Compute Natural Breaks (Jenks algorythm)
Project description
Compute “natural” break values (Jenks algorythm) on list/tuple/numpy.ndarray of integers/floats.
(Intented compatibility: CPython 2.7+ and 3.3+)
Usage :
>>> import random
>>> list_of_values = [random.random()*5000 for _ in range(12000)]
>>> import jenkspy
>>> breaks = jenkspy.jenks_breaks(list_of_values, nb_class=6)
>>> import json
>>> with open('test.json', 'r') as f:
... data = json.loads(f.read())
...
>>> jenkspy.jenks_breaks(data, nb_class=5)
(0.0028109620325267315, 2.0935479691252112, 4.205495140049607, 6.178148351609707, 8.09175917180255, 9.997982932254672)
Installation :
pip install jenkspy
git clone http://github.com/mthh/jenkspy
cd jenkspy/
python setup.py install
Requirements (only for building from source):
C compiler
Python C headers
Motivation :
Could be used as an eventual dependency in other package (using appveyor and travis to build wheels for easier installation via pip).
Getting the break values! (and fast!)
Other python implementations are currently existing.
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