'Lazily estimate d_p(A) ~= || A^p ||^(1/p) where ||.|| is the 1-norm.'

def d(self, p):

    if (p not in self._d):
        est = _onenormest_matrix_power(self._A, p, self._ell)
        self._d[p] = (est ** (1.0 / p))
    return (self._scale * self._d[p])
