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ZH: period_from_shower sort by maxima

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Start by correlating the strongest signals
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Eric Teunis de Boone 2022-12-08 15:22:27 +01:00
parent f96d3adb15
commit ecc79a8c91
1 changed files with 12 additions and 0 deletions
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simulations/airshower_beacon_simulation/ca_period_from_shower.py
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@ -28,6 +28,7 @@ def find_best_sample_shifts_summing_at_location(test_loc, antennas, allowed_samp
t_ = [] t_ = []
t_min = 1e9 t_min = 1e9
t_max = -1e9 t_max = -1e9
a_maxima = []
if dt is None: if dt is None:
dt = antennas[0].t_AxB[1] - antennas[0].t_AxB[0] dt = antennas[0].t_AxB[1] - antennas[0].t_AxB[0]
@ -41,12 +42,18 @@ def find_best_sample_shifts_summing_at_location(test_loc, antennas, allowed_samp
t__ = np.subtract(ant.t_AxB, delta) t__ = np.subtract(ant.t_AxB, delta)
t_.append(t__) t_.append(t__)
a_.append(ant.E_AxB) a_.append(ant.E_AxB)
a_maxima.append(max(ant.E_AxB))
if t__[0] < t_min: if t__[0] < t_min:
t_min = t__[0] t_min = t__[0]
if t__[-1] > t_max: if t__[-1] > t_max:
t_max = t__[-1] t_max = t__[-1]
# sort traces with descending maxima
sort_idx = np.argsort(a_maxima)[::-1]
t_ = [ t_[i] for i in sort_idx ]
a_ = [ a_[i] for i in sort_idx ]
# Interpolate and find best sample shift # Interpolate and find best sample shift
max_neg_shift = 0 #np.min(allowed_sample_shifts) * dt max_neg_shift = 0 #np.min(allowed_sample_shifts) * dt
max_pos_shift = 0 #np.max(allowed_sample_shifts) * dt max_pos_shift = 0 #np.max(allowed_sample_shifts) * dt
@ -92,6 +99,11 @@ def find_best_sample_shifts_summing_at_location(test_loc, antennas, allowed_samp
fig.savefig(path.join(fig_dir, __file__ + '.loc{:.1f}-{:.1f}-{:.1f}'.format(*test_loc) + f'.i{i}{fig_distinguish}.pdf')) fig.savefig(path.join(fig_dir, __file__ + '.loc{:.1f}-{:.1f}-{:.1f}'.format(*test_loc) + f'.i{i}{fig_distinguish}.pdf'))
plt.close(fig) plt.close(fig)
# sort by antenna (undo sorting by maximum)
undo_sort_idx = np.argsort(sort_idx)
best_sample_shifts = best_sample_shifts[undo_sort_idx]
# Return ks # Return ks
return best_sample_shifts, np.max(a_sum) return best_sample_shifts, np.max(a_sum)