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- 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
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