scipy.signal.impulse2#
- scipy.signal.impulse2(system, X0=None, T=None, N=None, **kwargs)[source]#
Impulse response of a single-input, continuous-time linear system.
Deprecated since version 1.11.0: Function
impulse2
is deprecated in favor of the fasterimpulse
function.impulse2
will be removed in SciPy 1.13.- Parameters:
- systeman 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)
- X01-D array_like, optional
The initial condition of the state vector. Default: 0 (the zero vector).
- T1-D 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.
- Nint, optional
Number of time points to compute. Default: 100.
- kwargsvarious types
Additional keyword arguments are passed on to the function
scipy.signal.lsim2
, which in turn passes them on toscipy.integrate.odeint
; see the latterâ€™s documentation for information about these arguments.
- Returns:
- Tndarray
The time values for the output.
- youtndarray
The output response of the system.
See also
Notes
The solution is generated by calling
scipy.signal.lsim2
, which uses the differential equation solverscipy.integrate.odeint
.As
impulse2
is now deprecated, users are advised to switch to the faster and more accurateimpulse
function. Keyword arguments forscipy.integrate.odeint
are not supported inimpulse
, but not needed in general.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
Compute the impulse response of a 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)