# Source code for qiskit.result.distributions.quasi

```
# This code is part of Qiskit.
#
# (C) Copyright IBM 2021.
#
# 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
# of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.
#
# Any modifications or derivative works of this code must retain this
# copyright notice, and modified files need to carry a notice indicating
# that they have been altered from the originals.
"""Quasidistribution class"""
from math import sqrt
import re
from .probability import ProbDistribution
# NOTE: A dict subclass should not overload any dunder methods like __getitem__
# this can cause unexpected behavior and issues as the cPython dict
# implementation has many standard methods in C for performance and the dunder
# methods are not always used as expected. For example, update() doesn't call
# __setitem__ so overloading __setitem__ would not always provide the expected
# result
[docs]class QuasiDistribution(dict):
"""A dict-like class for representing qasi-probabilities."""
_bitstring_regex = re.compile(r"^[01]+$")
def __init__(self, data, shots=None):
"""Builds a quasiprobability distribution object.
Parameters:
data (dict): Input quasiprobability data. Where the keys
represent a measured classical value and the value is a
float for the quasiprobability of that result.
The keys can be one of several formats:
* A hexadecimal string of the form ``"0x4a"``
* A bit string e.g. ``'0b1011'`` or ``"01011"``
* An integer
shots (int): Number of shots the distribution was derived from.
Raises:
TypeError: If the input keys are not a string or int
ValueError: If the string format of the keys is incorrect
"""
self.shots = shots
if data:
first_key = next(iter(data.keys()))
if isinstance(first_key, int):
pass
elif isinstance(first_key, str):
if first_key.startswith("0x"):
hex_raw = data
data = {int(key, 0): value for key, value in hex_raw.items()}
elif first_key.startswith("0b"):
bin_raw = data
data = {int(key, 0): value for key, value in bin_raw.items()}
elif self._bitstring_regex.search(first_key):
bin_raw = data
data = {int("0b" + key, 0): value for key, value in bin_raw.items()}
else:
raise ValueError(
"The input keys are not a valid string format, must either "
"be a hex string prefixed by '0x' or a binary string "
"optionally prefixed with 0b"
)
else:
raise TypeError("Input data's keys are of invalid type, must be str or int")
super().__init__(data)
[docs] def nearest_probability_distribution(self, return_distance=False):
"""Takes a quasiprobability distribution and maps
it to the closest probability distribution as defined by
the L2-norm.
Parameters:
return_distance (bool): Return the L2 distance between distributions.
Returns:
ProbDistribution: Nearest probability distribution.
float: Euclidean (L2) distance of distributions.
Notes:
Method from Smolin et al., Phys. Rev. Lett. 108, 070502 (2012).
"""
sorted_probs = dict(sorted(self.items(), key=lambda item: item[1]))
num_elems = len(sorted_probs)
new_probs = {}
beta = 0
diff = 0
for key, val in sorted_probs.items():
temp = val + beta / num_elems
if temp < 0:
beta += val
num_elems -= 1
diff += val * val
else:
diff += (beta / num_elems) * (beta / num_elems)
new_probs[key] = sorted_probs[key] + beta / num_elems
if return_distance:
return ProbDistribution(new_probs, self.shots), sqrt(diff)
return ProbDistribution(new_probs, self.shots)
[docs] def binary_probabilities(self, num_bits=None):
"""Build a quasi-probabilities dictionary with binary string keys
Parameters:
num_bits (int): number of bits in the binary bitstrings (leading
zeros will be padded). If None, the length will be derived
from the largest key present.
Returns:
dict: A dictionary where the keys are binary strings in the format
``"0110"``
"""
n = len(bin(max(self.keys(), default=0))) - 2 if num_bits is None else num_bits
return {format(key, "b").zfill(n): value for key, value in self.items()}
[docs] def hex_probabilities(self):
"""Build a quasi-probabilities dictionary with hexadecimal string keys
Returns:
dict: A dictionary where the keys are hexadecimal strings in the
format ``"0x1a"``
"""
return {hex(key): value for key, value in self.items()}
```