ellipord — SciPy v1.15.3 Manual (original) (raw)
scipy.signal.
scipy.signal.ellipord(wp, ws, gpass, gstop, analog=False, fs=None)[source]#
Elliptic (Cauer) filter order selection.
Return the order of the lowest order digital or analog elliptic filter that loses no more than gpass dB in the passband and has at least_gstop_ dB attenuation in the stopband.
Parameters:
wp, wsfloat
Passband and stopband edge frequencies.
For digital filters, these are in the same units as fs. By default,fs is 2 half-cycles/sample, so these are normalized from 0 to 1, where 1 is the Nyquist frequency. (wp and ws are 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, wp and ws are angular frequencies (e.g., rad/s).
gpassfloat
The maximum loss in the passband (dB).
gstopfloat
The minimum attenuation in the stopband (dB).
analogbool, optional
When True, return an analog filter, otherwise a digital filter is returned.
fsfloat, optional
The sampling frequency of the digital system.
Added in version 1.2.0.
Returns:
ordint
The lowest order for an Elliptic (Cauer) filter that meets specs.
wnndarray or float
The Chebyshev natural frequency (the “3dB frequency”) for use withellip to give filter results. If fs is specified, this is in the same units, and fs must also be passed to ellip.
See also
Filter design using order and critical points
Find order and critical points from passband and stopband spec
General filter design using order and critical frequencies
General filter design using passband and stopband spec
Examples
Design an analog highpass filter such that the passband is within 3 dB above 30 rad/s, while rejecting -60 dB at 10 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.ellipord(30, 10, 3, 60, True) b, a = signal.ellip(N, 3, 60, Wn, 'high', True) w, h = signal.freqs(b, a, np.logspace(0, 3, 500)) plt.semilogx(w, 20 * np.log10(abs(h))) plt.title('Elliptical highpass filter fit to constraints') plt.xlabel('Frequency [rad/s]') plt.ylabel('Amplitude [dB]') plt.grid(which='both', axis='both') plt.fill([.1, 10, 10, .1], [1e4, 1e4, -60, -60], '0.9', lw=0) # stop plt.fill([30, 30, 1e9, 1e9], [-99, -3, -3, -99], '0.9', lw=0) # pass plt.axis([1, 300, -80, 3]) plt.show()