def run(self, clf):
        """Run correlation-based voxel selection in master-worker model.

        Sort the voxels based on the cross-validation accuracy
        of their correlation vectors

        Parameters
        ----------
        clf: classification function
            the classifier to be used in cross validation

        Returns
        -------
        results: list of tuple (voxel_id, accuracy)
            the accuracy numbers of all voxels, in accuracy descending order
            the length of array equals the number of voxels
        """
        rank = MPI.COMM_WORLD.Get_rank()
        if rank == self.master_rank:
            results = self._master()
            # Sort the voxels
            results.sort(key=lambda tup: tup[1], reverse=True)
        else:
            self._worker(clf)
            results = []
        return results
def run ( self , clf ) : rank = MPI . COMM_WORLD . Get_rank ( ) if rank == self . master_rank : results = self . _master ( ) results . sort ( key = lambda tup : tup [ 1 ] , reverse = True ) else : self . _worker ( clf ) results = [ ] return results
Run correlation-based voxel selection in master-worker model.

        Sort the voxels based on the cross-validation accuracy
        of their correlation vectors

        Parameters
        ----------
        clf: classification function
            the classifier to be used in cross validation

        Returns
        -------
        results: list of tuple (voxel_id, accuracy)
            the accuracy numbers of all voxels, in accuracy descending order
            the length of array equals the number of voxels