def _init_classes(self, y):
        """Map all possible classes to the range [0,..,C-1]

        Parameters
        ----------

        y : list of arrays of int, each element has shape=[samples_i,]
            Labels of the samples for each subject


        Returns
        -------
        new_y : list of arrays of int, each element has shape=[samples_i,]
            Mapped labels of the samples for each subject

        Note
        ----
            The mapping of the classes is saved in the attribute classes_.
        """
        self.classes_ = unique_labels(utils.concatenate_not_none(y))
        new_y = [None] * len(y)
        for s in range(len(y)):
            new_y[s] = np.digitize(y[s], self.classes_) - 1
        return new_y
def _init_classes ( self , y ) : self . classes_ = unique_labels ( utils . concatenate_not_none ( y ) ) new_y = [ None ] * len ( y ) for s in range ( len ( y ) ) : new_y [ s ] = np . digitize ( y [ s ] , self . classes_ ) - 1 return new_y
Map all possible classes to the range [0,..,C-1]

        Parameters
        ----------

        y : list of arrays of int, each element has shape=[samples_i,]
            Labels of the samples for each subject


        Returns
        -------
        new_y : list of arrays of int, each element has shape=[samples_i,]
            Mapped labels of the samples for each subject

        Note
        ----
            The mapping of the classes is saved in the attribute classes_.