from pylab import text,show,cm,axis,figure,subplot,imshow,zeros
figure(1)
im = 0
result = np.array([])
for x,t in zip(data,num): # scatterplot
w = drmap.winner(x)
result.resize((im+1,3))
result[im][0]=w[0]
result[im][1]=w[1]
result[im][2]=num[im]
text(w[0]+.5, w[1]+.5, str(t), color=cm.Dark2(t / 8.), fontdict={'weight': 'bold', 'size': 11})
im = im + 1
axis([0,drmap.weights.shape[0],0,drmap.weights.shape[1]])
# Save SOM file
drmap.save_map()
else:
if mode == 2:
print "Using LLE"
construct = manifold.LocallyLinearEmbedding(n_neighbors, n_components=2, method='standard')
if fresh_data == 1:
print "Training..."
drmap = construct.fit(data)
print "\n...ready!"
f = open('LLE','w')
pickle.dump(drmap,f)
f.close()
else:
print "Loading Data"
f = open('LLE', 'r')
