DataGenerator/ContinuousNonZero.py [27:55]:
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	reset_counter = 0
	for t in range(number_timesteps-1):
		
		# GET B
		if t>0:
			# b_array[t] = np.random.binomial(1,prob_b_given_x)
			# b_array_dataset[i,t] = np.random.binomial(1,pb_x[0,x_array_dataset[i,t]])

			# If 3,4,5 timesteps have passed, terminate. 
			if reset_counter>=3 and reset_counter<5:
				b_array_dataset[i,t] = np.random.binomial(1,0.33)
			elif reset_counter==5:
				b_array_dataset[i,t] = 1

		# GET Y
		if b_array_dataset[i,t]:
			y_array_dataset[i,t] = np.random.random_integers(0,high=3)
			reset_counter = 0
		else:
			reset_counter+=1
			y_array_dataset[i,t] = y_array_dataset[i,t-1]

		# GET A

		# -0.05 is because the noise is from 0-0.1, so to balance this we make it -0.05
		a_array_dataset[i,t] = action_map[y_array_dataset[i,t]]-0.05+0.1*np.random.random((2)) 

		# GET X
		x_array_dataset[i,t+1] = x_array_dataset[i,t]+a_array_dataset[i,t]
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DataGenerator/ContinuousTrajs.py [25:51]:
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	reset_counter = 0
	for t in range(number_timesteps-1):
		
		# GET B
		if t>0:
			# b_array[t] = np.random.binomial(1,prob_b_given_x)
			# b_array_dataset[i,t] = np.random.binomial(1,pb_x[0,x_array_dataset[i,t]])

			# If 3,4,5 timesteps have passed, terminate. 
			if reset_counter>=3 and reset_counter<5:
				b_array_dataset[i,t] = np.random.binomial(1,0.33)
			elif reset_counter==5:
				b_array_dataset[i,t] = 1

		# GET Y
		if b_array_dataset[i,t]:
			y_array_dataset[i,t] = np.random.random_integers(0,high=3)
			reset_counter = 0
		else:
			reset_counter+=1
			y_array_dataset[i,t] = y_array_dataset[i,t-1]

		# GET A
		a_array_dataset[i,t] = action_map[y_array_dataset[i,t]]-0.05+0.1*np.random.random((2))  		

		# GET X
		x_array_dataset[i,t+1] = x_array_dataset[i,t]+a_array_dataset[i,t]
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