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