bundles / scipy latest / scipy / signal / _filter_design / lp2bs
function
scipy.signal._filter_design:lp2bs
Signature
def lp2bs ( b , a , wo = 1.0 , bw = 1.0 ) Summary
Transform a lowpass filter prototype to a bandstop filter.
Extended Summary
Return an analog band-stop 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_likeNumerator polynomial coefficients.
a: array_likeDenominator polynomial coefficients.
wo: floatDesired stopband center, as angular frequency (e.g., rad/s). Defaults to no change.
bw: floatDesired stopband width, as angular frequency (e.g., rad/s). Defaults to 1.
Returns
b: array_likeNumerator polynomial coefficients of the transformed band-stop filter.
a: array_likeDenominator polynomial coefficients of the transformed band-stop filter.
Notes
This is derived from the s-plane substitution
This is the "wideband" transformation, producing a stopband with geometric (log frequency) symmetry about wo.
Array API Standard Support
lp2bs 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 ⛔ ⛔ Dask ⚠️ computes graph n/a ==================== ==================== ====================
See
dev-arrayapifor more information.
Examples
from scipy import signal import matplotlib.pyplot as plt✓
lp = signal.lti([1.0], [1.0, 1.5]) bs = signal.lti(*signal.lp2bs(lp.num, lp.den)) w, mag_lp, p_lp = lp.bode() w, mag_bs, p_bs = bs.bode(w)✓
plt.plot(w, mag_lp, label='Lowpass') plt.plot(w, mag_bs, label='Bandstop') plt.semilogx()✗
plt.grid(True)
✓plt.xlabel('Frequency [rad/s]') plt.ylabel('Amplitude [dB]') plt.legend()✗
See also
Aliases
-
scipy.signal.lp2bs