Use Agg backend when saving images. Add option for UTC times.

poretools/hist.py

@@ -18,6 +18,10 @@ def plot_hist(sizes, args):
     """
     sizes = [s for s in sizes if args.min_length < s < args.max_length]
 
+    if args.saveas is not None:
+        plt.switch_backend('Agg') # Use non-interactive backend in case this is
+                                  # running on a headless system.
+
     if args.theme_bw:
         sns.set_style("whitegrid")
     plt.hist(sizes, args.num_bins)

poretools/occupancy.py

@@ -25,6 +25,9 @@ def plot_performance(parser, args, pore_measure):
     """
     Plot the pore performance in terms of reads per pore
     """
+    if args.saveas is not None:
+        plt.switch_backend('Agg') # Use non-interactive backend in case this is
+                                  # running on a headless system.
     flowcell_layout = minion_flowcell_layout()
 
     pore_values = []

poretools/poretools_main.py

@@ -445,6 +445,11 @@ def main():
     ##########
     parser_times = subparsers.add_parser('times',
                                         help='Return the start times from a set of FAST5 files in tabular format')
+    parser_times.add_argument('--utc',
+                               dest='utc',
+                               default=False,
+                               action='store_true',
+                               help="Show timestamps in UTC.")
     parser_times.add_argument('files', metavar='FILES', nargs='+',
                                help='The input FAST5 files.')
     parser_times.set_defaults(func=run_subtool)

poretools/qual_v_pos.py

@@ -1,6 +1,7 @@
 import Fast5File
 from collections import defaultdict
 import pandas
+import sys
 import matplotlib.pyplot as plt
 
 #logging
@@ -42,6 +43,10 @@ def run(parser, args):
 
         fast5.close()
 
+    if args.saveas is not None:
+        plt.switch_backend('Agg') # Use non-interactive backend in case this is
+                                  # running on a headless system.
+
     logger.info("Processing data...")
     data = [qualpos[e] for e in sorted(qualpos.keys())]
     logger.info("Constructing box plot...")
@@ -53,10 +58,10 @@ def run(parser, args):
     if args.saveas is not None:
             logger.info("Writing plot to file...")
             plot_file = args.saveas
-            if plot_file.endswith(".pdf") or plot_file.endswith(".jpg"):
+            if plot_file.endswith(".pdf") or plot_file.endswith(".png") or plot_file.endswith(".svg"):
                     plt.savefig(plot_file)
             else:
-                    logger.error("Unrecognized extension for %s! Try .pdf or .jpg" % (plot_file))
+                    logger.error("Unrecognized extension for %s! Try .pdf, .png, or .svg" % (plot_file))
                     sys.exit()
 
     else:

poretools/squiggle.py

@@ -36,6 +36,10 @@ def plot_squiggle(args, filename, start_times, mean_signals):
     starts = df.groupby('cat')['start']
     mins, maxs = list(starts.min()), list(starts.max())
 
+    if args.saveas is not None:
+        plt.switch_backend('Agg') # Use non-interactive backend in case this is
+                                  # running on a headless system.
+
     grid = sns.FacetGrid(df, row="cat", sharex=False, size=8)
     #plt.gcf().tight_layout()
     grid.fig.suptitle('Squiggle plot for read: ' + filename + "\nTotal time (sec): " + str(total_time))

poretools/times.py

@@ -1,5 +1,5 @@
 import Fast5File
-from time import strftime, localtime
+from time import strftime, localtime, gmtime
 import sys
 
 #logging
@@ -28,7 +28,10 @@ def run(parser, args):
 			else:
 				read_length = 0
 
-			lt = localtime(start_time)
+			if args.utc:
+				lt = gmtime(start_time)
+			else:
+				lt = localtime(start_time)
 			print "\t".join([str(fast5.get_channel_number()),
 				fast5.filename, 
 				str(read_length),

poretools/yield_plot.py

@@ -50,6 +50,10 @@ def plot_collectors_curve(args, start_times, read_lengths):
         if args.theme_bw:
             sns.set_style("whitegrid")
 
+        if args.saveas is not None:
+            plt.switch_backend('Agg') # Use non-interactive backend in case this is
+                                      # running on a headless system.
+
         # plot
         plt.plot(df['start'], df['cumul'])
         plt.xlabel('Time (hours)')