annotate distance_multiple.py @ 9:fd987ff06ceb draft default tip

"planemo upload for repository https://github.com/galaxycomputationalchemistry/galaxy-tools-compchem/ commit f1c3c88c7395f2e84cbc533199406aadb79c5c07"
author chemteam
date Fri, 13 Nov 2020 19:42:40 +0000
parents d540ea77b909
children
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d540ea77b909 "planemo upload for repository https://github.com/galaxycomputationalchemistry/galaxy-tools-compchem/ commit 12823af06b7926cc56aaf9b59cfea9f16d342b8c"
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1 import argparse
d540ea77b909 "planemo upload for repository https://github.com/galaxycomputationalchemistry/galaxy-tools-compchem/ commit 12823af06b7926cc56aaf9b59cfea9f16d342b8c"
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2 import sys
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4 import MDAnalysis as mda
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5 from MDAnalysis.analysis import distances
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7 import numpy as np
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10 def parse_command_line(argv):
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11 parser = argparse.ArgumentParser()
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12 parser.add_argument('--itraj', help='input traj')
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13 parser.add_argument('--istr', help='input str')
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14 parser.add_argument('--itrajext', help='input traj ext')
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15 parser.add_argument('--istrext', help='input str ext')
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16 parser.add_argument('--list1', help='list 2')
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17 parser.add_argument('--list2', help='list 2')
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18 parser.add_argument('--output', help='output')
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19 parser.add_argument('--header', dest='header', action='store_true')
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20 return parser.parse_args()
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23 args = parse_command_line(sys.argv)
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25 u = mda.Universe(args.istr, args.itraj,
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26 topology_format=args.istrext, format=args.itrajext)
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28 list1 = np.loadtxt(args.list1, dtype=str, delimiter="\t", ndmin=1)
d540ea77b909 "planemo upload for repository https://github.com/galaxycomputationalchemistry/galaxy-tools-compchem/ commit 12823af06b7926cc56aaf9b59cfea9f16d342b8c"
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29 list2 = np.loadtxt(args.list2, dtype=str, delimiter="\t", ndmin=1)
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31 sel1 = [u.select_atoms(selection) for selection in list1]
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32 sel2 = [u.select_atoms(selection) for selection in list2]
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34 d = np.empty((u.trajectory.n_frames, list1.shape[0], list2.shape[0]),)
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36 for ts in u.trajectory:
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37 c_o_m1 = np.array([selection.center_of_mass() for selection in sel1])
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38 c_o_m2 = np.array([selection.center_of_mass() for selection in sel2])
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39 distances.distance_array(c_o_m1, c_o_m2, result=d[ts.frame])
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41 d = np.hstack((
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42 np.array(np.reshape(np.arange(
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43 0, d.shape[0]), (d.shape[0], 1)), dtype=int), # add column w frame
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44 np.reshape(d, (d.shape[0], d.shape[1] * d.shape[2]))
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45 ))
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47 if args.header:
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48 header = 'Frame\t' + '\t'.join(
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49 ['-'.join(pair) for pair in zip(
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50 sum([[n, ] * len(list2) for n in list1], []),
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51 list(list2) * len(list1),)]).replace(' ', '_')
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52 else:
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53 header = ''
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55 np.savetxt(args.output, d, header=header, comments='',
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56 fmt=['%d'] + ['%f'] * (d.shape[1] - 1), delimiter='\t')