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ProbDistribution

class ProbDistribution(data, shots=None)

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Bases: dict

A generic dict-like class for probability distributions.

Builds a probability distribution object.

Parameters

  • data (dict) –

    Input probability data. Where the keys represent a measured classical value and the value is a float for the probability 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

ProbDistribution.binary_probabilities(num_bits=None)

Build a probabilities dictionary with binary string keys

Parameters

num_bits (int) – number of bits in the binary bitstrings (leading zeros will be padded). If None, a default value will be used. If keys are given as integers or strings with binary or hex prefix, the default value will be derived from the largest key present. If keys are given as bitstrings without prefix, the default value will be derived from the largest key length.

Returns

A dictionary where the keys are binary strings in the format

"0110"

Return type

dict

clear

ProbDistribution.clear() → None.  Remove all items from D.

copy

ProbDistribution.copy() → a shallow copy of D

fromkeys

ProbDistribution.fromkeys(value=None, /)

Create a new dictionary with keys from iterable and values set to value.

get

ProbDistribution.get(key, default=None, /)

Return the value for key if key is in the dictionary, else default.

hex_probabilities

ProbDistribution.hex_probabilities()

Build a probabilities dictionary with hexadecimal string keys

Returns

A dictionary where the keys are hexadecimal strings in the

format "0x1a"

Return type

dict

items

ProbDistribution.items() → a set-like object providing a view on D's items

keys

ProbDistribution.keys() → a set-like object providing a view on D's keys

pop

ProbDistribution.pop(k[, d]) → v, remove specified key and return the corresponding value.

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

popitem

ProbDistribution.popitem()

Remove and return a (key, value) pair as a 2-tuple.

Pairs are returned in LIFO (last-in, first-out) order. Raises KeyError if the dict is empty.

setdefault

ProbDistribution.setdefault(key, default=None, /)

Insert key with a value of default if key is not in the dictionary.

Return the value for key if key is in the dictionary, else default.

update

ProbDistribution.update([E, ]**F) → None.  Update D from dict/iterable E and F.

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

ProbDistribution.values() → an object providing a view on D's values

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