magni.cs.reconstruction.amp._config moduleΒΆ
Module providing configuration options for the magni.cs.reconstruction.amp
subpackage.
See also
magni.cs.reconstruction._config.Configger
- The Configger class used.
Notes
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).