#Transition Band
df = 0.3
#Passband && stopband tolerance
d = 0.15
#sampling rate
Fs = 48
def W(Fs, F):
w = 2 * float(F) / Fs
return w
N, R1, R2, ao, B, alp, als, ap1, ap2, as1, as2 = parameters(
Fp2, Fp1, df, d, Fs)
e = 0.6197
w_bp = np.linspace(-0.5, 0.5, 200)
s = (1 - np.exp(-1j * w_bp * np.pi)) / (1 + np.exp(-1j * w_bp * np.pi))
s_L = (((s)**2) + ao**2) / (B * s)
H_bp = filt_design(N, e, alp, s_L)
wp1 = W(Fs, Fp1)
wp2 = W(Fs, Fp2)
ws1 = W(Fs, Fp1 + df)
ws2 = W(Fs, Fp2 - df)
from Gen_LPF_Coeff import filt_design
#Passband Cutoffs
Fp2 = 6.0
Fp1 = 7.2
#Transition Band
df = 0.3
#Passband && stopband tolerance
d = 0.15
#sampling rate
Fs = 48
N, R1, R2, alp = parameters(Fp2, Fp1, df, d, Fs)
e_array = np.linspace(R1, R2, 6)
Omga_L = np.linspace(0, 2, 200)
s = 1j * Omga_L
for e in e_array:
b, a = filt_design(N, e, alp)
H_lp = np.polyval(b, s) / np.polyval(a, s)
plt.plot(Omga_L, abs(H_lp), label=round(e, 2))
plt.xlabel('$Frequency(\Omega)$')
from N_epsilon import parameters
#Passband Cutoffs
Fp2=6.0
Fp1=7.2
#Transition Band
df=0.3
#Passband && stopband tolerance
d=0.15
#sampling rate
Fs=48
N,R1,R2,ao,B = parameters(Fp2,Fp1,df,d,Fs)
e=0.37
e_2=e**2
Omga_L=np.linspace(0,2,200)
s=1j*Omga_L
h_spec=np.sqrt(1/(1+e_2*((8*(Omga_L**4)-8*(Omga_L**2)+1)**2)))
h_design=(0.3125)/(((s)**4)+(1.1068*(s)**3)+(1.6125*(s)**2)+(0.9140*s)+0.3366)
plt.plot(Omga_L,h_spec,label='specifications')
plt.plot(Omga_L,abs(h_design),'o',label='design')
plt.xlabel('$Frequency$')
plt.ylabel('$Magnitude$')
plt.legend()
plt.grid()
from N_epsilon import parameters #Passband Cutoffs Fp2 = 6.0 Fp1 = 7.2 #Transition Band df = 0.3 #Passband && stopband tolerance d = 0.15 #sampling rate Fs = 48 N, R1, R2, ao, B, alp, als = parameters(Fp2, Fp1, df, d, Fs) print R1, "<= e <=", R2 print "N>=", N # order of the filter