def select_columns(self, indices, target):
    """
    copies some columns of self into target.
    <indices> must be a row vector. Its elements are float32's representing integers, e.g. "34.0" means the integer "34".
    after this call, for all r,c, target[r,c]=self[r,indices[c]].
    This returns target.
    Negative indices are interpreted in the usual Python way: all elements of <indices> had better be in the range [-self.shape[1], self.shape[1]-1].
    This does bounds checking, but out of bounds indices do not raise an exception (because the programmer was lazy). Instead, they result in NaN values in <target>.
    """

    err_code = _eigenmat.selectRows(self.p_mat, target.p_mat, indices.p_mat)

    if err_code:
      raise generate_exception(err_code)

    return target

    copies some columns of self into target.
    <indices> must be a row vector. Its elements are float32's representing integers, e.g. "34.0" means the integer "34".
    after this call, for all r,c, target[r,c]=self[r,indices[c]].
    This returns target.
    Negative indices are interpreted in the usual Python way: all elements of <indices> had better be in the range [-self.shape[1], self.shape[1]-1].
    This does bounds checking, but out of bounds indices do not raise an exception (because the programmer was lazy). Instead, they result in NaN values in <target>.
    
eigenmat/eigenmat.py