deepmd.infer.deep_property

deepmd.infer.deep_property#

Properties of structures.

class deepmd.infer.deep_property.DeepProperty(model_file: str, *args: Any, auto_batch_size: bool | int | deepmd.utils.batch_size.AutoBatchSize = True, neighbor_list: ase.neighborlist.NewPrimitiveNeighborList | None = None, **kwargs: Any)[source]#

Properties of structures.

Parameters:

model_filePath: The name of the frozen model file.
*argslist: Positional arguments.
auto_batch_sizebool or int or AutoBatchSize, default: True: If True, automatic batch size will be used. If int, it will be used as the initial batch size.
neighbor_listase.neighborlist.NewPrimitiveNeighborList, optional: The ASE neighbor list class to produce the neighbor list. If None, the neighbor list will be built natively in the model.
**kwargsdict: Keyword arguments.

output_def() → deepmd.dpmodel.output_def.ModelOutputDef[source]#: Get the output definition of this model. But in property_fitting, the output definition is not known until the model is loaded. So we need to rewrite the output definition after the model is loaded. See detail in change_output_def.

change_output_def() → None[source]#: Change the output definition of this model. In property_fitting, the output definition is known after the model is loaded. We need to rewrite the output definition and related information.

eval(coords: numpy.ndarray, cells: numpy.ndarray | None, atom_types: list[int] | numpy.ndarray, atomic: bool = False, fparam: numpy.ndarray | None = None, aparam: numpy.ndarray | None = None, mixed_type: bool = False, **kwargs: dict[str, Any]) → tuple[numpy.ndarray, Ellipsis][source]#

Evaluate properties. If atomic is True, also return atomic property.

Parameters:

coordsnp.ndarray: The coordinates of the atoms, in shape (nframes, natoms, 3).
cellsnp.ndarray: The cell vectors of the system, in shape (nframes, 9). If the system is not periodic, set it to None.
atom_typeslist[int] or np.ndarray: The types of the atoms. If mixed_type is False, the shape is (natoms,); otherwise, the shape is (nframes, natoms).
atomicbool, optional: Whether to return atomic property, by default False.
fparamnp.ndarray, optional: The frame parameters, by default None.
aparamnp.ndarray, optional: The atomic parameters, by default None.
mixed_typebool, optional: Whether the atom_types is mixed type, by default False.
**kwargsdict[str, Any]: Keyword arguments.

Returns: