qiskit.aqua.algorithms.AmplitudeEstimationResult¶

class AmplitudeEstimationResult(a_dict=None)[source]¶

AmplitudeEstimation Result.

__init__(a_dict=None)¶: Initialize self. See help(type(self)) for accurate signature.

Methods

`__init__`([a_dict])	Initialize self.
`clear`()	rtype `None`
`combine`(result)	Any property from the argument that exists in the receiver is updated.
`copy`()
`from_dict`(a_dict)	create new object from a dictionary
`fromkeys`(iterable[, value])
`get`(k[,d])
`items`()
`keys`()
`pop`(key[, default])	If key is not found, d is returned if given, otherwise KeyError is raised.
`popitem`()	as a 2-tuple; but raise KeyError if D is empty.
`setdefault`(k[,d])
`update`(args, *kwargs)	If E present and has a .keys() method, does: for k in E: D[k] = E[k] If E present and lacks .keys() method, does: for (k, v) in E: D[k] = v In either case, this is followed by: for k, v in F.items(): D[k] = v
`values`()

Attributes

`a_estimation`	return a_estimation
`a_samples`	return a_samples
`circuit_result`	return circuit result
`confidence_interval`	return confidence_interval
`estimation`	return estimation
`mapped_a_samples`	return mapped_a_samples
`mapped_values`	return mapped_values
`max_probability`	return max_probability
`ml_value`	returns ml_value
`mle`	return mle
`num_oracle_queries`	return num_oracle_queries
`probabilities`	return probabilities
`shots`	return shots
`y_measurements`	return y_measurements

property a_estimation¶

return a_estimation

Return type: float

property a_samples¶

return a_samples

Return type: List[Tuple[float, float]]

property circuit_result¶

return circuit result

Return type: Union[ndarray, Dict[str, int], None]

clear()¶

Return type: None

combine(result)¶

Any property from the argument that exists in the receiver is updated. :type result: AlgorithmResult :param result: Argument result with properties to be set.

Raises: TypeError – Argument is None
Return type: None

property confidence_interval¶

return confidence_interval

Return type: List[float]

property estimation¶

return estimation

Return type: float

static from_dict(a_dict)[source]¶

create new object from a dictionary

Return type: AmplitudeEstimationResult

get(k[, d]) → D[k] if k in D, else d. d defaults to None.¶

items() → a set-like object providing a view on D’s items¶

keys() → a set-like object providing a view on D’s keys¶

property mapped_a_samples¶

return mapped_a_samples

Return type: List[float]

property mapped_values¶

return mapped_values

Return type: List[float]

property max_probability¶

return max_probability

Return type: float

property ml_value¶

returns ml_value

Return type: float

property mle¶

return mle

Return type: float

property num_oracle_queries¶

return num_oracle_queries

Return type: int

pop(key, default=None)¶

If key is not found, d is returned if given, otherwise KeyError is raised.

Return type: object

popitem()¶

as a 2-tuple; but raise KeyError if D is empty.

Return type: Tuple[object, object]

property probabilities¶

return probabilities

Return type: List[float]

setdefault(k[, d]) → D.get(k,d), also set D[k]=d if k not in D¶

property shots¶

return shots

Return type: int

update(*args, **kwargs)¶

If E present and has a .keys() method, does: for k in E: D[k] = E[k] If E present and lacks .keys() method, does: for (k, v) in E: D[k] = v In either case, this is followed by: for k, v in F.items(): D[k] = v

Return type: None

values() → an object providing a view on D’s values¶

property y_measurements¶

return y_measurements

Return type: List[Tuple[int, float]]