Mercurial > repos > chemteam > mdanalysis_distance

annotate ramachandran_auto_protein.py @ 7:ffd6f8d159e1 draft

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"planemo upload for repository https://github.com/galaxycomputationalchemistry/galaxy-tools-compchem/ commit 1b23e024af45cc0999d9142d07de6897d4189ec2"
author chemteam
date Mon, 24 Aug 2020 16:14:05 -0400
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7
ffd6f8d159e1 "planemo upload for repository https://github.com/galaxycomputationalchemistry/galaxy-tools-compchem/ commit 1b23e024af45cc0999d9142d07de6897d4189ec2"
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1 #!/usr/bin/env python
ffd6f8d159e1 "planemo upload for repository https://github.com/galaxycomputationalchemistry/galaxy-tools-compchem/ commit 1b23e024af45cc0999d9142d07de6897d4189ec2"
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ffd6f8d159e1 "planemo upload for repository https://github.com/galaxycomputationalchemistry/galaxy-tools-compchem/ commit 1b23e024af45cc0999d9142d07de6897d4189ec2"
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3 import argparse
ffd6f8d159e1 "planemo upload for repository https://github.com/galaxycomputationalchemistry/galaxy-tools-compchem/ commit 1b23e024af45cc0999d9142d07de6897d4189ec2"
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4 import base64
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5 import importlib
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6 import sys
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ffd6f8d159e1 "planemo upload for repository https://github.com/galaxycomputationalchemistry/galaxy-tools-compchem/ commit 1b23e024af45cc0999d9142d07de6897d4189ec2"
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8 import MDAnalysis as mda
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9 from MDAnalysis.analysis.dihedrals import Ramachandran
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11 import h5py
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13 from jinja2 import Environment, FileSystemLoader
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15 import matplotlib
ffd6f8d159e1 "planemo upload for repository https://github.com/galaxycomputationalchemistry/galaxy-tools-compchem/ commit 1b23e024af45cc0999d9142d07de6897d4189ec2"
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16 import matplotlib.pyplot as plt
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17 import matplotlib.ticker as ticker
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19 import numpy as np
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20 import numpy.linalg
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22 import seaborn as sns
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25 matplotlib.use('Agg') # noqa
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28 def parse_command_line(argv):
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29 parser = argparse.ArgumentParser()
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30 parser.add_argument('--itraj', help='input traj')
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31 parser.add_argument('--istr', help='input str')
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32 parser.add_argument('--itrajext', help='input traj ext')
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33 parser.add_argument('--istrext', help='input str ext')
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34 parser.add_argument('--isegid1', help='segid 1')
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35 parser.add_argument('--iresid1', help='resid start')
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36 parser.add_argument('--iresid2', help='resid end')
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37 parser.add_argument('--iresname', help='resname e.g. ALA')
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38 parser.add_argument('--igroupby', help='groupby names or ids')
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39 parser.add_argument('--itemplatepath', help='template path')
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40 parser.add_argument('--o_plot1', help='MDA Ramachandran plot')
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41 parser.add_argument('--o_plot2', help='Seaborn Ramachandran plot')
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42 parser.add_argument('--o_data1', help='Timeseries in HDF5 format')
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43 parser.add_argument('--o_html1', help='Html overview output of all plots')
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44 return parser.parse_args()
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47 args = parse_command_line(sys.argv)
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48
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49 currentpath = "."
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50 if args.itemplatepath is not None:
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51 currentpath = args.itemplatepath
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52
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53
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54 u = mda.Universe(args.istr, args.itraj,
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55 topology_format=args.istrext, format=args.itrajext)
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56 selection = "(segid %s)" % \
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57 (args.isegid1)
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58
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59 if args.iresname is not None:
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60 selection = "(segid %s and resname %s)" % \
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61 (args.isegid1, args.iresname)
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62
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63 if args.iresid1 is not None and args.iresid2 is not None:
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64 assert(int(args.iresid1) > 0), "ResID numbering starts at 1 for this tool."
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65 assert(int(args.iresid2) > 0), "ResID numbering starts at 1 for this tool."
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66 assert(int(args.iresid2) > int(args.iresid1)
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67 ), "ResID2 must be at least ResID1+1"
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68 selection = "(segid %s and resid %s-%s)" % \
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69 (args.isegid1, int(args.iresid1), int(args.iresid2))
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70 if args.iresname is not None:
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71 selection = "(segid %s and resid %s-%s and resname %s)" % \
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72 (args.isegid1, int(args.iresid1), int(args.iresid2), args.iresname)
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73
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74 r = u.select_atoms(selection)
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75
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76 assert(r != u.select_atoms('name thiscannotpossiblyexist')
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77 ), \
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78 """The selection you specified returns an empty result.
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79 Check segment names and residue ID's. Also check the
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80 structure and trajectory file selected are the correct ones"""
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81
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82 if args.igroupby is not None:
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83 group_selections = {} # dictionary of selections
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84 if args.igroupby == 'name':
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85 groupby = sorted(list(set(r.resnames)))
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86 for e in groupby:
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87 s = r & u.select_atoms("resname %s" % e)
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88 this_sel = "%s and resname %s" % (selection, e)
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89 group_selections[this_sel] = s
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90 elif args.igroupby == 'id':
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91 groupby = sorted(list(set(r.resids)))
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92 for e in groupby:
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93 s = r & u.select_atoms("resid %s" % e)
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94 this_sel = "%s and resid %s" % (selection, e)
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95 group_selections[this_sel] = s
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96 else:
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97 assert False, ("Invalid argument for igroupby. "
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98 "Only name and id are valid options.")
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99
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100
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101 def ramachandran_plot(atomgroup, selection, outputfile1, outputfile2,
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102 image_format='png'):
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103 # plot standard mdanalysis and seaborn 2D with kde
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104 R = Ramachandran(atomgroup).run()
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105 fig, ax = plt.subplots(figsize=plt.figaspect(1))
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106 R.plot(ax=ax, color='k', marker='.', ref=True)
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107
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108 a = R.angles.reshape(np.prod(R.angles.shape[:2]), 2)
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109 # open hdf file
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110 with h5py.File(args.o_data1, 'a') as f:
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111 setname = "%s" % (selection)
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112 f["/" + setname + "/ramachandran/phi"] = a[:, 0]
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113 f["/" + setname + "/ramachandran/psi"] = a[:, 1]
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114 plt.tight_layout()
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115 # svg is better but sticking with png for now
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116 plt.savefig(outputfile1, format=image_format)
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117
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118 sns.reset_defaults()
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119 importlib.reload(plt)
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120 importlib.reload(sns)
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121 with sns.axes_style("white"):
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122 h = sns.jointplot(x=a[:, 0], y=a[:, 1],
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123 kind="kde", space=0)
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124 h.set_axis_labels(r'$\phi$ (deg)', r'$\psi$ (deg)')
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125 h.ax_joint.set_xlim(-180, 180)
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126 h.ax_joint.set_ylim(-180, 180)
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127 h.ax_joint.xaxis.set_major_locator(ticker.MultipleLocator(60))
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128 h.ax_joint.yaxis.set_major_locator(ticker.MultipleLocator(60))
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129 plt.savefig(outputfile2, format=image_format, bbox_inches='tight')
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130
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131
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132 def get_base64_encoded_image(image_path):
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133 """ encode image to string for use in html later"""
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134 with open(image_path, "rb") as img_file:
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135 return base64.b64encode(img_file.read()).decode('utf-8')
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136
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137
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138 plots = []
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139 if args.igroupby is not None:
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140 for k, v in group_selections.items():
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141 print(k, v)
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142 try:
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143 ramachandran_plot(v, str(k), "ramachandran1" +
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144 str(k), "ramachandran2" + str(k))
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145 plots.append({'Name': "%s" % (k), 'plot1':
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146 get_base64_encoded_image("ramachandran1" + str(k)),
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147 'plot2': get_base64_encoded_image("ramachandran2"
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148 + str(k))})
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149 except Exception as einstance:
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150 print(type(einstance))
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151 print(einstance.args)
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152 print(einstance)
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153
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154 ramachandran_plot(r, selection, args.o_plot1, args.o_plot2)
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155 plots.insert(0, {'Name': selection, 'plot1': get_base64_encoded_image(
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156 args.o_plot1), 'plot2': get_base64_encoded_image(args.o_plot2)})
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157
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158 template_environment = Environment(loader=FileSystemLoader(
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159 currentpath), lstrip_blocks=True, trim_blocks=True)
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160 template = template_environment.get_template(
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161 'ramachandran_auto_protein_html.j2')
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162 with open(args.o_html1, 'w+') as f:
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163 f.write(template.render(title="Ramachandran Plots", plots=plots))