colors = ['red', 'blue', 'darkgreen', 'orange', 'purple', 'gray']
cmaps = [
plt.cm.Reds, plt.cm.Blues, plt.cm.Greens, plt.cm.Oranges, plt.cm.Purples,
plt.cm.gray_r
]
i = 0
for k, v, in res.iteritems():
plt.subplot(1, 3, i + 1)
i += 1
xmin = np.min(v[:, 0])
xmax = np.max(v[:, 0])
ymin = np.min(v[:, 1])
ymax = np.max(v[:, 1])
for l in range(nstrains):
idx = label == l
fplt.plot_embedding(v[idx], title=k, color=colors[l])
fplt.plot_embedding_contours(v[idx],
cmap=cmaps[l],
contours=15,
xmin=xmin,
xmax=xmax,
ymin=ymin,
ymax=ymax)
#fig.suptitle('Embeddings JS-Diverence all')
if fig_dir is not None:
fig.savefig(
os.path.join(fig_dir, 'new_JSD_embedding_all_tbins=%d.pdf' % (tbins)))
fig.savefig(
os.path.join(fig_dir, 'new_JSD_embedding_all_tbins=%d.png' % (tbins)))
for algo_name in algorithms:
assert(algo_name in ALGORITHMS, "Unknown algorithm: %s" % algo_name)
title = algo_name.title() + "-" + dataset.title()
algo_class = getattr(algos, algo_name)
algo = algo_class(n_components=2, **ALGORITHMS.get(algo_name, {}))
try:
logging.info("Running " + " ".join(title.split("-")))
if type == ARTIFICIAL:
X_data = X[0]
X_data.dtype='float64'
X_reduced = algo.run(X_data)
plot_artificial_dataset(X_data, X_reduced, color=X[1], title=title, save=args.save, saveDir=output_dir)
else:
X_data = X["data"]
X_reduced = algo.run(X_data)
# For 2 dimensional
plot_embedding(X_reduced, X["target"], X["images"], X['target'], title, save=args.save, saveDir=output_dir)
if args.threeD:
# For 3 dimensional
algo = algo_class(n_components=3, n_neighbors=30)
X_reduced = algo.run(X_data)
title = title + "-" + "3D"
plot_embedding_3D(X_reduced, X["target"], title, save=args.save, saveDir=output_dir)
except Exception, e:
logging.error("Dataset: %s, Algorithm: %s crashed. Error::%s" % (dataset, algo_name, e))