# scipy.signal.step2

scipy.signal.step2(system, X0=None, T=None, N=None, **kwargs)

  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.

  Deprecated since version 1.11.0: Function `step2` is deprecated in favor of the faster `step` function. `step2` will be removed in SciPy 1.13.

  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.

  See also

  `scipy.signal.step`

  Notes

  As `step2` is now deprecated, users are advised to switch to the faster and more accurate `step` function. Keyword arguments for `scipy.integrate.odeint` are not supported in `step`, 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

      >>> from scipy import signal
      >>> import matplotlib.pyplot as plt

      >>> lti = signal.lti([1.0], [1.0, 1.0])
      >>> t, y = signal.step2(lti)

      >>> plt.plot(t, y)
      >>> plt.xlabel('Time [s]')
      >>> plt.ylabel('Amplitude')
      >>> plt.title('Step response for 1. Order Lowpass')
      >>> plt.grid()