| # Authors: The scikit-learn developers | |
| # SPDX-License-Identifier: BSD-3-Clause | |
| from .validation import check_random_state | |
| def _init_arpack_v0(size, random_state): | |
| """Initialize the starting vector for iteration in ARPACK functions. | |
| Initialize a ndarray with values sampled from the uniform distribution on | |
| [-1, 1]. This initialization model has been chosen to be consistent with | |
| the ARPACK one as another initialization can lead to convergence issues. | |
| Parameters | |
| ---------- | |
| size : int | |
| The size of the eigenvalue vector to be initialized. | |
| random_state : int, RandomState instance or None, default=None | |
| The seed of the pseudo random number generator used to generate a | |
| uniform distribution. If int, random_state is the seed used by the | |
| random number generator; If RandomState instance, random_state is the | |
| random number generator; If None, the random number generator is the | |
| RandomState instance used by `np.random`. | |
| Returns | |
| ------- | |
| v0 : ndarray of shape (size,) | |
| The initialized vector. | |
| """ | |
| random_state = check_random_state(random_state) | |
| v0 = random_state.uniform(-1, 1, size) | |
| return v0 | |