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.

See also

freqs

Compute the frequency response of an analog filter in TF form

freqs_zpk

Compute the frequency response of an analog filter in ZPK form

freqz

Compute the frequency response of a digital filter in TF form

scipy.signal.freqz_zpk