Bug fix that caused an issue with the RMSD matrix being the same desp…

…ite the "-sr" argument.

environment.yml

@@ -14,3 +14,4 @@ dependencies:
 - scikit-learn
 - prettytable
 - numba
+- hashlib

requirements.txt

@@ -14,4 +14,5 @@ prettytable
 scipy >= 0.18
 scitkit-learn
 mdtraj >= 1.7
-numba
+numba
+hashlib

setup.py

@@ -1,8 +1,8 @@
 from setuptools import setup, find_packages
 
 MAJOR = 4
-MINOR = 8
-PATCH = 4
+MINOR = 10
+PATCH = 0
 VERSION = "{}.{}.{}".format(MAJOR, MINOR, PATCH)
 
 with open("ttclust/version.py", "w") as f:
@@ -30,6 +30,7 @@
                       'scipy >= 0.18',
                       'scikit-learn',
                       'numba',
+                      'hashlib'
                       'mdtraj >= 1.7'],
 
     entry_points={'console_scripts':['ttclust=ttclust.ttclust:main']},

ttclust/ttclust.py

@@ -539,8 +539,8 @@ def create_DM(traj, args):
                                                      traj=traj,
                                                      args=args)
 
-        RMSD_selection = return_selection_atom("RMSD", traj=traj,
-                                               args=args)
+        # RMSD_selection = return_selection_atom("RMSD", traj=traj,
+        #                                        args=args)
 
         # Trajectory superposition  (aligment)
         traj_aligned = traj.superpose(traj[0],
@@ -549,12 +549,15 @@ def create_DM(traj, args):
     else:
         traj_aligned = traj
 
-    select_align = improve_nucleic_acid(args["select_alignement"])
+    # select_align = improve_nucleic_acid(args["select_alignement"])
+    # Transform the RMSD string for nucleic acids.
     untouch_rmsd_string = args["select_rmsd"]
     rmsd_string = improve_nucleic_acid(args["select_rmsd"])
 
+    # If the RMSD string is not empty
     if rmsd_string:
         print("NOTE : Extraction of subtrajectory for time optimisation")
+        # Extract the subpart.
         traj_aligned = extract_selected_atoms(rmsd_string, traj_aligned, args["logname"])
     # matrix initialization
     distances = np.zeros((traj.n_frames, traj.n_frames))
@@ -568,14 +571,14 @@ def create_DM(traj, args):
         return np.load(distance_file)
     else:  # otherwise
 
-        pbar = pg.ProgressBar(widgets=WIDGETS, maxval=traj.n_frames).start()
+        pbar = pg.ProgressBar(widgets=WIDGETS, maxval=traj_aligned.n_frames).start()
         counter = 0
         # Pairwise RMSD calculation (matrix n²)
-        for i in range(traj.n_frames):
+        for i in range(traj_aligned.n_frames):
             # distances[i] = md.rmsd(traj_aligned, traj_aligned, frame=i)
 
-            for j in range(i + 1, traj.n_frames):
-                rmsd = calc_rmsd_2frames(traj.xyz[i], traj.xyz[j])
+            for j in range(i + 1, traj_aligned.n_frames):
+                rmsd = calc_rmsd_2frames(traj_aligned.xyz[i], traj_aligned.xyz[j])
                 distances[i][j] = rmsd
                 distances[j][i] = rmsd
             pbar.update(counter)

ttclust/version.py

@@ -1 +1 @@
-__version__ = '4.9.0'
+__version__ = '4.10.0'