`scipy.signal._ltisys:freqresp`

source: /scipy/signal/_ltisys.py :2212

Signature

def freqresp ( system , w = None , n = 10000 )

Summary

Calculate the frequency response of a continuous-time system.

Parameters

system : an instance of the `lti` class or a tuple 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)

w : array_like, optional

Array of frequencies (in rad/s). Magnitude and phase data is calculated for every value in this array. If not given, a reasonable set will be calculated.

n : int, optional

Number of frequency points to compute if w is not given. The n frequencies are logarithmically spaced in an interval chosen to include the influence of the poles and zeros of the system.

Returns

w : 1D ndarray: Frequency array [rad/s]
H : 1D ndarray: Array of complex magnitude values

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

freqresp 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-arrayapi for more information.

Examples

Generating the Nyquist plot of a transfer function

from scipy import signal
import matplotlib.pyplot as plt

✓

Construct the transfer function :math:`H(s) = \frac{5}{(s-1)^3}`:

s1 = signal.ZerosPolesGain([], [1, 1, 1], [5])

✓

w, H = signal.freqresp(s1)

✓

plt.figure()
plt.plot(H.real, H.imag, "b")
plt.plot(H.real, -H.imag, "r")

✗

plt.show()

✓

Aliases

scipy.signal.freqresp