#!/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()