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IBM Quantum Platform

qiskit_noise_learning.math.IndexedVector

class qiskit_noise_learning.math.IndexedVector

GitHub

Bases: dict[Index, float]

A vector of floats with arbitrary index, or axis label, data.

__init__

__init__(*args, **kwargs)


Methods

Column 1
Column 2
__init__(*args, **kwargs)
add(other)Return a new indexed vector that is the sum of self and other.
clear()
copy()
fromkeys(iterable[, 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.
items()
keys()
mul(const)Return a new indexed vector by multipling self with a constant.
pop(k[,d])If the key is not found, return the default if given; otherwise, raise a KeyError.
popitem()Remove and return a (key, value) pair as a 2-tuple.
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.keys(): 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()

add

add(other: Self) → Self

Return a new indexed vector that is the sum of self and other.

mul

mul(const: float) → Self

Return a new indexed vector by multipling self with a constant.

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