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

#!/usr/bin/env python3
# vim: fdm=marker ts=4

"""
Add a beacon measurement on top of the
simulated airshower.
"""

import numpy as np
import json
import h5py
import os.path as path
from copy import deepcopy

from earsim import REvent, Antenna, block_filter
import lib

# {{{ vim marker
tx_fname = 'tx.json'
antennas_fname = 'antennas.hdf5'

def write_tx_file(fname, tx, f_beacon, **kwargs):
    with open(fname, 'w') as fp:
        return json.dump(
                {
                    **kwargs,
                    **dict(
                        f_beacon=f_beacon,
                        tx=dict(
                            x=tx.x,
                            y=tx.y,
                            z=tx.z,
                            name=tx.name
                        )
                    )
                },
                fp
               )

def read_tx_file(fname):
    with open(fname, 'r') as fp:
        data = json.load(fp)

    f_beacon = data['f_beacon']
    tx = Antenna(**data['tx'])

    del data['f_beacon']
    del data['tx']

    return tx, f_beacon, data

def read_beacon_hdf5(fname, **h5ant_kwargs):
    with h5py.File(fname, 'r') as h5:
        tx = Antenna_from_h5ant(h5['tx'], traces_key=None)
        f_beacon = tx.attrs['f_beacon']

        antennas = []
        for k, h5ant in h5['antennas'].items():
            ant = Antenna_from_h5ant(h5ant, **h5ant_kwargs)

            antennas.append(ant)

    return f_beacon, tx, antennas

def Antenna_from_h5ant(h5ant, traces_key='traces', raise_exception=True, read_AxB=True, read_beacon_info=True):
    mydict = { k:h5ant.attrs.get(k) for k in ['x', 'y', 'z', 'name'] }
    ant = Antenna(**mydict)
    if h5ant.attrs:
        ant.attrs = {**h5ant.attrs}

    # Traces
    if traces_key is None:
        pass
    elif traces_key not in h5ant:
        if raise_exception:
            raise ValueError("Traces_key not in file")
    else:
        ant.t  = deepcopy(h5ant[traces_key][0])
        ant.Ex = deepcopy(h5ant[traces_key][1])
        ant.Ey = deepcopy(h5ant[traces_key][2])
        ant.Ez = deepcopy(h5ant[traces_key][3])
        if len(h5ant[traces_key]) > 4:
            ant.beacon = deepcopy(h5ant[traces_key][4])

    # E_AxB
    if read_AxB and 'E_AxB' in h5ant:
        ant.t_AxB = deepcopy(h5ant['E_AxB'][0])
        ant.E_AxB = deepcopy(h5ant['E_AxB'][1])

    # Beacons
    if read_beacon_info and 'beacon_info' in h5ant:
        h5beacon = h5ant['beacon_info']

        beacon_info = {}
        for name in h5beacon.keys():
            beacon_info[name] = dict(h5beacon[name].attrs)

        ant.beacon_info = beacon_info

    return ant


def init_antenna_hdf5(fname, tx = None, f_beacon = None):
    with h5py.File(fname, 'w') as fp:
        if tx is not None or f_beacon is not None:
            tx_group = fp.create_group('tx')
            tx_attrs = tx_group.attrs

            if f_beacon is not None:
                tx_attrs['f_beacon'] = f_beacon

            if tx is not None:
                tx_attrs['x'] = tx.x
                tx_attrs['y'] = tx.y
                tx_attrs['z'] = tx.z
                tx_attrs['name'] = tx.name

    return fname

def append_antenna_hdf5(fname, antenna, columns = [], name='traces', prepend_time=True, overwrite=True, attrs_dict={}):
    if not overwrite:
        raise NotImplementedError

    with h5py.File(fname, 'a') as fp:
        if 'antennas' in fp.keys():
            if not overwrite:
                raise NotImplementedError
            group = fp['antennas']
        else:
            group = fp.create_group('antennas')


        if antenna.name in group:
            if not overwrite:
                raise NotImplementedError
            h5ant = group[antenna.name]
        else:
            h5ant = group.create_group(antenna.name)

        h5ant_attrs = h5ant.attrs
        h5ant_attrs['x'] = antenna.x
        h5ant_attrs['y'] = antenna.y
        h5ant_attrs['z'] = antenna.z
        h5ant_attrs['name'] = antenna.name

        for k,v in attrs_dict.items():
            h5ant_attrs[k] = v

        if name in h5ant:
            if not overwrite:
                raise NotImplementedError
            del h5ant[name]

        dset = h5ant.create_dataset(name, (len(columns) + 1*prepend_time, len(columns[0])), dtype='f')

        if prepend_time:
            dset[0] = antenna.t

        for i, col in enumerate(columns, 1*prepend_time):
            dset[i] = col


def read_baseline_time_diffs_hdf5(fname):
    """
    Read Baseline Time Diff information from HDF5 storage.
    """
    with h5py.File(fname, 'r') as fp:
        group_name = 'baseline_time_diffs'
        base_dset_name = 'baselines'
        dset_name = 'time_diffs'

        group = fp[group_name]

        names = group[base_dset_name][:].astype(str)

        dset = group[dset_name]
        time_diffs = dset[:,0]
        f_beacon = dset[:,1]
        true_phase_diffs = dset[:,2]
        k_periods = dset[:,3]

        return names, time_diffs, f_beacon, true_phase_diffs, k_periods


def write_baseline_time_diffs_hdf5(fname, baselines, true_phase_diffs, k_periods, f_beacon, time_diffs=None, overwrite=True):
    """
    Write a combination of baselines, phase_diff, k_period and f_beacon to file.

    Note that f_beacon is allowed to broadcast, but the others are not.
    """

    if not hasattr(baselines[0], '__len__'):
        # this is a single baseline
        N_baselines = 1
        baselines = [baselines]
        true_phase_diffs = [true_phase_diffs]
        k_periods = [k_periods]
        f_beacon = np.array([f_beacon])

    else:
        N_baselines = len(baselines)

        # Expand the f_beacon list
        if not hasattr(f_beacon, '__len__'):
            f_beacon = np.array([f_beacon]*N_baselines)

    if time_diffs is None:
        time_diffs = k_periods/f_beacon + true_phase_diffs/(2*np.pi*f_beacon)

    assert len(baselines) == len(true_phase_diffs) == len(k_periods) == len(f_beacon)

    with h5py.File(fname, 'a') as fp:
        group_name = 'baseline_time_diffs'
        base_dset_name = 'baselines'
        dset_name = 'time_diffs'

        group = fp.require_group(group_name)

        if base_dset_name in group:
            if not overwrite:
                raise NotImplementedError
            del group[base_dset_name]

        if dset_name in group:
            if not overwrite:
                raise NotImplementedError
            del group[dset_name]

        # save baselines list
        basenames = np.array([ [b[0].name, b[1].name] for b in baselines ], dtype='S')

        base_dset = group.create_dataset(base_dset_name, data=basenames)

        data = np.vstack( (time_diffs, f_beacon, true_phase_diffs, k_periods) ).T
        dset = group.create_dataset(dset_name, data=data)

# }}} vim marker

if __name__ == "__main__":
    from os import path

    fname = "ZH_airshower/mysim.sry"

    # Transmitter
    remake_tx = True

    tx = Antenna(x=-2e3,y=0,z=0,name='tx') # m
    if False:
        # Move tx out a long way
        tx.x, tx.y = -75e3, 75e3 # m
    elif False:
        # Move it to 0,0,0 (among the antennas)
        tx.x, tx.y = 0, 0 #m

    # Beacon properties
    if False: # slowest beacon to be found:
        f_beacon =  10e-3 # GHz
        low_bp = 5e-3 # GHz
        high_bp = 80e-3 # GHz
    else: # original wanted beacon
        f_beacon = 51.53e-3 # GHz

        # Bandpass for E field blockfilter
        low_bp = 30e-3 # GHz
        high_bp = 80e-3 # GHz

    beacon_amplitudes = 1e-6*np.array([1e5, 0, 0]) # mu V/m
    beacon_radiate_rsq = True # beacon_amplitude is repaired for distance to 0,0,0

    # modify beacon power to be beacon_amplitude at 0,0,0
    if beacon_radiate_rsq:
        dist = lib.distance(tx, Antenna(x=0, y=0, z=0))

        ampl = max(1, dist**2)

        beacon_amplitudes *= ampl

    # Disable block_filter
    if False:
        block_filter = lambda x, dt, low, high: x

    ####
    fname_dir = path.dirname(fname)
    tx_fname = path.join(fname_dir, tx_fname)
    antennas_fname = path.join(fname_dir, antennas_fname)

    # read/write tx properties
    if not path.isfile(tx_fname) or remake_tx:
        write_tx_file(tx_fname, tx, f_beacon, amplitudes=beacon_amplitudes.tolist(), radiate_rsq=beacon_radiate_rsq)
    else:
        tx, f_beacon, _ = read_tx_file(tx_fname)


    print("Beacon amplitude at (0,0,0) [muV/m]:", beacon_amplitudes)
    print("Tx location:", [tx.x, tx.y, tx.z])

    # read in antennas
    ev = REvent(fname)
    N_antennas = len(ev.antennas)

    # initialize hdf5 file
    init_antenna_hdf5(antennas_fname, tx, f_beacon)

    # make beacon per antenna
    for i, antenna in enumerate(ev.antennas):
        t0 = lib.distance(tx, antenna)/3e8 * 1e9 # ns

        beacon = lib.beacon_from(tx, antenna, f_beacon, antenna.t, t0=t0, c_light=np.inf, radiate_rsq=beacon_radiate_rsq)

        traces = np.array([antenna.Ex, antenna.Ey, antenna.Ez, beacon])

        # add to relevant polarisation
        # and apply block filter
        dt = antenna.t[1] - antenna.t[0]
        for j, amp in enumerate(beacon_amplitudes):
            traces[j] = block_filter(traces[j] + amp*beacon, dt, low_bp, high_bp)

        append_antenna_hdf5( antennas_fname, antenna, traces, name='traces', prepend_time=True, attrs_dict=dict(t0=t0))

        # Save E field in E_AxB
        E = [np.dot(ev.uAxB,[ex,ey,ez]) for ex,ey,ez in zip(traces[0], traces[1], traces[2])]

        append_antenna_hdf5( antennas_fname, antenna, [E], name='E_AxB', prepend_time=True)

    print("Antenna HDF5 file written as " + str(antennas_fname))