bundles / scipy latest / scipy / signal / _filter_design / buttord
function
scipy.signal._filter_design:buttord
Signature
def buttord ( wp , ws , gpass , gstop , analog = False , fs = None ) Summary
Butterworth filter order selection.
Extended Summary
Return the order of the lowest order digital or analog Butterworth filter that loses no more than gpass dB in the passband and has at least gstop dB attenuation in the stopband.
Parameters
wp, ws: float or array-likePassband and stopband edge frequencies.
For digital filters, these are in the same units as
fs. By default,fsis 2 half-cycles/sample, so these are normalized from 0 to 1, where 1 is the Nyquist frequency. (wpandwsare thus in half-cycles / sample.) For example:Lowpass: wp = 0.2, ws = 0.3
Highpass: wp = 0.3, ws = 0.2
Bandpass: wp = [0.2, 0.5], ws = [0.1, 0.6]
Bandstop: wp = [0.1, 0.6], ws = [0.2, 0.5]
For analog filters,
wpandwsare angular frequencies (e.g., rad/s).gpass: floatThe maximum loss in the passband (dB).
gstop: floatThe minimum attenuation in the stopband (dB).
analog: bool, optionalWhen True, return an analog filter, otherwise a digital filter is returned.
fs: float, optionalThe sampling frequency of the digital system.
Returns
Notes
Array API Standard Support
buttord 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 ==================== ==================== ====================
The torch backend on GPU does not support the case where wp and ws specify a Bandstop filter.
See
dev-arrayapifor more information.
Examples
Design an analog bandpass filter with passband within 3 dB from 20 to 50 rad/s, while rejecting at least -40 dB below 14 and above 60 rad/s. Plot its frequency response, showing the passband and stopband constraints in gray.from scipy import signal import matplotlib.pyplot as plt import numpy as np✓
N, Wn = signal.buttord([20, 50], [14, 60], 3, 40, True) b, a = signal.butter(N, Wn, 'band', True) w, h = signal.freqs(b, a, np.logspace(1, 2, 500))✓
plt.semilogx(w, 20 * np.log10(abs(h))) plt.title('Butterworth bandpass filter fit to constraints') plt.xlabel('Frequency [rad/s]') plt.ylabel('Amplitude [dB]')✗
plt.grid(which='both', axis='both')
✓plt.fill([1, 14, 14, 1], [-40, -40, 99, 99], '0.9', lw=0) # stop plt.fill([20, 20, 50, 50], [-99, -3, -3, -99], '0.9', lw=0) # pass plt.fill([60, 60, 1e9, 1e9], [99, -40, -40, 99], '0.9', lw=0) # stop plt.axis([10, 100, -60, 3])✗
plt.show()
✓
See also
Aliases
-
scipy.signal.buttord