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linedance-app/venv/lib/python3.12/site-packages/sklearn/utils/_arpack.py

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+# Authors: The scikit-learn developers
+# SPDX-License-Identifier: BSD-3-Clause
+
+from sklearn.utils.validation import check_random_state
+
+
+def _init_arpack_v0(size, random_state):
+    """Initialize the starting vector for iteration in ARPACK functions.
+
+    Initialize an 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