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

170 lines
5.9 KiB
Python
Executable file

#!/usr/bin/env python3
# vim: fdm=indent ts=4
import h5py
from itertools import combinations, zip_longest
import matplotlib.pyplot as plt
import numpy as np
import aa_generate_beacon as beacon
import lib
if __name__ == "__main__":
from os import path
import sys
import os
import matplotlib
if os.name == 'posix' and "DISPLAY" not in os.environ:
matplotlib.use('Agg')
fname = "ZH_airshower/mysim.sry"
show_plots = True
ref_ant_id = None # leave None for all baselines
####
fname_dir = path.dirname(fname)
antennas_fname = path.join(fname_dir, beacon.antennas_fname)
time_diffs_fname = 'time_diffs.hdf5' if False else antennas_fname
fig_dir = "./figures" # set None to disable saving
basenames, time_diffs, f_beacons, true_phase_diffs, k_periods = beacon.read_baseline_time_diffs_hdf5(time_diffs_fname)
f_beacon, tx, antennas = beacon.read_beacon_hdf5(antennas_fname)
# TODO: allow multiple frequencies
if (f_beacon != f_beacons).any():
raise NotImplementedError
N_base = len(basenames)
N_ant = len(antennas)
# reshape time_diffs into N_ant x N_ant array
sigma_phase_matrix = np.full( (N_ant, N_ant), np.nan, dtype=float)
#sigma_phase_matrix = np.arange(0, N_ant**2, dtype=float).reshape( (N_ant,N_ant))
name2idx = lambda name: int(name)-1
for i, b in enumerate(basenames):
idx = (name2idx(b[0]), name2idx(b[1]))
if idx[0] == idx[1]:
pass
sigma_phase_matrix[(idx[0], idx[1])] = true_phase_diffs[i]
sigma_phase_matrix[(idx[1], idx[0])] = true_phase_diffs[i]
# for each row j subtract the 0,j element from the whole row
# and apply phase_mod
first_row = sigma_phase_matrix[0]
sigma_phase_matrix = sigma_phase_matrix - first_row[:,np.newaxis]
sigma_phase_matrix = lib.phase_mod(sigma_phase_matrix)
# Except for the first row, these are all separate measurements
# Condense into phase offset per antenna
if True: # do not use the first row
my_mask = np.arange(1, len(sigma_phase_matrix), dtype=int)
else:
my_mask = np.arange(0, len(sigma_phase_matrix), dtype=int)
mean_sigma_phase = np.nanmean(sigma_phase_matrix[my_mask], axis=0)
std_sigma_phase = np.nanstd( sigma_phase_matrix[my_mask], axis=0)
# write into antenna hdf5
with h5py.File(antennas_fname, 'a') as fp:
group = fp['antennas']
freq_name = None
for i, ant in enumerate(antennas):
h5ant = group[ant.name]
h5beacon_info = h5ant['beacon_info']
# find out freq_name
if freq_name is None:
freq_name = [ k for k in h5beacon_info.keys() if np.isclose(h5beacon_info[k].attrs['freq'], f_beacon)][0]
h5attrs = h5beacon_info[freq_name].attrs
idx = name2idx(ant.name)
h5attrs['sigma_phase_mean'] = mean_sigma_phase[idx]
h5attrs['sigma_phase_std'] = std_sigma_phase[idx]
##############################
# Compare actual time shifts #
##############################
antenna_time_shifts = { a.name: a.attrs['clock_offset'] for a in antennas }
if True:
# show means and std
fig, axs = plt.subplots(1,2, sharey=True)
axs[0].set_title("")
axs[0].set_xlabel("Antenna no.")
axs[0].set_ylabel("Antenna Phase $\\Delta_\\varphi$")
axs[1].set_xlabel("#")
if True:
forward = lambda x: x/(2*np.pi*f_beacon)
inverse = lambda x: 2*np.pi*x*f_beacon
secax = axs[1].secondary_yaxis('right', functions=(forward, inverse))
secax.set_ylabel('Time $\\Delta\\varphi/(2\\pi f_{beac})$ [ns]')
l = axs[0].errorbar(np.arange(N_ant), mean_sigma_phase, yerr=std_sigma_phase, marker='.', alpha=0.7)
axs[1].hist(mean_sigma_phase, bins='sqrt', density=False, orientation='horizontal', color=l[0].get_color(), histtype='step')
# Actual time shifts
if True:
actual_phase_shifts = [ -1*lib.phase_mod(2*np.pi*f_beacon*v) for k,v in antenna_time_shifts.items() ]
antenna_names = [int(k) for k,v in antenna_time_shifts.items() ]
# make sure to keep the same offset
if True:
phase_offset = mean_sigma_phase[0] - actual_phase_shifts[0]
actual_phase_shifts += phase_offset
l = axs[0].plot(antenna_names, actual_phase_shifts, ls='none', marker='3', alpha=0.8)
if True:
axs[1].hist(actual_phase_shifts, bins='sqrt', density=False, orientation='horizontal', ls='dashed', color=l[0].get_color(), histtype='step')
fig.tight_layout()
if fig_dir:
fig.savefig(path.join(fig_dir, __file__ + f".residuals.pdf"))
##########################
##########################
##########################
actual_time_shifts = []
for i,b in enumerate(basenames):
actual_time_shift = lib.phase_mod(lib.phase_mod(antenna_time_shifts[b[0]]*2*np.pi*f_beacon) - lib.phase_mod(antenna_time_shifts[b[1]]*2*np.pi*f_beacon))
actual_time_shifts.append(actual_time_shift)
# unpack mean_sigma_phase back into a list of time diffs
measured_time_diffs = []
for i,b in enumerate(basenames):
time0, time1 = mean_sigma_phase[name2idx(b[0])], mean_sigma_phase[name2idx(b[1])]
measured_time_diffs.append(time1 - time0)
# Make a plot
if True:
fig, ax = plt.subplots()
ax.set_xlabel("Baseline no.")
ax.set_ylabel("$\\Delta t$[ns]")
if True: # indicate single beacon period span
ax.plot((-1, -1), (0, 1/f_beacon), marker='3', ms=10, label='1/f_beacon')
ax.plot(np.arange(N_base), actual_time_shifts, marker='+', label='actual time shifts')
ax.plot(np.arange(N_base), measured_time_diffs, marker='x', label='calculated')
ax.legend()
if fig_dir:
fig.savefig(path.join(fig_dir, __file__ + f".calculated_shifts.pdf"))
if show_plots:
plt.show()