# scipy.signal.freqs¶

scipy.signal.freqs(b, a, worN=None, plot=None)

Compute frequency response of analog filter.

Given the numerator (b) and denominator (a) of a filter compute its frequency response:

```        b[0]*(jw)**(nb-1) + b[1]*(jw)**(nb-2) + ... + b[nb-1]
H(w) = -------------------------------------------------------
a[0]*(jw)**(na-1) + a[1]*(jw)**(na-2) + ... + a[na-1]```
Parameters : b : ndarray Numerator of a linear filter. a : ndarray Denominator of a linear filter. worN : {None, int}, optional If None, then compute at 200 frequencies around the interesting parts of the response curve (determined by pole-zero locations). If a single integer, the compute at that many frequencies. Otherwise, compute the response at frequencies given in worN. plot : callable A callable that takes two arguments. If given, the return parameters w and h are passed to plot. Useful for plotting the frequency response inside freqz. w : ndarray The frequencies at which h was computed. h : ndarray The frequency response.

freqz
Compute the frequency response of a digital filter.

Notes

Using Matplotlib’s “plot” function as the callable for plot produces unexpected results, this plots the real part of the complex transfer function, not the magnitude.

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