2022-09-26 17:18:07 +02:00
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#!/usr/bin/env python3
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2022-11-14 20:49:35 +01:00
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# vim: fdm=indent ts=4
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"""
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Add a beacon measurement on top of the
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simulated airshower.
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"""
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2022-09-26 17:18:07 +02:00
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import numpy as np
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import json
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import h5py
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import os.path as path
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from copy import deepcopy
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2022-11-22 09:40:58 +01:00
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from earsim import REvent, Antenna, block_filter
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import lib
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tx_fname = 'tx.json'
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antennas_fname = 'antennas.hdf5'
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def write_tx_file(fname, tx, f_beacon):
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with open(fname, 'w') as fp:
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return json.dump(
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dict(
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f_beacon=f_beacon,
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tx=dict(
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x=tx.x,
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y=tx.y,
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z=tx.z,
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name=tx.name
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)
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),
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fp
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)
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def read_tx_file(fname):
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with open(fname, 'r') as fp:
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data = json.load(fp)
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f_beacon = data['f_beacon']
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tx = Antenna(**data['tx'])
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return tx, f_beacon
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2022-11-22 11:06:15 +01:00
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def read_beacon_hdf5(fname, **h5ant_kwargs):
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with h5py.File(fname, 'r') as h5:
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tx = Antenna_from_h5ant(h5['tx'], traces_key=None)
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f_beacon = tx.attrs['f_beacon']
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antennas = []
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for k, h5ant in h5['antennas'].items():
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ant = Antenna_from_h5ant(h5ant, **h5ant_kwargs)
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antennas.append(ant)
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return f_beacon, tx, antennas
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def Antenna_from_h5ant(h5ant, traces_key='traces', raise_exception=True, read_AxB=True, read_beacon_info=True):
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mydict = { k:h5ant.attrs.get(k) for k in ['x', 'y', 'z', 'name'] }
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ant = Antenna(**mydict)
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if h5ant.attrs:
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ant.attrs = {**h5ant.attrs}
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# Traces
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if traces_key is None:
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pass
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elif traces_key not in h5ant:
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if raise_exception:
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raise ValueError("Traces_key not in file")
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else:
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ant.t = deepcopy(h5ant[traces_key][0])
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ant.Ex = deepcopy(h5ant[traces_key][1])
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ant.Ey = deepcopy(h5ant[traces_key][2])
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ant.Ez = deepcopy(h5ant[traces_key][3])
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if len(h5ant[traces_key]) > 4:
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ant.beacon = deepcopy(h5ant[traces_key][4])
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# E_AxB
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if read_AxB and 'E_AxB' in h5ant:
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ant.t_AxB = deepcopy(h5ant['E_AxB'][0])
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ant.E_AxB = deepcopy(h5ant['E_AxB'][1])
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# Beacons
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if read_beacon_info and 'beacon_info' in h5ant:
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h5beacon = h5ant['beacon_info']
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beacon_info = {}
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for name in h5beacon.keys():
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beacon_info[name] = dict(h5beacon[name].attrs)
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ant.beacon_info = beacon_info
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return ant
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def init_antenna_hdf5(fname, tx = None, f_beacon = None):
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with h5py.File(fname, 'w') as fp:
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if tx is not None or f_beacon is not None:
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tx_group = fp.create_group('tx')
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tx_attrs = tx_group.attrs
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if f_beacon is not None:
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tx_attrs['f_beacon'] = f_beacon
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if tx is not None:
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tx_attrs['x'] = tx.x
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tx_attrs['y'] = tx.y
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tx_attrs['z'] = tx.z
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tx_attrs['name'] = tx.name
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return fname
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def append_antenna_hdf5(fname, antenna, columns = [], name='traces', prepend_time=True, overwrite=True, attrs_dict={}):
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if not overwrite:
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raise NotImplementedError
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with h5py.File(fname, 'a') as fp:
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if 'antennas' in fp.keys():
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if not overwrite:
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raise NotImplementedError
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group = fp['antennas']
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else:
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group = fp.create_group('antennas')
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if antenna.name in group:
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if not overwrite:
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raise NotImplementedError
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h5ant = group[antenna.name]
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else:
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h5ant = group.create_group(antenna.name)
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h5ant_attrs = h5ant.attrs
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h5ant_attrs['x'] = antenna.x
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h5ant_attrs['y'] = antenna.y
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h5ant_attrs['z'] = antenna.z
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h5ant_attrs['name'] = antenna.name
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for k,v in attrs_dict.items():
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h5ant_attrs[k] = v
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if name in h5ant:
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if not overwrite:
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raise NotImplementedError
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del h5ant[name]
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dset = h5ant.create_dataset(name, (len(columns) + 1*prepend_time, len(columns[0])), dtype='f')
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if prepend_time:
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dset[0] = antenna.t
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for i, col in enumerate(columns, 1*prepend_time):
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dset[i] = col
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2022-11-23 16:53:33 +01:00
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def read_baseline_time_diffs_hdf5(fname):
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"""
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Read Baseline Time Diff information from HDF5 storage.
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"""
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with h5py.File(fname, 'r') as fp:
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group_name = 'baseline_time_diffs'
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base_dset_name = 'baselines'
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dset_name = 'time_diffs'
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group = fp[group_name]
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names = group[base_dset_name][:]
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dset = group[dset_name]
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f_beacon = dset[:,0]
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true_phase_diffs = dset[:,1]
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k_periods = dset[:,2]
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return names, f_beacon, true_phase_diffs, k_periods
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def write_baseline_time_diffs_hdf5(fname, baselines, true_phase_diffs, k_periods, f_beacon, overwrite=True):
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"""
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Write a combination of baselines, phase_diff, k_period and f_beacon to file.
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Note that f_beacon is allowed to broadcast, but the others are not.
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"""
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if not hasattr(baselines[0], '__len__'):
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# this is a single baseline
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N_baselines = 1
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baselines = [baselines]
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true_phase_diffs = [true_phase_diffs]
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k_periods = [k_periods]
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f_beacon = [f_beacon]
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else:
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N_baselines = len(baselines)
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# Expand the f_beacon list
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if not hasattr(f_beacon, '__len__'):
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f_beacon = [f_beacon]*N_baselines
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assert len(baselines) == len(true_phase_diffs) == len(k_periods) == len(f_beacon)
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with h5py.File(fname, 'a') as fp:
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group_name = 'baseline_time_diffs'
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base_dset_name = 'baselines'
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dset_name = 'time_diffs'
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group = fp.require_group(group_name)
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if base_dset_name in group:
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if not overwrite:
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raise NotImplementedError
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del group[base_dset_name]
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if dset_name in group:
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if not overwrite:
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raise NotImplementedError
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del group[dset_name]
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# save baselines list
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basenames = np.array([ [b[0].name, b[1].name] for b in baselines ], dtype='S')
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base_dset = group.create_dataset(base_dset_name, data=basenames)
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data = np.vstack( (f_beacon, true_phase_diffs, k_periods) ).T
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dset = group.create_dataset(dset_name, data=data)
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if __name__ == "__main__":
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from os import path
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remake_tx = True
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fname = "ZH_airshower/mysim.sry"
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tx = Antenna(x=-500,y=0,z=0,name='tx') # m
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if not True: # slowest beacon to be found:
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f_beacon = 10e-3 # GHz
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low_bp = 5e-3 # GHz
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high_bp = 80e-3 # GHz
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else: # original wanted beacon
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f_beacon = 51.53e-3 # GHz
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2022-11-22 15:57:00 +01:00
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# Bandpass for E field blockfilter
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low_bp = 30e-3 # GHz
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high_bp = 80e-3 # GHz
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# Disable block_filter
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if False:
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block_filter = lambda x, dt, low, high: x
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beacon_amplitudes = 1e-6*np.array([1e2, 0, 0]) # mu V/m
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beacon_radiate_rsq = True
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if beacon_radiate_rsq:
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# Move tx out, and magnify beacon_amplitude (at tx)
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tx = Antenna(x=-20e3,y=0,z=0,name='tx') # m
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dist = lib.distance(tx, Antenna(x=0, y=0, z=0))
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ampl = max(1, dist**2)
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beacon_amplitudes *= ampl
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####
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fname_dir = path.dirname(fname)
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tx_fname = path.join(fname_dir, tx_fname)
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antennas_fname = path.join(fname_dir, antennas_fname)
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if not path.isfile(tx_fname) or remake_tx:
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write_tx_file(tx_fname, tx, f_beacon)
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else:
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tx, f_beacon = read_tx_file(tx_fname)
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# read in antennas
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ev = REvent(fname)
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N_antennas = len(ev.antennas)
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# initialize hdf5 file
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init_antenna_hdf5(antennas_fname, tx, f_beacon)
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# make beacon per antenna
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for i, antenna in enumerate(ev.antennas):
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t0 = lib.distance(tx, antenna)/3e8 * 1e9 # ns
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2022-11-18 16:19:44 +01:00
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beacon = lib.beacon_from(tx, antenna, f_beacon, antenna.t, t0=t0, c_light=np.inf, radiate_rsq=beacon_radiate_rsq)
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traces = np.array([antenna.Ex, antenna.Ey, antenna.Ez, beacon])
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# add to relevant polarisation
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# and apply block filter
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dt = antenna.t[1] - antenna.t[0]
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2022-11-22 15:57:00 +01:00
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for j, amp in enumerate(beacon_amplitudes):
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traces[j] = block_filter(traces[j] + amp*beacon, dt, low_bp, high_bp)
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2022-09-28 13:21:41 +02:00
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2022-11-22 14:38:56 +01:00
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append_antenna_hdf5( antennas_fname, antenna, traces, name='traces', prepend_time=True, attrs_dict=dict(t0=t0))
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2022-09-28 13:21:41 +02:00
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2022-11-22 09:40:58 +01:00
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# Save E field in E_AxB
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2022-11-22 14:38:56 +01:00
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E = [np.dot(ev.uAxB,[ex,ey,ez]) for ex,ey,ez in zip(traces[0], traces[1], traces[2])]
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2022-11-22 09:40:58 +01:00
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append_antenna_hdf5( antennas_fname, antenna, [E], name='E_AxB', prepend_time=True)
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2022-09-28 13:21:41 +02:00
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print("Antenna HDF5 file written as " + str(antennas_fname))
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