two new arguments added to force "Frame" label in barplot axis and to…

… adjust size limit for distance matrix.

Per default, the distance matrix size limit should be high enough for every trajectory. If this graph takes too much time to generate, decrease this limit

README.md

@@ -189,6 +189,13 @@ the interactive prompt.
                         number of group ('-ng') 
   -i INTERACTIVE, --interactive INTERACTIVE
                         Interactive mode for distance matrix (Y/n)
+  -axis AXIS, --axis AXIS
+                        if something is wrong in the axis of timed barplot
+                        graph (wrong time unit), and you just want 'frame'
+                        instead of time Choose 'frame' here.
+  -limitmat LIMITMAT, --limitmat LIMITMAT
+                        If the distance matrix is too long to generate choose
+                        a limit here. Default is 100000000
 ```
 
 ## USAGE: 

setup.py

@@ -2,7 +2,7 @@
 
 MAJOR = 4
 MINOR = 7
-PATCH = 3
+PATCH = 4
 VERSION = "{}.{}.{}".format(MAJOR, MINOR, PATCH)
 
 with open("ttclust/version.py", "w") as f:

ttclust/ttclust.py

@@ -350,6 +350,13 @@ def parseArg():
     # Interactive mode for distance matrix:
     arguments.add_argument('-i', '--interactive', help="Use saved distance matrix ? (Y/n)", default="Y")
 
+
+    # Optional for graphics
+    arguments.add_argument('-axis', '--axis', help="if something is wrong in the axis of timed barplot graph "
+                                                   "(wrong time unit), and you just want 'frame' instead of time "
+                                                   " Choose 'frame' here.", default="default")
+    arguments.add_argument('-limitmat', '--limitmat', help= "If the distance matrix is too long to generate "
+                                                   "choose a limit here. Default is 100000000", default=100000000, type = int)
     args = vars(arguments.parse_args())
 
     # Activate autoclustering if autoclust is True and if no values was specified for ngroup or cutoff
@@ -752,14 +759,15 @@ def get_cmap(num_cluster):
     return cmap
 
 
-def plot_barplot(clusters_list, logname, size, traj):
+def plot_barplot(clusters_list, logname, size, traj, args):
     """
     DESCRIPTION
     This function is used to plot the linear barplots.
     Args:
         clusters_list (list) : list of cluster label in order or appearance
         logname (str) : output logname
         size (int): number of frames
+        args (dict): dictionnary of arguments
     Returns:
         colors_list (list of list) : list of colors in RGBA format
     """
@@ -778,7 +786,7 @@ def plot_barplot(clusters_list, logname, size, traj):
     fig, ax = plt.subplots(figsize=(10, 1.5))
 
     # get time if present
-    if traj.time.sum() < 0.0000005:
+    if traj.time.sum() < 0.0000005 or args["axis"].lower() == "frame" :
         timeMin, timeMax = 0, np.shape(data)[1]
         plt.xlabel("Frame")
 
@@ -1063,7 +1071,7 @@ def plot_2D_distance_projection(rmsd_m, clusters_list, colors, logname):
     plt.close()
 
 
-def generate_graphs(clusters_list, output, size, linkage, cutoff, distances, traj):
+def generate_graphs(clusters_list, output, size, linkage, cutoff, distances, traj, args):
     """
     DESCRIPTION
     Create a linear cluster mapping graph where every frame is printed as a
@@ -1076,13 +1084,16 @@ def generate_graphs(clusters_list, output, size, linkage, cutoff, distances, tra
         cutoff (float): cutoff distance value for clustering (in the dendogram)
         distances(numpy array): distance matrix
         traj (Trajectory): trajectory for time usage in axis barplot
+        args (dict): dictionnary of arguments.
     Return:
         colors_list (list) to be used with 2D distance projection graph
     """
-    colors_list = plot_barplot(clusters_list, output, size, traj)
+    colors_list = plot_barplot(clusters_list, output, size, traj, args)
     plot_dendro(linkage, output, cutoff, colors_list, clusters_list)
     plot_hist(clusters_list, output, colors_list)
-    if (distances.shape[0] < 10002):
+
+
+    if (distances.shape[0] < args["limitmat"]):
         plot_distmat(distances, output)
     else:
         printScreenLogfile("Too many frames (>=10002)! The RMSD distance matrix will not be generated")
@@ -1202,7 +1213,7 @@ def Cluster_analysis_call(args):
     # reordering the list by the cluster number
     clusters_list.sort(key=operator.attrgetter("id"))
     print("====== Generating Graph ======")
-    colors_list = generate_graphs(clusters_list, logname, traj.n_frames, linkage, cutoff, distances, traj)
+    colors_list = generate_graphs(clusters_list, logname, traj.n_frames, linkage, cutoff, distances, traj, args)
     print("====== Calc. repr. frame  ======")
     calculate_representative_frame_spread(clusters_list, distances)
 

ttclust/version.py

@@ -1 +1,2 @@
-__version__ = '4.7.3'
+__version__ = '4.7.4'
+