def deprecate(self):
"""show deprecate message"""
warn_deprecated("0.2.0",
DeprecatedType.ENUM,
self.__class__.__name__,
new_name="NewEnum",
stack_level=3)
def __init__(self):
super().__init__(self.__class__.__name__)
warn_deprecated(
"0.4.0",
DeprecatedType.CLASS,
"PseudoProperty",
DeprecatedType.CLASS,
"Interpretable",
additional_msg=
("The PseudoProperty class is deprecated. Instead, of requiring an `interpret()` "
"method on the Property base-class, this is now handled via the `Interpretable` "
"protocol."),
)
def sample(self, problem: BaseProblem,
points: List[float]) -> BOPESSamplerResult:
"""Run the sampler at the given points, potentially with repetitions.
Args:
problem: BaseProblem whose driver should be based on a Molecule object that has
perturbations to be varied.
points: The points along the degrees of freedom to evaluate.
Returns:
BOPES Sampler Result
Raises:
QiskitNatureError: if the driver does not have a molecule specified.
"""
self._problem = problem
self._driver = problem.driver
if isinstance(self._driver, DeprecatedBaseDriver):
warn_deprecated(
"0.2.0",
DeprecatedType.CLASS,
f"{self._driver.__class__.__module__}.{self._driver.__class__.__qualname__}",
new_name=
"ElectronicStructureMoleculeDriver or VibrationalStructureMoleculeDriver",
additional_msg="from qiskit_nature.drivers.second_quantization",
)
elif not isinstance(self._driver,
(ElectronicStructureMoleculeDriver,
VibrationalStructureMoleculeDriver)):
raise QiskitNatureError(
"Driver must be ElectronicStructureMoleculeDriver or VibrationalStructureMoleculeDriver."
)
if self._driver.molecule is None:
raise QiskitNatureError(
"Driver MUST be configured with a Molecule.")
# full dictionary of points
self._raw_results = self._run_points(points)
# create results dictionary with (point, energy)
self._points = list(self._raw_results.keys())
self._energies = []
for res in self._raw_results.values():
energy = res.total_energies[0]
self._energies.append(energy)
result = BOPESSamplerResult(self._points, self._energies,
self._raw_results)
return result
def __init__(self, name: str) -> None:
"""
Args:
name: the name of the property.
"""
self._name = name
warn_deprecated(
"0.5.0",
old_type=DeprecatedType.CLASS,
old_name="qiskit_nature.properties.Property",
new_type=DeprecatedType.CLASS,
new_name="qiskit_nature.second_q.properties.Property",
category=NatureDeprecationWarning,
)
def __init__(self, values: Optional[ListOrDictType] = None):
"""
Args:
values: an optional object of `list` or `dict` type.
"""
warn_deprecated(
"0.5.0",
old_type=DeprecatedType.CLASS,
old_name="qiskit_nature.ListOrDict",
additional_msg=
(". Qiskit Nature will now always produce dictionary-style auxiliary operators."
),
category=NatureDeprecationWarning,
)
if isinstance(values, list):
values = dict(enumerate(values))
elif values is None:
values = {}
super().__init__(values)
def _run_single_point(self, point: float) -> EigenstateResult:
"""Run the sampler at the given single point
Args:
point: The value of the degree of freedom to evaluate.
Returns:
Results for a single point.
Raises:
QiskitNatureError: Invalid Driver
"""
# update molecule geometry and thus resulting Hamiltonian based on specified point
if isinstance(self._driver, DeprecatedBaseDriver):
warn_deprecated(
"0.2.0",
DeprecatedType.CLASS,
f"{self._driver.__class__.__module__}.{self._driver.__class__.__qualname__}",
new_name=
"ElectronicStructureMoleculeDriver or VibrationalStructureMoleculeDriver",
additional_msg="from qiskit_nature.drivers.second_quantization",
)
elif not isinstance(self._driver,
(ElectronicStructureMoleculeDriver,
VibrationalStructureMoleculeDriver)):
raise QiskitNatureError(
"Driver must be ElectronicStructureMoleculeDriver or VibrationalStructureMoleculeDriver."
)
self._driver.molecule.perturbations = [point]
# find closest previously run point and take optimal parameters
if isinstance(
self._gss.solver,
VariationalAlgorithm) and self._bootstrap: # type: ignore
prev_points = list(self._points_optparams.keys())
prev_params = list(self._points_optparams.values())
n_pp = len(prev_points)
# set number of points to bootstrap
if self._extrapolator is None:
n_boot = len(prev_points) # bootstrap all points
else:
n_boot = self._num_bootstrap
# Set initial params # if prev_points not empty
if prev_points:
if n_pp <= n_boot:
distances = np.array(point) - np.array(
prev_points).reshape(n_pp, -1)
# find min 'distance' from point to previous points
min_index = np.argmin(np.linalg.norm(distances, axis=1))
# update initial point
self._gss.solver.initial_point = prev_params[
min_index] # type: ignore
else: # extrapolate using saved parameters
opt_params = self._points_optparams
param_sets = self._extrapolator.extrapolate(
points=[point], param_dict=opt_params)
# update initial point, note param_set is a dictionary
self._gss.solver.initial_point = param_sets.get(
point) # type: ignore
# the output is an instance of EigenstateResult
result = self._gss.solve(self._problem)
# Save optimal point to bootstrap
if isinstance(self._gss.solver, VariationalAlgorithm): # type: ignore
# at every point evaluation, the optimal params are updated
optimal_params = result.raw_result.optimal_point
self._points_optparams[point] = optimal_params
return result
def __init__(self):
warn_deprecated("0.3.0", DeprecatedType.CLASS, "DeprecatedClass1",
DeprecatedType.CLASS, "NewClass")
self.value = 10
