Live plotting

lammps_logfile/File.py

@@ -19,6 +19,7 @@ def __init__(self, ifile):
         self.keywords = []
         self.output_before_first_run = ""
         self.partial_logs = []
+        self.num_timesteps = []
         if hasattr(ifile, "read"):
             self.logfile = ifile
         else:
@@ -35,6 +36,11 @@ def read_file_to_dict(self):
             if before_first_run_flag:
                 self.output_before_first_run += line
 
+            if line.startswith("run "):
+                splitted = line.split()
+                if splitted[1].isdigit():
+                    self.num_timesteps.append(int(splitted[1]))
+
             if keyword_flag:
                 keywords = line.split()
                 tmpString = ""
@@ -47,7 +53,7 @@ def read_file_to_dict(self):
                         line = contents[i]
                     else:
                         break
-                partialLogContents = pd.read_table(StringIO(tmpString), sep=r'\s+')
+                partialLogContents = pd.read_table(StringIO(tmpString), sep=r'\s+', error_bad_lines=False)
 
                 if (self.keywords != keywords):
                     # If the log keyword changes, i.e. the thermo data to be outputted chages,
@@ -123,3 +129,8 @@ def to_exdir_group(self, name, exdirfile):
 
     def get_num_partial_logs(self):
         return len(self.partial_logs)
+
+
+    def get_num_timesteps(self):
+        """Return list of number of timesteps for each partial log."""
+        return self.num_timesteps

lammps_logfile/cmd_interface.py

@@ -2,29 +2,66 @@
 from lammps_logfile import running_mean
 import argparse
 import matplotlib.pyplot as plt
+from matplotlib.animation import FuncAnimation
 
 def get_parser():
     parser = argparse.ArgumentParser(description="Plot contents from lammps log files")
     parser.add_argument("input_file", type=str, help="Lammps log file containing thermo output from lammps simulation.")
-    parser.add_argument("-x", type=str, default="Time", help="Data to plot on the first axis")
+    parser.add_argument("-x", type=str, default="Time", help="Data to plot on the first axis.")
     parser.add_argument("-y", type=str, nargs="+", help="Data to plot on the second axis. You can supply several names to get several plot lines in the same figure.")
-    parser.add_argument("-a", "--running_average", type=int, default=1, help="Optionally average over this many log entries with a running average. Some thermo properties fluctuate wildly, and often we are interested in te running average of properties like temperature and pressure.")
+    parser.add_argument("-a", "--running_average", type=int, default=1, help="Optionally average over this many log entries with a running average. Some thermo properties fluctuate wildly, and often we are interested in the running average of properties like temperature and pressure.")
+    parser.add_argument("-s", "--subplots", default=False, action='store_true', help="Show subplot panels for different graphs.")
+    parser.add_argument("-p", "--progress", default=False, action='store_true', help="Show progress of simulation. This requires that 'Step' is written to log file.")
+    parser.add_argument("-l", "--live", default=False, action='store_true', help="Show live visualisation of graphs. This is useful when monitoring thermo outputs during simulation.")
     return parser
 
+
+def create_progress_string(log):
+    """Returning string with progress"""
+    try:
+        steps = log.get("Step")
+    except:
+        raise ValueError("'Step' is not written to logfile! Not able to monitor progress.")
+    rel_step = int(steps[-1] - steps[0])
+    num_steps = log.num_timesteps[-1]
+    return f"{rel_step}/{num_steps}"
+
+
 def run():
     args = get_parser().parse_args()
-    log = File(args.input_file)
-    x = log.get(args.x)
-    print(x)
-    for y in args.y:
-        data = log.get(y)
-        print(data)
-
-        if args.running_average >= 2:
-            x = running_mean(x, args.running_average)
-            data = running_mean(data, args.running_average)
-
-        plt.plot(x, data, label=y)
-    plt.legend()
-    plt.show()
+    if args.subplots:
+        fig, ax = plt.subplots(len(args.y), sharex=True, squeeze=False)
+    else:
+        fig = plt.figure()
+
+    def get_data(i=0):
+        log = File(args.input_file)
+        x = log.get(args.x)
+        #print(x)
+        plt.cla()
+        for i, y in enumerate(args.y):
+            data = log.get(y)
+            #print(data)
+
+            if args.running_average >= 2:
+                x = running_mean(x, args.running_average)
+                data = running_mean(data, args.running_average)
+
+            if args.subplots:
+                ax[i, 0].cla()
+                ax[i, 0].plot(x, data)
+                ax[-1, 0].set_xlabel(args.x)
+                ax[i, 0].set_ylabel(y)
+            else:
+                plt.plot(x, data, label=y)
+                plt.legend()
+        if args.progress:
+            fig.suptitle(create_progress_string(log))
+        plt.tight_layout(rect=[0, 0.03, 1, 0.95])
 
+    if args.live:
+        ani = FuncAnimation(fig, get_data, interval=1000)
+    else:
+        get_data()
+    plt.show()
+