qiskit.result.ProbDistribution¶

class
ProbDistribution
(data, shots=None)[Quellcode]¶ A generic dictlike class for probability distributions.
Builds a probability distribution object.
 Parameter
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.
 Verursacht
TypeError – If the input keys are not a string or int
ValueError – If the string format of the keys is incorrect

__init__
(data, shots=None)[Quellcode]¶ Builds a probability distribution object.
 Parameter
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.
 Verursacht
TypeError – If the input keys are not a string or int
ValueError – If the string format of the keys is incorrect
Methods
__init__
(data[, shots])Builds a probability distribution object.
binary_probabilities
([num_bits])Build a probabilities dictionary with binary string keys
clear
()copy
()fromkeys
([value])Create a new dictionary with keys from iterable and values set to value.
get
(key[, default])Return the value for key if key is in the dictionary, else default.
Build a probabilities dictionary with hexadecimal string keys
items
()keys
()pop
(k[,d])If key is not found, d is returned if given, otherwise KeyError is raised
popitem
()Remove and return a (key, value) pair as a 2tuple.
setdefault
(key[, default])Insert key with a value of default if key is not in the dictionary.
update
([E, ]**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
()
binary_probabilities
(num_bits=None)[Quellcode]¶ Build a probabilities dictionary with binary string keys
 Parameter
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.
 Rückgabe
 A dictionary where the keys are binary strings in the format
"0110"
 Rückgabetyp
dict

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

copy
() → a shallow copy of D¶

fromkeys
(value=None, /)¶ Create a new dictionary with keys from iterable and values set to value.

get
(key, default=None, /)¶ Return the value for key if key is in the dictionary, else default.

hex_probabilities
()[Quellcode]¶ Build a probabilities dictionary with hexadecimal string keys
 Rückgabe
 A dictionary where the keys are hexadecimal strings in the
format
"0x1a"
 Rückgabetyp
dict

items
() → a setlike object providing a view on D’s items¶

keys
() → a setlike object providing a view on D’s keys¶

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
()¶ Remove and return a (key, value) pair as a 2tuple.
Pairs are returned in LIFO (lastin, firstout) order. Raises KeyError if the dict is empty.

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