`scipy.sparse.linalg._matfuncs:_onenormest_matrix_power`

Signature

def _onenormest_matrix_power(A, p, t = 2, itmax = 5, compute_v = False, compute_w = False, structure = None)

Efficiently estimate the 1-norm of A^p.

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.

est : float: An underestimate of the 1-norm of the sparse arrays.
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.