
import numpy as np

def generate_quadrant(items):
    X = np.random.uniform(low=-1, high=1, size=(items, 2)).astype('float32')

    t = np.zeros(items, dtype='int32')
    t += np.all([X[:, 0] < 0, X[:, 1] >= 0], axis=0) * 1
    t += np.all([X[:, 0] < 0, X[:, 1] < 0], axis=0) * 2
    t += np.all([X[:, 0] >= 0, X[:, 1] < 0], axis=0) * 3
    return (X, t)

@@ -14,16 +14,17 @@
  as np%0A%0A
+%0A
 def gene
@@ -350,8 +350,229 @@
  (X, t)%0A
+%0A%0Adef generate_accumulated(items, T=5):%0A    X = np.random.randint(0, 11, size=(items, 2, T))%0A%0A    t = np.sum(X, axis=1)%0A    t = np.cumsum(t, axis=1)%0A    t = np.mod(t, 10)%0A    return (X.astype('int32'), t.astype('int32'))%0A

add sequence dataset generator