# coding: utf-8
# Copyright (c) Max-Planck-Institut für Eisenforschung GmbH - Computational Materials Design (CM) Department
# Distributed under the terms of "New BSD License", see the LICENSE file.
from __future__ import print_function
import hashlib
import warnings
from collections import OrderedDict
import numpy as np
from lammpsparser.units import LAMMPS_UNIT_CONVERSIONS
from pyiron_base import GenericParameters, state
__author__ = "Joerg Neugebauer, Sudarsan Surendralal, Jan Janssen"
__copyright__ = (
"Copyright 2021, Max-Planck-Institut für Eisenforschung GmbH - "
"Computational Materials Design (CM) Department"
)
__version__ = "1.0"
__maintainer__ = "Sudarsan Surendralal"
__email__ = "surendralal@mpie.de"
__status__ = "production"
__date__ = "Sep 1, 2017"
[docs]
class LammpsControl(GenericParameters):
[docs]
def __init__(self, input_file_name=None, **qwargs):
super(LammpsControl, self).__init__(
input_file_name=input_file_name, table_name="control_inp", comment_char="#"
)
self._init_block_dict()
self._force_skewed = False
@property
def dataset(self):
return self._dataset
def _init_block_dict(self):
block_dict = OrderedDict()
block_dict["read_restart"] = "read_restart"
block_dict["environment"] = (
"units",
"dimension",
"boundary",
"atom_style",
"atom_modify",
"newton",
)
block_dict["structure"] = ("read_data", "include", "region")
block_dict["potential"] = (
"group",
"set",
"pair_style",
"pair_coeff",
"bond_style",
"bond_coeff",
"angle_style",
"angle_coeff",
"kspace_style",
"neighbor",
)
block_dict["compute"] = (
"compute",
"compute_modify",
"fix",
"variable",
"fix_modify",
)
block_dict["setup"] = (
"min_style",
"min_modify",
"neigh_modify",
"velocity",
"timestep",
"dielectric",
"reset_timestep",
)
block_dict["control"] = (
"dump",
"dump_modify",
"thermo_style",
"thermo_modify",
"thermo",
)
block_dict["run"] = ("run", "minimize")
block_dict["write_restart"] = "write_restart"
self._block_dict = block_dict
[docs]
def load_default(self, file_content=None):
if file_content is None:
file_content = (
"units metal\n"
+ "dimension 3\n"
+ "boundary p p p\n"
+ "atom_style atomic\n"
+ "read_data structure.inp\n"
+ "include potential.inp\n"
+ "fix___ensemble all nve\n"
+ "variable___dumptime equal 100\n"
+ "variable___thermotime equal 100\n"
+ "dump___1 all custom ${dumptime} dump.out id type xsu ysu zsu fx fy fz vx vy vz\n"
+ 'dump_modify___1 sort id format line "%d %d %20.15g %20.15g %20.15g %20.15g %20.15g %20.15g %20.15g %20.15g %20.15g"\n'
+ "thermo_style custom step temp pe etotal pxx pxy pxz pyy pyz pzz vol\n"
+ "thermo_modify format float %20.15g\n"
+ "thermo ${thermotime}\n"
+ "run 0\n"
)
self.load_string(file_content)
[docs]
def pressure_to_lammps(self, pressure, rotation_matrix):
"""
Convert a singular value, list of values, or combination of values to the appropriate six elements for Lammps
pxx, pyy, pzz, pxy, pxz, and pyz pressure tensor representation.
Lammps handles complex cells in a particular way, namely by using an upper triangular cell. This means we may
need to convert our pressure tensor to a new coordinate frame. We also handle that transformation here.
In case of a single pressure value, it is again returned as a single pressure value, to be used with the "iso"
option (i.e., coupled deformation in x, y, and z).
Finally, we also ensure that the units are converted from pyiron's GPa to whatever Lammps needs.
Args:
pressure (float/list/tuple/numpy.ndarray): The pressure(s) to convert.
rotation_matrix (numpy.ndarray): The 3x3 matrix rotating from the pyiron to Lammps coordinate frame.
Returns:
(list): pxx, pyy, pzz, pxy, pxz, and pyz to be passed to Lammps.
or
(float): a single, isotropic pressure to be used with the "iso" option
"""
# If pressure is a scalar, only unit conversion is needed.
if np.isscalar(pressure):
return float(pressure) * LAMMPS_UNIT_CONVERSIONS[self["units"]]["pressure"]
# Normalize pressure to a list of 6 entries of either float or NoneType type.
if len(pressure) > 6:
raise ValueError(
"Pressure can have a maximum of 6 values, (x, y, z, xy, xz, and yz), but got "
+ "{}".format(len(pressure))
)
pressure = [float(p) if p is not None else None for p in pressure]
pressure += (6 - len(pressure)) * [None]
if all(p is None for p in pressure):
raise ValueError("Pressure cannot have a length but all be None")
# If necessary, rotate the pressure tensor to the Lammps coordinate frame.
# Isotropic, hydrostatic pressures are rotation invariant.
if not np.isclose(
np.matrix.trace(rotation_matrix), 3
) and not self._is_isotropic_hydrostatic(pressure):
if any(p is None for p in pressure):
raise ValueError(
"Cells which are not orthorhombic or an upper-triangular cell are incompatible with Lammps "
"constant pressure calculations unless the entire pressure tensor is defined. "
"The reason is that Lammps demands such cells be represented with an "
"upper-triangular unit cell, thus a rotation between Lammps and pyiron coordinate "
"frames is required; it is not possible to rotate the pressure tensor if any of "
"its components is None."
)
pxx, pyy, pzz, pxy, pxz, pyz = pressure
pressure_tensor = np.array(
[[pxx, pxy, pxz], [pxy, pyy, pyz], [pxz, pyz, pzz]]
)
lammps_pressure_tensor = (
rotation_matrix.T @ pressure_tensor @ rotation_matrix
)
pressure = list(
lammps_pressure_tensor[[0, 1, 2, 0, 0, 1], [0, 1, 2, 1, 2, 2]]
)
return [
(
p * LAMMPS_UNIT_CONVERSIONS[self["units"]]["pressure"]
if p is not None
else p
)
for p in pressure
]
@staticmethod
def _is_isotropic_hydrostatic(pressure):
axial_all_alike = None not in pressure[:3] and np.allclose(
pressure[:3], pressure[0]
)
shear_all_none = all(p is None for p in pressure[3:])
shear_all_zero = None not in pressure[3:] and np.allclose(pressure[3:], 0)
return axial_all_alike and (shear_all_none or shear_all_zero)
[docs]
def calc_minimize(
self,
ionic_energy_tolerance=0.0,
ionic_force_tolerance=1e-4,
max_iter=100000,
pressure=None,
n_print=100,
style="cg",
rotation_matrix=None,
):
"""
Sets parameters required for minimization.
Args:
ionic_energy_tolerance (float): If the magnitude of difference between energies of two consecutive steps is
lower than or equal to `ionic_energy_tolerance`, the minimisation terminates. (Default is 0.0 eV.)
ionic_force_tolerance (float): If the magnitude of the global force vector at a step is lower than or equal
to `ionic_force_tolerance`, the minimisation terminates. (Default is 1e-4 eV/angstrom.)
e_tol (float): Same as ionic_energy_tolerance (deprecated)
f_tol (float): Same as ionic_force_tolerance (deprecated)
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 is 100000.)
pressure (None/float/numpy.ndarray/list): Target pressure. If set to None, an isochoric (constant V)
calculation is performed. If set to a scalar, the shear of the cell and the ratio of the x, y, and
z components is kept constant, while an isotropic, hydrostatic pressure is applied. A list of up to
length 6 can be given to specify xx, yy, zz, xy, xz, and yz components of the pressure tensor,
respectively. These values can mix floats and `None` to allow only certain degrees of cell freedom
to change. (Default is None, run isochorically.)
n_print (int): Write (dump or print) to the output file every n steps (Default: 100)
style ('cg'/'sd'/other values from Lammps docs): The style of the numeric minimization, either conjugate
gradient, steepest descent, or other keys permissible from the Lammps docs on 'min_style'. (Default
is 'cg' -- conjugate gradient.)
rotation_matrix (numpy.ndarray): The rotation matrix from the pyiron to Lammps coordinate frame.
"""
# This docstring is a source for the calc_minimize method in pyiron_atomistics.lammps.base.LammpsBase.calc_minimize and
# pyiron_atomistics.lammps.interactive.LammpsInteractive.calc_minimize -- Please ensure that changes to signature or
# defaults stay consistent!
max_evaluations = 100 * max_iter
if n_print > max_iter:
state.logger.warning(
"n_print larger than max_iter, adjusting to n_print=max_iter"
)
n_print = max_iter
if self["units"] not in LAMMPS_UNIT_CONVERSIONS.keys():
raise NotImplementedError
energy_units = LAMMPS_UNIT_CONVERSIONS[self["units"]]["energy"]
force_units = LAMMPS_UNIT_CONVERSIONS[self["units"]]["force"]
ionic_energy_tolerance *= energy_units
ionic_force_tolerance *= force_units
if pressure is not None:
if rotation_matrix is None:
raise ValueError(
"No rotation matrix given while trying to convert pressure. "
"This is most likely due to no structure being defined."
)
self._force_skewed = False
pressure = self.pressure_to_lammps(pressure, rotation_matrix)
if np.isscalar(pressure):
str_press = " iso {}".format(pressure)
else:
str_press = ""
for ii, (press, str_axis) in enumerate(
zip(pressure, ["x", "y", "z", "xy", "xz", "yz"])
):
if press is not None:
str_press += " {} {}".format(str_axis, press)
if ii > 2:
self._force_skewed = True
if len(str_press) > 1:
str_press += " couple none"
self.set(fix___ensemble=r"all box/relax" + str_press)
self.remove_keys(["fix___nve"])
self.set(min_style=style)
self.set(
minimize=str(ionic_energy_tolerance)
+ " "
+ str(ionic_force_tolerance)
+ " "
+ str(int(max_iter))
+ " "
+ str(int(max_evaluations))
)
self.remove_keys(["run", "velocity"])
self.modify(
variable___dumptime="equal " + str(n_print),
variable___thermotime="equal " + str(n_print),
)
def calc_static(self):
self.set(run="0")
self.remove_keys(["minimize", "velocity"])
[docs]
def set_initial_velocity(
self,
temperature,
seed=None,
gaussian=False,
append_value=False,
zero_lin_momentum=True,
zero_rot_momentum=True,
job_name="",
):
"""
Create initial velocities via velocity all create. More information can be found on LAMMPS website:
https://lammps.sandia.gov/doc/velocity.html
Args:
temperature: (int or float)
seed: (int) Seed for the initial random number generator
gaussian: (True/False) Create velocity according to the Gaussian distribution (otherwise uniform)
append_value: (True/False) Add the velocity values to the current velocities (probably not functional now)
zero_lin_momentum: (True/False) Cancel the total linear momentum
zero_rot_momentum: (True/False) Cancel the total angular momentum
job_name: (str) job name to generate seed
"""
if seed is None:
seed = self.generate_seed_from_job(job_name=job_name, seed=1)
arg = ""
if gaussian:
arg = " dist gaussian"
if append_value:
arg += " sum yes"
if not zero_lin_momentum:
arg += " mom no"
if not zero_rot_momentum:
arg += " rot no"
self.modify(
velocity="all create " + str(temperature) + " " + str(seed) + arg,
append_if_not_present=True,
)
[docs]
@staticmethod
def generate_seed_from_job(job_name="", seed=0):
"""
Generate a unique seed from the job name.
Args:
job_name (str): job_name of the current job to generate the seed
seed (int): integer to access part of the seed
Returns:
int: random seed generated based on the hash
"""
return int(
str(int(hashlib.sha256(job_name.encode()).hexdigest(), 16))[
5 * seed : 5 * seed + 5
]
)
[docs]
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,
job_name="",
rotation_matrix=None,
):
"""
Set an MD calculation within LAMMPS. Nosé Hoover is used by default.
Args:
temperature (None/float/list): Target temperature value(-s). If set to None, an NVE
calculation is performed. It is required when the pressure is set or langevin is set
It can be a list of temperature values, containing the initial target temperature and
the final target temperature (in between the target value is varied linearly).
pressure (None/float/numpy.ndarray/list): Target pressure. If set to None, an NVE or an
NVT calculation is performed. If set to a scalar, the shear of the cell and the
ratio of the x, y, and z components is kept constant, while an isotropic, hydrostatic
pressure is applied. A list of up to length 6 can be given to specify xx, yy, zz, xy,
xz, and yz components of the pressure tensor, respectively. These values can mix
floats and `None` to allow only certain degrees of cell freedom to change. (Default
is None, run isochorically.)
n_ionic_steps (int): Number of ionic steps
time_step (float): Step size in fs between two steps.
n_print (int): Print frequency
temperature_damping_timescale (float): The time associated with the thermostat adjusting
the temperature. (In fs. After rescaling to appropriate time units, is equivalent to
Lammps' `Tdamp`.)
pressure_damping_timescale (float): The time associated with the barostat adjusting the
temperature. (In fs. After rescaling to appropriate time units, is equivalent to
Lammps' `Pdamp`.)
seed (int): Seed for the random number generation used for the intiial velocity creation
and langevin dynamics - otherwise ignored. If not specified, the seed is created via
job name
tloop:
initial_temperature (None/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 (bool): (True or False) Activate Langevin dynamics
delta_temp (float): Thermostat timescale, but in your Lammps time units, whatever those
are. (DEPRECATED.)
delta_press (float): Barostat timescale, but in your Lammps time units, whatever those
are. (DEPRECATED.)
job_name (str): Job name of the job to generate a unique random seed.
rotation_matrix (numpy.ndarray): The rotation matrix from the pyiron to Lammps coordinate
frame.
"""
if self["units"] not in LAMMPS_UNIT_CONVERSIONS.keys():
raise NotImplementedError
time_units = LAMMPS_UNIT_CONVERSIONS[self["units"]]["time"]
temperature_units = LAMMPS_UNIT_CONVERSIONS[self["units"]]["temperature"]
# Transform time
if time_step is not None:
try:
self["timestep"] = time_step * time_units
except KeyError:
raise NotImplementedError()
# Transform thermostat strength (time)
if delta_temp is not None:
warnings.warn(
"WARNING: `delta_temp` is deprecated, please use `temperature_damping_timescale`."
)
temperature_damping_timescale = delta_temp
else:
temperature_damping_timescale *= time_units
# Transform barostat strength (time)
if delta_press is not None:
warnings.warn(
"WARNING: `delta_press` is deprecated, please use `pressure_damping_timescale`."
)
pressure_damping_timescale = delta_press
else:
pressure_damping_timescale *= time_units
# Transform temperature
if temperature is not None:
temperature = np.array([temperature], dtype=float).flatten()
if len(temperature) == 1:
temperature = np.array(2 * temperature.tolist())
elif len(temperature) != 2:
raise ValueError(
"At most two temperatures can be provided "
"(for a linearly ramping target temperature), "
"but got {}".format(len(temperature))
)
temperature *= temperature_units
# Apply initial overheating (default uses the theorem of equipartition of energy between KE and PE)
if initial_temperature is None and temperature is not None:
initial_temperature = 2 * temperature[0]
if seed is None:
seed = self.generate_seed_from_job(job_name=job_name)
if seed <= 0:
raise ValueError("Seed must be a positive integer larger than 0")
# Set thermodynamic ensemble
if pressure is not None: # NPT
if temperature is None or temperature.min() <= 0:
raise ValueError(
"Target temperature for fix nvt/npt/nph cannot be 0 or negative"
)
self._force_skewed = False
pressure = self.pressure_to_lammps(pressure, rotation_matrix)
if np.isscalar(pressure):
pressure_string = " iso {0} {0} {1}".format(
pressure, pressure_damping_timescale
)
else:
pressure_string = ""
for ii, (coord, value) in enumerate(
zip(["x", "y", "z", "xy", "xz", "yz"], pressure)
):
if value is not None:
pressure_string += " {0} {1} {1} {2}".format(
coord, value, pressure_damping_timescale
)
if ii > 2:
self._force_skewed = True
if langevin: # NPT(Langevin)
fix_ensemble_str = "all nph" + pressure_string
self.modify(
fix___langevin="all langevin {0} {1} {2} {3} zero yes".format(
str(temperature[0]),
str(temperature[1]),
str(temperature_damping_timescale),
str(seed),
),
append_if_not_present=True,
)
else: # NPT(Nose-Hoover)
fix_ensemble_str = "all npt temp {0} {1} {2}".format(
str(temperature[0]),
str(temperature[1]),
str(temperature_damping_timescale),
)
fix_ensemble_str += pressure_string
elif temperature is not None: # NVT
if temperature.min() <= 0:
raise ValueError(
"Target temperature for fix nvt/npt/nph cannot be 0 or negative"
)
if langevin: # NVT(Langevin)
fix_ensemble_str = "all nve"
self.modify(
fix___langevin="all langevin {0} {1} {2} {3} zero yes".format(
str(temperature[0]),
str(temperature[1]),
str(temperature_damping_timescale),
str(seed),
),
append_if_not_present=True,
)
else: # NVT(Nose-Hoover)
fix_ensemble_str = "all nvt temp {0} {1} {2}".format(
str(temperature[0]),
str(temperature[1]),
str(temperature_damping_timescale),
)
else: # NVE
if langevin:
warnings.warn("Temperature not set; Langevin ignored.")
fix_ensemble_str = "all nve"
if tloop is not None:
fix_ensemble_str += " tloop " + str(tloop)
self.remove_keys(["minimize"])
self.modify(
fix___ensemble=fix_ensemble_str,
variable___dumptime=" equal {} ".format(n_print),
variable___thermotime=" equal {} ".format(n_print),
run=int(n_ionic_steps),
append_if_not_present=True,
)
if initial_temperature is not None and initial_temperature > 0:
self.set_initial_velocity(
temperature=initial_temperature,
seed=seed,
gaussian=True,
job_name=job_name,
)
[docs]
def calc_vcsgc(
self,
mu,
ordered_element_list,
target_concentration=None,
kappa=1000.0,
mc_step_interval=100,
swap_fraction=0.1,
temperature_mc=None,
window_size=None,
window_moves=None,
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,
initial_temperature=None,
langevin=False,
job_name="",
rotation_matrix=None,
):
"""
Run variance-constrained semi-grand-canonical MD/MC for a binary system. In addition to VC-SGC arguments, all
arguments for a regular MD calculation are also accepted.
https://vcsgc-lammps.materialsmodeling.org
Note:
For easy visualization later (with `get_structure`), it is highly recommended that the initial structure
contain at least one atom of each species.
Warning:
Assumes the units are metal, otherwise units for the constraints may be off.
Args:
mu (dict): A dictionary of chemical potentials, one for each element the potential treats, where the
dictionary keys are just the chemical symbol. Note that only the *relative* chemical potentials are used
here, such that the swap acceptance probability is influenced by the chemical potential difference
between the two species (a more negative value increases the odds of swapping *to* that element.)
ordered_element_list (list): A list of the chemical species symbols in the order they appear in the
definition of the potential in the Lammps' input file.
target_concentration: A dictionary of target simulation domain concentrations for each species *in the
potential*. Dictionary keys should be the chemical symbol of the corresponding species, and the sum of
all concentrations must be 1. (Default is None, which runs regular semi-grand-canonical MD/MC without
any variance constraint.)
kappa: Variance constraint for the MC. Larger value means a tighter adherence to the target concentrations.
(Default is 1000.)
mc_step_interval (int): How many steps of MD between each set of MC moves. (Default is 100.) Must divide the
number of ionic steps evenly.
swap_fraction (float): The fraction of atoms whose species is swapped at each MC phase. (Default is 0.1.)
temperature_mc (float): The temperature for accepting MC steps. (Default is None, which uses the MD
temperature.)
window_size (float): The size of the sampling window for parallel calculations as a fraction of something
unspecified in the VC-SGC docs, but it must lie between 0.5 and 1. (Default is None, window is
determined automatically.)
window_moves (int): The number of times the sampling window is moved during one MC cycle. (Default is None,
number of moves is determined automatically.)
rotation_matrix (numpy.ndarray): The rotation matrix from the pyiron to Lammps coordinate frame.
"""
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=None,
initial_temperature=initial_temperature,
langevin=langevin,
job_name=job_name,
rotation_matrix=rotation_matrix,
)
if self["units"] not in LAMMPS_UNIT_CONVERSIONS.keys():
raise NotImplementedError
temperature_units = LAMMPS_UNIT_CONVERSIONS[self["units"]]["temperature"]
energy_units = LAMMPS_UNIT_CONVERSIONS[self["units"]]["energy"]
if temperature_mc is None:
if temperature is None:
raise ValueError("If temperature is not given, temperature_mc must be.")
temperature_mc = temperature * temperature_units
if seed is None:
seed = self.generate_seed_from_job(job_name=job_name)
if set(mu.keys()) != set(ordered_element_list):
raise ValueError(
"Exactly one chemical potential must be given for each element treated by the potential."
)
calibrating_el = ordered_element_list[0]
# Apply the actual SGC string
fix_vcsgc_str = "all sgcmc {0} {1} {2} {3} randseed {4}".format(
str(mc_step_interval),
str(swap_fraction),
str(temperature_mc),
str(
" ".join(
str((mu[el] - mu[calibrating_el]) * energy_units)
for el in ordered_element_list[1:]
)
),
str(seed),
)
# Add VC to the SGC if target concentrations were provided
if target_concentration is not None:
if set(target_concentration.keys()) != set(ordered_element_list):
raise ValueError(
"Exactly one target concentration must be given for each element treated by the "
"potential."
)
if not np.isclose(np.sum([v for _, v in target_concentration.items()]), 1):
raise ValueError(
"Target concentrations must sum to 1 but were {}.".format(
np.sum([v for _, v in target_concentration.items()])
)
)
fix_vcsgc_str += " variance {0} {1}".format(
str(kappa),
str(
" ".join(
[
str(target_concentration[el])
for el in ordered_element_list[1:]
]
)
),
)
# Set optional windowing parameters
if window_moves is not None:
if int(window_moves) != window_moves or window_moves < 0:
raise ValueError("Window moves must be a non-negative integer.")
fix_vcsgc_str += " window_moves {0}".format(window_moves)
if window_size is not None:
if not 0.5 <= window_size <= 1.0:
raise ValueError("Window size must be a fraction between 0.5 and 1")
fix_vcsgc_str += " window_size {0}".format(window_size)
self.modify(fix___vcsgc=fix_vcsgc_str, append_if_not_present=True)
[docs]
def measure_mean_value(self, key, every=1, repeat=None, name=None, atom=False):
"""
Args:
key (str): property to take an average value of (e.g. 'energy_pot' v.i.)
every (int): number of steps there should be between two measurements
repeat (int): number of measurements for each output (default: n_print/every)
name (str): name to give in the output string (ignored if a pyiron predefined tag is used)
Comments:
Currently available keys: 'energy_pot', 'energy_tot', 'temperature', 'volume',
'pressures', 'positions', 'forces, 'velocities'
Future keys: 'cells'
"""
if every <= 0:
raise AssertionError("every must be a positive integer")
if repeat is None:
self["variable___mean_repeat_times"] = (
"equal round(${thermotime}/" + str(every) + ")"
)
else:
self["variable___mean_repeat_times"] = "equal {}".format(repeat)
if key == "energy_pot":
self._measure_mean_value("energy_pot", "pe", every)
elif key == "energy_tot":
self._measure_mean_value("energy_tot", "etotal", every)
elif key == "temperature":
self._measure_mean_value("temperature", "temp", every)
elif key == "volume":
self._measure_mean_value("volume", "vol", every)
elif key == "pressures":
self._measure_mean_value(
"pressure", ["pxx", "pyy", "pzz", "pxy", "pxz", "pyz"], every
)
elif key == "positions":
self["compute___unwrap"] = "all property/atom xu yu zu"
self["fix___mean_positions"] = (
"all ave/atom "
+ str(every)
+ " ${mean_repeat_times} ${thermotime} c_unwrap[*]"
)
self["dump___1"] = (
self["dump___1"]
+ " "
+ " ".join(["f_mean_positions[{}]".format(ii + 1) for ii in range(3)])
)
self["dump_modify___1"] = (
self["dump_modify___1"][:-1] + " " + " ".join(["%20.15g"] * 3) + '"'
)
elif key == "forces":
self._measure_mean_value("forces", ["fx", "fy", "fz"], every, atom=True)
elif key == "velocities":
self._measure_mean_value("velocities", ["vx", "vy", "vz"], every, atom=True)
elif name is not None:
if "**" in key:
warnings.warn("** is replaced by ^ (as it is understood by LAMMPS)")
key = key.replace("**", "^")
self._measure_mean_value(name, key, every, atom)
else:
raise NotImplementedError(key + " is not implemented")
[docs]
def energy_pot_per_atom(self):
"""
Enable the output of per atom potential energies. This will add an additional key 'energy_pot_per_atom' to the HDF output.
"""
if self["compute___energy_pot_per_atom"] is None:
self["compute___energy_pot_per_atom"] = "all pe/atom"
self["dump___1"] += " c_energy_pot_per_atom"
self["dump_modify___1"] = self["dump_modify___1"][:-1] + ' %20.15g"'
[docs]
def energy_kin_per_atom(self):
"""
Enable the output of per atom kinetic energies. This will add an additional key 'energy_kin_per_atom' to the HDF output.
"""
if self["compute___energy_kin_per_atom"] is None:
self["compute___energy_kin_per_atom"] = "all ke/atom"
self["dump___1"] += " c_energy_kin_per_atom"
self["dump_modify___1"] = self["dump_modify___1"][:-1] + ' %20.15g"'
def _set_group_by_id(self, group_name, ids):
if len(ids) < 1:
raise ValueError(
"Group ids must have at least length one, but got {}".format(ids)
)
if np.any(
[
isinstance(id_, bool) or not isinstance(id_, (int, np.integer))
for id_ in ids
]
):
# Note: it turns out bool is a subclass of int. Weird, eh.
raise TypeError("Group ids must be integers, but got {}".format(ids))
if np.any(np.array(ids) < 0):
raise ValueError(
"Group ids must be non-negative to be parsed by Lammps, but got {}".format(
ids
)
)
self["group___{}".format(group_name)] = "id {}".format(
" ".join(np.array(ids).astype(int).astype(str))
)
def _fix_with_three_vector(self, ids, vector, fix_string, conversion):
if len(vector) != 3:
raise ValueError(
"{} must have three components, but got {}".format(fix_string, vector)
)
vector = list(vector)
for i, v in enumerate(vector):
if v is None:
vector[i] = "NULL"
else:
vector[i] = str(v * conversion)
name = str(hash(tuple(ids))).replace("-", "m") # A unique name for the group
self._set_group_by_id(name, ids)
self["fix___{}_{}".format(fix_string.replace(" ", "_"), name)] = (
"{} {} {}".format(name, fix_string, " ".join(vector))
)
[docs]
def fix_move_linear_by_id(self, ids, velocity):
"""
Displace atoms at each timestep. Creates a new group with a unique name based off the hash of the ids.
Args:
ids (list/numpy.ndarray): Integer ids of the atoms to move in the job's structure.
velocity (list/numpy.ndarray/tuple): The velocity in x-y-z-direction for the group. `None` arguments are
converted to Lammps 'NULL' values and the velocity in this direction is left unchanged.
Warning: This fix does not exclude these atoms from [other fixes](https://lammps.sandia.gov/doc/fix_move.html).
You may wish to combine this call with `selective_dynamics` on your corresponding structure. Future
developers can find a more complete discussion [here](https://github.com/pyiron/pyiron/pull/1212) when
further modifying this capability. Further, it will malfunction if the Lammps coordinate frame and pyiron
coordinate frame differ.
"""
warnings.warn(
"This fix does not exclude these atoms from other fixes. You may wish to combine this call with "
"`selective_dynamics` on your corresponding structure. Further, it will malfunction if the "
"Lammps coordinate frame and pyiron coordinate frame differ."
)
self._fix_with_three_vector(
ids,
velocity,
"move linear",
LAMMPS_UNIT_CONVERSIONS[self["units"]]["velocity"],
)
[docs]
def fix_setforce_by_id(self, ids, force):
"""
Set the force on a collection of atoms to a specified value.
ids (list/numpy.ndarray): Integer ids of the atoms to move in the job's structure.
force (list/numpy.ndarray/tuple): The force in x-y-z-direction for the group. `None` arguments are
converted to Lammps 'NULL' values and the force in this direction is left unchanged.
Warning: This fix will malfunction (silently) if the Lammps coordinate frame and pyiron coordinate frame differ.
"""
warnings.warn(
"This fix will malfunction (silently) if the Lammps coordinate frame and pyiron coordinate frame "
"differ."
)
self._fix_with_three_vector(
ids, force, "setforce", LAMMPS_UNIT_CONVERSIONS[self["units"]]["force"]
)
def _measure_mean_value(self, key_pyiron, key_lmp, every, atom=False):
"""
Args:
key (str): property to take an average value of (e.g. 'energy_pot' v.i.)
every (int): number of steps there should be between two measurements
repeat (int): number of measurements for each output (default: n_print/every)
freq (int): output frequency (default: n_print)
Comments:
Currently available keys: 'energy_pot', 'energy_tot', 'temperature', 'volume',
'pressures', 'psitions', 'forces, 'velocities'
Future keys: 'cells'
"""
if isinstance(key_lmp, str):
self["variable___{}".format(key_pyiron)] = "equal {}".format(key_lmp)
self["fix___mean_{}".format(key_pyiron)] = (
"all ave/time "
+ str(every)
+ " ${mean_repeat_times} ${thermotime} v_"
+ str(key_pyiron)
)
self["thermo_style"] = self["thermo_style"] + " f_mean_{}".format(
key_pyiron
)
else:
if atom is True:
for ii, _ in enumerate(key_lmp):
self["variable___{}_{}".format(key_pyiron, ii)] = "atom {}".format(
key_lmp[ii]
)
self["fix___mean_{}".format(key_pyiron)] = (
"all ave/atom "
+ str(every)
+ " ${mean_repeat_times} ${thermotime} "
+ str(
" ".join(
[
"v_{}_{}".format(key_pyiron, ii)
for ii in range(len(key_lmp))
]
)
)
)
self["dump___1"] = (
self["dump___1"]
+ " "
+ " ".join(
[
"f_mean_{}[{}]".format(key_pyiron, ii + 1)
for ii in range(len(key_lmp))
]
)
)
self["dump_modify___1"] = (
self["dump_modify___1"][:-1]
+ " "
+ " ".join(["%20.15g"] * len(key_lmp))
+ '"'
)
else:
for ii, _ in enumerate(key_lmp):
self["variable___{}_{}".format(key_pyiron, ii)] = "equal {}".format(
key_lmp[ii]
)
self["fix___mean_{}".format(key_pyiron)] = (
"all ave/time "
+ str(every)
+ " ${mean_repeat_times} ${thermotime} "
+ str(
" ".join(
[
"v_{}_{}".format(key_pyiron, ii)
for ii in range(len(key_lmp))
]
)
)
)
self["thermo_style"] = (
self["thermo_style"]
+ " "
+ " ".join(
[
"f_mean_{}[{}]".format(key_pyiron, ii + 1)
for ii in range(len(key_lmp))
]
)
)
