...

Author: Dom Laetsch

lib/BtIO.py

@@ -202,7 +202,7 @@ def readCas(infile, order_of_blobs):
                     seqs_parsed += 1
                 except:
                     pass
-            BtLog.progress(seqs_parsed, progress_unit, seqs_total)
+                BtLog.progress(seqs_parsed, progress_unit, seqs_total)
     return cov_dict, reads_total, reads_mapped, read_cov_dict
 
 def readTax(infile, set_of_blobs):

lib/BtLog.py

@@ -22,7 +22,7 @@ def error(message, *argv):
 def progress(iteration, steps, max_value):
     if int(iteration == max_value):
         sys.stdout.write('\r')
-        print "[PROGRESS]\t: %d%%" % (100)
+        print "[PROGRESS]\t: %d%%\n" % (100)
     elif int(iteration) % int(steps) == 0:
         sys.stdout.write('\r')
         print "[PROGRESS]\t: %d%%" % (float(int(iteration)/int(max_value))*100),

lib/BtPlot.py

@@ -587,6 +587,12 @@ def plotBlobs(self, cov_lib, info_flag):
                 if group == "no-hit":
                     alpha = 0.5
                 weights_array = group_length_array/1000
+                print group
+                print group_gc_array
+                print group_cov_array
+                print weights_array
+                print top_bins
+                print right_bins
                 # generate label for legend
                 fmt_seqs = "{:,}".format(group_number_of_seqs)
                 fmt_span = "{:,}".format(group_span_in_mb)
@@ -596,12 +602,6 @@ def plotBlobs(self, cov_lib, info_flag):
                     print BtLog.info_d['0'] % (group, fmt_seqs, fmt_span, fmt_n50)
                 legend_handles.append(Line2D([0], [0], linewidth = 0.5, linestyle="none", marker="o", alpha=1, markersize=24, markerfacecolor=colour))
                 legend_labels.append(label)
-                print group
-                print group_gc_array
-                print group_cov_array
-                print weights_array
-                print top_bins
-                print right_bins
                 if (self.hist_type == "span"):
                     axHistx.hist(group_gc_array, weights=weights_array, color = colour, bins = top_bins, histtype='step', lw = 3)
                     axHisty.hist(group_cov_array, weights=weights_array, color = colour, bins = right_bins, histtype='step', orientation='horizontal', lw = 3)