Bandpass Butterworth filter frequencies in scipy

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() ``` 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?