def _onenormest_m1_power(A, p,<EOL>t=<NUM_LIT:2>, itmax=<NUM_LIT:5>, compute_v=False, compute_w=False):
return onenormest(_MatrixM1PowerOperator(A, p),<EOL>t=t, itmax=itmax, compute_v=compute_v, compute_w=compute_w)<EOL>
Efficiently estimate the 1-norm of (A - I)^p.

Parameters
----------
A : ndarray
    Matrix whose 1-norm of a power is to be computed.
p : int
    Non-negative integer power.
t : int, optional
    A positive parameter controlling the tradeoff between
    accuracy versus time and memory usage.
    Larger values take longer and use more memory
    but give more accurate output.
itmax : int, optional
    Use at most this many iterations.
compute_v : bool, optional
    Request a norm-maximizing linear operator input vector if True.
compute_w : bool, optional
    Request a norm-maximizing linear operator output vector if True.

Returns
-------
est : float
    An underestimate of the 1-norm of the sparse matrix.
v : ndarray, optional
    The vector such that ||Av||_1 == est*||v||_1.
    It can be thought of as an input to the linear operator
    that gives an output with particularly large norm.
w : ndarray, optional
    The vector Av which has relatively large 1-norm.
    It can be thought of as an output of the linear operator
    that is relatively large in norm compared to the input.