mirror of
https://gitlab.science.ru.nl/mthesis-edeboone/m-thesis-introduction.git
synced 2024-11-14 02:23:32 +01:00
232 lines
8.5 KiB
Python
Executable file
232 lines
8.5 KiB
Python
Executable file
#!/usr/bin/env python3
|
|
# vim: fdm=indent ts=4
|
|
|
|
"""
|
|
Show Signal to noise for the original simulation signal,
|
|
the beacon signal and the combined signal for each antenna
|
|
"""
|
|
|
|
import numpy as np
|
|
import h5py
|
|
import matplotlib.pyplot as plt
|
|
import numpy as np
|
|
|
|
from earsim import REvent, block_filter
|
|
import aa_generate_beacon as beacon
|
|
import lib
|
|
|
|
if __name__ == "__main__":
|
|
from os import path
|
|
import sys
|
|
import matplotlib
|
|
import os
|
|
if os.name == 'posix' and "DISPLAY" not in os.environ:
|
|
matplotlib.use('Agg')
|
|
|
|
from scriptlib import MyArgumentParser
|
|
parser = MyArgumentParser()
|
|
|
|
# Bandpass
|
|
parser.add_argument('-p', '--use-passband', type=bool, default=True, help='(Default: %(default)d)')
|
|
parser.add_argument('-l', '--passband-low', type=float, default=30e-3, help='Lower frequency [GHz] of the passband filter. (set -1 for np.inf) (Default: %(default)d)')
|
|
parser.add_argument('-u', '--passband-high', type=float, default=80e-3, help='Upper frequency [GHz] of the passband filter. (set -1 for np.inf) (Default: %(default)d)')
|
|
|
|
args = parser.parse_args()
|
|
|
|
figsize = (12,8)
|
|
|
|
fig_dir = args.fig_dir
|
|
show_plots = args.show_plots
|
|
|
|
####
|
|
fname_dir = args.data_dir
|
|
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:
|
|
os.makedirs(fig_dir, exist_ok=True)
|
|
|
|
# Read in antennas from file
|
|
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
|
|
beacon_amp = np.max(txdata['amplitudes'])# mu V/m
|
|
|
|
# General Bandpass
|
|
low_bp = args.passband_low if args.passband_low >= 0 else np.inf # GHz
|
|
high_bp = args.passband_high if args.passband_high >= 0 else np.inf # GHz
|
|
pb = lib.passband(low_bp, high_bp) # GHz
|
|
|
|
noise_pb = pb
|
|
|
|
if args.use_passband: # Apply filter to raw beacon/noise to compare with Filtered Traces
|
|
myfilter = lambda x: block_filter(x, dt, pb[0], pb[1])
|
|
else: # Compare raw beacon/noise with Filtered Traces
|
|
myfilter = lambda x: x
|
|
|
|
##
|
|
## Debug plot of Beacon vs Noise SNR
|
|
##
|
|
if True:
|
|
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, mode='sine')
|
|
|
|
ax.legend(title="$\\langle SNR \\rangle$ = {: .1e}".format(np.mean(_debug_snrs)))
|
|
|
|
ax.set_title("Spectra and passband")
|
|
ax.set_xlabel("Frequency [GHz]")
|
|
ax.set_ylabel("Amplitude")
|
|
low_x, high_x = min(beacon_pb[0], noise_pb[0]), max(beacon_pb[1] or 0, noise_pb[1])
|
|
ax.set_xlim(low_x, high_x)
|
|
|
|
if fig_dir:
|
|
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, mode='sine') for i, ant in enumerate(antennas) ]
|
|
|
|
# write mean and std to file
|
|
beacon.write_snr_file(beacon_snr_fname, beacon_snrs)
|
|
|
|
fig, ax = plt.subplots(figsize=figsize)
|
|
ax.set_title(f"Maximum Beacon/Noise SNR (N_samples:{N_samples:.1e})")
|
|
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".beacon_vs_noise_snr.pdf"))
|
|
|
|
##
|
|
## 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, mode='sine') for ant in antennas ]
|
|
|
|
fig, ax = plt.subplots(figsize=figsize)
|
|
ax.set_title("Maximum Beacon/Total 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".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:
|
|
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], airshower_snrs, 'o', ls='none')
|
|
|
|
if fig_dir:
|
|
fig.savefig(path.join(fig_dir, path.basename(__file__) + f".airshower_vs_noise_snr.pdf"))
|
|
|
|
##
|
|
## Debug plot of Signal vs Beacon SNR
|
|
##
|
|
if True:
|
|
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")
|
|
ax.set_xlabel("Antenna no.")
|
|
ax.set_ylabel("SNR")
|
|
ax.plot([ int(ant.name) for ant in antennas], shower_snrs, 'o', ls='none')
|
|
|
|
if fig_dir:
|
|
fig.savefig(path.join(fig_dir, path.basename(__file__) + f".total_snr.pdf"))
|
|
|
|
if show_plots:
|
|
plt.show()
|