pyiron_atomistics.lammps.potential.LammpsPotential

class pyiron_atomistics.lammps.potential.LammpsPotential(input_file_name=None)

Bases: GenericParameters

This module helps write commands which help in the control of parameters related to the potential used in LAMMPS simulations

__init__(input_file_name=None)

Methods

__init__([input_file_name])
clear_all()	Clears all fields in the object
copy_pot_files(working_directory)
define_blocks(block_dict)	Define a block section within the GenericParameters
from_dict(obj_dict[, version])	Populate the object from the serialized object.
from_hdf(hdf[, group_name])	Restore the GenericParameters from an HDF5 file
get(parameter_name[, default_value])	Get the value of a specific parameter from GenericParameters - if the parameter is not available return default_value if that is set.
get_attribute(attribute_name)	Get the value of a specific parameter from GenericParameters
get_charge(element_symbol)	Return charge for element.
get_element_id(element_symbol)	Return numeric element id for element.
get_element_lst()
get_pandas()	Output the GenericParameters object as Pandas Dataframe for human readability.
get_string_lst()	Get list of strings from GenericParameters to write to input file
instantiate(obj_dict[, version])	Create a blank instance of this class.
keys()	Return keys of GenericParameters object
load_default()	Load defaults resets the dataset in the background to be empty
load_string(input_str)	Load a multi line string to overwrite the current parameter settings
modify([separator, append_if_not_present])	Modify values for existing parameters.
read_input(file_name[, ignore_trigger])	Read input file and store the data in GenericParameters - this overwrites the current parameter settings
remove_keys(key_list)	Remove a list of keys from the GenericParameters
remove_structure_block()
set([separator])	Set the value of multiple parameters or create new parameter key, if they do not exist already.
set_dict(dictionary)	Set a dictionary of key value pairs
set_value(line, val)	Set the value of a parameter in a specific line
to_dict()	Reduce the object to a dictionary.
to_hdf(hdf[, group_name])	Store the GenericParameters in an HDF5 file
write_file(file_name[, cwd])	Write GenericParameters to input file

Attributes

comment_char	Get the separator that characterizes comment
df
end_value_char	Get the special character at the end of every line
file_name	Get the file name of the input file
files
multi_word_separator	Get the multi word separator to have multi word keys
replace_char_dict	Get the dictionary to replace certain character combinations
separator_char	Get the separator that characterizes the split between key and value
table_name	Get the name of the input table inside the HDF5 file
val_only	Get the boolean option to switch from a key value list to an value only input file

clear_all() → None

Clears all fields in the object

property comment_char: str | None

Get the separator that characterizes comment

Returns:

comment character

Return type:

str

define_blocks(block_dict: Dict[str, List[str]]) → None

Define a block section within the GenericParameters

Parameters:

block_dict (dict) – dictionary to define the block

property end_value_char: str | None

Get the special character at the end of every line

Returns:

end of line character

Return type:

str

property file_name: str | None

Get the file name of the input file

Returns:

file name

Return type:

str

from_dict(obj_dict, version: str = None)

Populate the object from the serialized object.

Parameters:

• obj_dict (dict) – data previously returned from to_dict()

• version (str) – version tag written together with the data

from_hdf(hdf, group_name=None)

Restore the GenericParameters from an HDF5 file

Parameters:

• hdf (ProjectHDFio) – HDF5 group object

• group_name (str) – HDF5 subgroup name - optional

get(parameter_name: str, default_value: str | None = None) → str | None

Get the value of a specific parameter from GenericParameters - if the parameter is not available return default_value if that is set.

Parameters:

• parameter_name (str) – parameter key

• default_value (str) – default value to return is the parameter is not set

Returns:

value of the parameter

Return type:

str

get_attribute(attribute_name: str) → str | None

Get the value of a specific parameter from GenericParameters

Parameters:

attribute_name (str) – parameter key

Returns:

value of the parameter

Return type:

str

get_charge(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”.

Parameters:

element_symbol (str) – short symbol for element

Returns:

charge speicified for the given element

Return type:

float

Raises:

NameError – if potential does not specify charge for this element

get_element_id(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”.

Parameters:

element_symbol (str) – short symbol for element

Returns:

id matching the given symbol

Return type:

int

Raises:

NameError – if potential does not contain this element

get_pandas() → DataFrame

Output the GenericParameters object as Pandas Dataframe for human readability.

Returns:

Pandas Dataframe of the GenericParameters object

Return type:

pandas.DataFrame

get_string_lst() → List[str]

Get list of strings from GenericParameters to write to input file

Returns:

List of strings representing the GenericParameters object

Return type:

List[str]

classmethod instantiate(obj_dict: dict, version: str = None) → Self

Create a blank instance of this class.

This can be used when some values are already necessary for the objects __init__.

Parameters:

• obj_dict (dict) – data previously returned from to_dict()

• version (str) – version tag written together with the data

Returns:

a blank instance of the object that is sufficiently initialized to call _from_dict() on it

Return type:

object

keys() → List[str]

Return keys of GenericParameters object

load_default() → None

Load defaults resets the dataset in the background to be empty

load_string(input_str: str) → None

Load a multi line string to overwrite the current parameter settings

Parameters:

input_str (str) – multi line string

modify(separator: str | None = None, append_if_not_present: bool = False, **modify_dict: str | bool) → None

Modify values for existing parameters. The command is called as modify(param1=val1, param2=val2, …)

Parameters:

• separator (str) – needed if the parameter name contains special characters such as par: use then as input: modify(separator=”:”, par=val) - optional

• append_if_not_present (bool) – do not raise an exception but append the parameter in practice use set(par=val) - default=False

• **modify_dict (dict) – dictionary of parameter names and values

property multi_word_separator: str | None

Get the multi word separator to have multi word keys

Returns:

multi word separator

Return type:

str

read_input(file_name: str, ignore_trigger: str | None = None) → None

Read input file and store the data in GenericParameters - this overwrites the current parameter settings

Parameters:

• file_name (str) – absolute path to the input file

• ignore_trigger (str) – trigger for lines to be ignored

remove_keys(key_list: List[str]) → None

Remove a list of keys from the GenericParameters

Parameters:

key_list (list) – list of keys to be removed

property replace_char_dict: Dict[str, str] | None

Get the dictionary to replace certain character combinations

Returns:

character replace dictionary

Return type:

dict

property separator_char: str | None

Get the separator that characterizes the split between key and value

Returns:

separator character

Return type:

str

set(separator: str | None = None, **set_dict: str | bool) → None

Set the value of multiple parameters or create new parameter key, if they do not exist already.

Parameters:

• separator (float/int/str) – separator string - optional

• **set_dict (dict) – dictionary containing the parameter keys and their corresponding values to be set

set_dict(dictionary: Dict[str, str | bool]) → None

Set a dictionary of key value pairs

Parameters:

dictionary (dict) – dictionary of key value pairs

set_value(line: int, val: str | bytes) → None

Set the value of a parameter in a specific line

Parameters:

• line (float/int/str) – line number - starting with 0

• val (str/bytes) – value to be set

property table_name: str | None

Get the name of the input table inside the HDF5 file

Returns:

table name

Return type:

str

to_dict()

Reduce the object to a dictionary.

Returns:

serialized state of this object

Return type:

dict

to_hdf(hdf, group_name=None)

Store the GenericParameters in an HDF5 file

Parameters:

• hdf (ProjectHDFio) – HDF5 group object

• group_name (str) – HDF5 subgroup name - optional

property val_only: bool | None

Get the boolean option to switch from a key value list to an value only input file

Returns:

[True/False]

Return type:

bool

write_file(file_name: str, cwd: str | None = None) → None

Write GenericParameters to input file

Parameters:

• file_name (str) – name of the file, either absolute (then cwd must be None) or relative

• cwd (str) – path name (default: None)