TransformedDataDFT = []
TransformedDataFFT = []
Sampels = []
TimeBeforeFFT = []
TimeAfterFFT = []
TimeDifferenceFFT = []
TimeBeforeDFT = []
TimeAfterDFT = []
TimeDifferenceDFT = []
NumberOfData = []
for i in range(5):
Sampels.append([random.randint(1, 10000) for _ in range(2**(4 + i * 3))])
NumberOfData.append(len(Sampels[i]))
for i in range(5):
TimeBeforeFFT.append(time.time())
TransformedDataFFT.append(Fourier.FFT(Sampels[i]))
TimeAfterFFT.append(time.time())
TimeDifferenceFFT.append(TimeAfterFFT[i] - TimeBeforeFFT[i])
TimeBeforeDFT.append(time.time())
TransformedDataDFT.append(Fourier.DFT(Sampels[i]))
TimeAfterDFT.append(time.time())
TimeDifferenceDFT.append(TimeAfterDFT[i] - TimeBeforeDFT[i])
MeanSquareError.append(
np.square(np.subtract(TransformedDataDFT[i],
TransformedDataFFT[i])).mean())
print(MeanSquareError)
for i in range(len(MeanSquareError)):
Error.append(abs(MeanSquareError[i]))
plt.plot(NumberOfData, Error)
plt.ylim(-2, 2)
