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mds_plot.py mds_plot.xml static/images/mds_plot.png test_data/mds_plot_on_sm_dat.png test_data/sm.dat tool_dependencies.xml |
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| diff -r 000000000000 -r fe542273784f mds_plot.py --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/mds_plot.py Thu Aug 15 03:39:14 2013 -0400 |
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| @@ -0,0 +1,29 @@ +#!/usr/bin/env python + +import argparse +import os +import sklearn.manifold +import numpy +import math +import pylab + +if __name__ == "__main__": + parser = argparse.ArgumentParser( + description="""2D multidimenisnal scaling of NxN matrices with scatter plot""" + ) + + parser.add_argument("-i", "--input", dest="sm", + required=True, + help="Path to the input file.") + parser.add_argument("--oformat", default='png', help="Output format (png, svg)") + parser.add_argument("-o", "--output", dest="output_path", + help="Path to the output file.") + + args = parser.parse_args() + mds = sklearn.manifold.MDS( n_components=2, max_iter=300, eps=1e-6, dissimilarity='precomputed' ) + data = numpy.fromfile( args.sm ) + d = math.sqrt( len(data) ) + sm = numpy.reshape( data, ( d,d )) + pos = mds.fit( sm ).embedding_ + pylab.scatter( pos[:,0],pos[:,1] ) + pylab.savefig( args.output_path, format=args.oformat ) |
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| diff -r 000000000000 -r fe542273784f mds_plot.xml --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/mds_plot.xml Thu Aug 15 03:39:14 2013 -0400 |
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| @@ -0,0 +1,52 @@ +<tool id="ctb_mds_plot" name="MDS Scatter Plot" version="0.1"> + <description>of molecule similarity</description> + <requirements> + <requirement type="package" version="0.13.1">scikit_learn</requirement> + <requirement type="package" version="1.2.1">matplotlib</requirement> + </requirements> + <command interpreter='python'> + mds_plot.py + -i $infile + --oformat $oformat + -o $outfile + </command> + <inputs> + <param name="infile" type="data" format="binary" label="Similarity Matrix"/> + <param name='oformat' type='select' format='text' label="Format of the resulting picture"> + <option value='png'>PNG</option> + <option value='svg'>SVG</option> + </param> + </inputs> + <outputs> + <data type="data" format="png" name="outfile" label="${tool.name} on ${on_string}"></data> + </outputs> + <tests> + <test> + <param name="infile" ftype="tabular" value="sm.dat" /> + <output ftype="png" name="outfile" file='mds_plot_on_sm_dat.png' /> + </test> + </tests> + <help> + +**Note**. You need an NxN similarity matrix as input. Use the NxN Clustering tool to generate one. + +**What it does** + +Scatter plot of similarity matrix after embeding in 2D coordinates using Multidimensional Scaling (MDS). + +----- + +**Example** + +* input:: + Similarity Matrix + +* output:: + + Scatter plot + +.. image:: $PATH_TO_IMAGES/mds_plot.png + + </help> + +</tool> |
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| diff -r 000000000000 -r fe542273784f tool_dependencies.xml --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/tool_dependencies.xml Thu Aug 15 03:39:14 2013 -0400 |
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| @@ -0,0 +1,15 @@ +<?xml version="1.0"?> +<tool_dependency> + <package name="numpy" version="1.7.1"> + <repository changeset_revision="74c21f9bdc39" name="package_numpy_1_7" owner="iuc" prior_installation_required="True" toolshed="http://toolshed.g2.bx.psu.edu" /> + </package> + <package name="matplotlib" version="1.2.1"> + <repository changeset_revision="9d164359606b" name="package_matplotlib_1_2" owner="iuc" prior_installation_required="True" toolshed="http://toolshed.g2.bx.psu.edu" /> + </package> + <package name="scipy" version="0.12.0"> + <repository changeset_revision="aa5180c893f5" name="package_scipy_0_12" owner="iuc" prior_installation_required="True" toolshed="http://toolshed.g2.bx.psu.edu" /> + </package> + <package name="scikit_learn" version="0.13.1"> + <repository changeset_revision="76f69ae982b8" name="package_scikit_learn_0_13" owner="iuc" prior_installation_required="True" toolshed="http://toolshed.g2.bx.psu.edu" /> + </package> +</tool_dependency> |
