Butterworth Filter

from scipy import signal
import matplotlib.pyplot as plt
import numpy as np
N, Wn = signal.buttord([20, 50], [14, 60], 3, 40, True)
b, a = signal.butter(N, Wn, 'band', True)
w, h = signal.freqs(b, a, np.logspace(1, 2, 500))
plt.semilogx(w, 20 * np.log10(abs(h)))
plt.title('Butterworth bandpass filter fit to constraints')
plt.xlabel('Frequency [radians / second]')
plt.ylabel('Amplitude [dB]')
plt.grid(which='both', axis='both')
plt.fill([1,  14,  14,   1], [-40, -40, 99, 99], '0.9', lw=0) # stop
plt.fill([20, 20,  50,  50], [-99, -3, -3, -99], '0.9', lw=0) # pass
plt.fill([60, 60, 1e9, 1e9], [99, -40, -40, 99], '0.9', lw=0) # stop
plt.axis([10, 100, -60, 3])
plt.show()
 

from scipy import signal
import matplotlib.pyplot as plt
import numpy as np
b, a = signal.butter(4, 100, 'low', analog=True)
w, h = signal.freqs(b, a)
plt.semilogx(w, 20 * np.log10(abs(h)))
plt.title('Butterworth filter frequency response')
plt.xlabel('Frequency [radians / second]')
plt.ylabel('Amplitude [dB]')
plt.margins(0, 0.1)
plt.grid(which='both', axis='both')
plt.axvline(100, color='green') # cutoff frequency
plt.show()