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ZH: periods_from_shower enable figure for multiple shifting iterations
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1 changed files with 35 additions and 8 deletions
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@ -29,10 +29,17 @@ def find_best_sample_shifts_summing_at_location(test_loc, antennas, allowed_samp
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t_min = 1e9
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t_max = -1e9
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a_maxima = []
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N_ant = len(antennas)
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if dt is None:
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dt = antennas[0].t_AxB[1] - antennas[0].t_AxB[0]
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if not hasattr(plot_iteration_with_shifted_trace, '__len__'):
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if plot_iteration_with_shifted_trace:
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plot_iteration_with_shifted_trace = [ plot_iteration_with_shifted_trace ]
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else:
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plot_iteration_with_shifted_trace = []
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# propagate to test location
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for i, ant in enumerate(antennas):
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aloc = [ant.x, ant.y, ant.z]
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@ -72,9 +79,9 @@ def find_best_sample_shifts_summing_at_location(test_loc, antennas, allowed_samp
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continue
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# init figure
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if i == plot_iteration_with_shifted_trace:
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if i in plot_iteration_with_shifted_trace:
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fig, ax = plt.subplots()
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ax.set_title("Traces at ({:.1f},{:.1f},{:.1f})".format(*test_loc))
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ax.set_title("Traces at ({:.1f},{:.1f},{:.1f}) i={i}/{tot}".format(*test_loc, i=i, tot=N_ant))
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ax.set_xlabel("Time [ns]")
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ax.set_ylabel("Amplitude")
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ax.plot(t_sum, a_sum)
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@ -85,18 +92,38 @@ def find_best_sample_shifts_summing_at_location(test_loc, antennas, allowed_samp
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shift_maxima[j] = np.max(augmented_a + a_sum)
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if i == plot_iteration_with_shifted_trace:
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ax.plot(t_sum, augmented_a, label=f'{shift} shifted')
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if i in plot_iteration_with_shifted_trace:
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ax.plot(t_sum, augmented_a, alpha=0.8, label=f'{shift}')
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# transform maximum into best_sample_shift
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best_idx = np.argmax(shift_maxima)
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best_sample_shifts[i] = allowed_sample_shifts[best_idx]
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a_sum += np.roll(a_int, best_sample_shifts[i])
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# cleanup figure
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if i == plot_iteration_with_shifted_trace:
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if fig_dir: # note this is a global variable here
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fig.savefig(path.join(fig_dir, __file__ + '.loc{:.1f}-{:.1f}-{:.1f}'.format(*test_loc) + f'.i{i}{fig_distinguish}.pdf'))
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if i in plot_iteration_with_shifted_trace:
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ax.legend( ncol=5)
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if fig_dir:
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fname = path.join(fig_dir, __file__ + f'.{fig_distinguish}i{i}' + '.loc{:.1f}-{:.1f}-{:.1f}'.format(*test_loc))
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if True:
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old_xlim = ax.get_xlim()
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if True: # zoomed on part without peak of this trace
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wx = 100
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x = max(t_r) - wx
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ax.set_xlim(x-wx, x+wx)
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fig.savefig(fname + ".zoomed.beacon.pdf")
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if True: # zoomed on peak of this trace
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x = t_r[np.argmax(E_)]
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wx = 10 + max(best_sample_shifts) - min(best_sample_shifts)
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ax.set_xlim(x-wx, x+wx)
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fig.savefig(fname + ".zoomed.peak.pdf")
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ax.set_xlim(*old_xlim)
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fig.savefig(fname + ".pdf")
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plt.close(fig)
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# sort by antenna (undo sorting by maximum)
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@ -259,7 +286,7 @@ if __name__ == "__main__":
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yy.append(y_+yoff)
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# Find best k for each antenna
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shifts, maximum = find_best_sample_shifts_summing_at_location(test_loc, ev.antennas, allowed_sample_shifts, dt=dt, fig_dir=tmp_fig_subdir, plot_iteration_with_shifted_trace=len(ev.antennas)-1, fig_distinguish=f".run{r}")
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shifts, maximum = find_best_sample_shifts_summing_at_location(test_loc, ev.antennas, allowed_sample_shifts, dt=dt, fig_dir=tmp_fig_subdir, plot_iteration_with_shifted_trace=[ 5, len(ev.antennas)-1], fig_distinguish=f"run{r}.")
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# Translate sample shifts back into period multiple k
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ks = np.rint(shifts*f_beacon*dt)
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