magni.cs.reconstruction.amp._config moduleΒΆ

Module providing configuration options for the magni.cs.reconstruction.amp subpackage.

See also

The Configger class used.


This module instantiates the Configger class provided by magni.cs.reconstruction._config.Configger. The configuration options are the following:

iterations : int
The maximum number of iterations to do (the default is 300).
precision_float : {np.float, np.float16, np.float32, np.float64, np.float128,
np.complex64, np.complex128, np.complex256} The floating point precision used for the computations (the default is np.float64).
report_history : bool
The indicator of whether or not to return the progress history along with the result (the default is False).
stop_criterion : magni.utils.validation.types.StopCriterion
The stop criterion to use in the iterations (the default is magni.cs.reconstruction.gamp.stop_criterion.MSEConvergence).
threshold : magni.utils.validation.types.ThresholdOperator
The threshold operator to use (the default is magni.cs.reconstruction.amp.threshold_operator.SoftThreshold).
threshold_parameters : dict
The parameters used in the threshold operator (no default is provided, which implies that this must be specified by the user).
tolerance : float
The least acceptable stop criterion tolerance to break the interations (the default is 1e-6).
true_solution : ndarray or None
The true solution to allow for tracking the convergence of the algorithm in the artificial setup where the true solution is known a-priori (the default is None, which implies that no true solution tracking is used).
warm_start : ndarray
The initial guess of the solution vector (alpha_bar) (the default is None, which implies that alpha_bar is taken to be a vector of zeros).