Пример #1
0
    def __init__(self,
                 target,
                 prediction_parameterisation,
                 log=None,
                 verbosity=0,
                 track_step=False,
                 track_gradient=False,
                 track_parameter_correlation=False,
                 track_out_of_sample_rmsd=False,
                 max_iterations=None):

        AdaptLstbxBase.__init__(
            self,
            target,
            prediction_parameterisation,
            log=log,
            verbosity=verbosity,
            track_step=track_step,
            track_gradient=track_gradient,
            track_parameter_correlation=track_parameter_correlation,
            track_out_of_sample_rmsd=track_out_of_sample_rmsd,
            max_iterations=max_iterations)

        non_linear_ls_eigen_wrapper.__init__(self,
                                             n_parameters=len(
                                                 self._parameters))
Пример #2
0
  def __init__(self, target, prediction_parameterisation, log=None,
               verbosity = 0, track_step = False, track_gradient = False,
               track_parameter_correlation = False,
               track_out_of_sample_rmsd = False, max_iterations = None):

    AdaptLstbxBase.__init__(self, target, prediction_parameterisation,
             log=log, verbosity=verbosity, track_step=track_step,
             track_gradient=track_gradient,
             track_parameter_correlation=track_parameter_correlation,
             track_out_of_sample_rmsd=track_out_of_sample_rmsd,
             max_iterations=max_iterations)

    non_linear_ls_eigen_wrapper.__init__(self, n_parameters = len(self._parameters))
Пример #3
0
    def __init__(self,
                 target,
                 prediction_parameterisation,
                 constraints_manager=None,
                 log=None,
                 verbosity=0,
                 tracking=None,
                 max_iterations=None):

        AdaptLstbxBase.__init__(self,
                                target,
                                prediction_parameterisation,
                                constraints_manager=constraints_manager,
                                log=log,
                                verbosity=verbosity,
                                tracking=tracking,
                                max_iterations=max_iterations)

        non_linear_ls_eigen_wrapper.__init__(self, n_parameters=len(self.x))