lp2bp#
- scipy.signal.lp2bp(b, a, wo=1.0, bw=1.0)[source]#
- Transform a lowpass filter prototype to a bandpass filter. - Return an analog band-pass filter with center frequency wo and bandwidth bw from an analog low-pass filter prototype with unity cutoff frequency, in transfer function (‘ba’) representation. - Parameters:
- barray_like
- Numerator polynomial coefficients. 
- aarray_like
- Denominator polynomial coefficients. 
- wofloat
- Desired passband center, as angular frequency (e.g., rad/s). Defaults to no change. 
- bwfloat
- Desired passband width, as angular frequency (e.g., rad/s). Defaults to 1. 
 
- Returns:
- barray_like
- Numerator polynomial coefficients of the transformed band-pass filter. 
- aarray_like
- Denominator polynomial coefficients of the transformed band-pass filter. 
 
 - Notes - This is derived from the s-plane substitution \[s \rightarrow \frac{s^2 + {\omega_0}^2}{s \cdot \mathrm{BW}}\]- This is the “wideband” transformation, producing a passband with geometric (log frequency) symmetry about wo. - Examples - >>> from scipy import signal >>> import matplotlib.pyplot as plt - >>> lp = signal.lti([1.0], [1.0, 1.0]) >>> bp = signal.lti(*signal.lp2bp(lp.num, lp.den)) >>> w, mag_lp, p_lp = lp.bode() >>> w, mag_bp, p_bp = bp.bode(w) - >>> plt.plot(w, mag_lp, label='Lowpass') >>> plt.plot(w, mag_bp, label='Bandpass') >>> plt.semilogx() >>> plt.grid(True) >>> plt.xlabel('Frequency [rad/s]') >>> plt.ylabel('Amplitude [dB]') >>> plt.legend() 