venv/lib/python3.10/site-packages/sklearn/utils/_arpack.py

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