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…eigenvalues and corresponding eigenvectors of a graph based on its adjacency list. (#11906) - Utilized `lanczos_iteration` to construct tridiagonal matrices, optimized for large, sparse matrices. - Added `multiply_matrix_vector` for efficient matrix-vector multiplication using adjacency lists. - Included `validate_adjacency_list` for input validation. - Supports varied graph analysis applications, particularly for analyzing graph centrality. - Included type hints, comprehensive docstrings, and doctests. - PEP-8 compliant, with optimized handling of inputs and outputs. This module provides essential tools for eigenvalue-based graph analysis, ideal for centrality insights and structural assessments.
* Contributes to #9943 by adding tests to monotonic_array.py Addeded doctest in the if __name__. Checks for negaitves and an array of same integers * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --------- Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
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