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a hierachical clustering algorithm based on information theory

Project description

Travis Appveyor

Python binding

PyPI

How to build

The binding uses Cython. To package the library, use python setup.py bdist_wheel. Install the package by pip install --user pspartition. Below is the pre-built binary packages:

Platform py3.6 py3.7
Windows T T
MacOS T T
Linux T T

Demo code

import pspartition # classify the three data points shown in the above figure
g = pspartion.PsPartition(3, [(0,1,1),(1,2,1),(0,2,5)]) # index started from zero, similarity is 5 for vertex 0 and 2
g.run() # default to use psp_i algorithm to classify them
print(g.get_critical_values()) # [2,5]
print(g.get_partitions()) # get the result which has at least 2 categories, which is [0,1,0]

ChangeLog

  • Version 0.2: expose PSP (C++) class, which is high customizable in python.
  • Version 0.3: expose PyGraphPDT (C++) class, which has similar API as PyGraph but different inner implementation.
  • Version 0.5: expose run_psp_i for InfoCluster.
  • Version 0.7: change the python binding name from info_cluster to pspartition.

Project details


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Built Distributions

pspartition-0.7.post5-cp37-cp37m-win_amd64.whl (114.1 kB view hashes)

Uploaded CPython 3.7m Windows x86-64

pspartition-0.7.post5-cp37-cp37m-manylinux2010_x86_64.whl (220.3 kB view hashes)

Uploaded CPython 3.7m manylinux: glibc 2.12+ x86-64

pspartition-0.7.post5-cp37-cp37m-macosx_10_14_x86_64.whl (135.2 kB view hashes)

Uploaded CPython 3.7m macOS 10.14+ x86-64

pspartition-0.7.post5-cp36-cp36m-win_amd64.whl (114.2 kB view hashes)

Uploaded CPython 3.6m Windows x86-64

pspartition-0.7.post5-cp36-cp36m-manylinux2010_x86_64.whl (220.3 kB view hashes)

Uploaded CPython 3.6m manylinux: glibc 2.12+ x86-64

pspartition-0.7.post5-cp36-cp36m-macosx_10_13_x86_64.whl (136.6 kB view hashes)

Uploaded CPython 3.6m macOS 10.13+ x86-64

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