This is a pre-production deployment of Warehouse, however changes made here WILL affect the production instance of PyPI.
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Project Description

This Python package implements the clustering algorithm proposed by Alex Rodriguez and Alessandro Laio. It generates the initial rho and delta values for each observation then use these values to assign observations to clusters.

Installation

This version is for both python2 and python3. The first step is to install Python. Python is available from the Python project page. Dcluster depends on numpy and matplotlib. The next step is to install Dcluster.

You can download the source code at Github or at PyPi for Dcluster, and then run:

$ python setup.py install

Or install from PyPi using pip , a package manager for Python:

$ pip install Dcluster

Usage

The only input is the distance metrics between observations. See the test.dat. Dcluster supports interacive clustering based on Decision Graph:

import Dcluster as dcl
filein="test.dat"
dcl.run(fi=filein, sep='\t')

Test data

See the test.dat in test/. One can choose different cluster centers based on Decision Graph. And please first press key ‘n’ then ‘Enter’ to quit. Result will be saved automatically.

Contact

Author: Guipeng Li

Email: guipeng.lee@gmail.com

Refences

Rodriguez, A., & Laio, A. (2014). Clustering by fast search and find of density peaks. Science, 344(6191), 1492-1496. (paper)

Release History

Release History

0.5.2

This version

History Node

TODO: Figure out how to actually get changelog content.

Changelog content for this version goes here.

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0.5.0

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0.4.0

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0.3.0

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0.2.0

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Download Files

Download Files

TODO: Brief introduction on what you do with files - including link to relevant help section.

File Name & Checksum SHA256 Checksum Help Version File Type Upload Date
Dcluster-0.5.2.tar.gz (18.1 kB) Copy SHA256 Checksum SHA256 Source Mar 26, 2016

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