tf = open('novelty_plant.txt','r')
first = True
for line in tf.readlines():
if (not first):
data = [float(x) for x in line.strip().split('\t') if x != '']
# indata = tuple(data[:6])
# outdata = tuple(data[6:])
ds.addSample(data)
first = False
n = buildNetwork(ds.dim,8,8,1,recurrent=True)
t = DeepBeliefTrainer(n,ds, epochs=50)
t.trainEpochs(1)
t.testOnData(ds, verbose= True)
ds.addSample((0, 0), (0,))
ds.addSample((0, 1), (1,))
ds.addSample((1, 0), (1,))
ds.addSample((1, 1), (0,))
for input, target in ds:
print(input, target)
#net = buildNetwork(2, 3, 1, bias=True, hiddenclass=TanhLayer)#1000
# net = buildNetwork(2, 6, 1, bias=True) # 3000
net = buildNetwork(2, 3, 1, bias=True)
trainer = BackpropTrainer(net, ds)
