The scipy library of matplotlib in Python 3 contains a function "scipy.signal.freqz" which computes the frequency response of a digital filter. I am trying to write my own version of this function, to relay the same output as this imbedded function. I plan to use the inputs: freqz(b, a = 1, worN=None, whole=None): [b=numerator of linear filter; a=denominator of linear filter; worN=at none, compute at 512 frequencies equally spaced around the unit circle; whole=at none, frequency computed around upper half of unit circle, from 0 to pi]. This function should output two outputs: w and h

After implementing the function, it should pass all the tests provided in the last part of code.

DON'T USE FFT FUNCTION

I am going to provide the code that I am given.

Code:

import numpy as np import matplotlib.pyplot as plt import scipy.signal as sig import matplotlib as mpl mpl.rcParams['figure.figsize'] = (5,3) %matplotlib inline

# Implementation of freqz using different way.

def my_freqz(b, a = 1, worN=None, whole=None): #replace with your answer pass

Testing code:

from collections import namedtuple Test = namedtuple('Test',['b','a','worN','whole']) tests = [ Test([1,0.5,0.1], [1,1], 256, None), Test(1,1,None, True), Test(1,1,12, False), Test([1,2],1,[0,1,2,3], None) ]

b,a = sig.iirdesign(0.2, 0.3, 1, 20) tests.append(Test(b,a,None,None))

b = sig.firwin(63, 0.25) tests.append(Test(b,1,1024,None))

for test in tests: w, h = sig.freqz(test.b, test.a, test.worN, test.whole) my_w, my_h = my_freqz(test.b, test.a, test.worN, test.whole) print(np.allclose(w, my_w), np.allclose(h, my_h))

Tests should output TRUE for all.