from abc import abstractmethod
from typing import Any, Dict, List, Tuple
import numpy as np
from quara.objects.qoperation import QOperation
from quara.protocol.qtomography.qtomography_estimator import (
QTomographyEstimator,
QTomographyEstimationResult,
)
from quara.protocol.qtomography.standard.standard_qtomography import StandardQTomography
[docs]class StandardQTomographyEstimationResult(QTomographyEstimationResult):
def __init__(
self,
qtomography: StandardQTomography,
data,
estimated_var_sequence: List[np.ndarray],
computation_times: List[float],
):
super().__init__(computation_times)
self._qtomography: StandardQTomography = qtomography
self._data = data
self._estimated_var_sequence: List[np.ndarray] = estimated_var_sequence
@property
def qtomography(self) -> StandardQTomography:
"""returns the StandardQTomography used for estimation.
Returns
-------
StandardQTomography
the StandardQTomography used for estimation.
"""
return self._qtomography
@property
def data(self) -> Any:
"""returns the data used for estimation.
Returns
-------
Any
returns the data used for estimation.
"""
return self._data
@property
def estimated_var(self) -> np.ndarray:
"""returns the estimate. the type of each estimate is ``np.ndarray``.
Returns
-------
np.ndarray
the estimate.
"""
return self._estimated_var_sequence[0]
@property
def estimated_var_sequence(self) -> List[np.ndarray]:
"""returns the estimate sequence. the type of each estimate is ``np.ndarray``.
Returns
-------
List[np.ndarray]
the estimate sequence.
"""
return self._estimated_var_sequence
@property
def estimated_qoperation(self) -> QOperation:
"""returns the estimate. the type of each estimate is ``QOperation``.
Returns
-------
QOperation
the estimate.
"""
qoperation = self._qtomography.convert_var_to_qoperation(
self._estimated_var_sequence[0]
)
return qoperation
@property
def estimated_qoperation_sequence(self) -> List[QOperation]:
"""returns the estimate sequence. the type of each estimate is ``QOperation``.
Returns
-------
List[QOperation]
the estimate sequence.
"""
qoperations = [
self._qtomography.convert_var_to_qoperation(var)
for var in self._estimated_var_sequence
]
return qoperations
@property
def num_data(self) -> List[int]:
num_data = [data[0][0] for data in self._data]
return num_data
[docs]class StandardQTomographyEstimator(QTomographyEstimator):
def __init__(self):
super().__init__()
[docs] @abstractmethod
def calc_estimate(
self,
qtomography: StandardQTomography,
empi_dists: List[Tuple[int, np.ndarray]],
is_computation_time_required: bool = False,
) -> StandardQTomographyEstimationResult:
"""calculates estimate variables.
this function must be implemented in the subclass.
Parameters
----------
qtomography : StandardQTomography
StandardQTomography to calculates estimate variables.
empi_dists : List[Tuple[int, np.ndarray]]
empirical distributions to calculates estimate variables.
is_computation_time_required : bool, optional
whether to include computation time in the return value or not, by default False.
Returns
-------
StandardQTomographyEstimationResult
estimation result.
Raises
------
NotImplementedError
this function does not be implemented in the subclass.
"""
raise NotImplementedError()
[docs] @abstractmethod
def calc_estimate_sequence(
self,
qtomography: StandardQTomography,
empi_dists_sequence: List[List[Tuple[int, np.ndarray]]],
is_computation_time_required: bool = False,
) -> StandardQTomographyEstimationResult:
"""calculates sequence of estimate variables.
this function must be implemented in the subclass.
Parameters
----------
qtomography : StandardQTomography
StandardQTomography to calculates estimate variables.
empi_dists_sequence : List[List[Tuple[int, np.ndarray]]]
sequence of empirical distributions to calculates estimate variables.
is_computation_time_required : bool, optional
whether to include computation time in the return value or not, by default False.
Returns
-------
StandardQTomographyEstimationResult
estimation result.
Raises
------
NotImplementedError
this function does not be implemented in the subclass.
"""
raise NotImplementedError()