def spiral_data(minv=-0.1, maxv=0.1):
global N
data = []
labels = []
for i in xrange(N / 2):
r = i / N * 5 + convnet.randf(minv, maxv)
t = 1.25 * i / N * 2 * math.pi + convnet.randf(minv, maxv)
data.append((r * math.sin(t), r * math.cos(t)))
labels.append(1)
for i in xrange(N / 2):
r = i / N * 5 + convnet.randf(minv, maxv)
t = 1.25 * i / N * 2 * math.pi + math.pi + convnet.randf(minv, maxv)
data.append((r * math.sin(t), r * math.cos(t)))
labels.append(0)
return data, labels
def random_data(minv=-3, maxv=3):
global N
data = [(convnet.randf(minv, maxv), convnet.randf(minv, maxv)) for x in xrange(N)]
labels = [1 if convnet.randf(0, 1) > 0.5 else 0 for i in xrange(N)] # Randomly assign red / green
return data, labels
