def sqsum(self, axis, target=None):
    """
    Find the sum of squares along the given dimension, where 0 represents the
    leading dimension and 1 represents the non-leading dimension. If a target
    is not prvided, a new vector is created for storing the result.
    """

    m, n = self.shape

    if axis == 0:
      if not target:
        target = empty((1, n))
 
    elif axis == 1:
      if not target:
        target = empty((m, 1))

    err_code = _eigenmat.sqsum_by_axis(self.p_mat, target.p_mat, ct.c_int(axis))
    if err_code:
      raise generate_exception(err_code)

    return target

    Find the sum of squares along the given dimension, where 0 represents the
    leading dimension and 1 represents the non-leading dimension. If a target
    is not prvided, a new vector is created for storing the result.
    
eigenmat/eigenmat.py