scipy.signal.step2¶

scipy.signal.step2(system, X0=None, T=None, N=None, **kwargs)[source]¶

Step response of continuous-time system.

This function is functionally the same as scipy.signal.step, but it uses the function scipy.signal.lsim2 to compute the step response.

Parameters:

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) X0 : array_like, optional Initial state-vector (default is zero). T : array_like, optional Time points (computed if not given). N : int, optional Number of time points to compute if T is not given. kwargs : various types Additional keyword arguments are passed on the function `scipy.signal.lsim2`, which in turn passes them on to `scipy.integrate.odeint`. See the documentation for `scipy.integrate.odeint` for information about these arguments.
Returns:	T : 1D ndarray Output time points. yout : 1D ndarray Step response of system.

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)

X0 : array_like, optional

Initial state-vector (default is zero).

T : array_like, optional

Time points (computed if not given).

N : int, optional

Number of time points to compute if T is not given.

kwargs : various types

Additional keyword arguments are passed on the function scipy.signal.lsim2, which in turn passes them on to scipy.integrate.odeint. See the documentation for scipy.integrate.odeint for information about these arguments.

Returns:

T : 1D ndarray

Output time points.

yout : 1D ndarray

Step response of system.