README.md

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SuffixArray Library

This project implements a suffix array based on the doubling algorithm, supporting efficient string processing and suitable for UTF-8 text. The core part is written in C++ and wrapped as a Python extension module via Cython.

Features

• Time Complexity: $\mathcal{O}(n\log n)$
• Space Complexity: $\mathcal{O}(n)$ (with a large constant, be cautious with large datasets)
• Multilingual Support: Input must be UTF-8 encoded

Implemented Functions

• size(): Returns the length of the text
• get_id(suf_rank): Given a suffix rank (1-indexed), returns its position in the text (0-indexed)
• get_suf(suf_rank): Given a suffix rank (1-indexed), returns the corresponding suffix
• get_rank(suf_id): Given the left boundary position of a suffix (0-indexed), returns its lexicographical rank
• get_count(pattern): Given a pattern string, returns the number of its occurrences in the text
• get_prob(prompt): Given a text prompt, returns the probability distribution of the next character
• get_branch_entropy(prompt): Given a text prompt, returns its right branch entropy
• get_mutual_information(text): Given a text, returns its mutual information

Installation & Build

It is recommended to use pip for local development installation:

pip install -e .

Or manually build the extension module:

python setup.py build_ext --inplace

The generated library file (e.g., SuffixArray.*.so) can be placed in your project directory and imported in Python code.

Testing

test.ipynb provides simple test cases. If you encounter unexpected outputs, feel free to open an issue.

Notes

• Currently, a linear-time construction algorithm is not used
• The space constant is large, not suitable for ultra-large datasets
• Test cases are limited, mainly for personal study and experimentation

License

This project is licensed under the MIT License. Free to use and modify.