bundles / scipy 1.17.1 / scipy / signal / _ltisys / impulse
function
scipy.signal._ltisys:impulse
source: /scipy/signal/_ltisys.py :2011
Signature
def impulse ( system , X0 = None , T = None , N = None ) Summary
Impulse response of continuous-time system.
Parameters
system: an instance of the LTI class or a tuple of array_likedescribing 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, optionalInitial state-vector. Defaults to zero.
T: array_like, optionalTime points. Computed if not given.
N: int, optionalThe number of time points to compute (if
Tis not given).
Returns
T: ndarrayA 1-D array of time points.
yout: ndarrayA 1-D array containing the impulse response of the system (except for singularities at zero).
Notes
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]).
Array API Standard Support
impulse has experimental support for Python Array API Standard compatible backends in addition to NumPy. Please consider testing these features by setting an environment variable SCIPY_ARRAY_API=1 and providing CuPy, PyTorch, JAX, or Dask arrays as array arguments. The following combinations of backend and device (or other capability) are supported.
==================== ==================== ==================== Library CPU GPU ==================== ==================== ==================== NumPy ✅ n/a CuPy n/a ✅ PyTorch ✅ ✅ JAX ✅ ✅ Dask ✅ n/a ==================== ==================== ====================
See
dev-arrayapifor more information.
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.impulse(system) import matplotlib.pyplot as plt✓
plt.plot(t, y)
✗Aliases
-
scipy.signal.impulse