m-thesis-introduction/simulations/airshower_beacon_simulation/ac_show_signal_to_noise.py

115 lines
4 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()
fname = "ZH_airshower/mysim.sry"
figsize = (9,6)
fig_dir = args.fig_dir
show_plots = args.show_plots
####
fname_dir = path.dirname(fname)
antennas_fname = path.join(fname_dir, beacon.antennas_fname)
tx_fname = path.join(fname_dir, beacon.tx_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)
_, __, txdata = beacon.read_tx_file(tx_fname)
# general properties
dt = antennas[0].t[1] - antennas[0].t[0] # ns
beacon_pb = lib.passband(f_beacon-1e-3, f_beacon+1e-3) # 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
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
##
## Beacon vs Noise SNR
##
if True:
beacon_snrs = [ lib.signal_to_noise(myfilter(beacon_amp*ant.beacon), myfilter(ant.noise), samplerate=1/dt, signal_band=beacon_pb, noise_band=pb) for ant in antennas ]
fig, ax = plt.subplots(figsize=figsize)
ax.set_title("Maximum Beacon/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')
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) 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"))
##
## Airshower signal vs Noise 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 ]
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()