# sort by LL and select best
mixtures.sort()
best_bound, best_mixture = mixtures[-1]
logging.info("Best variational bound = %f", best_bound)
# save model if requested
if options.model_file:
logging.info("Saving model to %s", options.model_file)
cPickle.dump(best_mixture, open(options.model_file, "w"))
# plot distribution if requested
if options.plot_file:
logging.info("Plotting distribution to %s", options.plot_file)
from cookbook.pylab_utils import set_rcParams_for_latex, get_fig_size_for_latex
set_rcParams_for_latex()
# fig_size = get_fig_size_for_latex(1000)
pl.rcParams["figure.figsize"] = (4.652, 3.2)
pl.figure()
mixture_x, mixture = best_mixture.plot(log=options.log_plot, legend=False)
pl.savefig("mixture-%s.eps" % options.plot_file, format="eps")
pl.close()
mixture_x, mixture = best_mixture.plot(log=options.log_plot, legend=False, scale=False)
pl.savefig("mixture-unscaled-%s.eps" % options.plot_file, format="eps")
pl.close()
beta.plot_density_with_R(x, weights, options.plot_file, mixture_x, mixture, adjust=0.15)
# write predictions if requested
if options.predictions_file:
P.loglog(fasta_sizes, stem_timings[
W], label='STEME W=%d' % W, ls='-', color=colour)
P.loglog(fasta_sizes, meme_timings[
W], label='MEME W=%d' % W, ls='-.', color=colour)
P.legend(loc='upper left')
P.xlabel('\\# bases in data set')
P.ylabel('seconds')
P.savefig(os.path.join(output_dir, 'timings.eps'))
P.savefig(os.path.join(output_dir, 'timings.png'))
P.close()
#
# do the timings.
#
pylab_utils.set_rcParams_for_latex()
stem_timings = DictOf(list)
meme_timings = DictOf(list)
fasta_sizes = []
for fasta in fastas:
for W in Ws:
options.min_w = options.max_w = W
options.output_dir = os.path.join(
output_dir, 'W=%02d-%s' % (W, stempy.basename_wo_ext(fasta)))
stempy.ensure_dir_exists(options.output_dir)
stem_algorithm = stem.Algorithm(options)
meme_algorithm = meme.Algorithm(options)
stem_timings[W].append(timeit(lambda: stem_algorithm(fasta)))
meme_timings[W].append(timeit(lambda: meme_algorithm(fasta)))
fasta_sizes.append(stem_algorithm.num_bases)
save_timings()
