mirror of
https://gitlab.science.ru.nl/mthesis-edeboone/m-thesis-introduction.git
synced 2024-11-14 02:23:32 +01:00
315 lines
12 KiB
Python
Executable file
315 lines
12 KiB
Python
Executable file
#!/usr/bin/env python3
|
|
# vim: fdm=indent ts=4
|
|
|
|
"""
|
|
Show how the Power changes when incorporating the
|
|
various clock offsets by plotting on a grid.
|
|
"""
|
|
|
|
import matplotlib.pyplot as plt
|
|
from mpl_toolkits.mplot3d import Axes3D # required for projection='3d' on old matplotliblib versions
|
|
import numpy as np
|
|
from os import path
|
|
import joblib
|
|
|
|
from earsim import REvent
|
|
from atmocal import AtmoCal
|
|
import aa_generate_beacon as beacon
|
|
import lib
|
|
from lib import rit
|
|
|
|
|
|
def save_overlapping_traces_figure(test_location, ev, N_plot = 30, wx=200, title_extra=None, fname_distinguish='', fig_dir=None, **fig_kwargs):
|
|
P, t_, a_, a_sum, t_sum = rit.pow_and_time(test_location, ev, dt=1)
|
|
|
|
fig, axs = plt.subplots(**fig_kwargs)
|
|
axs.set_title("Antenna traces" + (("\n" + title_extra) if title_extra is not None else '') )
|
|
axs.set_xlabel("Time [ns]")
|
|
axs.set_ylabel("Amplitude [$\\mu V/m$]")
|
|
if False:
|
|
text_loc = (0.02, 0.95)
|
|
axs.text(*text_loc, '[' + ', '.join(['{:.2e}'.format(x) for x in test_location]) + ']', ha='left', transform=axs.transAxes)
|
|
|
|
a_max = [ np.amax(ant.E_AxB) for ant in ev.antennas ]
|
|
power_sort_idx = np.argsort(a_max)
|
|
|
|
for i, idx in enumerate(reversed(power_sort_idx)):
|
|
if i >= N_plot:
|
|
break
|
|
|
|
alpha = max(0.4, 1/N_plot)
|
|
|
|
axs.plot(t_[idx], a_[idx], color='r', alpha=alpha, lw=2)
|
|
|
|
if fig_dir:
|
|
if fname_distinguish:
|
|
fname_distinguish = "." + fname_distinguish
|
|
|
|
fig.tight_layout()
|
|
|
|
fig.savefig(path.join(fig_dir, path.basename(__file__) + f'{fname_distinguish}.trace_overlap.{case}.pdf'))
|
|
fig.savefig(path.join(fig_dir, path.basename(__file__) + f'{fname_distinguish}.trace_overlap.{case}.png'), transparent=True)
|
|
|
|
# Take center between t_low and t_high
|
|
if True:
|
|
orig_xlims = axs.get_xlim()
|
|
|
|
if not True: # t_high and t_low from strongest signal
|
|
t_low = np.min(t_[power_sort_idx[-1]])
|
|
t_high = np.max(t_[power_sort_idx[-1]])
|
|
else: # take t_high and t_low from plotted signals
|
|
a = [np.min(t_[idx]) for idx in power_sort_idx[-N_plot:]]
|
|
t_low = np.nanmin(a)
|
|
b = [np.max(t_[idx]) for idx in power_sort_idx[-N_plot:]]
|
|
t_high = np.nanmax(b)
|
|
|
|
if False:
|
|
axs.plot(a, [0]*N_plot, 'gx', ms=10)
|
|
axs.plot(b, [0]*N_plot, 'b+', ms=10)
|
|
|
|
center_x = (t_high - t_low)/2 + t_low
|
|
|
|
low_xlim = max(orig_xlims[0], center_x - wx)
|
|
high_xlim = min(orig_xlims[1], center_x + wx)
|
|
|
|
axs.set_xlim(low_xlim, high_xlim)
|
|
fig.savefig(path.join(fig_dir, path.basename(__file__) + f'{fname_distinguish}.trace_overlap.zoomed.{case}.pdf'))
|
|
fig.savefig(path.join(fig_dir, path.basename(__file__) + f'{fname_distinguish}.trace_overlap.zoomed.{case}.png'), transparent=True)
|
|
|
|
return fig
|
|
|
|
if __name__ == "__main__":
|
|
valid_cases = ['no_offset', 'repair_none', 'repair_phases', 'repair_all']
|
|
|
|
import sys
|
|
import os
|
|
import matplotlib
|
|
if os.name == 'posix' and "DISPLAY" not in os.environ:
|
|
matplotlib.use('Agg')
|
|
|
|
atm = AtmoCal()
|
|
|
|
from scriptlib import MyArgumentParser
|
|
parser = MyArgumentParser()
|
|
parser.add_argument('--input-fname', type=str, default=None, help='Path to mysim.sry, either directory or path. If empty it takes DATA_DIR and appends mysim.sry. (Default: %(default)s)')
|
|
|
|
group = parser.add_argument_group('figures')
|
|
for case in valid_cases:
|
|
group.add_argument('--'+case.replace('_','-'), dest='figures', action='append_const', const=case)
|
|
|
|
args = parser.parse_args()
|
|
|
|
if not args.input_fname:
|
|
args.input_fname = args.data_dir
|
|
|
|
if path.isdir(args.input_fname):
|
|
args.input_fname = path.join(args.input_fname, "mysim.sry")
|
|
|
|
wanted_cases = args.figures
|
|
|
|
if not wanted_cases or 'all' in wanted_cases:
|
|
wanted_cases = valid_cases
|
|
|
|
figsize = (12,8)
|
|
|
|
fig_dir = args.fig_dir
|
|
show_plots = args.show_plots
|
|
|
|
remove_beacon_from_traces = True
|
|
apply_signal_window_from_max = True
|
|
|
|
####
|
|
fname_dir = args.data_dir
|
|
antennas_fname = path.join(fname_dir, beacon.antennas_fname)
|
|
pickle_fname = path.join(fname_dir, 'res.pkl')
|
|
tx_fname = path.join(fname_dir, beacon.tx_fname)
|
|
|
|
# create fig_dir
|
|
if fig_dir:
|
|
os.makedirs(fig_dir, exist_ok=True)
|
|
|
|
# Read in antennas from file
|
|
_, tx, antennas = beacon.read_beacon_hdf5(antennas_fname)
|
|
_, __, txdata = beacon.read_tx_file(tx_fname)
|
|
# Read original REvent
|
|
ev = REvent(args.input_fname)
|
|
bak_ants = ev.antennas
|
|
# .. patch in our antennas
|
|
ev.antennas = antennas
|
|
|
|
##
|
|
## Setup grid
|
|
##
|
|
X = 400
|
|
zgr = 0 #not exact
|
|
dXref = atm.distance_to_slant_depth(np.deg2rad(ev.zenith),750,zgr+ev.core[2])
|
|
scale2d = dXref*np.tan(np.deg2rad(2.))
|
|
scale4d = dXref*np.tan(np.deg2rad(4.))
|
|
scale02d = dXref*np.tan(np.deg2rad(0.2))
|
|
|
|
Nx, Ny = 21, 21
|
|
scales = {
|
|
'scale2d': scale2d,
|
|
'scale4d': scale4d,
|
|
'scale02d': scale02d,
|
|
}
|
|
|
|
N_plot = 30
|
|
trace_zoom_wx = 100
|
|
|
|
plot_titling = {
|
|
'no_offset': "no clock offset",
|
|
'repair_none': "unrepaired clock offset",
|
|
'repair_phases': "phase resolved clock offsets repaired",
|
|
'repair_all': "final measured clock offsets repaired"
|
|
}
|
|
|
|
# For now only implement using one freq_name
|
|
freq_names = ev.antennas[0].beacon_info.keys()
|
|
if len(freq_names) > 1:
|
|
raise NotImplementedError
|
|
|
|
freq_name = next(iter(freq_names))
|
|
|
|
# Pre remove the beacon from the traces
|
|
#
|
|
# We need to remove it here, so we do not shoot ourselves in
|
|
# the foot when changing to the various clock offsets.
|
|
#
|
|
# Note that the bandpass filter is applied only after E_AxB is
|
|
# reconstructed so we have to manipulate the original traces.
|
|
if remove_beacon_from_traces:
|
|
tx_amps = txdata['amplitudes']
|
|
tx_amps_sum = np.sum(tx_amps)
|
|
|
|
for i, ant in enumerate(ev.antennas):
|
|
beacon_phase = ant.beacon_info[freq_name]['beacon_phase']
|
|
f = ant.beacon_info[freq_name]['freq']
|
|
ampl_AxB = ant.beacon_info[freq_name]['amplitude']
|
|
calc_beacon = lib.sine_beacon(f, ev.antennas[i].t, amplitude=ampl_AxB, phase=beacon_phase)
|
|
|
|
# Split up contribution to the various polarisations
|
|
for j, amp in enumerate(tx_amps):
|
|
if j == 0:
|
|
ev.antennas[i].Ex -= amp*(1/tx_amps_sum)*calc_beacon
|
|
elif j == 1:
|
|
ev.antennas[i].Ey -= amp*(1/tx_amps_sum)*calc_beacon
|
|
elif j == 2:
|
|
ev.antennas[i].Ez -= amp*(1/tx_amps_sum)*calc_beacon
|
|
|
|
# Subtract the beacon from E_AxB
|
|
ev.antennas[i].E_AxB -= calc_beacon
|
|
|
|
# Slice the traces to a small part around the peak
|
|
if apply_signal_window_from_max:
|
|
N_pre, N_post = 250, 250 # TODO: make this configurable
|
|
|
|
for i, ant in enumerate(ev.antennas):
|
|
# Get max idx from all the traces
|
|
# and select the strongest
|
|
max_idx = []
|
|
maxs = []
|
|
|
|
for trace in [ant.Ex, ant.Ey, ant.Ez]:
|
|
idx = np.argmax(np.abs(trace))
|
|
max_idx.append(idx)
|
|
maxs.append( np.abs(trace[idx]) )
|
|
|
|
idx = np.argmax(maxs)
|
|
max_idx = max_idx[idx]
|
|
|
|
|
|
low_idx = max(0, max_idx-N_pre)
|
|
high_idx = min(len(ant.t), max_idx+N_post)
|
|
|
|
ev.antennas[i].t = ant.t[low_idx:high_idx]
|
|
ev.antennas[i].t_AxB = ant.t_AxB[low_idx:high_idx]
|
|
|
|
ev.antennas[i].Ex = ant.Ex[low_idx:high_idx]
|
|
ev.antennas[i].Ey = ant.Ey[low_idx:high_idx]
|
|
ev.antennas[i].Ez = ant.Ez[low_idx:high_idx]
|
|
ev.antennas[i].E_AxB = ant.E_AxB[low_idx:high_idx]
|
|
|
|
## Apply polarisation and bandpass filter
|
|
rit.set_pol_and_bp(ev)
|
|
|
|
# backup antenna times
|
|
backup_antenna_t = [ ant.t for ant in ev.antennas ]
|
|
backup_antenna_t_AxB = [ ant.t_AxB for ant in ev.antennas ]
|
|
|
|
fig = save_overlapping_traces_figure([0,0,0], ev, N_plot=1, wx=trace_zoom_wx, title_extra = plot_titling[case], fname_distinguish=f'single', fig_dir=fig_dir, figsize=figsize)
|
|
plt.close(fig)
|
|
|
|
with joblib.parallel_backend("loky"):
|
|
for case in wanted_cases:
|
|
print(f"Starting {case} figure")
|
|
# Repair clock offsets with the measured offsets
|
|
transl_modes = {'no_offset':'orig', 'repair_phases':'phases', 'repair_all':'all'}
|
|
|
|
if case in transl_modes:
|
|
transl_mode = transl_modes[case]
|
|
measured_offsets = beacon.read_antenna_clock_repair_offsets(antennas, mode=transl_mode, freq_name=freq_name)
|
|
else:
|
|
measured_offsets = [0]*len(ev.antennas)
|
|
|
|
for i, ant in enumerate(ev.antennas):
|
|
total_clock_offset = measured_offsets[i]
|
|
|
|
ev.antennas[i].t = backup_antenna_t[i] + total_clock_offset
|
|
ev.antennas[i].t_AxB = backup_antenna_t_AxB[i] + total_clock_offset
|
|
|
|
if i == 0:
|
|
# Specifically compare the times
|
|
print("backup time, time with measured_offset, true clock offset, measured clock offset")
|
|
print(bak_ants[i].t[0], ev.antennas[i].t[0], ev.antennas[i].attrs['clock_offset'], measured_offsets[i])
|
|
|
|
#
|
|
# Plot overlapping traces at 0,0,0
|
|
#
|
|
fig = save_overlapping_traces_figure([0,0,0], ev, N_plot=N_plot, wx=trace_zoom_wx, title_extra = plot_titling[case], fname_distinguish=f'{case}.0', fig_dir=fig_dir, figsize=figsize)
|
|
plt.close(fig)
|
|
|
|
# Measure power on grid
|
|
# and plot overlapping traces at position with highest power
|
|
for scalename, scale in scales.items():
|
|
wx, wy = scale, scale
|
|
print(f"Starting grid measurement for figure {case} with {scalename}")
|
|
xx, yy, p, maxp_loc = rit.shower_plane_slice(ev, X=X, Nx=Nx, Ny=Nx, wx=wx, wy=wy, zgr=zgr)
|
|
|
|
fig, axs = rit.slice_figure(ev, X, xx, yy, p, mode='sp', scatter_kwargs=dict(
|
|
vmax=1e5,
|
|
vmin=0,
|
|
s=150,
|
|
cmap='inferno',
|
|
# edgecolor='black',
|
|
))
|
|
|
|
suptitle = fig._suptitle.get_text()
|
|
fig.suptitle("")
|
|
axs.set_title(suptitle +"\n" +plot_titling[case])
|
|
#axs.set_aspect('equal', 'datalim')
|
|
|
|
if fig_dir:
|
|
fig.tight_layout()
|
|
fig.savefig(path.join(fig_dir, path.basename(__file__) + f'.X{X}.{case}.{scalename}.pdf'))
|
|
plt.close(fig)
|
|
|
|
#
|
|
# Plot overlapping traces at highest power of each scale
|
|
#
|
|
fig = save_overlapping_traces_figure(maxp_loc, ev, N_plot=N_plot, wx=trace_zoom_wx, title_extra = plot_titling[case] + ', ' + scalename + ' best', fname_distinguish=scalename+'.best', fig_dir=fig_dir, figsize=figsize)
|
|
|
|
#
|
|
# and plot overlapping traces at two other locations
|
|
#
|
|
if True:
|
|
for dist in [ 0.5, 5, 10, 50, 100]:
|
|
# only add distance horizontally
|
|
location = maxp_loc + np.sqrt(dist*1e3)*np.array([1,1,0])
|
|
|
|
fig = save_overlapping_traces_figure(location, ev, N_plot=N_plot, wx=wx, title_extra = plot_titling[case] + ', ' + scalename + f', x + {dist}km', fname_distinguish=f'{scalename}.{dist}', fig_dir=fig_dir, figsize=figsize)
|
|
plt.close(fig)
|
|
|
|
|
|
if args.show_plots:
|
|
plt.show()
|