def removeconfounds(self, confounds=None, clean_params=None, transpose=None, njobs=None, update_pipeline=True, overwrite=True, tag=None):
        """
        Removes specified confounds using nilearn.signal.clean

        Parameters
        ----------
        confounds : list
            List of confounds. Can be prespecified in set_confounds
        clean_params : dict
            Dictionary of kawgs to pass to nilearn.signal.clean
        transpose : bool (default False)
            Default removeconfounds works on time,node dimensions. Pass transpose=True to transpose pre and post confound removal.
        njobs : int
            Number of jobs. Otherwise tenetoBIDS.njobs is run.
        update_pipeline : bool
            update pipeline with '_clean' tag for new files created
        overwrite : bool
        tag : str

        Returns
        -------
        Says all TenetBIDS.get_selected_files with confounds removed with _rmconfounds at the end.

        Note
        ----
        There may be some issues regarding loading non-cleaned data through the TenetoBIDS functions instead of the cleaned data. This depeneds on when you clean the data.
        """
        if not njobs:
            njobs = self.njobs
        self.add_history(inspect.stack()[0][3], locals(), 1)

        if not self.confounds and not confounds:
            raise ValueError(
                'Specified confounds are not found. Make sure that you have run self.set_confunds([\'Confound1\',\'Confound2\']) first or pass confounds as input to function.')

        if not tag:
            tag = ''
        else:
            tag = 'desc-' + tag

        if confounds:
            self.set_confounds(confounds)
        files = sorted(self.get_selected_files(quiet=1))
        confound_files = sorted(
            self.get_selected_files(quiet=1, pipeline='confound'))
        files, confound_files = confound_matching(files, confound_files)
        if not clean_params:
            clean_params = {}

        with ProcessPoolExecutor(max_workers=njobs) as executor:
            job = {executor.submit(
                self._run_removeconfounds, f, confound_files[i], clean_params, transpose, overwrite, tag) for i, f in enumerate(files)}
            for j in as_completed(job):
                j.result()

        self.set_pipeline('teneto_' + teneto.__version__)
        self.set_bids_suffix('roi')
        if tag:
            self.set_bids_tags({'desc': tag.split('-')[1]})
def removeconfounds ( self , confounds = None , clean_params = None , transpose = None , njobs = None , update_pipeline = True , overwrite = True , tag = None ) : if not njobs : njobs = self . njobs self . add_history ( inspect . stack ( ) [ 0 ] [ 3 ] , locals ( ) , 1 ) if not self . confounds and not confounds : raise ValueError ( 'Specified confounds are not found. Make sure that you have run self.set_confunds([\'Confound1\',\'Confound2\']) first or pass confounds as input to function.' ) if not tag : tag = '' else : tag = 'desc-' + tag if confounds : self . set_confounds ( confounds ) files = sorted ( self . get_selected_files ( quiet = 1 ) ) confound_files = sorted ( self . get_selected_files ( quiet = 1 , pipeline = 'confound' ) ) files , confound_files = confound_matching ( files , confound_files ) if not clean_params : clean_params = { } with ProcessPoolExecutor ( max_workers = njobs ) as executor : job = { executor . submit ( self . _run_removeconfounds , f , confound_files [ i ] , clean_params , transpose , overwrite , tag ) for i , f in enumerate ( files ) } for j in as_completed ( job ) : j . result ( ) self . set_pipeline ( 'teneto_' + teneto . __version__ ) self . set_bids_suffix ( 'roi' ) if tag : self . set_bids_tags ( { 'desc' : tag . split ( '-' ) [ 1 ] } )
Removes specified confounds using nilearn.signal.clean

        Parameters
        ----------
        confounds : list
            List of confounds. Can be prespecified in set_confounds
        clean_params : dict
            Dictionary of kawgs to pass to nilearn.signal.clean
        transpose : bool (default False)
            Default removeconfounds works on time,node dimensions. Pass transpose=True to transpose pre and post confound removal.
        njobs : int
            Number of jobs. Otherwise tenetoBIDS.njobs is run.
        update_pipeline : bool
            update pipeline with '_clean' tag for new files created
        overwrite : bool
        tag : str

        Returns
        -------
        Says all TenetBIDS.get_selected_files with confounds removed with _rmconfounds at the end.

        Note
        ----
        There may be some issues regarding loading non-cleaned data through the TenetoBIDS functions instead of the cleaned data. This depeneds on when you clean the data.