ZH: beacon phase finding working

This commit is contained in:
Eric Teunis de Boone 2022-11-18 19:31:24 +01:00
parent 726c506816
commit 7aed162fa8
2 changed files with 62 additions and 22 deletions

View file

@ -14,9 +14,11 @@ if __name__ == "__main__":
f_beacon_band = (49e-3,55e-3) #GHz
allow_frequency_fitting = True
allow_frequency_fitting = False
read_frequency_from_file = True
show_plots = True
fname = "ZH_airshower/mysim.sry"
####
@ -65,40 +67,72 @@ if __name__ == "__main__":
sys.exit(1)
traces = ant_group['traces']
t_trace = traces[0]
freqs, phases, amps = find_beacon_in_traces(
traces[1:-1], traces[0],
f_beacon_estimate=f_beacon,
frequency_fit=allow_frequency_fitting,
f_beacon_estimate_band=f_beacon_estimate_band
)
if not True:
# only take the Beacon trace
test_traces = traces[4]
orients = ['B']
else:
test_traces = traces[1:]
orients = ['Ex', 'Ey', 'Ez', 'B']
# only take Ex for now
frequency = freqs[-1]
phase = phases[-1]
amplitude = amps[-1]
if True:
freqs, phases, amps = lib.find_beacon_in_traces(
test_traces, t_trace,
f_beacon_estimate=f_beacon,
frequency_fit=allow_frequency_fitting,
f_beacon_estimate_band=f_beacon_estimate_band
)
else:
# Testing
freqs = [f_beacon]
t0 = ant_group.attrs['t0']
print(frequency, phase, amplitude)
phases = [ 2*np.pi*t0*f_beacon ]
amps = [ 3e-7 ]
# choose highest amp
#idx = np.argmax(amps, axis=1)
idx = 0
frequency = freqs[idx]
phase = phases[idx]
amplitude = amps[idx]
orientation = orients[idx]
if show_plots and (i == 60 or i == 72):
fig, ax = plt.subplots()
trace_amp = max(traces[-1]) - min(traces[-1])
myt = np.linspace(min(traces[0]), max(traces[0]), 10*len(traces[0]))
ax.plot(t_trace, traces[-1], marker='.', label='trace')
ax.plot(myt, lib.sine_beacon(frequency, myt, amplitude=amplitude, phase=phase), ls='dashed', label='simulated')
ax.set_title(f"Beacon at antenna {ant_group}\nF:{frequency}, P:{phase}, A:{amplitude}")
ax.legend()
ant_group.attrs['beacon_freq'] = frequency
ant_group.attrs['beacon_phase'] = phase
ant_group.attrs['beacon_amplitude'] = amplitude
ant_group.attrs['beacon_orientation'] = 'Ex'
ant_group.attrs['beacon_orientation'] = orientation
found_data[i] = frequency, phase, amplitude
print("Beacon Phases, Amplitudes and Frequencies written to", antennas_fname)
# show histogram of found frequencies
if True:
if show_plots:
if True or allow_frequency_fitting:
fig, ax = plt.subplots()
ax.set_xlabel("Frequency")
ax.set_ylabel("Counts")
ax.hist(found_data[:,0], bins='auto', density=False)
ax.axvline(f_beacon, ls='dashed', color='g')
ax.hist(found_data[:,0], bins='sqrt', density=False)
if True:
fig, ax = plt.subplots()
ax.set_xlabel("Amplitudes")
ax.set_ylabel("Counts")
ax.hist(found_data[:,2], bins='auto', density=False)
ax.hist(found_data[:,2], bins='sqrt', density=False)
plt.show()

View file

@ -11,7 +11,7 @@ def sine_beacon(f, t, t0=0, amplitude=1, baseline=0, phase=0):
"""
Return a sine appropriate as a beacon
"""
return amplitude * np.cos(2*np.pi*f*(t+t0) + phase) + baseline
return amplitude * np.sin(2*np.pi*f*(t+t0) + phase) + baseline
def distance(x1, x2):
@ -74,6 +74,9 @@ def direct_fourier_transform(freqs, time, samplesets_iterable):
return np.dot(c_k, samplesets_iterable), np.dot(s_k, samplesets_iterable)
def phase_field_from_tx(x, y, tx, f_beacon, c_light=3e8, t0=0, wrap_phase=True, return_meshgrid=True):
assert type(tx) in [Antenna]
xs, ys = np.meshgrid(x, y, sparse=True)
x_distances = (tx.x - xs)**2
@ -128,8 +131,8 @@ def find_beacon_in_traces(
real, imag = ft_amp
amps = 1/n_samples * ( real**2 + imag**2)**0.5
# find frequency peak and surrounding
# bins valid for parabola fitting
# find frequency peak and surrounding bins
# that are valid for the parabola fit
max_amp_idx = np.argmax(amps)
max_amp = amps[max_amp_idx]
@ -170,9 +173,12 @@ def find_beacon_in_traces(
freq = deriv.roots()[0]
frequencies[i] = freq
else:
else: # no frequency finding
frequencies[:] = f_beacon_estimate
n_samples = len(t_trace)
# evaluate fourier transform at freq for each trace
for i, freq in enumerate(frequencies):
if freq is np.nan:
@ -183,6 +189,6 @@ def find_beacon_in_traces(
real, imag = direct_fourier_transform(freq, t_trace, traces[i])
phases[i] = np.arctan2(real, imag)
amplitudes[i] = 2/len(t_trace) * (real**2 + imag**2)**0.5
amplitudes[i] = 2/n_samples * (real**2 + imag**2)**0.5
return frequencies, phases, amplitudes