lempel-ziv-complexity 0.2.2

Creator: bradpython12

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Description:

lempelzivcomplexity 0.2.2

This repository contains a small, simple and efficient implement of the Lempel-Ziv complexity algorithm.

Examples

Simple usage
If the lempel_ziv_complexity.py file is accessible in your PATH or in Python’s path:
>>> from lempel_ziv_complexity import lempel_ziv_complexity
>>> s = '1001111011000010'
>>> lempel_ziv_complexity(s) # 1 / 0 / 01 / 11 / 10 / 110 / 00 / 010
8


Documentation
See this file.


With the C extension
If the lempel_ziv_complexity.so file is accessible in your PATH or in Python’s path, the same can be used.


Small benchmark
There is also a Cython version, to have a faster implementation:
$ ipython
...
>>> s = '1001111011000010'
>>> %timeit lempel_ziv_complexity(s)
6.1 µs ± 33.6 ns per loop (mean ± std. dev. of 7 runs, 100000 loops each)
>>> %timeit lempel_ziv_complexity_cython(s)
132 ns ± 2.55 ns per loop (mean ± std. dev. of 7 runs, 10000000 loops each)
The speedup is typically between x50 and x100.
It is not shipped with the PyPi version, see directly on GitHub if needed.



Demo on a Jupyter notebook
See this notebook: on nbviewever.



Install and build
Manually ?
Easy!
Clone this repository, go in the folder, compile, test, and if it works,
install it.
cd /tmp/
git clone https://GitHub.com/Naereen/Lempel-Ziv_Complexity
cd Lempel-Ziv_Complexity/src/
make build
make test # should pass
make install # mv the build/lib*/*.so files where you need them
Be sure to include the dynamic library when you need it, or in a folder
accessible by your Python interpreter (somewhere in sys.path). The
file is lempel_ziv_complexity_cython.so (for Python 2) or the
lempel_ziv_complexity_cython.cpython-35m-x86_64-linux-gnu.so (for
Python 3.5, or higher, adapt the name).


With pip ?
This project is hosted on the Pypi package repository.
sudo pip install lempel_ziv_complexity
python -c "from lempel_ziv_complexity import lempel_ziv_complexity; print(lempel_ziv_complexity('1001111011000010') == 6)" # test






About

Language?
Python v2.7+ or Python v3.1+.

Numba can be used to speed up the pure
Python version.
Cython is needed to build the C extension
(faster).



License ?
MIT Licensed (file
LICENSE). © Lilian
Besson, 2017.

License

For personal and professional use. You cannot resell or redistribute these repositories in their original state.

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