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m-thesis-introduction
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Pulse: Waveform figure: show SNR levels

This commit is contained in:
Eric Teunis de Boone 2023-05-17 17:50:17 +02:00
parent de92e25b75
commit 4e96342342
1 changed files with 37 additions and 18 deletions
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55
simulations/11_pulsed_timing.py
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@ -235,6 +235,8 @@ def get_time_residuals_for_template(
true_time_offset = antenna.peak_time - template.peak_time
antenna.signal_level = np.max(antenna.signal)
if False: # flip polarisation
antenna.signal *= -1
@ -245,26 +247,43 @@ def get_time_residuals_for_template(
antenna.signal += filtered_noise
antenna.noise_level = np.sqrt(np.mean(filtered_noise**2))
antenna.signal_to_noise = antenna.signal_level/antenna.noise_level
# Show signals
if do_plots:
fig, axs = plt.subplots(2, sharex=True)
if not hasattr(axs, '__len__'):
axs = [axs]
axs[0].set_title("Antenna Waveform")
axs[-1].set_xlabel("Time [ns]")
axs[0].set_ylabel("Amplitude")
axs[0].plot(antenna.t, antenna.signal, label='bandpassed w/ noise', alpha=0.9)
axs[0].plot(antenna.t, antenna.signal - filtered_noise, label='bandpassed w/o noise', alpha=0.9)
axs[0].legend()
l1 = axs[0].plot(antenna.t, antenna.signal, label='Filtered w/ noise', alpha=0.7)
l2 = axs[0].plot(antenna.t, antenna.signal - filtered_noise, label='Filtered w/o noise', alpha=0.7)
l3 = axs[0].plot(antenna.t, filtered_noise, label='Noise', alpha=0.7)
axs[1].set_title("Template")
axs[1].set_ylabel("Amplitude")
axs[1].plot(template.t, template.signal, label='orig')
axs[1].plot(template.t + true_time_offset, template.signal, label='true moved orig')
axs[1].legend()
if True: # indicate signal and noise levels
level_kwargs = dict(ls='dashed', alpha=0.4)
axs[0].axhline(antenna.signal_level, color=l2[0].get_color(), **level_kwargs, label='Signal Level')
axs[0].axhline(antenna.noise_level, color=l3[0].get_color(), **level_kwargs, label='Noise Level')
axs[0].legend(title=f'SNR = {antenna.signal_to_noise:.1g}')
axs[0].grid()
axs[1].grid()
fig.savefig('figures/11_antenna_signals.pdf')
if len(axs) > 1:
axs[1].set_title("Template")
axs[1].set_ylabel("Amplitude")
axs[1].plot(template.t, template.signal, label='orig')
axs[1].plot(template.t + true_time_offset, template.signal, label='true moved orig')
axs[1].legend()
axs[1].grid()
fig.tight_layout()
fig.savefig(f'figures/11_antenna_signals_tdt{template.dt:.1g}.pdf')
if True: # zoom
wx = 100
@ -272,7 +291,7 @@ def get_time_residuals_for_template(
old_xlims = axs[0].get_xlim()
axs[0].set_xlim( x0-wx, x0+wx)
fig.savefig('figures/11_antenna_signals_zoom.pdf')
fig.savefig(f'figures/11_antenna_signals_tdt{template.dt:.1g}_zoom.pdf')
# restore
axs[0].set_xlim(*old_xlims)
@ -294,12 +313,12 @@ def get_time_residuals_for_template(
axs2[0].plot(upsampled_t, upsampled_trace, label='upsampled')
axs2[0].legend(loc='upper right')
fig2.savefig('figures/11_upsampled.pdf')
fig2.savefig(f'figures/11_upsampled_tdt{template.dt:.1g}.pdf')
wx = 1e2
x0 = upsampled_t[0] + wx - 5
axs2[0].set_xlim(x0-wx, x0+wx)
fig2.savefig('figures/11_upsampled_zoom.pdf')
fig2.savefig(f'figures/11_upsampled_tdt{template.dt:.1g}_zoom.pdf')
if True:
plt.close(fig2)
@ -345,7 +364,7 @@ def get_time_residuals_for_template(
offset_list = [
[best_time_lag, dict(label=template.name, color='orange')],
[true_time_offset, dict(label='True offset', color='green')],
[true_time_offset, dict(label='True offset', ls='dashed', color='green')],
]
# Signal
@ -379,18 +398,18 @@ def get_time_residuals_for_template(
if True: # zoom
wx = len(template.signal) * (template.dt)/2
t0 = best_time_lag
wx = len(template.signal) * (min(1,template.dt))/4
t0 = true_time_offset
old_xlims = axs[0].get_xlim()
axs[i].set_xlim( x0-wx, x0+3*wx)
fig.savefig('figures/11_corrs_zoom.pdf')
fig.savefig(f'figures/11_corrs_tdt{template.dt:.1g}_zoom.pdf')
# restore
axs[i].set_xlim(*old_xlims)
fig.tight_layout()
fig.savefig('figures/11_corrs.pdf')
fig.savefig(f'figures/11_corrs_tdt{template.dt:.1g}.pdf')
if True:
plt.close(fig)