Metadata-Version: 1.0
Name: dynamicTreeCut
Version: 0.1.1
Summary: Dynamic Tree Cut
Home-page: https://github.com/kylessmith/dynamicTreeCut
Author: Kyle S. Smith
Author-email: kyle.smith@stjude.org
License: GPL-3 Licenses
Description: |Stars| |PyPIDownloads| |PyPI| |Build Status| |Coffee|
        
        .. |Stars| image:: https://img.shields.io/github/stars/kylessmith/dynamicTreeCut?logo=GitHub&color=yellow
           :target: https://github.com/kylessmith/dynamicTreeCut/stargazers
        .. |PyPIDownloads| image:: https://pepy.tech/badge/dynamicTreeCut
           :target: https://pepy.tech/project/dynamicTreeCut
        .. |PyPI| image:: https://img.shields.io/pypi/v/dynamicTreeCut.svg
           :target: https://pypi.org/project/dynamicTreeCut
        .. |Build Status| image:: https://travis-ci.org/kylessmith/dynamicTreeCut.svg?branch=master
           :target: https://travis-ci.org/kylessmith/dynamicTreeCut
        .. |Coffee| image:: https://img.shields.io/badge/-buy_me_a%C2%A0coffee-gray?logo=buy-me-a-coffee&color=ff69b4
           :target: https://www.buymeacoffee.com/kylessmith
        
        
        Python translation of the hybrid dynamicTreeCut method created by Peter Langfelder and Bin Zhang.
        
        dynamicTreeCut was originally published by in *Bioinformatics*:
        	Langfelder P, Zhang B, Horvath S (2007) Defining clusters from a hierarchical cluster tree:
        	the Dynamic Tree Cut package for R. Bioinformatics 2008 24(5):719-720
        
        dynamicTreeCut R code is distributed under the GPL-3 License and
        original sources should be cited.
        
        
        dynamicTreeCut contains methods for detection of clusters in hierarchical clustering dendrograms.
        *NOTE: though the clusters match the R output, the cluster names are shuffled*
        
        Installing
        ==========
        
        To install, it's best to create an environment after installing and downloading the
        `Anaconda Python Distribution <https://www.continuum.io/downloads>`__
        
            conda env create --file environment.yml
        
        PyPI install, presuming you have all its requirements (numpy and scipy) installed::
        
        	pip install dynamicTreeCut
        
        	
        Importation
        ===========
        ::
        
        	>>> from dynamicTreeCut import cutreeHybrid
        	>>> from scipy.spatial.distance import pdist
        	>>> import numpy as np
        	>>> from scipy.cluster.hierarchy import linkage
        	>>> d = np.transpose(np.arange(1,10001).reshape(100,100))
        	>>> distances = pdist(d, "euclidean")
        	>>> link = linkage(distances, "average")
        	>>> clusters = cutreeHybrid(link, distances)
        	..cutHeight not given, setting it to 495.1  ===>  99% of the (truncated) height range in dendro.
        	..done.
        	>>> clusters["labels"]
        	[2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3
         	 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 1 1 1 1 1 1 1 1 1 1
         	 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1]
        	
        	
        Compared to R::
        
        	> library(dynamicTreeCut)
        	> d = matrix(1:10000, 100)
        	> distances <- dist(d, method="euclidean")
        	> dendro <- hclust(distances, method="average")
        	> clusters <- cutreeDynamic(dendro, distM=as.matrix(distances))
        	  ..cutHeight not given, setting it to 495  ===>  99% of the (truncated) height range in dendro.
        	  ..done.
        	> clusters
        	  [1] 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3
         	  [38] 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 1 1 1 1 1 1 1 1 1 1
         	  [75] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
        
        Installation
        ============
        
        If you dont already have numpy and scipy installed, it is best to download
        `Anaconda`, a python distribution that has them included.  
        
            https://continuum.io/downloads
        
        Dependencies can be installed by::
        
            pip install -r requirements.txt
        
        
        License
        =======
        
        dynamicTreeCut is available under the GPL-3 License
        
Platform: UNKNOWN
