def __init__(self, A, structure=None, use_exact_onenorm=False):
self.A = A<EOL>self._A2 = None<EOL>self._A4 = None<EOL>self._A6 = None<EOL>self._A8 = None<EOL>self._A10 = None<EOL>self._d4_exact = None<EOL>self._d6_exact = None<EOL>self._d8_exact = None<EOL>self._d10_exact = None<EOL>self._d4_approx = None<EOL>self._d6_approx = None<EOL>self._d8_approx = None<EOL>self._d10_approx = None<EOL>self.ident = _ident_like(A)<EOL>self.structure = structure<EOL>self.use_exact_onenorm = use_exact_onenorm<EOL>
Initialize the object.

Parameters
----------
A : a dense or sparse square numpy matrix or ndarray
    The matrix to be exponentiated.
structure : str, optional
    A string describing the structure of matrix `A`.
    Only `upper_triangular` is currently supported.
use_exact_onenorm : bool, optional
    If True then only the exact one-norm of matrix powers and products
    will be used. Otherwise, the one-norm of powers and products
    may initially be estimated.