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1 #!/usr/bin/env python
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2
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3 import argparse
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4 import os
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5 import sklearn.manifold
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6 import numpy
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7 import math
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8 import pylab
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9
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10 if __name__ == "__main__":
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11 parser = argparse.ArgumentParser(
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12 description="""2D multidimenisnal scaling of NxN matrices with scatter plot"""
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13 )
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14
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15 parser.add_argument("-i", "--input", dest="sm",
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16 required=True,
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17 help="Path to the input file.")
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18 parser.add_argument("--oformat", default='png', help="Output format (png, svg)")
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19 parser.add_argument("-o", "--output", dest="output_path",
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20 help="Path to the output file.")
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21
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22 args = parser.parse_args()
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23 mds = sklearn.manifold.MDS( n_components=2, max_iter=300, eps=1e-6, dissimilarity='precomputed' )
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24 data = numpy.fromfile( args.sm )
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25 d = math.sqrt( len(data) )
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26 sm = numpy.reshape( data, ( d,d ))
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27 pos = mds.fit( sm ).embedding_
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28 pylab.scatter( pos[:,0],pos[:,1] )
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29 pylab.savefig( args.output_path, format=args.oformat )
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