lp2hp(b, a, wo=1.0)
Return an analog high-pass filter with cutoff frequency :None:None:`wo` from an analog low-pass filter prototype with unity cutoff frequency, in transfer function ('ba') representation.
This is derived from the s-plane substitution
$$s \rightarrow \frac{\omega_0}{s}$$This maintains symmetry of the lowpass and highpass responses on a logarithmic scale.
Numerator polynomial coefficients.
Denominator polynomial coefficients.
Desired cutoff, as angular frequency (e.g., rad/s). Defaults to no change.
Numerator polynomial coefficients of the transformed high-pass filter.
Denominator polynomial coefficients of the transformed high-pass filter.
Transform a lowpass filter prototype to a highpass filter.
>>> from scipy import signal
... import matplotlib.pyplot as plt
>>> lp = signal.lti([1.0], [1.0, 1.0])
... hp = signal.lti(*signal.lp2hp(lp.num, lp.den))
... w, mag_lp, p_lp = lp.bode()
... w, mag_hp, p_hp = hp.bode(w)
>>> plt.plot(w, mag_lp, label='Lowpass')See :
... plt.plot(w, mag_hp, label='Highpass')
... 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_zpk
scipy.signal._filter_design.lp2hp
scipy.signal._filter_design.lp2lp
scipy.signal._filter_design.lp2bs
scipy.signal._filter_design.lp2bp
scipy.signal._filter_design.bilinear
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