qiskit_noise_learning.analysis.LeastSquaresSolve

class qiskit_noise_learning.analysis.LeastSquaresSolve(non_negative: bool = True, solver: Literal['cvxpy', 'scipy'] | None = None)

GitHub

Bases: ModelSolve

Solves for ModelData by least squares, with optional non-negativity constraints.

Minimizes $\|A x - b\|_2^2$ over the design matrix A and target b. See ModelSolve for the general responsibility of a model solver in this library.

Parameters

non_negative – Whether to constrain the solution to be non-negative (x >= 0). Defaults to True.
solver – Either "cvxpy" (default) or "scipy". If "cvxpy" is requested but not installed, warns and falls back to "scipy".

Raises

ValueError – If solver is not "cvxpy" or "scipy".

init

__init__(non_negative: bool = True, solver: Literal['cvxpy', 'scipy'] | None = None)

Methods

Kolumne „ 1 “	Kolumne „ 2 “
`__init__`([non_negative, solver])
`run`(fit)	Run this stage, returning a new `Fit` with the output level populated.

Attributes

Kolumne „ 1 “	Kolumne „ 2 “
`input_level`	The data level this stage reads.
`output_level`	The data level this stage writes.

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