length_heights = []
lengths = []
for length in length_rows:
length_heights.append(length[0])
lengths.append(length[1])
return length_heights, lengths
#plt.figure()
for event_name, event_statement in zip(event_names, event_statements):
heights,lengths = get_region_lengths(event_statement)
if args.normalize:
heights = [height/float(sum(heights)) for height in heights]
if args.cumulative:
heights = [sum(heights[:i]) for i in range(len(heights))]
plt.plot(lengths, heights, label = event_name)
plt.legend(loc='center left', bbox_to_anchor=(1, 0.5))
plt.xlabel("Length of " + args.region + " region in amino acids")
if args.cumulative:
title = "Cumulative frequency"
else:
title = "Observed frequency"
if args.normalize:
title = title + " (normalized)"
plt.ylabel(title)
ttl = plt.title(igplt.plot_log(args.region + ' region length distribution', sys.argv, db))
plt.savefig(args.outputdir + "/%s_%s_%s_%s" % (args.event_infile, args.locus, args.region, title) + '.pdf', bbox_extra_artists=(ttl,), bbox_inches='tight')
plt.figure(figsize=(0.3*len(gene_labels), 7))
if args.normalize == True:
norm_fact = 1./sum(gene_heights)
gene_heights = [height*norm_fact for height in gene_heights]
norm = "norm"
plt.ylabel("Relative Frequencies")
else:
norm_fact = 1
norm = "abs"
plt.ylabel("Absolute frequencies")
positions = np.arange(0,len(gene_heights),1)
plt.bar(positions, gene_heights, color = 'grey')
ticks = plt.xticks(positions + 0.4, gene_labels, rotation = 90, fontsize = 12)
ttl = plt.title(event_name + "\n" + igplt.plot_log('Segment usage', sys.argv))
plt.savefig("%s_%s_%s_%s_%s_%s_%s" % (args.event_infile, event_name, resolve, segment, args.locus, args.plotstyle, norm)
+ '.pdf', bbox_extra_artists=(ttl,), bbox_inches='tight')
elif args.plotstyle == 'stacked':
plt.figure(figsize=(7, 0.7*len(event_statements)))
label_list = []
for event_statement, i in zip(event_statements, range(len(event_statements))):
#print event_statement
gene_heights, gene_labels = get_gene_list(event_statement)
if args.normalize == True:
norm_fact = 1./sum(gene_heights)
plt.xlim(0,1)
norm = "norm"
else:
norm_fact = 1
