m-thesis-introduction/simulations/airshower_beacon_simulation/ca_beacon_periods.py

#!/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
    save_result = True
    ref_ant_id = None # leave None for all baselines

    ####
    fname_dir = path.dirname(fname)
    antennas_fname = path.join(fname_dir, beacon.antennas_fname)
    time_diffs_fname = 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):
        if i%50==0:
            print(i, "out of", len(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

            # 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 a 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]

            print('i',i,f"B({base[0].name},{base[1].name})", 'k[T]',k_period, 'rest[ns]',t_rest, 'T[ns]',1/f_beacon, 'dT_coher[ns]', delta_t_coherence, 'dT_beac[ns]', delta_t_beacon)

            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'$\\Delta t_{{\\varphi}}$ + ($k={k_period:.0f}$)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'$\\Delta t_{{\\varphi}}$ + ($k={k_period:.0f}$)T', alpha=0.8, color=l3[0].get_color())

            if False:
                if False:
                    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")

    # Report back to CLI
    print("Period Multiples resolved from", antennas_fname)
    if save_result:
        # Save integer periods to antennas
        beacon.write_baseline_time_diffs_hdf5(time_diffs_fname, baselines, time_diffs[:,0], time_diffs[:,1], time_diffs[:,2])
        print("Timediffs saved to", time_diffs_fname)

    plt.show()