scipy.signal.impulse2¶

scipy.signal.
impulse2
(system, X0=None, T=None, N=None, **kwargs)[source]¶ Impulse response of a singleinput, continuoustime linear system.
Parameters:  system : an instance of the LTI class or a tuple of array_like
describing the system. The following gives the number of elements in the tuple and the interpretation:
 1 (instance of
lti
)  2 (num, den)
 3 (zeros, poles, gain)
 4 (A, B, C, D)
 1 (instance of
 X0 : 1D array_like, optional
The initial condition of the state vector. Default: 0 (the zero vector).
 T : 1D array_like, optional
The time steps at which the input is defined and at which the output is desired. If T is not given, the function will generate a set of time samples automatically.
 N : int, optional
Number of time points to compute. Default: 100.
 kwargs : various types
Additional keyword arguments are passed on to the function
scipy.signal.lsim2
, which in turn passes them on toscipy.integrate.odeint
; see the latter’s documentation for information about these arguments.
Returns:  T : ndarray
The time values for the output.
 yout : ndarray
The output response of the system.
Notes
The solution is generated by calling
scipy.signal.lsim2
, which uses the differential equation solverscipy.integrate.odeint
.If (num, den) is passed in for
system
, coefficients for both the numerator and denominator should be specified in descending exponent order (e.g.s^2 + 3s + 5
would be represented as[1, 3, 5]
).New in version 0.8.0.
Examples
Second order system with a repeated root: x’‘(t) + 2*x(t) + x(t) = u(t)
>>> from scipy import signal >>> system = ([1.0], [1.0, 2.0, 1.0]) >>> t, y = signal.impulse2(system) >>> import matplotlib.pyplot as plt >>> plt.plot(t, y)