# QuasiDistribution¶

class QuasiDistribution(data, shots=None)[source]

Bases: dict

A dict-like class for representing qasi-probabilities.

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

Methods

 binary_probabilities Build a quasi-probabilities dictionary with binary string keys clear copy fromkeys Create a new dictionary with keys from iterable and values set to value. get Return the value for key if key is in the dictionary, else default. hex_probabilities Build a quasi-probabilities dictionary with hexadecimal string keys items keys nearest_probability_distribution Takes a quasiprobability distribution and maps it to the closest probability distribution as defined by the L2-norm. pop If key is not found, d is returned if given, otherwise KeyError is raised popitem Remove and return a (key, value) pair as a 2-tuple. setdefault Insert key with a value of default if key is not in the dictionary. update If E is present and has a .keys() method, then does: for k in E: D[k] = E[k] If E is present and lacks a .keys() method, then does: for k, v in E: D[k] = v In either case, this is followed by: for k in F: D[k] = F[k] values