freqresp#
- scipy.signal.freqresp(system, w=None, n=10000)[source]#
- Calculate the frequency response of a continuous-time system. - Parameters:
- systeman instance of the lticlass 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) 
 
- warray_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. 
- nint, 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. 
 
- systeman instance of the 
- Returns:
- w1D ndarray
- Frequency array [rad/s] 
- H1D 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 + 5would be represented as- [1, 3, 5]).- Examples - Generating the Nyquist plot of a transfer function - >>> from scipy import signal >>> import matplotlib.pyplot as plt - Construct the transfer function \(H(s) = \frac{5}{(s-1)^3}\): - >>> 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() 