plt.xlabel('t')
>>> plt.show()

In a second example, we simulate a double integrator ``y'' = u``, with
a constant input ``u = 1``.  We'll use the state space representation
of the integrator.

>>> from scipy.signal import lti
>>> A = np.array([[0.0, 1.0], [0.0, 0.0]])
>>> B = np.array([[0.0], [1.0]])
>>> C = np.array([[1.0, 0.0]])
>>> D = 0.0
>>> system = lti(A, B, C, D)

`t` and `u` define the time and input signal for the system to
be simulated.

>>> t = np.linspace(0, 5, num=50)
>>> u = np.ones_like(t)

Compute the simulation, and then plot `y`.  As expected, the plot shows
the curve ``y = 0.5*t**2``.

>>> tout, y, x = lsim(system, u, t)
>>> plt.plot(t, y)
>>> plt.grid(alpha=0.3)
>>> plt.xlabel('t')
>>> plt.show()

z3lsim can only be used with continuous-time systems.r