scipy中的带通巴特沃斯滤波器频率 [英] Bandpass butterworth filter frequencies in scipy

问题描述

我正在按照烹饪书的方式在scipy中设计一个带通滤波器.但是，如果我过多地降低了过滤频率，我最终会在高阶过滤器上产生垃圾.我在做什么错了?

I'm designing a bandpass filter in scipy following the cookbook. However, if I decrecrease the filtering frequencies too much I end up with garbage at high order filters. What am I doing wrong?

from scipy.signal import butter, lfilter

def butter_bandpass(lowcut, highcut, fs, order=5):
    nyq = 0.5 * fs
    low = lowcut / nyq
    high = highcut / nyq
    b, a = butter(order, [low, high], btype='band')
    return b, a

if __name__ == "__main__":
    import numpy as np
    import matplotlib.pyplot as plt
    from scipy.signal import freqz  
    # Sample rate and desired cutoff frequencies (in Hz).
    fs = 25
    # Plot the frequency response for a few different orders.
    plt.figure(1)
    plt.clf()
    for order in [1, 3, 5, 6, 9]:
        b, a = butter_bandpass(0.5, 4, fs, order=order)
        w, h = freqz(b, a, worN=2000)#np.logspace(-4, 3, 2000))
        plt.semilogx((fs * 0.5 / np.pi) * w, abs(h), label="order = %d" % order)  
    plt.xlabel('Frequency (Hz)')
    plt.ylabel('Gain')
    plt.grid(True)
    plt.legend(loc='best')

    plt.figure(2)
    plt.clf()
    for order in [1, 3, 5, 6, 9]:
        b, a = butter_bandpass(0.05, 0.4, fs, order=order)
        w, h = freqz(b, a, worN=2000)#np.logspace(-4, 3, 2000))
        plt.semilogx((fs * 0.5 / np.pi) * w, abs(h), label="order = %d" % order)  
    plt.xlabel('Frequency (Hz)')
    plt.ylabel('Gain')
    plt.grid(True)
    plt.legend(loc='best')

    plt.show()

更新:已在Scipy 0.14上讨论并显然解决了该问题.但是，在Scipy更新之后，该图看起来仍然非常糟糕.怎么了?

Update: the issue was discussed and apparently solved on Scipy 0.14. However, the plot still looks really bad after Scipy update. What's wrong?

推荐答案

显然，该问题是已知的错误:

Apparently the issue is a known bug:

Github

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