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ZH: elaborate power on grid plots

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It now produces trace view aswell as power on grid for different positions while looking for the best location
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Eric Teunis de Boone 2023-03-27 16:59:28 +02:00
parent 878c476a4a
commit 7a7647f231
1 changed files with 96 additions and 58 deletions
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154
simulations/airshower_beacon_simulation/dc_grid_power_time_fixes.py
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@ -19,6 +19,65 @@ import lib
from lib import rit 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__": if __name__ == "__main__":
valid_cases = ['no_offset', 'repair_none', 'repair_phases', 'repair_all'] valid_cases = ['no_offset', 'repair_none', 'repair_phases', 'repair_all']
@ -95,6 +154,9 @@ if __name__ == "__main__":
'scale02d': scale02d, 'scale02d': scale02d,
} }
N_plot = 30
trace_zoom_wx = 100
plot_titling = { plot_titling = {
'no_offset': "no clock offset", 'no_offset': "no clock offset",
'repair_none': "unrepaired clock offset", 'repair_none': "unrepaired clock offset",
@ -175,6 +237,9 @@ if __name__ == "__main__":
backup_antenna_t = [ ant.t for ant in ev.antennas ] backup_antenna_t = [ ant.t for ant in ev.antennas ]
backup_antenna_t_AxB = [ ant.t_AxB 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"): with joblib.parallel_backend("loky"):
for case in wanted_cases: for case in wanted_cases:
print(f"Starting {case} figure") print(f"Starting {case} figure")
@ -195,73 +260,29 @@ if __name__ == "__main__":
if i == 0: if i == 0:
# Specifically compare the times # Specifically compare the times
print(bak_ants[i].t[0], ev.antennas[i].t[0], ev.antennas[i].t[0], ev.antennas[i].attrs['clock_offset'], measured_offsets[i]) 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 # Plot overlapping traces at 0,0,0
# #
if True: 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)
P, t_, a_, a_sum, t_sum = rit.pow_and_time([0,0,0], ev, dt=1) plt.close(fig)
fig, axs = plt.subplots(figsize=figsize)
axs.set_title("Antenna traces" + "\n" + plot_titling[case])
axs.set_xlabel("Time [ns]")
axs.set_ylabel("Amplitude [$\\mu V/m$]")
a_max = [ np.amax(ant.E_AxB) for ant in ev.antennas ]
power_sort_idx = np.argsort(a_max)
N_plot = 30
for i, idx in enumerate(reversed(power_sort_idx)):
if i > N_plot:
break
alpha = max(0.4, 1/len(a_))
axs.plot(t_[idx], a_[idx], color='r', alpha=alpha, lw=2)
if fig_dir:
fig.tight_layout()
fig.savefig(path.join(fig_dir, path.basename(__file__) + f'.trace_overlap.{case}.pdf'))
fig.savefig(path.join(fig_dir, path.basename(__file__) + f'.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:]]
axs.plot(a, [0]*N_plot, 'gx', ms=10)
t_low = np.nanmin(a)
b = [np.max(t_[idx]) for idx in power_sort_idx[-N_plot:]]
axs.plot(b, [0]*N_plot, 'b+', ms=10)
t_high = np.nanmax(b)
center_x = (t_high - t_low)/2 + t_low
wx = 200
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'.trace_overlap.zoomed.{case}.pdf'))
fig.savefig(path.join(fig_dir, path.basename(__file__) + f'.trace_overlap.zoomed.{case}.png'), transparent=True)
if True:
continue
# Measure power on grid # Measure power on grid
# and plot overlapping traces at position with highest power
for scalename, scale in scales.items(): for scalename, scale in scales.items():
wx, wy = scale, scale wx, wy = scale, scale
print(f"Starting grid measurement for figure {case} with {scalename}") print(f"Starting grid measurement for figure {case} with {scalename}")
xx, yy, p, maxp = rit.shower_plane_slice(ev, X=X, Nx=Nx, Ny=Nx, wx=wx, wy=wy) 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') 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() suptitle = fig._suptitle.get_text()
fig.suptitle("") fig.suptitle("")
@ -271,7 +292,24 @@ if __name__ == "__main__":
if fig_dir: if fig_dir:
fig.tight_layout() fig.tight_layout()
fig.savefig(path.join(fig_dir, path.basename(__file__) + f'.X{X}.{case}.{scalename}.pdf')) 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: if args.show_plots:
plt.show() plt.show()