Source code for qiskit_nature.second_q.formats.qcschema.qc_schema_input

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# (C) Copyright IBM 2022, 2023.
# This code is licensed under the Apache License, Version 2.0. You may
# obtain a copy of this license in the LICENSE.txt file in the root directory
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"""The QCSchema input dataclass."""

from __future__ import annotations

from dataclasses import dataclass
from typing import Any, Mapping, cast

import h5py

from .qc_base import _QCBase
from .qc_model import QCModel
from .qc_topology import QCTopology

[docs]@dataclass class QCSchemaInput(_QCBase): """A dataclass containing all *classical input* components of the QCSchema. For more information refer to [here]( """ schema_name: str """The name of this schema. This value is expected to be `qcschema` or `qc_schema`.""" schema_version: int """The version of this specific schema.""" molecule: QCTopology """An instance of :class:`QCTopology`.""" driver: str """The type of computation. Example values are `energy`, `gradient`, and `hessian`.""" model: QCModel """An instance of :class:`QCModel`.""" keywords: Mapping[str, Any] """Any additional program-specific parameters."""
[docs] @classmethod def from_dict(cls, data: dict[str, Any]) -> QCSchemaInput: model = QCModel(**data.pop("model")) molecule = QCTopology(**data.pop("molecule")) return cls(**data, model=model, molecule=molecule)
[docs] def to_hdf5(self, group: h5py.Group) -> None: group.attrs["schema_name"] = self.schema_name group.attrs["schema_version"] = self.schema_version group.attrs["driver"] = self.driver molecule_group = group.require_group("molecule") self.molecule.to_hdf5(molecule_group) model_group = group.require_group("model") self.model.to_hdf5(model_group) keywords_group = group.require_group("keywords") for key, value in self.keywords.items(): keywords_group.attrs[key] = value
@classmethod def _from_hdf5_group(cls, h5py_group: h5py.Group) -> QCSchemaInput: data = dict(h5py_group.attrs.items()) data["molecule"] = cast(QCTopology, QCTopology.from_hdf5(h5py_group["molecule"])) data["model"] = cast(QCModel, QCModel.from_hdf5(h5py_group["model"])) data["keywords"] = dict(h5py_group["keywords"].attrs.items()) return cls(**data)