def _interactive_lib_command(self, command):
self._logger.debug("Lammps library: " + command)
self._interactive_library.command(command)
def interactive_positions_getter(self):
positions = np.reshape(
np.array(self._interactive_library.gather_atoms("x", 1, 3)),
(len(self.structure), 3),
)
if np.matrix.trace(self._prism.R) != 3:
positions = np.matmul(positions, self._prism.R.T)
return positions.tolist()
def interactive_positions_setter(self, positions):
if np.matrix.trace(self._prism.R) != 3:
positions = np.array(positions).reshape(-1, 3)
positions = np.matmul(positions, self._prism.R)
positions = np.array(positions).flatten()
if self.server.run_mode.interactive and self.server.cores == 1:
self._interactive_library.scatter_atoms(
"x", 1, 3, (len(positions) * c_double)(*positions))
else:
self._interactive_library.scatter_atoms("x", 1, 3, positions)
self._interactive_lib_command("change_box all remap")
def interactive_cells_getter(self):
cc = np.array([
[self._interactive_library.get_thermo("lx"), 0, 0],
[
self._interactive_library.get_thermo("xy"),
self._interactive_library.get_thermo("ly"),
0,
],
[
self._interactive_library.get_thermo("xz"),
self._interactive_library.get_thermo("yz"),
self._interactive_library.get_thermo("lz"),
],
])
return self._prism.unfold_cell(cc)
def interactive_cells_setter(self, cell):
self._prism = UnfoldingPrism(cell)
lx, ly, lz, xy, xz, yz = self._prism.get_lammps_prism()
if np.matrix.trace(self._prism.R) != 3:
warnings.warn(
"Warning: setting upper trangular matrix might slow down the calculation"
)
is_skewed = self._prism.is_skewed()
is_scaled = self.structure._is_scaled
if is_skewed and is_scaled:
self._interactive_lib_command(
"change_box all x final 0 %f y final 0 %f z final 0 %f \
xy final %f xz final %f yz final %f triclinic remap units box"
% (lx, ly, lz, xy, xz, yz))
elif is_skewed and not is_scaled:
self._interactive_lib_command(
"change_box all x final 0 %f y final 0 %f z final 0 %f \
xy final %f xz final %f yz final %f triclinic units box" %
(lx, ly, lz, xy, xz, yz))
elif not is_skewed and is_scaled:
self._interactive_lib_command(
"change_box all x final 0 %f y final 0 %f z final 0 %f remap units box"
% (lx, ly, lz))
else: # is neither skewed nor scaled
self._interactive_lib_command(
"change_box all x final 0 %f y final 0 %f z final 0 %f units box"
% (lx, ly, lz))
def interactive_volume_getter(self):
return self._interactive_library.get_thermo("vol")
def interactive_forces_getter(self):
ff = np.reshape(
np.array(self._interactive_library.gather_atoms("f", 1, 3)),
(len(self.structure), 3),
)
if np.matrix.trace(self._prism.R) != 3:
ff = np.matmul(ff, self._prism.R.T)
return ff.tolist()
def interactive_execute(self):
self._interactive_lib_command(self._interactive_run_command)
def _interactive_lammps_input(self):
del self.input.control["dump___1"]
del self.input.control["dump_modify___1"]
for key, value in zip(self.input.control.dataset["Parameter"],
self.input.control.dataset["Value"]):
if key in [
"read_data",
"units",
"dimension",
"boundary",
"atom_style",
"atom_modify",
"include",
"run",
"minimize",
]:
continue
else:
self._interactive_lib_command(" ".join(
key.split(self.input.control.multi_word_separator)) + " " +
str(value))
def _interactive_set_potential(self):
potential_lst = []
if self.input.potential.files is not None:
for potential in self.input.potential.files:
if not os.path.exists(potential):
raise ValueError("Potential not found: ", potential)
potential_lst.append([potential.split("/")[-1], potential])
style_full = self.input.control["atom_style"] == "full"
for line in self.input.potential.get_string_lst():
for potential in potential_lst:
if ' ' + potential[0] in line:
line = line.replace(' ' + potential[0], ' ' + potential[1])
# Don't write the kspace_style or pair style commands if the atom style is "full"
if not (style_full and ("kspace" in line or "pair" in line)):
self._interactive_lib_command(line.split("\n")[0])
if len(potential_lst) == 0:
self._interactive_lib_command(line.split("\n")[0])
if style_full:
# Currently supports only water molecules. Please feel free to expand this
self._interactive_water_setter()
def _executable_activate_mpi(self):
if (self.server.run_mode.interactive
or self.server.run_mode.interactive_non_modal):
pass
else:
super(LammpsInteractive, self)._executable_activate_mpi()
def _reset_interactive_run_command(self):
df = pd.DataFrame(self.input.control.dataset)
self._interactive_run_command = " ".join(df.T[df.index[-1]].values)
def interactive_initialize_interface(self):
if self.server.run_mode.interactive and self.server.cores == 1:
lammps = getattr(importlib.import_module("lammps"), "lammps")
self._interactive_library = lammps(cmdargs=["-screen", "none"])
else:
self._create_working_directory()
self._interactive_library = LammpsLibrary(
cores=self.server.cores,
working_directory=self.working_directory)
if not all(self.structure.pbc):
self.input.control["boundary"] = " ".join(
["p" if coord else "f" for coord in self.structure.pbc])
self._reset_interactive_run_command()
self.interactive_structure_setter(self.structure)
def calc_minimize(self,
e_tol=0.0,
f_tol=1e-4,
max_iter=100000,
pressure=None,
n_print=100,
style='cg'):
# Docstring set programmatically -- Please ensure that changes to signature or defaults stay consistent!
if self.server.run_mode.interactive_non_modal:
warnings.warn(
"calc_minimize() is not implemented for the non modal interactive mode use calc_static()!"
)
super(LammpsInteractive, self).calc_minimize(
e_tol=e_tol,
f_tol=f_tol,
max_iter=max_iter,
pressure=pressure,
n_print=n_print,
style=style,
)
if self.interactive_is_activated() and (
self.server.run_mode.interactive
or self.server.run_mode.interactive_non_modal):
self.interactive_structure_setter(self.structure)
calc_minimize.__doc__ = LammpsControl.calc_minimize.__doc__
def calc_md(
self,
temperature=None,
pressure=None,
n_ionic_steps=1000,
time_step=1.0,
n_print=100,
temperature_damping_timescale=100.0,
pressure_damping_timescale=1000.0,
seed=None,
tloop=None,
initial_temperature=None,
langevin=False,
delta_temp=None,
delta_press=None,
):
super(LammpsInteractive, self).calc_md(
temperature=temperature,
pressure=pressure,
n_ionic_steps=n_ionic_steps,
time_step=time_step,
n_print=n_print,
temperature_damping_timescale=temperature_damping_timescale,
pressure_damping_timescale=pressure_damping_timescale,
seed=seed,
tloop=tloop,
initial_temperature=initial_temperature,
langevin=langevin,
delta_temp=delta_temp,
delta_press=delta_press,
)
if self.interactive_is_activated() and (
self.server.run_mode.interactive
or self.server.run_mode.interactive_non_modal):
self.interactive_structure_setter(self.structure)
def run_if_interactive(self):
if self._generic_input["calc_mode"] in ["md", "vcsgc"]:
self.input.control["run"] = self._generic_input["n_print"]
super(LammpsInteractive, self).run_if_interactive()
self._reset_interactive_run_command()
counter = 0
iteration_max = int(self._generic_input["n_ionic_steps"] /
self._generic_input["n_print"])
while counter < iteration_max:
self.interactive_execute()
self.interactive_collect()
counter += 1
else:
super(LammpsInteractive, self).run_if_interactive()
self.interactive_execute()
self.interactive_collect()
def run_if_interactive_non_modal(self):
if not self._interactive_fetch_completed:
print("Warning: interactive_fetch being effectuated")
self.interactive_fetch()
super(LammpsInteractive, self).run_if_interactive()
self.interactive_execute()
self._interactive_fetch_completed = False
def interactive_fetch(self):
if (self._interactive_fetch_completed
and self.server.run_mode.interactive_non_modal):
print("First run and then fetch")
else:
self.interactive_collect()
self._logger.debug("interactive run - done")
def interactive_structure_setter(self, structure):
self._interactive_lib_command("clear")
self._set_selective_dynamics()
self._interactive_lib_command("units " + self.input.control["units"])
self._interactive_lib_command("dimension " +
str(self.input.control["dimension"]))
self._interactive_lib_command("boundary " +
self.input.control["boundary"])
self._interactive_lib_command("atom_style " +
self.input.control["atom_style"])
self._interactive_lib_command("atom_modify map array")
self._prism = UnfoldingPrism(structure.cell)
if np.matrix.trace(self._prism.R) != 3:
warnings.warn(
"Warning: setting upper trangular matrix might slow down the calculation"
)
xhi, yhi, zhi, xy, xz, yz = self._prism.get_lammps_prism()
if self._prism.is_skewed():
self._interactive_lib_command("region 1 prism" + " 0.0 " +
str(xhi) + " 0.0 " + str(yhi) +
" 0.0 " + str(zhi) + " " + str(xy) +
" " + str(xz) + " " + str(yz) +
" units box")
else:
self._interactive_lib_command("region 1 block" + " 0.0 " +
str(xhi) + " 0.0 " + str(yhi) +
" 0.0 " + str(zhi) + " units box")
el_struct_lst = self.structure.get_species_symbols()
el_obj_lst = self.structure.get_species_objects()
el_eam_lst = self.input.potential.get_element_lst()
if self.input.control["atom_style"] == "full":
self._interactive_lib_command("create_box " +
str(len(el_eam_lst)) + " 1 " +
"bond/types 1 " + "angle/types 1 " +
"extra/bond/per/atom 2 " +
"extra/angle/per/atom 2 ")
else:
self._interactive_lib_command("create_box " +
str(len(el_eam_lst)) + " 1")
el_dict = {}
for id_eam, el_eam in enumerate(el_eam_lst):
if el_eam in el_struct_lst:
id_el = list(el_struct_lst).index(el_eam)
el = el_obj_lst[id_el]
el_dict[el] = id_eam + 1
self._interactive_lib_command("mass {0:3d} {1:f}".format(
id_eam + 1, el.AtomicMass))
else:
self._interactive_lib_command("mass {0:3d} {1:f}".format(
id_eam + 1, 1.00))
self._interactive_lib_command("create_atoms 1 random " +
str(len(structure)) + " 12345 1")
positions = structure.positions.flatten()
if np.matrix.trace(self._prism.R) != 3:
positions = np.array(positions).reshape(-1, 3)
positions = np.matmul(positions, self._prism.R)
positions = positions.flatten()
elem_all = np.array(
[el_dict[el] for el in structure.get_chemical_elements()])
if self.server.run_mode.interactive and self.server.cores == 1:
self._interactive_library.scatter_atoms(
"x", 1, 3, (len(positions) * c_double)(*positions))
self._interactive_library.scatter_atoms(
"type", 0, 1, (len(elem_all) * c_int)(*elem_all))
else:
self._interactive_library.scatter_atoms("x", 1, 3, positions)
self._interactive_library.scatter_atoms("type", 0, 1, elem_all)
self._interactive_lib_command("change_box all remap")
# if self.input.control['atom_style'] == "full":
# Do not scatter or manipulate when you have water/ use atom_style full in your system
# self._interactive_water_setter()
self._interactive_lammps_input()
self._interactive_set_potential()
def _interactive_water_setter(self):
"""
This function writes the bonds for water molecules present in the structure. It is assumed that only intact
water molecules are present and the H atoms are within 1.3 $\AA$ of each O atom. Once the neighbor list is
generated, the bonds and angles are created. This function needs to be generalized/extended to account for
dissociated water. This function can also be used as an example to create bonds between other molecules.
"""
neighbors = self.structure.get_neighbors(cutoff=1.3)
o_indices = self.structure.select_index("O")
h_indices = self.structure.select_index("H")
h1_indices = np.intersect1d(
np.vstack(neighbors.indices[o_indices])[:, 0], h_indices)
h2_indices = np.intersect1d(
np.vstack(neighbors.indices[o_indices])[:, 1], h_indices)
o_ind_str = (np.array2string(o_indices + 1).replace("[", "").replace(
"]", "").strip())
h1_ind_str = (np.array2string(h1_indices + 1).replace("[", "").replace(
"]", "").strip())
h2_ind_str = (np.array2string(h2_indices + 1).replace("[", "").replace(
"]", "").strip())
group_o = "group Oatoms id {}".format(o_ind_str).replace(" ", " ")
group_h1 = "group H1atoms id {}".format(h1_ind_str).replace(" ", " ")
group_h2 = "group H2atoms id {}".format(h2_ind_str).replace(" ", " ")
self._interactive_lib_command(group_o)
self._interactive_lib_command(group_h1)
self._interactive_lib_command(group_h2)
# A dummy pair style that does not have any Coulombic interactions needs to be initialized to create the bonds
self._interactive_lib_command("pair_style lj/cut 2.5")
self._interactive_lib_command("pair_coeff * * 0.0 0.0")
self._interactive_lib_command(
"create_bonds many Oatoms H1atoms 1 0.7 1.4")
self._interactive_lib_command(
"create_bonds many Oatoms H2atoms 1 0.7 1.4")
for i, o_ind in enumerate(o_indices):
self._interactive_lib_command(
"create_bonds single/angle 1 {} {} {}".format(
int(h1_indices[i]) + 1,
int(o_ind) + 1,
int(h2_indices[i]) + 1))
# Now the actual pair styles are written
self._interactive_lib_command("pair_style " +
self.input.potential["pair_style"])
values = np.array(self.input.potential._dataset["Value"])
pair_val = values[[
"pair_coeff" in val
for val in self.input.potential._dataset["Parameter"]
]]
for val in pair_val:
self._interactive_lib_command("pair_coeff " + val)
self._interactive_lib_command("kspace_style " +
self.input.potential["kspace_style"])
def from_hdf(self, hdf=None, group_name=None):
"""
Recreates instance from the hdf5 file
Args:
hdf (str): Path to the hdf5 file
group_name (str): Name of the group which contains the object
"""
super(LammpsInteractive, self).from_hdf(hdf=hdf, group_name=group_name)
self.species_from_hdf()
def collect_output(self):
if (self.server.run_mode.interactive
or self.server.run_mode.interactive_non_modal):
pass
else:
super(LammpsInteractive, self).collect_output()
def update_potential(self):
self._interactive_lib_command(self.potential.Config[0][0])
self._interactive_lib_command(self.potential.Config[0][1])
def interactive_indices_getter(self):
lammps_indices = np.array(
self._interactive_library.gather_atoms("type", 0, 1))
indices = self.remap_indices(lammps_indices)
return indices.tolist()
def interactive_indices_setter(self, indices):
el_struct_lst = self._structure_current.get_species_symbols()
el_obj_lst = self._structure_current.get_species_objects()
el_eam_lst = self.input.potential.get_element_lst()
el_dict = {}
for id_eam, el_eam in enumerate(el_eam_lst):
if el_eam in el_struct_lst:
id_el = list(el_struct_lst).index(el_eam)
el = el_obj_lst[id_el]
el_dict[el] = id_eam + 1
elem_all = np.array(
[el_dict[self._structure_current.species[el]] for el in indices])
if self.server.run_mode.interactive and self.server.cores == 1:
self._interactive_library.scatter_atoms(
"type", 0, 1, (len(elem_all) * c_int)(*elem_all))
else:
self._interactive_library.scatter_atoms("type", 0, 1, elem_all)
def interactive_energy_pot_getter(self):
return self._interactive_library.get_thermo("pe")
def interactive_energy_tot_getter(self):
return self._interactive_library.get_thermo("etotal")
def interactive_steps_getter(self):
return self._interactive_library.get_thermo("step")
def interactive_temperatures_getter(self):
return self._interactive_library.get_thermo("temp")
def interactive_stress_getter(self):
"""
This gives back an Nx3x3 array of stress/atom defined in http://lammps.sandia.gov/doc/compute_stress_atom.html
Keep in mind that it is stress*volume in eV. Further discussion can be found on the website above.
Returns:
numpy.array: Nx3x3 np array of stress/atom
"""
if not "stress" in self.interactive_cache.keys():
self._interactive_lib_command("compute st all stress/atom NULL")
self._interactive_lib_command("run 0")
self.interactive_cache["stress"] = []
id_lst = self._interactive_library.extract_atom("id", 0)
id_lst = np.array([id_lst[i] for i in range(len(self.structure))]) - 1
id_lst = np.arange(len(id_lst))[np.argsort(id_lst)]
ind = np.array([0, 3, 4, 3, 1, 5, 4, 5, 2])
ss = self._interactive_library.extract_compute("st", 1, 2)
ss = np.array([
ss[i][j] for i in range(len(self.structure)) for j in range(6)
]).reshape(-1, 6)[id_lst]
ss = ss[:, ind].reshape(
len(self.structure), 3,
3) / constants.eV * constants.bar * constants.angstrom**3
if np.matrix.trace(self._prism.R) != 3:
ss = np.einsum('ij,njk->nik', self._prism.R, ss)
ss = np.einsum('nij,kj->nik', ss, self._prism.R)
return ss
def interactive_pressures_getter(self):
pp = np.array([
[
self._interactive_library.get_thermo("pxx"),
self._interactive_library.get_thermo("pxy"),
self._interactive_library.get_thermo("pxz"),
],
[
self._interactive_library.get_thermo("pxy"),
self._interactive_library.get_thermo("pyy"),
self._interactive_library.get_thermo("pyz"),
],
[
self._interactive_library.get_thermo("pxz"),
self._interactive_library.get_thermo("pyz"),
self._interactive_library.get_thermo("pzz"),
],
])
if np.matrix.trace(self._prism.R) != 3:
pp = np.dot(np.dot(self._prism.R, pp), self._prism.R.T)
return pp / 10000 # bar -> GPa
def interactive_close(self):
if self.interactive_is_activated():
self._interactive_library.close()
with self.project_hdf5.open("output") as h5:
if "interactive" in h5.list_groups():
for key in h5["interactive"].list_nodes():
h5["generic/" + key] = h5["interactive/" + key]
super(LammpsInteractive, self).interactive_close()
def collect_dump_file(self, file_name="dump.out", cwd=None):
"""
general purpose routine to extract static from a lammps dump file
Args:
file_name:
cwd:
Returns:
"""
file_name = self.job_file_name(file_name=file_name, cwd=cwd)
output = {}
with open(file_name, 'r') as ff:
dump = ff.readlines()
prism = UnfoldingPrism(self.structure.cell, digits=15)
rotation_lammps2orig = np.linalg.inv(prism.R)
time = np.genfromtxt([
dump[nn] for nn in
np.where([ll.startswith('ITEM: TIMESTEP') for ll in dump])[0] + 1
],
dtype=int)
time = np.array([time]).flatten()
output['time'] = time
natoms = np.genfromtxt([
dump[nn] for nn in
np.where([ll.startswith('ITEM: NUMBER OF ATOMS')
for ll in dump])[0] + 1
],
dtype=int)
natoms = np.array([natoms]).flatten()
cells = np.genfromtxt(' '.join(([
' '.join(dump[nn:nn + 3]) for nn in
np.where([ll.startswith('ITEM: BOX BOUNDS') for ll in dump])[0] + 1
])).split()).reshape(len(natoms), -1)
cells = np.array([to_amat(cc) for cc in cells])
output['cells'] = cells
l_start = np.where([ll.startswith('ITEM: ATOMS') for ll in dump])[0]
l_end = l_start + natoms + 1
content = [
pd.read_csv(StringIO('\n'.join(dump[llst:llen]).replace(
'ITEM: ATOMS ', '')),
delim_whitespace=True)
for llst, llen in zip(l_start, l_end)
]
forces = np.array([
np.stack((cc['fx'], cc['fy'], cc['fz']), axis=-1) for cc in content
])
output['forces'] = np.einsum('ijk,kl->ijl', forces,
rotation_lammps2orig)
unwrapped_positions = np.array([
np.stack((cc['xsu'], cc['ysu'], cc['zsu']), axis=-1)
for cc in content
])
positions = unwrapped_positions - np.floor(unwrapped_positions)
unwrapped_positions = np.einsum('ikj,ilk->ilj', cells,
unwrapped_positions)
output['unwrapped_positions'] = np.einsum('ijk,kl->ijl',
unwrapped_positions,
rotation_lammps2orig)
positions = np.einsum('ikj,ilk->ilj', cells, positions)
output['positions'] = np.einsum('ijk,kl->ijl', positions,
rotation_lammps2orig)
with self.project_hdf5.open("output/generic") as hdf_output:
for k, v in output.items():
hdf_output[k] = v
def collect_dump_file(self, file_name="dump.out", cwd=None):
"""
general purpose routine to extract static from a lammps dump file
Args:
file_name:
cwd:
Returns:
"""
file_name = self.job_file_name(file_name=file_name, cwd=cwd)
tag_dict = {"ITEM: TIMESTEP": {"arg": "0",
"rows": 1,
"h5": "time"},
# "ITEM: NUMBER OF ATOMS": {"arg": "0",
# "rows": 1,
# "h5": "number_of_atoms"},
"ITEM: BOX BOUNDS": {"arg": "0",
"rows": 3,
"h5": "cells",
"func": to_amat},
"ITEM: ATOMS": {"arg": ":,:",
"rows": len(self.structure),
"splitArg": True}
}
h5_dict = {"id": "id",
"type": "type",
"xsu": "coord_xs",
"ysu": "coord_ys",
"zsu": "coord_zs",
"f_ave[1]": "coord_xs",
"f_ave[2]": "coord_ys",
"f_ave[3]": "coord_zs",
"fx": "force_x",
"fy": "force_y",
"fz": "force_z",
}
lammps_dict = None
lf = Logstatus()
lf.extract_file(file_name=file_name,
tag_dict=tag_dict,
h5_dict=h5_dict,
key_dict=lammps_dict)
lf.combine_xyz('force_x', 'force_y', 'force_z', 'forces')
lf.combine_xyz('coord_xs', 'coord_ys', 'coord_zs', 'positions')
prism = UnfoldingPrism(self.structure.cell, digits=15)
rel_positions = list()
for ind, (pos, forc, cel) in enumerate(
zip(lf.status_dict["positions"], lf.status_dict["forces"], lf.status_dict["cells"])):
cell = cel[1]
positions = pos[1]
forces = forc[1]
# rotation matrix from lammps(unfolded) cell to original cell
rotation_lammps2orig = np.linalg.inv(prism.R)
# convert from scaled positions to absolute in lammps cell
positions = np.array([np.dot(cell.T, r) for r in positions])
# rotate positions from lammps to original
positions_atoms = np.array([np.dot(np.array(r), rotation_lammps2orig) for r in positions])
# rotate forces from lammps to original cell
forces_atoms = np.array([np.dot(np.array(f), rotation_lammps2orig) for f in forces])
# unfold cell
cell = prism.unfold_cell(cell)
# rotate cell from unfolded lammps to original
cell_atoms = np.array([np.dot(np.array(f), rotation_lammps2orig) for f in cell])
lf.status_dict["positions"][ind][1] = positions_atoms
rel_positions.append(np.dot(positions_atoms, np.linalg.inv(cell_atoms)))
lf.status_dict["forces"][ind][1] = forces_atoms
lf.status_dict["cells"][ind][1] = cell_atoms
del lf.status_dict['id']
del lf.status_dict['type']
unwrapped_rel_pos = unwrap_coordinates(positions=np.array(rel_positions), is_relative=True)
unwrapped_pos = list()
# print(np.shape(unwrapped_rel_pos))
for i, cell in enumerate(lf.status_dict["cells"]):
unwrapped_pos.append(np.dot(np.array(unwrapped_rel_pos[i]), cell[1]))
lf.status_dict["unwrapped_positions"] = list()
for pos in unwrapped_pos:
lf.status_dict["unwrapped_positions"].append([[0], pos])
with self.project_hdf5.open("output/generic") as hdf_output:
lf.to_hdf(hdf_output)
return lf
class LammpsInteractive(LammpsBase, GenericInteractive):
def __init__(self, project, job_name):
super(LammpsInteractive, self).__init__(project, job_name)
self._check_opened = False
self._interactive_prism = None
self._interactive_run_command = None
self._interactive_grand_canonical = True
self.interactive_cache = {'cells': [],
'energy_pot': [],
'energy_tot': [],
'forces': [],
'positions': [],
'pressures': [],
'steps': [],
'indices': [],
'temperature': [],
'computation_time': [],
'volume': []}
@property
def structure(self):
return GenericInteractive.structure.fget(self)
@structure.setter
def structure(self, structure):
GenericInteractive.structure.fset(self, structure)
def get_structure(self, iteration_step=-1):
return GenericInteractive.get_structure(self, iteration_step=iteration_step)
def _interactive_lib_command(self, command):
self._logger.debug('Lammps library: ' + command)
self._interactive_library.command(command)
def interactive_positions_getter(self):
positions = np.reshape(np.array(self._interactive_library.gather_atoms("x", 1, 3)),
(len(self.structure), 3))
if np.matrix.trace(self._interactive_prism.R) != 3:
positions = np.dot(positions, self._interactive_prism.R.T)
return positions.tolist()
def interactive_positions_setter(self, positions):
if np.matrix.trace(self._interactive_prism.R) != 3:
positions = np.array(positions).reshape(-1, 3)
positions = np.dot(positions, self._interactive_prism.R)
positions = np.array(positions).flatten()
if self.server.run_mode.interactive_non_modal:
self._interactive_library.scatter_atoms("x", 1, 3, positions)
else:
self._interactive_library.scatter_atoms("x", 1, 3, (len(positions) * c_double)(*positions))
self._interactive_lib_command('change_box all remap')
def interactive_cells_getter(self):
cc = np.array([[self._interactive_library.get_thermo('lx'),
0,
0],
[self._interactive_library.get_thermo('xy'),
self._interactive_library.get_thermo('ly'),
0],
[self._interactive_library.get_thermo('xz'),
self._interactive_library.get_thermo('yz'),
self._interactive_library.get_thermo('lz')]])
return self._interactive_prism.unfold_cell(cc)
def interactive_cells_setter(self, cell):
self._interactive_prism = UnfoldingPrism(cell)
lx, ly, lz, xy, xz, yz = self._interactive_prism.get_lammps_prism()
if np.matrix.trace(self._interactive_prism.R) != 3:
print('Warning: setting upper trangular matrix might slow down the calculation')
if abs(xy) + abs(xz) + abs(yz) > 1.0e-6:
if self.structure._is_scaled:
self._interactive_lib_command(
'change_box all x final 0 %f y final 0 %f z final 0 %f \
xy final %f xz final %f yz final %f triclinic remap units box' % (lx, ly, lz, xy, xz, yz))
else:
self._interactive_lib_command(
'change_box all x final 0 %f y final 0 %f z final 0 %f \
xy final %f xz final %f yz final %f triclinic units box' % (lx, ly, lz, xy, xz, yz))
else:
if self.structure._is_scaled:
self._interactive_lib_command(
'change_box all x final 0 %f y final 0 %f z final 0 %f remap units box' % (lx, ly, lz))
else:
self._interactive_lib_command(
'change_box all x final 0 %f y final 0 %f z final 0 %f units box' % (lx, ly, lz))
def interactive_indices_setter(self, indices):
el_struct_lst = self._structure_current.get_species_symbols()
el_obj_lst = self._structure_current.get_species_objects()
el_eam_lst = self.input.potential.get_element_lst()
el_dict = {}
for id_eam, el_eam in enumerate(el_eam_lst):
if el_eam in el_struct_lst:
id_el = list(el_struct_lst).index(el_eam)
el = el_obj_lst[id_el]
el_dict[el] = id_eam + 1
elem_all = np.array([el_dict[self._structure_current.species[el]] for el in indices])
if self.server.run_mode.interactive_non_modal:
self._interactive_library.scatter_atoms('type', 0, 1, elem_all)
else:
self._interactive_library.scatter_atoms('type', 0, 1, (len(elem_all) * c_int)(*elem_all))
def interactive_volume_getter(self):
return self._interactive_library.get_thermo('vol')
def interactive_forces_getter(self):
ff = np.reshape(np.array(self._interactive_library.gather_atoms("f", 1, 3)), (len(self.structure), 3))
if np.matrix.trace(self._interactive_prism.R) != 3:
ff = np.dot(ff, self._interactive_prism.R.T)
return ff.tolist()
def _interactive_lammps_input(self):
del self.input.control['dump']
del self.input.control['dump_modify']
for key, value in zip(self.input.control.dataset['Parameter'], self.input.control.dataset['Value']):
if key in ['read_data', 'units', 'dimension', 'boundary', 'atom_style', 'atom_modify', 'include', 'run',
'minimize']:
continue
else:
self._interactive_lib_command(key + ' ' + str(value))
def _interactive_set_potential(self):
potential_lst = []
if self.input.potential.files is not None:
for potential in self.input.potential.files:
potential_lst.append([potential.split('/')[-1], potential])
for line in self.input.potential.get_string_lst():
if len(line) > 2:
for potential in potential_lst:
if potential[0] in line:
line = line.replace(potential[0], potential[1])
self._interactive_lib_command(line.split('\n')[0])
def _reset_interactive_run_command(self):
df = pd.DataFrame(self.input.control.dataset)
self._interactive_run_command = " ".join(df.T[df.index[-1]].values)
def interactive_initialize_interface(self):
if self.server.run_mode.interactive_non_modal:
self._interactive_library = LammpsLibrary()
else:
self._interactive_library = lammps()
if not all(self.structure.pbc):
self.input.control['boundary'] = ' '.join(['p' if coord else 'f' for coord in self.structure.pbc])
self._reset_interactive_run_command()
self.interactive_structure_setter(self.structure)
def calc_minimize(self, e_tol=1e-8, f_tol=1e-8, max_iter=1000, pressure=None, n_print=100):
if self.server.run_mode.interactive_non_modal:
warnings.warn('calc_minimize() is not implemented for the non modal interactive mode use calc_static()!')
super(LammpsInteractive, self).calc_minimize(e_tol=e_tol, f_tol=f_tol, max_iter=max_iter, pressure=pressure,
n_print=n_print)
def calc_md(self, temperature=None, pressure=None, n_ionic_steps=1000, time_step=1.0, n_print=100,
delta_temp=100.0, delta_press=1000.0, seed=None, tloop=None, initial_temperature=None, langevin=False):
"""
Set an MD calculation within LAMMPS. Nosé Hoover is used by default
Args:
temperature: (None or float) Target temperature. If set to None, an NVE calculation is performed.
It is required when the pressure is set or langevin is set
pressure: (None or float) Target pressure. If set to None, an NVE or an NVT calculation is performed.
(This tag will allow for a list in the future as it is done for calc_minimize())
n_ionic_steps: (int) Number of ionic steps
time_step: (float) Step size between two steps. In fs if units==metal
n_print: (int) Print frequency
delta_temp: (float) Temperature damping factor (cf. https://lammps.sandia.gov/doc/fix_nh.html)
delta_press: (float) Pressure damping factor (cf. https://lammps.sandia.gov/doc/fix_nh.html)
seed: (int) Seed for the random number generation (required for the velocity creation)
tloop:
initial_temperature: (None or float) Initial temperature according to which the initial velocity field
is created. If None, the initial temperature will be twice the target temperature
(which would go immediately down to the target temperature as described in
equipartition theorem). If 0, the velocity field is not initialized (in which case
the initial velocity given in structure will be used). If any other number is given,
this value is going to be used for the initial temperature.
langevin: (True or False) Activate Langevin dynamics
"""
if self.server.run_mode.interactive_non_modal:
warnings.warn('calc_md() is not implemented for the non modal interactive mode use calc_static()!')
super(LammpsInteractive, self).calc_md(temperature=temperature, pressure=pressure, n_ionic_steps=n_ionic_steps,
time_step=time_step, n_print=n_print, delta_temp=delta_temp,
delta_press=delta_press, seed=seed, tloop=tloop,
initial_temperature=initial_temperature, langevin=langevin)
def run_if_interactive(self):
if self._generic_input['calc_mode'] == 'md':
self.input.control['run'] = self._generic_input['n_print']
super(LammpsInteractive, self).run_if_interactive()
self._reset_interactive_run_command()
counter = 0
iteration_max = int(self._generic_input['n_ionic_steps'] / self._generic_input['n_print'])
while counter < iteration_max:
self._interactive_lib_command(self._interactive_run_command)
self.interactive_collect()
counter += 1
else:
super(LammpsInteractive, self).run_if_interactive()
self._interactive_lib_command(self._interactive_run_command)
self.interactive_collect()
def run_if_interactive_non_modal(self):
if not self._interactive_fetch_completed:
print('Warning: interactive_fetch being effectuated')
self.interactive_fetch()
super(LammpsInteractive, self).run_if_interactive()
self._interactive_lib_command(self._interactive_run_command)
self._interactive_fetch_completed = False
def interactive_fetch(self):
if self._interactive_fetch_completed and self.server.run_mode.interactive_non_modal:
print('First run and then fetch')
else:
self.interactive_collect()
self._logger.debug('interactive run - done')
def interactive_structure_setter(self, structure):
self._interactive_lib_command('clear')
self._set_selective_dynamics()
self._interactive_lib_command('units ' + self.input.control['units'])
self._interactive_lib_command('dimension ' + str(self.input.control['dimension']))
self._interactive_lib_command('boundary ' + self.input.control['boundary'])
self._interactive_lib_command('atom_style ' + self.input.control['atom_style'])
self._interactive_lib_command("atom_modify map array")
self._interactive_prism = UnfoldingPrism(structure.cell)
if np.matrix.trace(self._interactive_prism.R) != 3:
print('Warning: setting upper trangular matrix might slow down the calculation')
xhi, yhi, zhi, xy, xz, yz = self._interactive_prism.get_lammps_prism()
if self._interactive_prism.is_skewed():
self._interactive_lib_command('region 1 prism' +
' 0.0 ' + str(xhi) + ' 0.0 ' + str(yhi) + ' 0.0 ' + str(zhi) +
' ' + str(xy) + ' ' + str(xz) + ' ' + str(yz) + ' units box')
else:
self._interactive_lib_command('region 1 block' +
' 0.0 ' + str(xhi) + ' 0.0 ' + str(yhi) + ' 0.0 ' + str(zhi) + ' units box')
el_struct_lst = self.structure.get_species_symbols()
el_obj_lst = self.structure.get_species_objects()
el_eam_lst = self.input.potential.get_element_lst()
self._interactive_lib_command('create_box ' + str(len(el_eam_lst)) + ' 1')
el_dict = {}
for id_eam, el_eam in enumerate(el_eam_lst):
if el_eam in el_struct_lst:
id_el = list(el_struct_lst).index(el_eam)
el = el_obj_lst[id_el]
el_dict[el] = id_eam + 1
self._interactive_lib_command('mass {0:3d} {1:f}'.format(id_eam + 1, el.AtomicMass))
else:
self._interactive_lib_command('mass {0:3d} {1:f}'.format(id_eam + 1, 1.00))
self._interactive_lib_command('create_atoms 1 random ' + str(len(structure)) + ' 12345 1')
positions = structure.positions.flatten()
elem_all = np.array([el_dict[el] for el in structure.get_chemical_elements()])
if self.server.run_mode.interactive_non_modal:
self._interactive_library.scatter_atoms("x", 1, 3, positions)
self._interactive_library.scatter_atoms('type', 0, 1, elem_all)
else:
self._interactive_library.scatter_atoms("x", 1, 3, (len(positions) * c_double)(*positions))
self._interactive_library.scatter_atoms('type', 0, 1, (len(elem_all) * c_int)(*elem_all))
self._interactive_lib_command('change_box all remap')
self._interactive_lammps_input()
self._interactive_set_potential()
def from_hdf(self, hdf=None, group_name=None):
"""
Recreates instance from the hdf5 file
Args:
hdf (str): Path to the hdf5 file
group_name (str): Name of the group which contains the object
"""
super(LammpsInteractive, self).from_hdf(hdf=hdf, group_name=group_name)
self.species_from_hdf()
def collect_output(self):
if self.server.run_mode.interactive or self.server.run_mode.interactive_non_modal:
pass
else:
super(LammpsInteractive, self).collect_output()
def update_potential(self):
self._interactive_lib_command(self.potential.Config[0][0])
self._interactive_lib_command(self.potential.Config[0][1])
def interactive_indices_getter(self):
return super(LammpsInteractive, self).interactive_indices_getter().tolist()
def interactive_energy_pot_getter(self):
return self._interactive_library.get_thermo("pe")
def interactive_energy_tot_getter(self):
return self._interactive_library.get_thermo("etotal")
def interactive_steps_getter(self):
return self._interactive_library.get_thermo("step")
def interactive_temperatures_getter(self):
return self._interactive_library.get_thermo("temp")
def interactive_stress_getter(self):
"""
This gives back an Nx3x3 array of stress/atom defined in http://lammps.sandia.gov/doc/compute_stress_atom.html
Keep in mind that it is stress*volume in eV. Further discussion can be found on the website above.
Returns:
numpy.array: Nx3x3 np array of stress/atom
"""
if not 'stress' in self.interactive_cache.keys():
self._interactive_lib_command('compute st all stress/atom NULL')
self._interactive_lib_command('run 0')
self.interactive_cache['stress'] = []
ss = np.array([self._interactive_library.extract_compute('st', 1, 2)[i][j + (j != k) * (k + 2)]
for i in range(len(self.structure))
for j in range(3)
for k in range(3)]).reshape(len(self.structure), 3, 3)/1.602e6
if np.matrix.trace(self._interactive_prism.R) != 3:
ss = np.dot(np.dot(self._interactive_prism.R, ss), self._interactive_prism.R.T)
return ss
def interactive_pressures_getter(self):
pp = np.array([[self._interactive_library.get_thermo('pxx'),
self._interactive_library.get_thermo('pxy'),
self._interactive_library.get_thermo('pxz')],
[self._interactive_library.get_thermo('pxy'),
self._interactive_library.get_thermo('pyy'),
self._interactive_library.get_thermo('pyz')],
[self._interactive_library.get_thermo('pxz'),
self._interactive_library.get_thermo('pyz'),
self._interactive_library.get_thermo('pzz')]])
if np.matrix.trace(self._interactive_prism.R) != 3:
pp = np.dot(np.dot(self._interactive_prism.R, pp), self._interactive_prism.R.T)
return pp / 10000 # bar -> GPa
def interactive_close(self):
if self.interactive_is_activated():
self._interactive_library.close()
with self.project_hdf5.open("output") as h5:
if 'interactive' in h5.list_groups():
for key in h5['interactive'].list_nodes():
h5['generic/' + key] = h5['interactive/' + key]
super(LammpsInteractive, self).interactive_close()
class LammpsInteractive(LammpsBase, GenericInteractive):
def __init__(self, project, job_name):
super(LammpsInteractive, self).__init__(project, job_name)
self._check_opened = False
self._interactive_prism = None
self._interactive_run_command = None
self._interactive_grand_canonical = True
self.interactive_cache = {'cells': [],
'energy_pot': [],
'energy_tot': [],
'forces': [],
'positions': [],
'pressures': [],
'steps': [],
'indices': [],
'temperature': [],
'computation_time': [],
'volume': []}
@property
def structure(self):
return GenericInteractive.structure.fget(self)
@structure.setter
def structure(self, structure):
GenericInteractive.structure.fset(self, structure)
def get_structure(self, iteration_step=-1, wrap_atoms=True):
return GenericInteractive.get_structure(self, iteration_step=iteration_step, wrap_atoms=wrap_atoms)
def _interactive_lib_command(self, command):
self._logger.debug('Lammps library: ' + command)
self._interactive_library.command(command)
def interactive_positions_getter(self):
positions = np.reshape(np.array(self._interactive_library.gather_atoms("x", 1, 3)),
(len(self.structure), 3))
if np.matrix.trace(self._interactive_prism.R) != 3:
positions = np.dot(positions, self._interactive_prism.R.T)
return positions.tolist()
def interactive_positions_setter(self, positions):
if np.matrix.trace(self._interactive_prism.R) != 3:
positions = np.array(positions).reshape(-1, 3)
positions = np.dot(positions, self._interactive_prism.R)
positions = np.array(positions).flatten()
if self.server.run_mode.interactive and self.server.cores == 1:
self._interactive_library.scatter_atoms("x", 1, 3, (len(positions) * c_double)(*positions))
else:
self._interactive_library.scatter_atoms("x", 1, 3, positions)
self._interactive_lib_command('change_box all remap')
def interactive_cells_getter(self):
cc = np.array([[self._interactive_library.get_thermo('lx'),
0,
0],
[self._interactive_library.get_thermo('xy'),
self._interactive_library.get_thermo('ly'),
0],
[self._interactive_library.get_thermo('xz'),
self._interactive_library.get_thermo('yz'),
self._interactive_library.get_thermo('lz')]])
return self._interactive_prism.unfold_cell(cc)
def interactive_cells_setter(self, cell):
self._interactive_prism = UnfoldingPrism(cell)
lx, ly, lz, xy, xz, yz = self._interactive_prism.get_lammps_prism()
if np.matrix.trace(self._interactive_prism.R) != 3:
warnings.warn('Warning: setting upper trangular matrix might slow down the calculation')
if self._interactive_prism.is_skewed():
if self.structure._is_scaled:
self._interactive_lib_command(
'change_box all x final 0 %f y final 0 %f z final 0 %f \
xy final %f xz final %f yz final %f triclinic remap units box' % (lx, ly, lz, xy, xz, yz))
else:
self._interactive_lib_command(
'change_box all x final 0 %f y final 0 %f z final 0 %f \
xy final %f xz final %f yz final %f triclinic units box' % (lx, ly, lz, xy, xz, yz))
else:
if self.structure._is_scaled:
self._interactive_lib_command(
'change_box all x final 0 %f y final 0 %f z final 0 %f remap units box' % (lx, ly, lz))
else:
self._interactive_lib_command(
'change_box all x final 0 %f y final 0 %f z final 0 %f units box' % (lx, ly, lz))
def interactive_indices_setter(self, indices):
el_struct_lst = self._structure_current.get_species_symbols()
el_obj_lst = self._structure_current.get_species_objects()
el_eam_lst = self.input.potential.get_element_lst()
el_dict = {}
for id_eam, el_eam in enumerate(el_eam_lst):
if el_eam in el_struct_lst:
id_el = list(el_struct_lst).index(el_eam)
el = el_obj_lst[id_el]
el_dict[el] = id_eam + 1
elem_all = np.array([el_dict[self._structure_current.species[el]] for el in indices])
if self.server.run_mode.interactive and self.server.cores == 1:
self._interactive_library.scatter_atoms('type', 0, 1, (len(elem_all) * c_int)(*elem_all))
else:
self._interactive_library.scatter_atoms('type', 0, 1, elem_all)
def interactive_volume_getter(self):
return self._interactive_library.get_thermo('vol')
def interactive_forces_getter(self):
ff = np.reshape(np.array(self._interactive_library.gather_atoms("f", 1, 3)), (len(self.structure), 3))
if np.matrix.trace(self._interactive_prism.R) != 3:
ff = np.dot(ff, self._interactive_prism.R.T)
return ff.tolist()
def interactive_execute(self):
self._interactive_lib_command(self._interactive_run_command)
def _interactive_lammps_input(self):
del self.input.control['dump___1']
del self.input.control['dump_modify___1']
for key, value in zip(self.input.control.dataset['Parameter'], self.input.control.dataset['Value']):
if key in ['read_data', 'units', 'dimension', 'boundary', 'atom_style', 'atom_modify', 'include', 'run',
'minimize']:
continue
else:
self._interactive_lib_command(' '.join(key.split(self.input.control.multi_word_separator)) + ' ' + str(value))
def _interactive_set_potential(self):
potential_lst = []
if self.input.potential.files is not None:
for potential in self.input.potential.files:
if not os.path.exists(potential):
raise ValueError('Potential not found: ', potential)
potential_lst.append([potential.split('/')[-1], potential])
style_full = self.input.control['atom_style'] == 'full'
for line in self.input.potential.get_string_lst():
if len(line) > 2:
for potential in potential_lst:
if potential[0] in line:
line = line.replace(potential[0], potential[1])
# Don't write the kspace_style or pair style commands if the atom style is "full"
if not (style_full and ("kspace" in line or "pair" in line)):
self._interactive_lib_command(line.split('\n')[0])
if style_full:
# Currently supports only water molecules. Please feel free to expand this
self._interactive_water_setter()
def _executable_activate_mpi(self):
if self.server.run_mode.interactive or self.server.run_mode.interactive_non_modal:
pass
else:
super(LammpsInteractive, self)._executable_activate_mpi()
def _reset_interactive_run_command(self):
df = pd.DataFrame(self.input.control.dataset)
self._interactive_run_command = " ".join(df.T[df.index[-1]].values)
def interactive_initialize_interface(self):
if self.server.run_mode.interactive and self.server.cores == 1:
lammps = getattr(importlib.import_module('lammps'), 'lammps')
self._interactive_library = lammps(cmdargs=['-screen', 'none'])
else:
self._create_working_directory()
self._interactive_library = LammpsLibrary(cores=self.server.cores, working_directory=self.working_directory)
if not all(self.structure.pbc):
self.input.control['boundary'] = ' '.join(['p' if coord else 'f' for coord in self.structure.pbc])
self._reset_interactive_run_command()
self.interactive_structure_setter(self.structure)
def calc_minimize(self, e_tol=0.0, f_tol=1e-4, max_iter=1000, pressure=None, n_print=100):
"""
Sets parameters required for minimisation
Args:
e_tol (float): If the magnitude of difference between energies of two consecutive steps is lower
than or equal to e_tol, the minimisation terminates and is considered converged. (Default: 0.0)
f_tol (float): If the magnitude of the global force vector at a step is lower than or equal to
f_tol, the minimisation terminates and is considered converged. (Default: 1e-4)
max_iter (int): Maximum number of minimisation steps to carry out. If the minimisation converges
before 'max_iter' steps, terminate at the converged step. If the minimisation does
not converge up to 'max_iter' steps, terminate at the 'max_iter' step. Default: 1000)
pressure (float): Pressure at which minimisation is to be carried out. If 'None', isochoric
(constant volume) condition will be used. (Default: None)
n_print (int): Write (dump or print) to the output file every n steps (Default: 100)
"""
if self.server.run_mode.interactive_non_modal:
warnings.warn('calc_minimize() is not implemented for the non modal interactive mode use calc_static()!')
super(LammpsInteractive, self).calc_minimize(e_tol=e_tol, f_tol=f_tol, max_iter=max_iter, pressure=pressure,
n_print=n_print)
if self.interactive_is_activated() and \
(self.server.run_mode.interactive or self.server.run_mode.interactive_non_modal):
self.interactive_structure_setter(self.structure)
def calc_md(self, temperature=None, pressure=None, n_ionic_steps=1000, time_step=1.0, n_print=100,
temperature_damping_timescale=100.0, pressure_damping_timescale=1000.0, seed=None, tloop=None,
initial_temperature=None, langevin=False, delta_temp=None, delta_press=None):
super(LammpsInteractive, self).calc_md(temperature=temperature, pressure=pressure, n_ionic_steps=n_ionic_steps,
time_step=time_step, n_print=n_print,
temperature_damping_timescale=temperature_damping_timescale,
pressure_damping_timescale=pressure_damping_timescale, seed=seed,
tloop=tloop, initial_temperature=initial_temperature,
langevin=langevin, delta_temp=delta_temp, delta_press=delta_press)
if self.interactive_is_activated() and \
(self.server.run_mode.interactive or self.server.run_mode.interactive_non_modal):
self.interactive_structure_setter(self.structure)
def run_if_interactive(self):
if self._generic_input['calc_mode'] == 'md':
self.input.control['run'] = self._generic_input['n_print']
super(LammpsInteractive, self).run_if_interactive()
self._reset_interactive_run_command()
counter = 0
iteration_max = int(self._generic_input['n_ionic_steps'] / self._generic_input['n_print'])
while counter < iteration_max:
self.interactive_execute()
self.interactive_collect()
counter += 1
else:
super(LammpsInteractive, self).run_if_interactive()
self.interactive_execute()
self.interactive_collect()
def run_if_interactive_non_modal(self):
if not self._interactive_fetch_completed:
print('Warning: interactive_fetch being effectuated')
self.interactive_fetch()
super(LammpsInteractive, self).run_if_interactive()
self.interactive_execute()
self._interactive_fetch_completed = False
def interactive_fetch(self):
if self._interactive_fetch_completed and self.server.run_mode.interactive_non_modal:
print('First run and then fetch')
else:
self.interactive_collect()
self._logger.debug('interactive run - done')
def interactive_structure_setter(self, structure):
self._interactive_lib_command('clear')
self._set_selective_dynamics()
self._interactive_lib_command('units ' + self.input.control['units'])
self._interactive_lib_command('dimension ' + str(self.input.control['dimension']))
self._interactive_lib_command('boundary ' + self.input.control['boundary'])
self._interactive_lib_command('atom_style ' + self.input.control['atom_style'])
self._interactive_lib_command("atom_modify map array")
self._interactive_prism = UnfoldingPrism(structure.cell)
if np.matrix.trace(self._interactive_prism.R) != 3:
warnings.warn('Warning: setting upper trangular matrix might slow down the calculation')
xhi, yhi, zhi, xy, xz, yz = self._interactive_prism.get_lammps_prism()
if self._interactive_prism.is_skewed():
self._interactive_lib_command('region 1 prism' +
' 0.0 ' + str(xhi) + ' 0.0 ' + str(yhi) + ' 0.0 ' + str(zhi) +
' ' + str(xy) + ' ' + str(xz) + ' ' + str(yz) + ' units box')
else:
self._interactive_lib_command('region 1 block' +
' 0.0 ' + str(xhi) + ' 0.0 ' + str(yhi) + ' 0.0 ' + str(zhi) + ' units box')
el_struct_lst = self.structure.get_species_symbols()
el_obj_lst = self.structure.get_species_objects()
el_eam_lst = self.input.potential.get_element_lst()
if self.input.control['atom_style'] == "full":
self._interactive_lib_command('create_box ' + str(len(el_eam_lst)) + ' 1 ' + 'bond/types 1 '
+ 'angle/types 1 ' + 'extra/bond/per/atom 2 ' + 'extra/angle/per/atom 2 ')
else:
self._interactive_lib_command('create_box ' + str(len(el_eam_lst)) + ' 1')
el_dict = {}
for id_eam, el_eam in enumerate(el_eam_lst):
if el_eam in el_struct_lst:
id_el = list(el_struct_lst).index(el_eam)
el = el_obj_lst[id_el]
el_dict[el] = id_eam + 1
self._interactive_lib_command('mass {0:3d} {1:f}'.format(id_eam + 1, el.AtomicMass))
else:
self._interactive_lib_command('mass {0:3d} {1:f}'.format(id_eam + 1, 1.00))
self._interactive_lib_command('create_atoms 1 random ' + str(len(structure)) + ' 12345 1')
positions = structure.positions.flatten()
if np.matrix.trace(self._interactive_prism.R) != 3:
positions = np.array(positions).reshape(-1, 3)
positions = np.dot(positions, self._interactive_prism.R)
positions = positions.flatten()
elem_all = np.array([el_dict[el] for el in structure.get_chemical_elements()])
if self.server.run_mode.interactive and self.server.cores == 1:
self._interactive_library.scatter_atoms("x", 1, 3, (len(positions) * c_double)(*positions))
self._interactive_library.scatter_atoms('type', 0, 1, (len(elem_all) * c_int)(*elem_all))
else:
self._interactive_library.scatter_atoms("x", 1, 3, positions)
self._interactive_library.scatter_atoms('type', 0, 1, elem_all)
self._interactive_lib_command('change_box all remap')
# if self.input.control['atom_style'] == "full":
# Do not scatter or manipulate when you have water/ use atom_style full in your system
# self._interactive_water_setter()
self._interactive_lammps_input()
self._interactive_set_potential()
def _interactive_water_setter(self):
"""
This function writes the bonds for water molecules present in the structure. It is assumed that only intact
water molecules are present and the H atoms are within 1.3 $\AA$ of each O atom. Once the neighbor list is
generated, the bonds and angles are created. This function needs to be generalized/extended to account for
dissociated water. This function can also be used as an example to create bonds between other molecules.
"""
neighbors = self.structure.get_neighbors(cutoff=1.3)
o_indices = self.structure.select_index("O")
h_indices = self.structure.select_index("H")
h1_indices = np.intersect1d(np.vstack(neighbors.indices[o_indices])[:, 0], h_indices)
h2_indices = np.intersect1d(np.vstack(neighbors.indices[o_indices])[:, 1], h_indices)
o_ind_str = np.array2string(o_indices + 1).replace("[", "").replace("]", "").strip()
h1_ind_str = np.array2string(h1_indices + 1).replace("[", "").replace("]", "").strip()
h2_ind_str = np.array2string(h2_indices + 1).replace("[", "").replace("]", "").strip()
group_o = "group Oatoms id {}".format(o_ind_str).replace(" ", " ")
group_h1 = "group H1atoms id {}".format(h1_ind_str).replace(" ", " ")
group_h2 = "group H2atoms id {}".format(h2_ind_str).replace(" ", " ")
self._interactive_lib_command(group_o)
self._interactive_lib_command(group_h1)
self._interactive_lib_command(group_h2)
# A dummy pair style that does not have any Coulombic interactions needs to be initialized to create the bonds
self._interactive_lib_command("pair_style lj/cut 2.5")
self._interactive_lib_command("pair_coeff * * 0.0 0.0")
self._interactive_lib_command("create_bonds many Oatoms H1atoms 1 0.7 1.4")
self._interactive_lib_command("create_bonds many Oatoms H2atoms 1 0.7 1.4")
for i, o_ind in enumerate(o_indices):
self._interactive_lib_command("create_bonds single/angle 1 {} {} {}".format(
int(h1_indices[i]) + 1, int(o_ind) + 1, int(h2_indices[i]) + 1))
# Now the actual pair styles are written
self._interactive_lib_command("pair_style " + self.input.potential["pair_style"])
values = np.array(self.input.potential._dataset['Value'])
pair_val = values[["pair_coeff" in val for val in self.input.potential._dataset['Parameter']]]
for val in pair_val:
self._interactive_lib_command("pair_coeff " + val)
self._interactive_lib_command("kspace_style " + self.input.potential["kspace_style"])
def from_hdf(self, hdf=None, group_name=None):
"""
Recreates instance from the hdf5 file
Args:
hdf (str): Path to the hdf5 file
group_name (str): Name of the group which contains the object
"""
super(LammpsInteractive, self).from_hdf(hdf=hdf, group_name=group_name)
self.species_from_hdf()
def collect_output(self):
if self.server.run_mode.interactive or self.server.run_mode.interactive_non_modal:
pass
else:
super(LammpsInteractive, self).collect_output()
def update_potential(self):
self._interactive_lib_command(self.potential.Config[0][0])
self._interactive_lib_command(self.potential.Config[0][1])
def interactive_indices_getter(self):
return super(LammpsInteractive, self).interactive_indices_getter().tolist()
def interactive_energy_pot_getter(self):
return self._interactive_library.get_thermo("pe")
def interactive_energy_tot_getter(self):
return self._interactive_library.get_thermo("etotal")
def interactive_steps_getter(self):
return self._interactive_library.get_thermo("step")
def interactive_temperatures_getter(self):
return self._interactive_library.get_thermo("temp")
def interactive_stress_getter(self):
"""
This gives back an Nx3x3 array of stress/atom defined in http://lammps.sandia.gov/doc/compute_stress_atom.html
Keep in mind that it is stress*volume in eV. Further discussion can be found on the website above.
Returns:
numpy.array: Nx3x3 np array of stress/atom
"""
if not 'stress' in self.interactive_cache.keys():
self._interactive_lib_command('compute st all stress/atom NULL')
self._interactive_lib_command('run 0')
self.interactive_cache['stress'] = []
ss = np.array([self._interactive_library.extract_compute('st', 1, 2)[i][j + (j != k) * (k + 2)]
for i in range(len(self.structure))
for j in range(3)
for k in range(3)]).reshape(len(self.structure), 3, 3)/1.602e6
if np.matrix.trace(self._interactive_prism.R) != 3:
ss = np.dot(np.dot(self._interactive_prism.R, ss), self._interactive_prism.R.T)
return ss
def interactive_pressures_getter(self):
pp = np.array([[self._interactive_library.get_thermo('pxx'),
self._interactive_library.get_thermo('pxy'),
self._interactive_library.get_thermo('pxz')],
[self._interactive_library.get_thermo('pxy'),
self._interactive_library.get_thermo('pyy'),
self._interactive_library.get_thermo('pyz')],
[self._interactive_library.get_thermo('pxz'),
self._interactive_library.get_thermo('pyz'),
self._interactive_library.get_thermo('pzz')]])
if np.matrix.trace(self._interactive_prism.R) != 3:
pp = np.dot(np.dot(self._interactive_prism.R, pp), self._interactive_prism.R.T)
return pp / 10000 # bar -> GPa
def interactive_close(self):
if self.interactive_is_activated():
self._interactive_library.close()
with self.project_hdf5.open("output") as h5:
if 'interactive' in h5.list_groups():
for key in h5['interactive'].list_nodes():
h5['generic/' + key] = h5['interactive/' + key]
super(LammpsInteractive, self).interactive_close()