dsp/response at master · buha/dsp · GitHub

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import numpy as np
import matplotlib.pyplot as plt

# Some sampling frequency
fs = 48000.0
# Size of FFT analysis
N = 1024

def fir_freqz(b):
    # Get the frequency response
    X = np.fft.fft(b, N)
    # Take the magnitude
    Xm = np.abs(X)
    # Convert the magnitude to decibel scale
    Xdb = 20*np.log10(Xm/Xm.max())
    # Frequency vector
    f = np.arange(N)*fs/N

    return Xdb, f

if __name__ == "__main__":

    # FIR filter coefficients
    b = np.array([-0.0159147603287189,  0.000745724267485,
                   0.0404251831063147,  0.019042013872129,
                  -0.0644535904607569, -0.054523709591490,
                   0.0787623967281351,  0.105430811100048,
                  -0.0645610841865355, -0.148306808873938,
                   0.0257418551415616,  0.166568575042643,
                   0.0257418551415616, -0.148306808873938,
                  -0.0645610841865355,  0.105430811100048,
                   0.0787623967281351, -0.054523709591490,
                  -0.0644535904607569,  0.019042013872129,
                   0.0404251831063147,  0.000745724267485,
                  -0.0159147603287189])

    # Window to be used
    win = np.kaiser(len(b), 15)
    # Windowed filter coefficients
    b_win = win*b

    # Get frequency response of filter
    Xdb, f = fir_freqz(b)
    # ... and it mirrored version
    Xdb_win, f = fir_freqz(b_win)


    # Plot the impulse response
    plt.subplot(211)
    plt.stem(b, linefmt='b-', markerfmt='bo', basefmt='k-', label='Orig. coeff.')
    plt.grid(True)
    plt.hold(True)
    plt.stem(b_win, linefmt='r-', markerfmt='ro', basefmt='k-', label='Windowed coeff.')
    plt.plot(win*b.max(), '--g', label='Window function')

    plt.title('Impulse reponse')
    plt.xlabel('Sample')
    plt.ylabel('Amplitude')
    plt.legend()

    # Plot the frequency response
    plt.subplot(212)
    plt.plot(f, Xdb, 'b', label='Orig. coeff.')
    plt.grid(True)
    plt.hold(True)
    plt.plot(f, Xdb_win, 'r', label='Windowed coeff.')

    plt.title('Frequency reponse')
    plt.xlabel('Frequency [Hz]')
    plt.ylabel('Amplitude [dB]')
    plt.xlim((0, fs/2)) # Set the frequency limit - being lazy
    plt.legend()

    plt.show()