ericteunis
/
m-thesis-introduction
mirror of https://gitlab.science.ru.nl/mthesis-edeboone/m-thesis-introduction.git
1
0
Fork 0
Code Issues Packages Projects Releases Wiki Activity

ZH: Determine SNR for Airshower vs Noise

This commit is contained in:
Eric Teunis de Boone 2023-04-13 17:09:30 +02:00
parent aabdca4f98
commit 465b78c535
3 changed files with 113 additions and 14 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

10
airshower_beacon_simulation/aa_generate_beacon.py
View File

@ -18,7 +18,8 @@ import lib
# {{{ vim marker
tx_fname = 'tx.json'
antennas_fname = 'antennas.hdf5'
beacon_snr_fname = 'snr.json'
beacon_snr_fname = 'beacon_snr.json'
airshower_snr_fname = 'airshower_snr.json'
c_light = lib.c_light
def read_antenna_clock_repair_offsets(antennas, mode='all', freq_name=None):
@ -418,6 +419,12 @@ if __name__ == "__main__":
# Collect all data to be saved (with the first 3 values the E fields)
traces = np.array([antenna.Ex, antenna.Ey, antenna.Ez, beacon, noise_realisation])
append_antenna_hdf5( antennas_fname, antenna, traces, name='original_traces', prepend_time=True)
E_AxB = [np.dot(ev.uAxB,[ex,ey,ez]) for ex,ey,ez in zip(traces[0], traces[1], traces[2])]
t_AxB = antenna.t
append_antenna_hdf5( antennas_fname, antenna, [t_AxB, E_AxB, t_AxB, t_AxB], name='original_E_AxB', prepend_time=False)# Note the 4 element list containing dummys at idx 2 and 3
# add beacon and noise to relevant polarisations
for j, amp in enumerate(beacon_amplitudes):
traces[j] = traces[j] + amp*beacon + noise_realisation
@ -433,7 +440,6 @@ if __name__ == "__main__":
# Save filtered E field in E_AxB
E_AxB = [np.dot(ev.uAxB,[ex,ey,ez]) for ex,ey,ez in zip(traces[0], traces[1], traces[2])]
t_AxB = antenna.t
append_antenna_hdf5( antennas_fname, antenna, [t_AxB, E_AxB], name='E_AxB', prepend_time=False)

92
airshower_beacon_simulation/ac_show_signal_to_noise.py
View File

@ -43,6 +43,7 @@ if __name__ == "__main__":
antennas_fname = path.join(fname_dir, beacon.antennas_fname)
tx_fname = path.join(fname_dir, beacon.tx_fname)
beacon_snr_fname = path.join(fname_dir, beacon.beacon_snr_fname)
airshower_snr_fname = path.join(fname_dir, beacon.airshower_snr_fname)
# create fig_dir
if fig_dir:
@ -52,6 +53,17 @@ if __name__ == "__main__":
f_beacon, tx, antennas = beacon.read_beacon_hdf5(antennas_fname, traces_key='filtered_traces')
_, __, txdata = beacon.read_tx_file(tx_fname)
# Read zeropadded traces
_, __, signal_antennas = beacon.read_beacon_hdf5(antennas_fname, traces_key='original_E_AxB', read_AxB=False )
# !!HACK!! Repack traces in signal_antennas to antennas
for i, ant in enumerate(signal_antennas):
if antennas[i].name != ant.name:
print("Error!")
import sys
sys.exit()
antennas[i].orig_E_AxB = ant.Ex
# general properties
dt = antennas[0].t[1] - antennas[0].t[0] # ns
beacon_pb = lib.passband(f_beacon, None) # GHz
@ -76,7 +88,7 @@ if __name__ == "__main__":
ant = antennas[0]
fig, ax = plt.subplots(figsize=figsize)
_debug_snrs = lib.signal_to_noise(myfilter(beacon_amp*ant.beacon), myfilter(ant.noise), samplerate=1/dt, signal_band=beacon_pb, noise_band=noise_pb, debug_ax=ax)
_debug_snrs = lib.signal_to_noise(myfilter(beacon_amp*ant.beacon), myfilter(ant.noise), samplerate=1/dt, signal_band=beacon_pb, noise_band=noise_pb, debug_ax=ax, mode='sine')
ax.legend(title="$\\langle SNR \\rangle$ = {: .1e}".format(np.mean(_debug_snrs)))
@ -87,13 +99,14 @@ if __name__ == "__main__":
ax.set_xlim(low_x, high_x)
if fig_dir:
fig.savefig(path.join(fig_dir, path.basename(__file__) + f".debug_plot.pdf"))
fig.savefig(path.join(fig_dir, path.basename(__file__) + f".beacon_vs_noise_snr.debug_plot.pdf"))
##
## Beacon vs Noise SNR
##
if True:
N_samples = len(antennas[0].beacon)
beacon_snrs = [ lib.signal_to_noise(myfilter(beacon_amp*ant.beacon), myfilter(ant.noise), samplerate=1/dt, signal_band=beacon_pb, noise_band=noise_pb) for i, ant in enumerate(antennas) ]
beacon_snrs = [ lib.signal_to_noise(myfilter(beacon_amp*ant.beacon), myfilter(ant.noise), samplerate=1/dt, signal_band=beacon_pb, noise_band=noise_pb, mode='sine') for i, ant in enumerate(antennas) ]
# write mean and std to file
beacon.write_snr_file(beacon_snr_fname, beacon_snrs)
@ -111,7 +124,7 @@ if __name__ == "__main__":
## Beacon vs Total SNR
##
if True:
beacon_snrs = [ lib.signal_to_noise(myfilter(beacon_amp*ant.beacon), ant.E_AxB, samplerate=1/dt, signal_band=beacon_pb, noise_band=pb) for ant in antennas ]
beacon_snrs = [ lib.signal_to_noise(myfilter(beacon_amp*ant.beacon), ant.E_AxB, samplerate=1/dt, signal_band=beacon_pb, noise_band=pb, mode='sine') for ant in antennas ]
fig, ax = plt.subplots(figsize=figsize)
ax.set_title("Maximum Beacon/Total SNR")
@ -122,26 +135,89 @@ if __name__ == "__main__":
if fig_dir:
fig.savefig(path.join(fig_dir, path.basename(__file__) + f".beacon_vs_total_snr.pdf"))
##
## Debug plot of Signal vs Noise SNR
##
if True:
ant = antennas[0]
fig, ax = plt.subplots(figsize=figsize)
_debug_snrs = lib.signal_to_noise(myfilter(ant.orig_E_AxB), myfilter(ant.noise), samplerate=1/dt, debug_ax=ax, mode='pulse')
ax.legend(title="$\\langle SNR \\rangle$ = {: .1e}".format(np.mean(_debug_snrs)))
ax.set_title("Signal (max amp) and Noise (rms)")
ax.set_xlabel("Samples")
ax.set_ylabel("Amplitude")
if fig_dir:
fig.savefig(path.join(fig_dir, path.basename(__file__) + f".airshower_vs_noise_snr.debug_plot.pdf"))
##
## Signal vs Noise SNR
##
if True:
beacon_snrs = [ lib.signal_to_noise(myfilter(ant.E_AxB - beacon_amp*ant.beacon), myfilter(ant.noise), samplerate=1/dt, signal_band=beacon_pb, noise_band=pb) for ant in antennas ]
airshower_snrs = [ lib.signal_to_noise(myfilter(ant.orig_E_AxB), myfilter(ant.noise), samplerate=1/dt, mode='pulse') for ant in antennas ]
# write mean and std to file
beacon.write_snr_file(airshower_snr_fname, airshower_snrs)
fig, ax = plt.subplots(figsize=figsize)
ax.set_title("Maximum Airshower/Noise SNR")
ax.set_xlabel("Antenna no.")
ax.set_ylabel("SNR")
ax.plot([ int(ant.name) for ant in antennas], beacon_snrs, 'o', ls='none')
ax.plot([ int(ant.name) for ant in antennas], airshower_snrs, 'o', ls='none')
if fig_dir:
fig.savefig(path.join(fig_dir, path.basename(__file__) + f".airshower_vs_noise_snr.pdf"))
##
## Airshower signal vs Noise SNR
## Debug plot of Signal vs Beacon SNR
##
if True:
shower_snrs = [ lib.signal_to_noise(ant.E_AxB, myfilter(ant.noise), samplerate=1/dt, signal_band=pb, noise_band=pb) for ant in antennas ]
ant = antennas[0]
fig, ax = plt.subplots(figsize=figsize)
if False: #indirect SNR max_amp(signal) vs max_amp(beacon)
_debug_snrs_E_AxB = lib.signal_to_noise(myfilter(ant.orig_E_AxB), myfilter(ant.noise), samplerate=1/dt, debug_ax=ax, mode='pulse')
_debug_snrs_sine = lib.signal_to_noise(myfilter(beacon_amp*ant.beacon), myfilter(ant.noise), samplerate=1/dt, debug_ax=ax, mode='pulse')
_debug_snrs = _debug_snrs_E_AxB / _debug_snrs_sine
else: # direct max_amp(signal) vs rms(beacon)
_debug_snrs = lib.signal_to_noise(myfilter(ant.orig_E_AxB), myfilter(beacon_amp*ant.beacon), samplerate=1/dt, debug_ax=ax, mode='pulse')
ax.legend(title="$\\langle SNR \\rangle$ = {: .1e}".format(np.mean(_debug_snrs)))
ax.set_title("Signal (max amp), Beacon (max amp) and Noise (rms)")
ax.set_xlabel("Samples")
ax.set_ylabel("Amplitude")
if fig_dir:
fig.savefig(path.join(fig_dir, path.basename(__file__) + f".airshower_vs_beacon_snr.debug_plot.pdf"))
##
## Signal vs Beacon SNR
##
if True:
shower_beacon_snrs = [ lib.signal_to_noise(myfilter(ant.orig_E_AxB), myfilter(beacon_amp*ant.beacon), samplerate=1/dt, mode='pulse') for ant in antennas ]
fig, ax = plt.subplots(figsize=figsize)
ax.set_title("Maximum Airshower/Beacon RMS SNR")
ax.set_xlabel("Antenna no.")
ax.set_ylabel("SNR")
ax.plot([ int(ant.name) for ant in antennas], beacon_snrs, 'o', ls='none')
if fig_dir:
fig.savefig(path.join(fig_dir, path.basename(__file__) + f".airshower_vs_beacon_snr.pdf"))
##
## Total signal vs Noise SNR
##
if True:
shower_snrs = [ lib.signal_to_noise(ant.E_AxB, myfilter(ant.noise), samplerate=1/dt, mode='pulse') for ant in antennas ]
fig, ax = plt.subplots(figsize=figsize)
ax.set_title("Total (Signal+Beacon+Noise)/Noise SNR")

25
airshower_beacon_simulation/lib/snr.py
View File

@ -80,7 +80,7 @@ def bandpower(samples, samplerate=1, band=passband(), normalise_bandsize=True, d
return power
def signal_to_noise(samples, noise, samplerate=1, signal_band=passband(), noise_band=None, debug_ax=False):
def signal_to_noise(samples, noise, samplerate=1, signal_band=passband(), noise_band=None, debug_ax=False, mode='sine'):
if noise_band is None:
noise_band = signal_band
@ -90,8 +90,25 @@ def signal_to_noise(samples, noise, samplerate=1, signal_band=passband(), noise_
if debug_ax is True:
debug_ax = plt.gca()
noise_power = bandpower(noise, samplerate, noise_band, debug_ax=debug_ax)
if mode == 'sine':
noise_power = bandpower(noise, samplerate, noise_band, debug_ax=debug_ax)
noise_amplitude = np.sqrt(noise_power)
signal_power = bandpower(samples, samplerate, signal_band, debug_ax=debug_ax)
signal_power = bandpower(samples, samplerate, signal_band, debug_ax=debug_ax)
signal_amplitude = np.sqrt(signal_power)
return (signal_power/noise_power)**0.5
elif mode == 'pulse':
noise_amplitude = np.sqrt(np.mean(noise**2))
signal_amplitude = max(np.abs(samples))
if debug_ax:
l1 = debug_ax.plot(noise, alpha=0.5)
debug_ax.axhline(noise_amplitude, alpha=0.9, color=l1[0].get_color())
l2 = debug_ax.plot(samples, alpha=0.5)
debug_ax.axhline(signal_amplitude, alpha=0.9, color=l2[0].get_color())
else:
raise NotImplementedError("mode not in ['sine', 'pulse']")
return signal_amplitude/noise_amplitude