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