Source code for gmso.core.bond_type

"""Defined interactions between two bonded partners."""

from typing import Optional, Tuple

import unyt as u
from pydantic import ConfigDict, Field

from gmso.core.parametric_potential import ParametricPotential
from gmso.utils.expression import PotentialExpression

[docs] class BondType(ParametricPotential): """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 " "defining the members of this bond type", alias="member_types", ) member_classes_: Optional[Tuple[str, str]] = Field( None, description="List-like of of gmso.AtomType.atomclass " "defining the members of this bond type", alias="member_classes", ) model_config = ConfigDict( alias_to_fields=dict( **ParametricPotential.model_config["alias_to_fields"], **{ "member_types": "member_types_", "member_classes": "member_classes_", }, ), ) def __init__( self, name="BondType", expression=None, parameters=None, independent_variables=None, potential_expression=None, member_types=None, member_classes=None, tags=None, ): super(BondType, self).__init__( name=name, expression=expression, parameters=parameters, independent_variables=independent_variables, potential_expression=potential_expression, member_types=member_types, member_classes=member_classes, tags=tags, ) @property def member_types(self): """Return the members involved in this bondtype.""" return self.__dict__.get("member_types_") @property def member_classes(self): return self.__dict__.get("member_classes_") @staticmethod def _default_potential_expr(): return PotentialExpression( expression="0.5 * k * (r-r_eq)**2", independent_variables={"r"}, parameters={ "k": 1000 * u.Unit("kJ / (nm**2)"), "r_eq": 0.14 * u.nm, }, )