#!/usr/bin/env python3 # vim: fdm=indent ts=4 import h5py from itertools import combinations, zip_longest import matplotlib.pyplot as plt import numpy as np import aa_generate_beacon as beacon import lib if __name__ == "__main__": from os import path import sys fname = "ZH_airshower/mysim.sry" show_plots = True ref_ant_id = None # leave None for all baselines #### fname_dir = path.dirname(fname) antennas_fname = path.join(fname_dir, beacon.antennas_fname) # Read in antennas from file f_beacon, tx, antennas = beacon.read_beacon_hdf5(antennas_fname) # run over all baselines if ref_ant_id is None: print("Doing all baselines") baselines = list(combinations(antennas,2)) # use ref_ant else: 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() if len(freq_names) > 1: raise NotImplementedError freq_name = next(iter(freq_names)) # Determine integer multiple of periods to shift # and True phase differences time_diffs = np.empty( (len(baselines), 3) ) for i, base in enumerate(baselines): # which traces to keep track of traces = [ base[0].E_AxB, base[1].E_AxB ] # read f_beacon from the first antenna f_beacon = base[0].beacon_info[freq_name]['freq'] # 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 k_period, t_rest = np.divmod(delta_t_coherence, 1/f_beacon) # always keep the reference before traces[1] 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(lib.phase_mod(true_phases[0]) - lib.phase_mod(true_phases[1])) except IndexError: # 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 [ 1, 57 ] 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: fig, ax = plt.subplots() ax.set_title(f"Correlation Maxima {i}") ax.set_xlabel("k") ax.set_ylabel("Maximum correlation") ax.plot(ks, maxima) ax.plot(best_k, maxima[max_idx], marker='X') # Delta t due to the beacon # Note that we want to show some overlapping waveforms # Therefore we use the phase from the original waveforms # and not the true_phases (we lost t_d information there) phases = np.array([ant.beacon_info[freq_name]['phase'] for ant in base]) phases_diff = lib.phase_mod(lib.phase_mod(phases[0]) - lib.phase_mod(phases[1])) delta_t_beacon = phases_diff/(2*np.pi*f_beacon) # Do we make it shared plot with both the # signal and the beacon? beacons = None if True: try: beacons = [ base[0].beacon, base[1].beacon ] except: # No beacon waveforms available.. pass # Start the figure fig, axs = plt.subplots(1+(beacons is not None), 1, sharex=True) if beacons is None: axs = [axs] fig.suptitle( ", ".join([ f"$\\Delta$t_beacon [ns]: {delta_t_beacon:.2f}", f"$\\Delta\\varphi$: {phases_diff:.4f}", f"$\\Delta\\sigma_\\varphi$: {true_phases_diff:.4f}", f"", ]) ) axs[-1].set_xlabel('t [ns]') axs[0].set_ylabel('Amplitude [a.u.]') # plot vertical lines indicating f_beacon min_t, max_t = min(base[0].t[0], base[1].t[0]), max(base[0].t[-1], base[1].t[-1]) N_lines = int( (max_t - min_t)*f_beacon) +1 for i, t in enumerate(np.arange(N_lines)/f_beacon): for ax in axs: ax.axvline( min_t + t, color='k', alpha=0.3) # Plot traces l1 = axs[0].plot(base[0].t, traces[0], label=f'Ref: {base[0].name}', alpha=0.8) l2 = axs[0].plot(base[1].t, traces[1], label=f'Orig: {base[1].name}', alpha=0.3, marker='+', ms=5) axs[0].plot(base[0].t + k_period/f_beacon + t_rest, traces[1], label='Coherence', alpha=0.3, marker='x', ms=5) l3 = axs[0].plot(base[1].t - delta_t_beacon +k_period/f_beacon, traces[1], label=f'$\\Delta t_{{\\sigma\\varphi}}$ + ($k={k_period:.0f}$)T', alpha=0.8) axs[0].legend(fancybox=True, framealpha=0.5) # Plot beacon if available if beacons is not None: ax = axs[1] ax.set_title("Original Beacons") ax.plot(base[0].t, beacons[0], label=f'Ref: {base[0].name}', alpha=0.8, color=l1[0].get_color()) ax.plot(base[1].t, beacons[1], label=f'Orig: {base[1].name}', alpha=0.3, marker='+', ms=5, color=l2[0].get_color()) ax.plot(base[1].t -delta_t_beacon +k_period/f_beacon, beacons[1], label=f'$\\Delta t_{{\\sigma\\varphi}}$ + ($k={k_period:.0f}$)T', alpha=0.8, color=l3[0].get_color()) if True: fig.savefig(__file__ + f"_i{i}_k{k_period}_zoomed_out.pdf") ax.set_xlim(base[0].t[0]-1/f_beacon, base[0].t[0] + 5/f_beacon) fig.savefig(__file__ + f"_i{i}_k{k_period}.pdf") # Save integer periods to antennas beacon.write_baseline_time_diffs_hdf5(antennas_fname, baselines, time_diffs[:,0], time_diffs[:,1], time_diffs[:,2]) # Report back to CLI print("Period Multiples resolved and written to ", antennas_fname) plt.show()