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_onenormest_matrix_power(A, p, t=2, itmax=5, compute_v=False, compute_w=False)

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.

Efficiently estimate the 1-norm of A^p.

Examples

See :

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GitHub : /scipy/sparse/linalg/_expm_multiply.py#272
type: <class 'function'>
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