annotate pca_cosine.py @ 0:f739a9e4ed06 draft

planemo upload for repository https://github.com/galaxycomputationalchemistry/galaxy-tools-compchem/ commit 3ff06e3182c3a1546ea0a3b29e0d4383e12169e1
author chemteam
date Wed, 03 Apr 2019 15:40:31 -0400
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children b923959babb6
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f739a9e4ed06 planemo upload for repository https://github.com/galaxycomputationalchemistry/galaxy-tools-compchem/ commit 3ff06e3182c3a1546ea0a3b29e0d4383e12169e1
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1 #!/usr/bin/env python
f739a9e4ed06 planemo upload for repository https://github.com/galaxycomputationalchemistry/galaxy-tools-compchem/ commit 3ff06e3182c3a1546ea0a3b29e0d4383e12169e1
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3 import argparse
f739a9e4ed06 planemo upload for repository https://github.com/galaxycomputationalchemistry/galaxy-tools-compchem/ commit 3ff06e3182c3a1546ea0a3b29e0d4383e12169e1
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4 import csv
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5 import sys
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7 import MDAnalysis as mda
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8 import MDAnalysis.analysis.pca as pca
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10 import numpy as np
f739a9e4ed06 planemo upload for repository https://github.com/galaxycomputationalchemistry/galaxy-tools-compchem/ commit 3ff06e3182c3a1546ea0a3b29e0d4383e12169e1
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13 def parse_command_line(argv):
f739a9e4ed06 planemo upload for repository https://github.com/galaxycomputationalchemistry/galaxy-tools-compchem/ commit 3ff06e3182c3a1546ea0a3b29e0d4383e12169e1
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14 parser = argparse.ArgumentParser()
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15 parser.add_argument('--idcd', help='input dcd')
f739a9e4ed06 planemo upload for repository https://github.com/galaxycomputationalchemistry/galaxy-tools-compchem/ commit 3ff06e3182c3a1546ea0a3b29e0d4383e12169e1
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16 parser.add_argument('--ipdb', help='input pdb')
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17 parser.add_argument('--icomponents', help='number of principle components')
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18 parser.add_argument('--iindex', help='index of the PC')
f739a9e4ed06 planemo upload for repository https://github.com/galaxycomputationalchemistry/galaxy-tools-compchem/ commit 3ff06e3182c3a1546ea0a3b29e0d4383e12169e1
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19 parser.add_argument('--output', help='output')
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20 parser.add_argument('--cosout', help='cosine output')
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21 return parser.parse_args()
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24 args = parse_command_line(sys.argv)
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26 u = mda.Universe(args.ipdb, args.idcd, topology_format="PDB", format="DCD")
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28 components = int(args.icomponents)
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29 pca_index = int(args.iindex)
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31 PSF_pca = pca.PCA(u, select='backbone')
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32 PSF_pca.run()
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33 n_pcs = np.where(PSF_pca.cumulated_variance > 0.95)[0][0]
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34 atomgroup = u.select_atoms('backbone')
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36 pca_space = PSF_pca.transform(atomgroup, n_components=components)
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37 cosine = mda.analysis.pca.cosine_content(pca_space, pca_index)
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39 PCA = list(pca_space)
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41 with open(args.output, 'w') as f:
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42 writer = csv.writer(f, delimiter='\t')
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43 writer.writerows(PCA)
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45 with open(args.cosout, 'w') as f1:
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46 f1.write(str(cosine))