annotate hbonds.py @ 0:d710c7f00ae6 draft

planemo upload for repository https://github.com/galaxycomputationalchemistry/galaxy-tools-compchem/ commit 3ff06e3182c3a1546ea0a3b29e0d4383e12169e1
author chemteam
date Wed, 03 Apr 2019 15:46:32 -0400
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d710c7f00ae6 planemo upload for repository https://github.com/galaxycomputationalchemistry/galaxy-tools-compchem/ commit 3ff06e3182c3a1546ea0a3b29e0d4383e12169e1
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1 #!/usr/bin/env python
d710c7f00ae6 planemo upload for repository https://github.com/galaxycomputationalchemistry/galaxy-tools-compchem/ commit 3ff06e3182c3a1546ea0a3b29e0d4383e12169e1
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3 import argparse
d710c7f00ae6 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.analysis.hbonds
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9 import pandas as pd
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12 def parse_command_line(argv):
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13 parser = argparse.ArgumentParser()
d710c7f00ae6 planemo upload for repository https://github.com/galaxycomputationalchemistry/galaxy-tools-compchem/ commit 3ff06e3182c3a1546ea0a3b29e0d4383e12169e1
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14 parser.add_argument('--idcd', help='input dcd')
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15 parser.add_argument('--ipdb', help='input pdb')
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16 parser.add_argument('--isegid1', help='segid 1')
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17 parser.add_argument('--isegid2', help='segid 2')
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18 parser.add_argument('--idistance', help='cutoff distance')
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19 parser.add_argument('--iangle', help='ctoff angle')
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20 parser.add_argument('--output', help='output')
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21 parser.add_argument('--ofreq_output', help='frequency output')
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22 parser.add_argument('--onumber_output', help='number of hbond output')
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23 parser.add_argument('--otime_output', help='time steps output')
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24 return parser.parse_args()
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27 args = parse_command_line(sys.argv)
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29 selection1 = "segid %s" % args.isegid1
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30 selection2 = "segid %s" % args.isegid2
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31 distance = float(args.idistance)
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32 angle = float(args.iangle)
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34 u = MDAnalysis.Universe(
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35 args.ipdb, args.idcd, topology_format="PDB", format="DCD")
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37 h = MDAnalysis.analysis.hbonds.HydrogenBondAnalysis(
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38 u, selection1, selection2, distance=distance, angle=angle)
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39 h.run()
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40 h.generate_table()
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42 df = pd.DataFrame.from_records(h.table)
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43 df.to_csv(args.output, sep='\t')
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44
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45 t1 = list(h.count_by_type())
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46 t2 = list(h.count_by_time())
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47 t3 = list(h.timesteps_by_type())
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48
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49 with open(args.ofreq_output, 'w') as f:
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50 f.write("donor_index\tacceptor_index\t\
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51 donor_resname\tdonor_resid\tdonor_atom\t\
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52 hydrogen_atom\tacceptor_reansme\tacceptor_resid\t\
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53 acceptor_atom\tfrequency\n")
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54 writer = csv.writer(f, delimiter='\t')
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55 writer.writerows(t1)
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56
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57
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58 with open(args.onumber_output, 'w') as f1:
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59 f1.write("time_step\tno_of_h_bonds\n")
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60 writer = csv.writer(f1, delimiter='\t')
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61 writer.writerows(t2)
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62
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63 with open(args.otime_output, 'w') as f2:
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64 f2.write("donor_index\tacceptor_index\t\
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65 donor_resname\tdonor_resid\tdonor_atom\t\
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66 hydrogen_atom\tacceptor_reansme\tacceptor_resid\t\
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67 acceptor_atom\ttime_step\n")
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68 writer = csv.writer(f2, delimiter='\t')
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69 writer.writerows(t3)