from typing import Tuple, Optional
import unyt as u
from pydantic import Field
from gmso.core.parametric_potential import ParametricPotential
from gmso.utils._constants import BOND_TYPE_DICT
[docs]class BondType(ParametricPotential):
__base_doc__ = """A descripton of the interaction between 2 bonded partners.
This is a subclass of the gmso.core.Potential superclass.
BondType represents a bond type and includes the functional form describing
its interactions. The functional form of the potential is stored as a
`sympy` expression and the parameters, with units, are stored explicitly.
The AtomTypes that are used to define the bond type are stored as
`member_types`.
Notes
----
Inherits many functions from gmso.ParametricPotential:
__eq__, _validate functions
"""
member_types_: Optional[Tuple[str, str]] = Field(
None,
description='List-like of of gmso.AtomType.name or gmso.AtomType.atomclass '
'defining the members of this bond type'
)
def __init__(self,
name='BondType',
expression='0.5 * k * (r-r_eq)**2',
parameters=None,
independent_variables=None,
member_types=None,
topology=None,
tags=None):
if parameters is None:
parameters = {
'k': 1000 * u.Unit('kJ / (nm**2)'),
'r_eq': 0.14 * u.nm
}
if independent_variables is None:
independent_variables = {'r'}
super(BondType, self).__init__(
name=name,
expression=expression,
parameters=parameters,
independent_variables=independent_variables,
topology=topology,
member_types=member_types,
set_ref=BOND_TYPE_DICT,
tags=tags
)
@property
def member_types(self):
return self.__dict__.get('member_types_')
class Config:
fields = {
'member_types_': 'member_types'
}
alias_to_fields = {
'member_types': 'member_types_'
}