Merge branch 'master' of https://github.com/AdaptivePELE/AdaptivePELE

AdaptivePELE/analysis/backtrackAdaptiveTrajectory.py

@@ -88,8 +88,11 @@ def main(trajectory, snapshot, epoch, outputPath, out_filename, topology, use_pd
         epoch = str(epoch)
     sys.stderr.write("Writing pathway...\n")
     with open(outputPath+out_filename, "a") as f:
-        f.write("ENDMDL\n".join(itertools.chain.from_iterable(pathway)))
-
+        if topology:
+            #Quick fix to avoid problems when visualizing with PyMol
+            f.write("ENDMDL\nMODEL     2\n".join(itertools.chain.from_iterable(pathway)))
+        else:
+            f.write("ENDMDL\n".join(itertools.chain.from_iterable(pathway)))
 
 if __name__ == "__main__":
     traj, num_snapshot, num_epoch, output_path, output_filename, top, use_pdb = parseArguments()

AdaptivePELE/analysis/bestStructs.py

@@ -37,11 +37,12 @@
 OUTPUT_FOLDER = 'BestStructs'
 DIR = os.path.abspath(os.getcwd())
 STEPS=3
+HELP = "USE:\n\n- For xtc: python bestStructs.py 5 --top topology.pdb\n\n- For pdb:  python bestStructs.py 5"
 
 
 def parse_args():
 
-    parser = argparse.ArgumentParser()
+    parser = argparse.ArgumentParser(description=HELP, formatter_class=argparse.RawTextHelpFormatter)
     parser.add_argument("crit", type=str, nargs='+', help="Criteria we want to rank and output the strutures for. Must be a column of the report. i.e: Binding Energy")
     parser.add_argument("--crit2", type=str, nargs='+', help="Second Criteria we want to rank and output the strutures for. Must be a column of the report. i.e: SasaLig, i.e.2. 3", default="")
     parser.add_argument("--path", type=str, help="Path to Pele's results root folder i.e: path=/Pele/results/", default=DIR)
@@ -124,7 +125,7 @@ def main(criteria, path=DIR, n_structs=10, sort_order="min", out_freq=FREQ, outp
 def extract_snapshot_from_pdb(path, f_id, output, topology, step, out_freq, f_out):
     f_in = glob.glob(os.path.join(os.path.dirname(path), "*trajectory*_{}.pdb".format(f_id)))
     if not f_in:
-        glob.glob(os.path.join(os.path.dirname(path), "*trajectory*_{}.*".format(f_id)))
+        f_in = glob.glob(os.path.join(os.path.dirname(path), "*trajectory*_{}.*".format(f_id)))
     if len(f_in) == 0:
         sys.exit("Trajectory {} not found. Be aware that PELE trajectories must contain the label \'trajectory\' in their file name to be detected".format("*trajectory*_{}".format(f_id)))
     f_in = f_in[0]
@@ -147,7 +148,7 @@ def extract_snapshot_from_pdb(path, f_id, output, topology, step, out_freq, f_ou
             raise AttributeError("Model not found. Check the -f option.")
         traj.append("ENDMDL\n")
         f.write("\n".join(traj))
-
+    print("Model {} selected".format(os.path.join(output, f_out)))
 
 def extract_snapshot_from_xtc(path, f_id, output, topology, step, out_freq, f_out):
     f_in = glob.glob(os.path.join(os.path.dirname(path), "*trajectory*_{}.xtc".format(f_id)))
@@ -156,6 +157,8 @@ def extract_snapshot_from_xtc(path, f_id, output, topology, step, out_freq, f_ou
     if len(f_in) == 0: 
         sys.exit("Trajectory {} not found. Be aware that PELE trajectories must contain the label \'trajectory\' in their file name to be detected".format("*trajectory*_{}".format(f_id)))
     splitTrajectory.main(output, [f_in[0], ], topology, [(step)/out_freq+1, ], template= f_out)
+    print("Model {} selected".format(f_out))
+