lp2bp(b, a, wo=1.0, bw=1.0)
Return an analog band-pass filter with center frequency :None:None:`wo`
and bandwidth :None:None:`bw`
from an analog low-pass filter prototype with unity cutoff frequency, in transfer function ('ba') representation.
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 :None:None:`wo`
.
Numerator polynomial coefficients.
Denominator polynomial coefficients.
Desired passband center, as angular frequency (e.g., rad/s). Defaults to no change.
Desired passband width, as angular frequency (e.g., rad/s). Defaults to 1.
Numerator polynomial coefficients of the transformed band-pass filter.
Denominator polynomial coefficients of the transformed band-pass filter.
Transform a lowpass filter prototype to a bandpass filter.
>>> 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')See :
... plt.plot(w, mag_bp, label='Bandpass')
... plt.semilogx()
... plt.grid()
... plt.xlabel('Frequency [rad/s]')
... plt.ylabel('Magnitude [dB]')
... plt.legend()
The following pages refer to to this document either explicitly or contain code examples using this.
scipy.signal._filter_design.lp2hp
scipy.signal._filter_design.lp2lp
scipy.signal._filter_design.lp2bp_zpk
scipy.signal._filter_design.lp2bs
scipy.signal._filter_design.lp2bp
scipy.signal._filter_design.bilinear
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