How to use the tigramite.models.Models.__init__ function in tigramite

def __init__(self,
                 dataframe,
                 model_params=None,
                 data_transform=sklearn.preprocessing.StandardScaler(),
                 mask_type=None,
                 verbosity=0):
        # Initialize the member variables to None
        self.phi = None
        self.psi = None
        self.all_psi_k = None

        # Build the model using the parameters
        if model_params is None:
            model_params = {}
        this_model = sklearn.linear_model.LinearRegression(**model_params)
        Models.__init__(self,
                        dataframe=dataframe,
                        model=this_model,
                        data_transform=data_transform,
                        mask_type=mask_type,
                        verbosity=verbosity)

verbosity=0):

        # Default value for the mask
        mask = dataframe.mask
        if mask is None:
            mask = np.zeros(dataframe.values.shape, dtype='bool')
        # Get the dataframe shape
        T = len(dataframe.values)
        # Have the default dataframe be the training data frame
        train_mask = np.copy(mask)
        train_mask[[t for t in range(T) if t not in train_indices]] = True
        self.dataframe = DataFrame(dataframe.values,
                                   mask=train_mask,
                                   missing_flag=dataframe.missing_flag)
        # Initialize the models baseclass with the training dataframe
        Models.__init__(self,
                        dataframe=self.dataframe,
                        model=prediction_model,
                        data_transform=data_transform,
                        mask_type='y',
                        verbosity=verbosity)

        # Build the testing dataframe as well
        self.test_mask = np.copy(mask)
        self.test_mask[[t for t in range(T) if t not in test_indices]] = True

        # Setup the PCMCI instance
        if cond_ind_test is not None:
            # Force the masking
            cond_ind_test.set_mask_type('y')
            cond_ind_test.verbosity = verbosity
            PCMCI.__init__(self,