cupyx.scipy.signal.freqz_zpk#
- cupyx.scipy.signal.freqz_zpk(z, p, k, worN=512, whole=False, fs=6.283185307179586)[source]#
Compute the frequency response of a digital filter in ZPK form.
Given the Zeros, Poles and Gain of a digital filter, compute its frequency response:
\(H(z)=k \prod_i (z - Z[i]) / \prod_j (z - P[j])\)
where \(k\) is the gain, \(Z\) are the zeros and \(P\) are the poles.
- Parameters:
z (array_like) – Zeroes of a linear filter
p (array_like) – Poles of a linear filter
k (scalar) – Gain of a linear filter
worN ({None, int, array_like}, optional) –
If a single integer, then compute at that many frequencies (default is N=512).
If an array_like, compute the response at the frequencies given. These are in the same units as fs.
whole (bool, optional) – Normally, frequencies are computed from 0 to the Nyquist frequency, fs/2 (upper-half of unit-circle). If whole is True, compute frequencies from 0 to fs. Ignored if w is array_like.
fs (float, optional) – The sampling frequency of the digital system. Defaults to 2*pi radians/sample (so w is from 0 to pi).
- Returns:
w (ndarray) – The frequencies at which h was computed, in the same units as fs. By default, w is normalized to the range [0, pi) (radians/sample).
h (ndarray) – The frequency response, as complex numbers.