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ZH: improve temporary correlation figures
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1 changed files with 9 additions and 4 deletions
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@ -93,18 +93,23 @@ 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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shift_maxima[j] = np.max(augmented_a + a_sum)
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if i in plot_iteration_with_shifted_trace:
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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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ax.plot(t_sum, augmented_a, alpha=0.7, ls='dashed', label=f'{shift}')
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# transform maximum into best_sample_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_idx = np.argmax(shift_maxima)
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best_sample_shifts[i] = allowed_sample_shifts[best_idx]
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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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best_augmented_a = np.roll(a_int, best_sample_shifts[i])
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a_sum += best_augmented_a
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# cleanup figure
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# cleanup figure
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if i in plot_iteration_with_shifted_trace:
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if i in plot_iteration_with_shifted_trace:
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if True: # plot best k again
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ax.plot(t_sum, augmented_a, alpha=0.8, label=f'best k={best_sample_shifts[i]}', lw=2)
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ax.legend( ncol=5 )
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ax.legend( ncol=5 )
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if fig_dir:
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if fig_dir:
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fig.tight_layout()
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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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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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if True:
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old_xlim = ax.get_xlim()
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old_xlim = ax.get_xlim()
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@ -117,7 +122,7 @@ def find_best_sample_shifts_summing_at_location(test_loc, antennas, allowed_samp
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if True: # zoomed on peak of this trace
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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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x = t_r[np.argmax(E_)]
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wx = 10 + max(best_sample_shifts) - min(best_sample_shifts)
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wx = 50 + (max(best_sample_shifts) - min(best_sample_shifts))*dt
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ax.set_xlim(x-wx, x+wx)
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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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fig.savefig(fname + ".zoomed.peak.pdf")
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