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#These are the first parameters for choosing the time step of our vector
fs=98304
time_step=1.0/fs
t_ini=0
t_fin=0.25
time_vec=np.arange(t_ini,t_fin,time_step)
#The two frequences we're going to use for our different signals
f1=4000
f2=800
#This ensures me of getting the higher value of N who's a power of 2 and smaller than the length of the time_vec
N=int(math.pow(2,int(math.log(len(time_vec),2))))
x1=0.5*np.cos(2*np.pi*f1*time_vec)
x2=0.5*np.cos(2*np.pi*f2*time_vec)
liminf=-1
limsup=+1
#This will take our float-number signals, who were going from -0.5 to 0.5 (they were all sines), and quantize them into integers going from -32768 to 32767
#The liminf and limsup is what decides the maximum and minimum values for our quantizations
#quant16 is a function from the bin16 library
foriinrange(len(time_vec)):
x1[i]=quant16(x1[i],liminf,limsup)
x2[i]=quant16(x2[i],liminf,limsup)
#Now we obtain the values for the Fourier Transforms of both signals, with integer values as well (rounded in the function fft_CT)