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https://gitlab.science.ru.nl/mthesis-edeboone/m-thesis-introduction.git
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Pulse: move timeresidual matching to function
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1f00a3fe76
commit
168b0a60bc
1 changed files with 227 additions and 211 deletions
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@ -172,82 +172,17 @@ def create_template(dt=1, timelength=1, bp_freq=(0, np.inf), name=None, normalis
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return template, _deltapeak
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if __name__ == "__main__":
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import os
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import matplotlib
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import sys
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if os.name == 'posix' and "DISPLAY" not in os.environ:
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matplotlib.use('Agg')
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bp_freq = (30e-3, 80e-3) # GHz
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template_dt = 5e-2 # ns
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interp_template_dt = 5e-5 # ns
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template_length = 200 # ns
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N_residuals = 50*3 if len(sys.argv) < 2 else int(sys.argv[1])
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snr_factors = np.concatenate( # 1/noise_amplitude factor
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(
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#[0.25, 0.5, 0.75],
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[1, 1.5, 2, 2.5, 3, 4, 5, 7],
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[10, 20, 30, 50],
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[100, 200, 300, 500]
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),
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axis=None)
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antenna_dt = 2 # ns
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antenna_timelength = 1024 # ns
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cut_wrong_peak_matches = True
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normalise_noise = False
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h5_cache_fname = f'11_pulsed_timing.hdf5'
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#
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# Interpolation Template
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# to create an 'analog' sampled antenna
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interp_template, _deltapeak = create_template(dt=interp_template_dt, timelength=template_length, bp_freq=bp_freq, name='Interpolation Template', normalise=True)
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interp_template.interpolate = interpolate.interp1d(interp_template.t, interp_template.signal, assume_sorted=True, fill_value=0, bounds_error=False, copy=False)
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if True: # show interpolation template
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fig, ax = plt.subplots()
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ax.set_title("Deltapeak and Bandpassed Template")
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ax.set_xlabel("Time [ns]")
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ax.set_ylabel("Amplitude")
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ax.plot(interp_template.t, max(interp_template.signal)*_deltapeak[0], label='Impulse Template')
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ax.plot(interp_template.t, interp_template.signal, label='Filtered Template')
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ax.legend()
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fig.savefig('figures/11_interpolation_deltapeak.pdf')
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if True: # show filtering equivalence samplerates
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_deltapeak = util.deltapeak(timelength=template_length, samplerate=1/antenna_dt, offset=0)
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_time = util.sampled_time(end=template_length, sample_rate=1/antenna_dt)
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_bandpassed = antenna_bp(_deltapeak[0], *bp_freq, antenna_dt)
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ax.plot(_time, max(_bandpassed)*_deltapeak[0], label='Impulse Antenna')
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ax.plot(_time, _bandpassed, label='Filtered Antenna')
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ax.legend()
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fig.savefig('figures/11_interpolation_deltapeak+antenna.pdf')
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if True:
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plt.close(fig)
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#
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# Create the template
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# This is sampled at a lower samplerate than the interpolation template
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#
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template, _ = create_template(dt=template_dt, timelength=template_length, bp_freq=bp_freq, name='Template')
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#
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# Find time accuracies as a function of signal strength
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#
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time_accuracies = np.zeros(len(snr_factors))
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mask_counts = np.zeros(len(snr_factors))
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for k, snr_sigma_factor in tqdm(enumerate(snr_factors)):
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def get_time_residuals_for_template(
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N_residuals, template, interpolation_template=None,
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antenna_dt=1, antenna_timelength=100,
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snr_sigma_factor=10,bp_freq=(0,np.inf),
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normalise_noise=False, h5_cache_fname=None, read_cache=True, write_cache=None,
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rng=rng, tqdm=tqdm,
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):
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# Read in cached time residuals
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if True:
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if read_cache:
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cached_time_residuals = read_time_residuals_cache(h5_cache_fname, template.dt, antenna_dt, snr_sigma_factor)
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else:
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cached_time_residuals = np.array([])
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@ -261,8 +196,7 @@ if __name__ == "__main__":
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# receive at antenna
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## place the deltapeak signal at a random location
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antenna = Waveform(None, dt=antenna_dt, name='Signal')
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if False: # Create antenna trace without interpolation template
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if interpolation_template is None: # Create antenna trace without interpolation template
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antenna_true_signal, antenna_peak_sample = util.deltapeak(timelength=antenna_timelength, samplerate=1/antenna.dt, offset=[0.2, 0.8], rng=rng)
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antenna.peak_sample = antenna_peak_sample
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@ -278,7 +212,7 @@ if __name__ == "__main__":
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antenna.t = util.sampled_time(1/antenna.dt, start=0, end=antenna_timelength)
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# Sample the interpolation template
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antenna.signal = interp_template.interpolate(antenna.t - antenna.peak_time)
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antenna.signal = interpolation_template.interpolate(antenna.t - antenna.peak_time)
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antenna.peak_sample = antenna.peak_time/antenna.dt
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antenna_true_signal = antenna.signal
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@ -295,7 +229,8 @@ if __name__ == "__main__":
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antenna.signal += filtered_noise
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if do_plots: # show signals
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# Show signals
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if do_plots:
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fig, axs = plt.subplots(2, sharex=True)
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axs[0].set_title("Antenna Waveform")
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axs[-1].set_xlabel("Time [ns]")
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@ -332,7 +267,6 @@ if __name__ == "__main__":
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axs2 = None
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if True: # upsampled trace
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upsampled_trace, upsampled_t = trace_upsampler(antenna.signal, template.t, antenna.t)
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if do_plots: # Show upsampled traces
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fig2, axs2 = plt.subplots(1, sharex=True)
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if not hasattr(axs2, '__len__'):
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@ -445,23 +379,105 @@ if __name__ == "__main__":
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if True:
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plt.close(fig)
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print()# separating tqdm
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print()# separating tqdm
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# Were new time residuals calculated?
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# Add them to the cache file
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if len(time_residuals) > 1:
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# merge cached and calculated time residuals
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time_residuals = np.concatenate((cached_time_residuals, time_residuals), axis=None)
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if True: # write the cache
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if write_cache or read_cache and write_cache is None: # write the cache
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write_time_residuals_cache(h5_cache_fname, time_residuals, template_dt, antenna_dt, snr_sigma_factor)
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else:
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time_residuals = cached_time_residuals
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# Only return N_residuals (even if more have been cached)
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return time_residuals[:N_residuals]
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if __name__ == "__main__":
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import os
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import matplotlib
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import sys
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if os.name == 'posix' and "DISPLAY" not in os.environ:
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matplotlib.use('Agg')
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bp_freq = (30e-3, 80e-3) # GHz
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template_dt = 5e-2 # ns
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interp_template_dt = 5e-5 # ns
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template_length = 200 # ns
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N_residuals = 50*3 if len(sys.argv) < 2 else int(sys.argv[1])
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snr_factors = np.concatenate( # 1/noise_amplitude factor
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(
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#[0.25, 0.5, 0.75],
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[1, 1.5, 2, 2.5, 3, 4, 5, 7],
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[10, 20, 30, 50],
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[100, 200, 300, 500]
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),
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axis=None, dtype=float)
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antenna_dt = 2 # ns
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antenna_timelength = 1024 # ns
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cut_wrong_peak_matches = True
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normalise_noise = False
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h5_cache_fname = f'11_pulsed_timing.hdf5'
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#
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# Interpolation Template
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# to create an 'analog' sampled antenna
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interp_template, _deltapeak = create_template(dt=interp_template_dt, timelength=template_length, bp_freq=bp_freq, name='Interpolation Template', normalise=True)
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interp_template.interpolate = interpolate.interp1d(interp_template.t, interp_template.signal, assume_sorted=True, fill_value=0, bounds_error=False, copy=False)
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if True: # show interpolation template
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fig, ax = plt.subplots()
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ax.set_title("Deltapeak and Bandpassed Template")
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ax.set_xlabel("Time [ns]")
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ax.set_ylabel("Amplitude")
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ax.plot(interp_template.t, max(interp_template.signal)*_deltapeak[0], label='Impulse Template')
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ax.plot(interp_template.t, interp_template.signal, label='Filtered Template')
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ax.legend()
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fig.savefig('figures/11_interpolation_deltapeak.pdf')
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if True: # show filtering equivalence samplerates
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_deltapeak = util.deltapeak(timelength=template_length, samplerate=1/antenna_dt, offset=0)
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_time = util.sampled_time(end=template_length, sample_rate=1/antenna_dt)
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_bandpassed = antenna_bp(_deltapeak[0], *bp_freq, antenna_dt)
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ax.plot(_time, max(_bandpassed)*_deltapeak[0], label='Impulse Antenna')
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ax.plot(_time, _bandpassed, label='Filtered Antenna')
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ax.legend()
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fig.savefig('figures/11_interpolation_deltapeak+antenna.pdf')
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if True:
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plt.close(fig)
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#
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# Create the template
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# This is sampled at a lower samplerate than the interpolation template
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#
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template, _ = create_template(dt=template_dt, timelength=template_length, bp_freq=bp_freq, name='Template')
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#
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# Find time accuracies as a function of signal strength
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#
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time_accuracies = np.zeros(len(snr_factors))
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mask_counts = np.zeros(len(snr_factors))
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for k, snr_sigma_factor in tqdm(enumerate(snr_factors)):
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time_residuals = get_time_residuals_for_template(
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N_residuals, template, interpolation_template=interp_template,
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antenna_dt=antenna_dt, antenna_timelength=antenna_timelength,
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snr_sigma_factor=snr_sigma_factor, bp_freq=bp_freq, normalise_noise=normalise_noise,
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h5_cache_fname=h5_cache_fname, rng=rng, tqdm=tqdm)
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print()# separating tqdm
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print()# separating tqdm
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# Make a plot of the time residuals
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if N_residuals > 1:
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time_residuals = time_residuals[:N_residuals]
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for i in range(1 + cut_wrong_peak_matches):
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mask_count = 0
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