dimpulse — SciPy v1.16.0 Manual (original) (raw)
scipy.signal.
scipy.signal.dimpulse(system, x0=None, t=None, n=None)[source]#
Impulse response of discrete-time system.
Parameters:
systemdlti | tuple
An instance of the LTI class dlti or a tuple describing the system. The number of elements in the tuple determine the interpretation. I.e.:
system
: Instance of LTI class dlti. Note that derived instances, such as instances of TransferFunction, ZerosPolesGain, or StateSpace, are allowed as well.(num, den, dt)
: Rational polynomial as described in TransferFunction. The coefficients of the polynomials should be specified in descending exponent order, e.g., z² + 3z + 5 would be represented as[1, 3, 5]
.(zeros, poles, gain, dt)
: Zeros, poles, gain form as described in ZerosPolesGain.(A, B, C, D, dt)
: State-space form as described in StateSpace.
x0array_like, optional
Initial state-vector. Defaults to zero.
tarray_like, optional
Time points. Computed if not given.
nint, optional
The number of time points to compute (if t is not given).
Returns:
toutndarray
Time values for the output, as a 1-D array.
youttuple of ndarray
Impulse response of system. Each element of the tuple represents the output of the system based on an impulse in each input.
Examples
import numpy as np from scipy import signal import matplotlib.pyplot as plt ... dt = 1 # sampling interval is one => time unit is sample number bb, aa = signal.butter(3, 0.25, fs=1/dt) t, y = signal.dimpulse((bb, aa, dt), n=25) ... fig0, ax0 = plt.subplots() ax0.step(t, np.squeeze(y), '.-', where='post') ax0.set_title(r"Impulse Response of a 3rd3^\text{rd}3rd Order Butterworth Filter") ax0.set(xlabel='Sample number', ylabel='Amplitude') ax0.grid() plt.show()