Less-wrong single-file Numba-accelerated Python implementation of Gotoh affine gap penalty extensions for the Needleman–Wunsch, Smith-Waterman, and Levenshtein algorithms for sequence alignment
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Updated
Apr 4, 2025 - Python
Less-wrong single-file Numba-accelerated Python implementation of Gotoh affine gap penalty extensions for the Needleman–Wunsch, Smith-Waterman, and Levenshtein algorithms for sequence alignment
Efficient typo-tolerant search in 76 lines of code, with no dependencies.
Shortens the paragraph depending on the given keywords using Levenshtein distance
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Python scripts used to calculate 3 basic similarity measures, suitable for ad hoc information retrieval systems: Levenshtein Edit Distance, Jaccard, and a Term-Document matrix.
Find the best match for a token word with dictionary via min edit distance and levenshtein
Finding matching concepts in OCL MSF Source
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