fade_in_list = np.arange(0, 1001, 1)
fade_out = 0
# Spectrum of dirac for reference
dirac = np.zeros(pad * fs)
dirac[0] = 1
dirac_f = np.fft.rfft(dirac)
def get_results(fade_in):
excitation_windowed = excitation * windows.window_kaiser(
N, fade_in, fade_out, fs, beta)
excitation_windowed_zeropadded = generation.zero_padding(
excitation_windowed, pad, fs)
system_response = system(excitation_windowed_zeropadded)
ir = calculation.deconv_process(excitation_windowed_zeropadded,
system_response, fs)
return ir
with open("log_sweep_kaiser_window_script1.txt", "w") as f:
for fade_in in fade_in_list:
ir = get_results(fade_in)
pnr = calculation.pnr_db(ir[0], ir[1:4 * fs])
spectrum_distance = calculation.vector_distance(
dirac_f, np.fft.rfft(ir[:pad * fs]))
f.write(
str(fade_in) + " " + str(pnr) + " " + str(spectrum_distance) +
" \n")
# Spectrum of bandstop for reference
bandstop_f = calculation.butter_bandstop(f_low, f_high, fs, N * 2 + 1, order)
def get_results(fade_out):
excitation_windowed = excitation * windows.window_kaiser(N,
fade_in,
fade_out,
fs, beta)
excitation_windowed_zeropadded = generation.zero_padding(
excitation_windowed, pad, fs)
excitation_zeropadded = generation.zero_padding(excitation, pad, fs)
system_response = system(excitation_windowed_zeropadded)
ir = calculation.deconv_process(excitation_zeropadded,
system_response,
fs)
return ir
with open("log_sweep_kaiser_window_script4_1.txt", "w") as f:
for fade_out in fade_out_list:
ir = get_results(fade_out)
snr = calculation.pnr_db(ir[0], ir[t_noise * fs:pad * fs])
spectrum_distance = calculation.vector_distance(
bandstop_f, np.fft.rfft(ir[:pad * fs]))
f.write(
str(fade_out) + " " + str(snr) +
" " + str(spectrum_distance) + " \n")
