mirror of
https://gitlab.science.ru.nl/mthesis-edeboone/m-thesis-introduction.git
synced 2024-11-14 02:23:32 +01:00
85 lines
2.3 KiB
Python
Executable file
85 lines
2.3 KiB
Python
Executable file
#!/usr/bin/env python3
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# vim: fdm=indent ts=4
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"""
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Do a reconstruction of airshower after correcting for the
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clock offsets.
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"""
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import matplotlib.pyplot as plt
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from mpl_toolkits.mplot3d import Axes3D # required for projection='3d' on old matplotliblib versions
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import numpy as np
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from os import path
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import pickle
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import joblib
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from earsim import REvent
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from atmocal import AtmoCal
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import aa_generate_beacon as beacon
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import lib
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from lib import rit
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if __name__ == "__main__":
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import sys
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import os
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import matplotlib
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if os.name == 'posix' and "DISPLAY" not in os.environ:
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matplotlib.use('Agg')
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atm = AtmoCal()
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from scriptlib import MyArgumentParser
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parser = MyArgumentParser()
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args = parser.parse_args()
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fname = "ZH_airshower/mysim.sry"
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fig_dir = args.fig_dir
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fig_subdir = path.join(fig_dir, 'reconstruction')
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show_plots = args.show_plots
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####
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fname_dir = path.dirname(fname)
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antennas_fname = path.join(fname_dir, beacon.antennas_fname)
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pickle_fname = path.join(fname_dir, 'res.pkl')
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# create fig_dir
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if fig_dir:
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os.makedirs(fig_dir, exist_ok=True)
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if fig_subdir:
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os.makedirs(fig_subdir, exist_ok=True)
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# Read in antennas from file
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_, tx, antennas = beacon.read_beacon_hdf5(antennas_fname)
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# Read original REvent
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ev = REvent(fname)
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# .. patch in our antennas
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ev.antennas = antennas
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# For now only implement using one freq_name
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freq_names = antennas[0].beacon_info.keys()
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if len(freq_names) > 1:
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raise NotImplementedError
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freq_name = next(iter(freq_names))
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f_beacon = ev.antennas[0].beacon_info[freq_name]['freq']
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# Repair clock offsets with the measured offsets
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for i, ant in enumerate(ev.antennas):
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clock_phase_time = ant.beacon_info[freq_name]['sigma_phase_mean']/(2*np.pi*f_beacon)
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best_k_time = ant.beacon_info[freq_name]['best_k_time']
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total_clock_time = best_k_time + clock_phase_time
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ev.antennas[i].t += total_clock_time
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N_X, Xlow, Xhigh = 23, 100, 1200
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with joblib.parallel_backend("loky"):
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res = rit.reconstruction(ev, outfile=fig_subdir+'/fig.pdf', slice_outdir=fig_subdir+'/', Xlow=Xlow, N_X=N_X, Xhigh=Xhigh)
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## Save a pickle
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with open(pickle_fname, 'wb') as fp:
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pickle.dump(res,fp)
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if show_plots:
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plt.show()
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