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ZH: total time_diffs saved to file

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Eric Teunis de Boone 2022-11-24 14:47:29 +01:00
parent 0ffdee4496
commit 8da9d55c56
3 changed files with 60 additions and 34 deletions
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20
simulations/airshower_beacon_simulation/aa_generate_beacon.py
View file

@ -167,14 +167,15 @@ def read_baseline_time_diffs_hdf5(fname):
names = group[base_dset_name][:]
dset = group[dset_name]
f_beacon = dset[:,0]
true_phase_diffs = dset[:,1]
k_periods = dset[:,2]
time_diffs = dset[:,0]
f_beacon = dset[:,1]
true_phase_diffs = dset[:,2]
k_periods = dset[:,3]
return names, f_beacon, true_phase_diffs, k_periods
return names, time_diffs, f_beacon, true_phase_diffs, k_periods
def write_baseline_time_diffs_hdf5(fname, baselines, true_phase_diffs, k_periods, f_beacon, overwrite=True):
def write_baseline_time_diffs_hdf5(fname, baselines, true_phase_diffs, k_periods, f_beacon, time_diffs=None, overwrite=True):
"""
Write a combination of baselines, phase_diff, k_period and f_beacon to file.
@ -187,14 +188,17 @@ def write_baseline_time_diffs_hdf5(fname, baselines, true_phase_diffs, k_periods
baselines = [baselines]
true_phase_diffs = [true_phase_diffs]
k_periods = [k_periods]
f_beacon = [f_beacon]
f_beacon = np.array([f_beacon])
else:
N_baselines = len(baselines)
# Expand the f_beacon list
if not hasattr(f_beacon, '__len__'):
f_beacon = [f_beacon]*N_baselines
f_beacon = np.array([f_beacon]*N_baselines)
if time_diffs is None:
time_diffs = k_periods/f_beacon + true_phase_diffs/(2*np.pi*f_beacon)
assert len(baselines) == len(true_phase_diffs) == len(k_periods) == len(f_beacon)
@ -220,7 +224,7 @@ def write_baseline_time_diffs_hdf5(fname, baselines, true_phase_diffs, k_periods
base_dset = group.create_dataset(base_dset_name, data=basenames)
data = np.vstack( (f_beacon, true_phase_diffs, k_periods) ).T
data = np.vstack( (time_diffs, f_beacon, true_phase_diffs, k_periods) ).T
dset = group.create_dataset(dset_name, data=data)

58
simulations/airshower_beacon_simulation/bc_beacon_periods.py
View file

@ -31,7 +31,8 @@ if __name__ == "__main__":
baselines = list(combinations(antennas,2))
# use ref_ant
else:
ref_ant = antennas[ref_ant_idx]
ref_ant = antennas[ref_ant_id]
print(f"Doing all baselines with {ref_ant.name}")
baselines = list(zip_longest([], antennas, fillvalue=ref_ant))
freq_names = antennas[0].beacon_info.keys()
@ -47,38 +48,41 @@ if __name__ == "__main__":
# which traces to keep track of
traces = [ base[0].E_AxB, base[1].E_AxB ]
sampling_dt = (base[1].t[1] - base[1].t[0]) # ns
# how many samples do we need to shift
ks, maxima = lib.coherence_sum_maxima(traces[0], traces[1])
max_idx = np.argmax(maxima)
best_k = ks[max_idx]
delta_t_coherence = sampling_dt*best_k # ns
# read f_beacon from the first antenna
f_beacon = base[0].beacon_info[freq_name]['freq']
print('A1:', base[0].name, 'A2:', base[1].name, "K:", best_k, '= [ns]', delta_t_coherence)
# how many samples do we need to shift
sample_shifts, maxima = lib.coherence_sum_maxima(traces[0], traces[1], periodic=False)
best_sample_shift = sample_shifts[np.argmax(maxima)]
# turn sample_shift into time
sampling_dt = (base[1].t[1] - base[1].t[0]) # ns
delta_t_coherence = sampling_dt*best_sample_shift # ns
# get the amount of periods to move
f_beacon = base[0].beacon_info[freq_name]['freq']
k_period, rest = np.divmod(delta_t_coherence, 1/f_beacon)
k_period, t_rest = np.divmod(delta_t_coherence, 1/f_beacon)
# always keep the reference before traces[1]
if rest < 0:
if t_rest < 0: # np.divmod already does this
k_period -= 1
t_rest = 1/f_beacon + t_rest
# Get true phase diffs
try:
true_phases = np.array([ant.beacon_info[freq_name]['true_phase'] for ant in base])
true_phases_diff = lib.phase_mod(true_phases[0] - true_phases[1])
except IndexError:
# freq_name not in beacon_info
# or true_phase not determined yet
# true_phase not determined yet
print(f"Missing true_phases for {freq_name} in baseline {base[0].name},{base[1].name}")
true_phases_diff = np.nan
# save k_period with antenna names
time_diffs[i] = [true_phases_diff, k_period, f_beacon]
# Plotting for one or two iterations
if show_plots and i in [ 0, 1 ]:
print('i',i,'k[T]',k_period, 'rest[ns]',rest, 'T[ns]',1/f_beacon)
if show_plots and (i in [ 0, 1 ] or k_period > 3):
# More than three periods is quite much so report it
print('i',i,'k[T]',k_period, 'rest[ns]',t_rest, 'T[ns]',1/f_beacon, 'dT_coher[ns]', delta_t_coherence)
# Show correlation maxima plot
if not True:
@ -97,21 +101,29 @@ if __name__ == "__main__":
true_phases_diff = 0
delta_t_beacon = true_phases_diff/(2*np.pi*f_beacon)
print("t0[ns]", delta_t_antennas, "t_beacon[ns]", delta_t_beacon, "phase", true_phases_diff)
fig, ax = plt.subplots()
ax.set_xlabel('t')
ax.plot(base[0].t, traces[0], label=f'Reference {base[0].name}', alpha=0.5)
ax.set_title(
", ".join([
f"$\\Delta$t0 [ns] : {delta_t_antennas:.2f}",
f"$\\Delta$t_beacon [ns]: {delta_t_beacon:.2f}",
f"$\\Delta\\sigma_\\varphi$: {true_phases_diff:.4f}",
f"",
])
)
ax.set_xlabel('Sampling t [ns]')
ax.set_ylabel('Amplitude [a.u.]')
ax.plot(base[0].t, traces[0], label=f'Reference: {base[0].name}', alpha=0.5)
# plot vertical lines indicating f_beacon
min_t, max_t = base[0].t[0], base[0].t[-1]
N_lines = int( (max_t - min_t)*f_beacon) +1
for i, t in enumerate(np.arange(N_lines)/f_beacon):
ax.axvline( min_t + t, color='k', alpha=0.5, label=None if i!=0 else 'P_beacon')
ax.axvline( min_t + t, color='k', alpha=0.3)
ax.plot(base[1].t + delta_t_antennas, traces[1], label=f'Original {base[1].name} (t0 removed)', alpha=0.4, marker='+', ms=5)
ax.plot(base[1].t + delta_t_antennas + k_period/f_beacon + rest, traces[1], label='Coherence', alpha=0.3, marker='x', ms=5)
ax.plot(base[1].t + delta_t_antennas + k_period/f_beacon + delta_t_beacon, traces[1], label='Beacon only + Periods', alpha=0.6)
ax.plot(base[1].t + delta_t_antennas, traces[1], label=f'Original: {base[1].name} (t0 removed)', alpha=0.4, marker='+', ms=5)
ax.plot(base[1].t + delta_t_antennas + k_period/f_beacon + t_rest, traces[1], label='Coherence', alpha=0.3, marker='x', ms=5)
ax.plot(base[1].t + delta_t_antennas + k_period/f_beacon + delta_t_beacon, traces[1], label=f'$\\Delta t_\\varphi$ + $k={k_period:.0f}$ Periods', alpha=0.6)
ax.legend()
ax.legend(fancybox=True, framealpha=0.5)
# Save integer periods to antennas
beacon.write_baseline_time_diffs_hdf5(antennas_fname, baselines, time_diffs[:,0], time_diffs[:,1], time_diffs[:,2])

16
simulations/airshower_beacon_simulation/lib/lib.py
View file

@ -200,16 +200,26 @@ def find_beacon_in_traces(
return frequencies, phases, amplitudes
def coherence_sum_maxima(ref_x, y, k_step=1):
def coherence_sum_maxima(ref_x, y, k_step=1, k_start=0, k_end=None, periodic=True):
"""
Use the maximum of a coherent sum to determine
the best number of samples to move
"""
max_k = int( len(ref_x) )
ks = np.arange(0, max_k, step=k_step)
N_samples = int( len(ref_x) )
k_end = N_samples if k_end is None or k_end > max_k else k_end
ks = np.arange(k_start, k_end, step=k_step)
maxima = np.empty(len(ks))
if periodic is False:
# prepend zeros
N_zeros = N_samples
preshift = 0 # only required for testing purposes
ref_x = np.pad(ref_x, (N_zeros-0,0), 'constant')
y = np.pad(y, (N_zeros-preshift,preshift), 'constant')
for i,k in enumerate(ks, 0):
augmented_y = np.roll(y, k)
maxima[i] = max(ref_x + augmented_y)