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:
