mirror of
https://gitlab.science.ru.nl/mthesis-edeboone/m-thesis-introduction.git
synced 2024-11-13 01:53:31 +01:00
ZH: resolve integer multiples for each combination of antennas
This commit is contained in:
parent
71ca901d0b
commit
baf789e951
2 changed files with 105 additions and 4 deletions
|
@ -2,6 +2,7 @@
|
||||||
# vim: fdm=indent ts=4
|
# vim: fdm=indent ts=4
|
||||||
|
|
||||||
import h5py
|
import h5py
|
||||||
|
from itertools import combinations, zip_longest
|
||||||
import matplotlib.pyplot as plt
|
import matplotlib.pyplot as plt
|
||||||
import numpy as np
|
import numpy as np
|
||||||
|
|
||||||
|
@ -40,9 +41,8 @@ if __name__ == "__main__":
|
||||||
|
|
||||||
ant.attrs['beacon_phase_true'] = true_phases[i]
|
ant.attrs['beacon_phase_true'] = true_phases[i]
|
||||||
|
|
||||||
# True phase (without geometry determined)
|
# Plot True Phases
|
||||||
|
if True:
|
||||||
if True: # show antenna phases
|
|
||||||
fig, ax = plt.subplots()
|
fig, ax = plt.subplots()
|
||||||
spatial_unit=None
|
spatial_unit=None
|
||||||
fig.suptitle('f= {:2.0f}MHz'.format(f_beacon*1e3))
|
fig.suptitle('f= {:2.0f}MHz'.format(f_beacon*1e3))
|
||||||
|
@ -59,6 +59,83 @@ if __name__ == "__main__":
|
||||||
sc = ax.scatter(*antenna_locs, c=true_phases, **scatter_kwargs)
|
sc = ax.scatter(*antenna_locs, c=true_phases, **scatter_kwargs)
|
||||||
fig.colorbar(sc, ax=ax, label=color_label)
|
fig.colorbar(sc, ax=ax, label=color_label)
|
||||||
|
|
||||||
|
# run over all baselines
|
||||||
|
if True:
|
||||||
|
baselines = list(combinations(antennas,2))
|
||||||
|
# use ref_ant
|
||||||
|
else:
|
||||||
|
ref_ant = antennas[0]
|
||||||
|
baselines = list(zip_longest([], antennas, fillvalue=ref_ant))
|
||||||
|
|
||||||
|
integer_periods = None
|
||||||
|
# read integer ks from file if possible
|
||||||
|
# and save beacon_phase_true
|
||||||
|
with h5py.File(antennas_fname, 'a') as fp:
|
||||||
|
for i, ant in enumerate(antennas):
|
||||||
|
name = ant.name
|
||||||
|
# set true beacon_phase
|
||||||
|
fp['antennas'][name].attrs['beacon_phase_true'] = true_phases[i]
|
||||||
|
|
||||||
|
# read integer period from file
|
||||||
|
if True and 'beacon_ks' in fp:
|
||||||
|
integer_periods = np.array(fp['beacon_ks'])
|
||||||
|
|
||||||
|
|
||||||
|
# Determine integer multiple of periods to shift
|
||||||
|
if integer_periods is None:
|
||||||
|
integer_periods = np.empty( (len(baselines), 3) )
|
||||||
|
for i, base in enumerate(baselines):
|
||||||
|
# Delta between first timestamp from both antennas
|
||||||
|
delta_t_a = base[0].t[0] - base[1].t[0]
|
||||||
|
# + phase difference
|
||||||
|
delta_t_p = np.diff([ant.attrs['beacon_phase_true'] for ant in base])[0]/(2*np.pi*f_beacon)
|
||||||
|
|
||||||
|
sampling_dt = (base[1].t[1] - base[1].t[0])
|
||||||
|
|
||||||
|
print("DT(A,P)", delta_t_a, delta_t_p, 1/f_beacon)
|
||||||
|
|
||||||
|
# which traces to keep track of
|
||||||
|
traces = [ base[0].Ex, base[1].Ex ]
|
||||||
|
|
||||||
|
# how many samples to shift
|
||||||
|
ks, maxima = lib.coherence_sum_maxima(-1*traces[0], -1*traces[1])
|
||||||
|
max_idx = np.argmax(maxima)
|
||||||
|
delta_t_c = sampling_dt*ks[max_idx] # ns
|
||||||
|
print("K", ks[max_idx], sampling_dt, '=', delta_t_c)
|
||||||
|
|
||||||
|
k, rest = np.divmod(delta_t_c, f_beacon)
|
||||||
|
integer_periods[i] = [int(base[0].name), int(base[1].name), k]
|
||||||
|
|
||||||
|
|
||||||
|
print(k, rest*f_beacon, delta_t_p)
|
||||||
|
|
||||||
|
# Only continue for two random combinations
|
||||||
|
if i not in [ 50, 51 ]:
|
||||||
|
continue
|
||||||
|
|
||||||
|
fig, ax = plt.subplots()
|
||||||
|
ax.set_xlabel("k")
|
||||||
|
ax.set_ylabel("Maximum correlation")
|
||||||
|
ax.plot(ks, maxima)
|
||||||
|
ax.plot(ks[max_idx], maxima[max_idx], marker='X')
|
||||||
|
|
||||||
|
fig, ax = plt.subplots()
|
||||||
|
dt = base[1].t[1] - base[1].t[0]
|
||||||
|
ax.set_xlabel('t')
|
||||||
|
ax.plot(base[0].t, traces[0], label='Reference')
|
||||||
|
ax.plot(base[1].t, traces[1], label='Original', alpha=0.4)
|
||||||
|
ax.plot(base[1].t + delta_t_a + delta_t_c, traces[1], label='Coherence', alpha=0.6)
|
||||||
|
|
||||||
|
ax.legend()
|
||||||
|
|
||||||
|
# Save integer periods to antennas
|
||||||
|
with h5py.File(antennas_fname, 'a') as fp:
|
||||||
|
group_name = 'beacon_ks'
|
||||||
|
if group_name in fp:
|
||||||
|
del fp[group_name]
|
||||||
|
|
||||||
|
fp.create_dataset(group_name, data=integer_periods)
|
||||||
|
|
||||||
plt.show()
|
plt.show()
|
||||||
# Report back to CLI
|
# Report back to CLI
|
||||||
#print("Period Multiples resolved in", antenna_fname)
|
print("Period Multiples resolved in", antennas_fname)
|
||||||
|
|
|
@ -34,6 +34,12 @@ def distance(x1, x2):
|
||||||
|
|
||||||
return np.sqrt( np.sum( (x1-x2)**2 ) )
|
return np.sqrt( np.sum( (x1-x2)**2 ) )
|
||||||
|
|
||||||
|
def geometry_time(dist, x2=None, c_light=3e8):
|
||||||
|
if x2 is not None:
|
||||||
|
dist = distance(dist, x2)
|
||||||
|
|
||||||
|
return dist/c_light
|
||||||
|
|
||||||
def beacon_from(tx, rx, f, t=0, t0=0, c_light=3e8, radiate_rsq=True, amplitude=1,**kwargs):
|
def beacon_from(tx, rx, f, t=0, t0=0, c_light=3e8, radiate_rsq=True, amplitude=1,**kwargs):
|
||||||
dist = distance(tx,rx)
|
dist = distance(tx,rx)
|
||||||
t0 = t0 + dist/c_light
|
t0 = t0 + dist/c_light
|
||||||
|
@ -81,6 +87,8 @@ def direct_fourier_transform(freqs, time, samplesets_iterable):
|
||||||
return np.dot(c_k, samplesets_iterable), np.dot(s_k, 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):
|
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]
|
assert type(tx) in [Antenna]
|
||||||
|
|
||||||
|
@ -191,3 +199,19 @@ def find_beacon_in_traces(
|
||||||
amplitudes[i] = 2/n_samples * (real**2 + imag**2)**0.5
|
amplitudes[i] = 2/n_samples * (real**2 + imag**2)**0.5
|
||||||
|
|
||||||
return frequencies, phases, amplitudes
|
return frequencies, phases, amplitudes
|
||||||
|
|
||||||
|
def coherence_sum_maxima(ref_x, y, k_step=1):
|
||||||
|
"""
|
||||||
|
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)
|
||||||
|
|
||||||
|
maxima = np.empty(len(ks))
|
||||||
|
|
||||||
|
for i,k in enumerate(ks, 0):
|
||||||
|
augmented_y = np.roll(y, k)
|
||||||
|
maxima[i] = max(ref_x + augmented_y)
|
||||||
|
|
||||||
|
return ks, maxima
|
||||||
|
|
Loading…
Reference in a new issue