bundles / scipy 1.18.0 / scipy / signal / _filter_design / lp2bp_zpk
function
scipy.signal._filter_design:lp2bp_zpk
Signature
def lp2bp_zpk(z, p, k, 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, using zeros, poles, and gain ('zpk') representation.
Parameters
z: array_likeZeros of the analog filter transfer function.
p: array_likePoles of the analog filter transfer function.
k: floatSystem gain of the analog filter transfer function.
wo: floatDesired passband center, as angular frequency (e.g., rad/s). Defaults to no change.
bw: floatDesired passband width, as angular frequency (e.g., rad/s). Defaults to 1.
Returns
z: ndarrayZeros of the transformed band-pass filter transfer function.
p: ndarrayPoles of the transformed band-pass filter transfer function.
k: floatSystem gain of the transformed band-pass filter.
Notes
This is derived from the s-plane substitution
This is the "wideband" transformation, producing a passband with geometric (log frequency) symmetry about wo.
Array API Standard Support
lp2bp_zpk 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
Use the 'zpk' (Zero-Pole-Gain) representation of a lowpass filter to transform it to a bandpass filter with a center frequency wo and bandwidth bw.from scipy.signal import lp2bp_zpk z = [ 5 + 2j , 5 - 2j ] p = [ 7 , -16 ] k = 0.8 wo = 0.62 bw = 15✓
lp2bp_zpk(z, p, k, wo, bw)
✗(array([7.49955815e+01+3.00017676e+01j, 7.49955815e+01-3.00017676e+01j,
4.41850748e-03-1.76761126e-03j, 4.41850748e-03+1.76761126e-03j]), array([ 1.04996339e+02+0.j, -1.60167736e-03+0.j, 3.66108003e-03+0.j,
-2.39998398e+02+0.j]), 0.8)
See also
Aliases
scipy.signal.lp2bp_zpk