value = cursor.fetchall() value = value[0][0] try: value_channel_dict[channel].append(value) except KeyError: value_channel_dict[channel] = [] value_channel_dict[channel].append(value) # determine corresponding isotype if channel == channel1[0]: isotype = igdbq.get_H_isotype(int(event[0]), cursor) if isotype: isotype = isotype[0][0] try: color = igdbplt.get_color(isotype) # some are IGKC??? except KeyError: color = 'black' else: color = 'white' try: value_channel_dict['color'].append(color) except KeyError: value_channel_dict['color'] = [] value_channel_dict['color'].append(color) factor = 1 if args.mutation == True: factor = igdbq.get_mutation_count(int(event[0]), cursor) try:
if args.normalize == True: norm_fact = 1./sum(gene_heights) plt.xlim(0,1) norm = "norm" else: norm_fact = 1 norm = "abs" palette = igplt.random_colors(200) bottom = 0 for height, label in zip(gene_heights, gene_labels): # make redundant labels dissapear from legend if label not in label_list: label_list.append(label) leg_label = label else: leg_label = "" plt.bar(left = bottom, height = 0.8, width = height*norm_fact, orientation='horizontal', label = leg_label, bottom = i, color = igplt.get_color(label) + (0.8,)) bottom = height*norm_fact + bottom # format legend if len(label_list) > 15: ncol = 2 else: ncol = 1 lgd = plt.legend(loc='center left', bbox_to_anchor=(1, 0.5), ncol = ncol) plt.yticks(np.arange(len(event_names))+0.4, event_names) lbl = plt.xlabel('Counts') plt.ylim(-0.1, len(event_names)-0.1) ttl = plt.title(igplt.plot_log('Segment usage', sys.argv, db)) plt.savefig(args.outputdir + "/%s_%s_%s_%s_%s_%s_%s" % (db, args.event_infile, resolve, segment, args.locus, args.plotstyle, norm) + '.pdf', bbox_extra_artists=(ttl,lbl,), bbox_inches='tight') else: