(self, x1, x2, offset, scale)
return data1, data2
Extract and scale continuous columns from data tables.
        If the second table is None, it defaults to the first table.

        Values are scaled if `self.normalize` is `True`.

        Args:
            x1 (np.ndarray): first table
            x2 (np.ndarray or None): second table
            offset (float): a constant (e.g. mean, median) subtracted from data
            scale: (float): divider (e.g. deviation)

        Returns:
            data1 (np.ndarray): scaled continuous columns from `x1`
            data2 (np.ndarray): scaled continuous columns from `x2` or `x1`
Extract and scale continuous columns from data tables.
        If the second table is None, it defaults to the first table.
Extract and scale continuous columns from data tables . If the second table is None it defaults to the first table .
def continuous_columns(self, x1, x2, offset, scale):
        """
        Extract and scale continuous columns from data tables.
        If the second table is None, it defaults to the first table.

        Values are scaled if `self.normalize` is `True`.

        Args:
            x1 (np.ndarray): first table
            x2 (np.ndarray or None): second table
            offset (float): a constant (e.g. mean, median) subtracted from data
            scale: (float): divider (e.g. deviation)

        Returns:
            data1 (np.ndarray): scaled continuous columns from `x1`
            data2 (np.ndarray): scaled continuous columns from `x2` or `x1`
        """
        if self.continuous.all() and not self.normalize:
            data1, data2 = x1, x2
        else:
            data1 = x1[:, self.continuous]
            if x2 is not None:
                data2 = x2[:, self.continuous]
            if self.normalize:
                data1 = x1[:, self.continuous]
                data1 -= offset
                data1 /= scale
                if x2 is not None:
                    data2 = x2[:, self.continuous]
                    data2 -= offset
                    data2 /= scale
        if x2 is None:
            data2 = data1
        return data1, data2
def continuous_columns ( self , x1 , x2 , offset , scale ) : if self . continuous . all ( ) and not self . normalize : data1 , data2 = x1 , x2 else : data1 = x1 [ : , self . continuous ] if x2 is not None : data2 = x2 [ : , self . continuous ] if self . normalize : data1 = x1 [ : , self . continuous ] data1 -= offset data1 /= scale if x2 is not None : data2 = x2 [ : , self . continuous ] data2 -= offset data2 /= scale if x2 is None : data2 = data1 return data1 , data2