`scipy.signal._filter_design:lp2bp`

source: /scipy/signal/_filter_design.py:2143

Signature

def lp2bp(b, a, wo = 1.0, bw = 1.0)

Summary

Transform a lowpass filter prototype to a bandpass filter.

Extended Summary

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

b : array_like, shape (M,): Numerator polynomial coefficients. Must be 1-D.
a : array_like, shape (N,): Denominator polynomial coefficients. Must be 1-D.
wo : float: Desired passband center, as angular frequency (e.g., rad/s). Defaults to no change.
bw : float: Desired passband width, as angular frequency (e.g., rad/s). Defaults to 1.

Returns

b : array_like: Numerator polynomial coefficients of the transformed band-pass filter.
a : array_like: Denominator polynomial coefficients of the transformed band-pass filter.

Notes

This is derived from the s-plane substitution

s \to \frac{s ^{2} + ω _{0} ^{2}}{s \cdot BW}

This is the "wideband" transformation, producing a passband with geometric (log frequency) symmetry about wo.

Array API Standard Support

lp2bp 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                   ⚠️ no JIT             ⛔                   
Dask                  ⚠️ computes graph     n/a                 
====================  ====================  ====================

See dev-arrayapi for more information.

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()

✗

<matplotlib.legend.Legend object at 0x7fa8f6894830>

Aliases

scipy.signal.lp2bp