/
potential.py
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/
potential.py
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# 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 pandas as pd
import shutil
import os
from pyiron_base import state, GenericParameters
from pyiron_atomistics.atomistics.job.potentials import (
PotentialAbstract,
find_potential_file_base,
)
__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"
class LammpsPotential(GenericParameters):
"""
This module helps write commands which help in the control of parameters related to the potential used in LAMMPS
simulations
"""
def __init__(self, input_file_name=None):
super(LammpsPotential, self).__init__(
input_file_name=input_file_name,
table_name="potential_inp",
comment_char="#",
)
self._potential = None
self._attributes = {}
self._df = None
@property
def df(self):
return self._df
@df.setter
def df(self, new_dataframe):
self._df = new_dataframe
# ToDo: In future lammps should also support more than one potential file - that is currently not implemented.
try:
self.load_string("".join(list(new_dataframe["Config"])[0]))
except IndexError:
raise ValueError(
"Potential not found! "
"Validate the potential name by self.potential in self.list_potentials()."
)
def remove_structure_block(self):
self.remove_keys(["units"])
self.remove_keys(["atom_style"])
self.remove_keys(["dimension"])
@property
def files(self):
if len(self._df["Filename"].values[0]) > 0 and self._df["Filename"].values[
0
] != [""]:
absolute_file_paths = [
files for files in list(self._df["Filename"])[0] if os.path.isabs(files)
]
relative_file_paths = [
files
for files in list(self._df["Filename"])[0]
if not os.path.isabs(files)
]
env = os.environ
resource_path_lst = state.settings.resource_paths
for conda_var in ["CONDA_PREFIX", "CONDA_DIR"]:
if conda_var in env.keys(): # support iprpy-data package
path_to_add = state.settings.convert_path_to_abs_posix(
os.path.join(env[conda_var], "share", "iprpy")
)
if path_to_add not in resource_path_lst:
resource_path_lst.append(path_to_add)
for path in relative_file_paths:
absolute_file_paths.append(
find_potential_file_base(
path=path,
resource_path_lst=resource_path_lst,
rel_path=os.path.join("lammps", "potentials"),
)
)
if len(absolute_file_paths) != len(list(self._df["Filename"])[0]):
raise ValueError("Was not able to locate the potentials.")
else:
return absolute_file_paths
def copy_pot_files(self, working_directory):
if self.files is not None:
_ = [shutil.copy(path_pot, working_directory) for path_pot in self.files]
def get_element_lst(self):
return list(self._df["Species"])[0]
def _find_line_by_prefix(self, prefix):
"""
Find a line that starts with the given prefix. Differences in white
space are ignored. Raises a ValueError if not line matches the prefix.
Args:
prefix (str): line prefix to search for
Returns:
list: words of the matching line
Raises:
ValueError: if not matching line was found
"""
def isprefix(prefix, lst):
if len(prefix) > len(lst):
return False
return all(n == l for n, l in zip(prefix, lst))
# compare the line word by word to also match lines that differ only in
# whitespace
prefix = prefix.split()
for parameter, value in zip(self._dataset["Parameter"], self._dataset["Value"]):
words = (parameter + " " + value).strip().split()
if isprefix(prefix, words):
return words
raise ValueError('No line with prefix "{}" found.'.format(" ".join(prefix)))
def get_element_id(self, element_symbol):
"""
Return numeric element id for element. If potential does not contain
the element raise a :class:NameError. Only makes sense for potentials
with pair_style "full".
Args:
element_symbol (str): short symbol for element
Returns:
int: id matching the given symbol
Raise:
NameError: if potential does not contain this element
"""
try:
line = "group {} type".format(element_symbol)
return int(self._find_line_by_prefix(line)[3])
except ValueError:
msg = "potential does not contain element {}".format(element_symbol)
raise NameError(msg) from None
def get_charge(self, element_symbol):
"""
Return charge for element. If potential does not specify a charge,
raise a :class:NameError. Only makes sense for potentials
with pair_style "full".
Args:
element_symbol (str): short symbol for element
Returns:
float: charge speicified for the given element
Raises:
NameError: if potential does not specify charge for this element
"""
try:
line = "set group {} charge".format(element_symbol)
return float(self._find_line_by_prefix(line)[4])
except ValueError:
msg = "potential does not specify charge for element {}".format(
element_symbol
)
raise NameError(msg) from None
def to_hdf(self, hdf, group_name=None):
if self._df is not None:
with hdf.open("potential") as hdf_pot:
hdf_pot["Config"] = self._df["Config"].values[0]
hdf_pot["Filename"] = self._df["Filename"].values[0]
hdf_pot["Name"] = self._df["Name"].values[0]
hdf_pot["Model"] = self._df["Model"].values[0]
hdf_pot["Species"] = self._df["Species"].values[0]
if "Citations" in self._df.columns.values:
hdf_pot["Citations"] = self._df["Citations"].values[0]
super(LammpsPotential, self).to_hdf(hdf, group_name=group_name)
def from_hdf(self, hdf, group_name=None):
with hdf.open("potential") as hdf_pot:
try:
entry_dict = {
"Config": [hdf_pot["Config"]],
"Filename": [hdf_pot["Filename"]],
"Name": [hdf_pot["Name"]],
"Model": [hdf_pot["Model"]],
"Species": [hdf_pot["Species"]],
}
if "Citations" in hdf_pot.list_nodes():
entry_dict["Citations"] = [hdf_pot["Citations"]]
self._df = pd.DataFrame(entry_dict)
except ValueError:
pass
super(LammpsPotential, self).from_hdf(hdf, group_name=group_name)
class LammpsPotentialFile(PotentialAbstract):
"""
The Potential class is derived from the PotentialAbstract class, but instead of loading the potentials from a list,
the potentials are loaded from a file.
Args:
potential_df:
default_df:
selected_atoms:
"""
def __init__(self, potential_df=None, default_df=None, selected_atoms=None):
if potential_df is None:
potential_df = self._get_potential_df(
plugin_name="lammps",
file_name_lst={"potentials_lammps.csv"},
backward_compatibility_name="lammpspotentials",
)
super(LammpsPotentialFile, self).__init__(
potential_df=potential_df,
default_df=default_df,
selected_atoms=selected_atoms,
)
def default(self):
if self._default_df is not None:
atoms_str = "_".join(sorted(self._selected_atoms))
return self._default_df[
(self._default_df["Name"] == self._default_df.loc[atoms_str].values[0])
]
return None
def find_default(self, element):
"""
Find the potentials
Args:
element (set, str): element or set of elements for which you want the possible LAMMPS potentials
path (bool): choose whether to return the full path to the potential or just the potential name
Returns:
list: of possible potentials for the element or the combination of elements
"""
if isinstance(element, set):
element = element
elif isinstance(element, list):
element = set(element)
elif isinstance(element, str):
element = set([element])
else:
raise TypeError("Only, str, list and set supported!")
element_lst = list(element)
if self._default_df is not None:
merged_lst = list(set(self._selected_atoms + element_lst))
atoms_str = "_".join(sorted(merged_lst))
return self._default_df[
(self._default_df["Name"] == self._default_df.loc[atoms_str].values[0])
]
return None
def __getitem__(self, item):
potential_df = self.find(element=item)
selected_atoms = self._selected_atoms + [item]
return LammpsPotentialFile(
potential_df=potential_df,
default_df=self._default_df,
selected_atoms=selected_atoms,
)
class PotentialAvailable(object):
def __init__(self, list_of_potentials):
self._list_of_potentials = {
"pot_" + v.replace("-", "_").replace(".", "_"): v
for v in list_of_potentials
}
def __getattr__(self, name):
if name in self._list_of_potentials.keys():
return self._list_of_potentials[name]
else:
raise AttributeError
def __dir__(self):
return list(self._list_of_potentials.keys())
def __repr__(self):
return str(dir(self))