def acceptance_sim(radius_km=10.,
num_particles=10000,
zenith_angle_deg=None,
log10_energy=17.,
SNR_thresh=5.,
N_trig=16,
verbose=False):
'''
SETUP
'''
geom = Geometry(radius_km, num_particles, zenith_angle_deg)
XMC = Xmax_calc()
# I want to provide the energy, cosmic ray ground position and direction, and get the Xmax position
XMC.get_Xmax_position(log10_energy, geom)
Xmax_altitude = np.sqrt(XMC.x_max**2 + XMC.y_max**2 + XMC.z_max**2
) - XMC.Earth_radius - XMC.detector_altitude_km
det_arr = Detector_Array(mode='Ryan')
rad_em = Radio_Emission(plots=False)
det = Detector()
# loop through simulated events:
trigger = 0
trig_evn = []
thz_array = []
flat_residual = [] # a proxy for Ryan's 1 - % power in Gaussian.
for evn in range(0, num_particles):
if evn % 500 == 0:
if verbose:
print '%d of %d' % (evn, num_particles)
det_arr.get_distances_and_view_angles(XMC, geom, event=evn)
# first cut by minimum view angle here.
if np.min(det_arr.th_view * 180. / pi) > 10.: continue
th_z = np.arccos(geom.k_z[evn]) * 180. / pi
E_field, dist = rad_em.radio_beam_model2(th_z, det_arr.th_view,
1.2) # 1.2 is the altitude
E_field *= 10**(log10_energy - 17.)
x_pol, y_pol, z_pol = rad_em.get_pol(XMC.x_max[evn], XMC.y_max[evn],
XMC.z_max[evn] - XMC.Earth_radius,
geom.x_pos[evn], geom.y_pos[evn],
geom.z_pos[evn])
max_val = np.max(np.array(E_field) * 1.e6)
# then cut by maximum voltage here
V_x = det.Efield_2_Voltage(np.array(E_field * x_pol), th_z)
V_y = det.Efield_2_Voltage(np.array(E_field * y_pol), th_z)
V_z = det.Efield_2_Voltage(np.array(E_field * z_pol), th_z)
V_mag = np.sqrt(V_x**2 + V_y**2 + V_z**2)
max_val_V = np.max(V_mag) * 1.e6
#SNR_x = np.abs(V_x + np.random.normal(0., det.V_rms, len(V_x)))/det.V_rms
#SNR_y = np.abs(V_y + np.random.normal(0., det.V_rms, len(V_x)))/det.V_rms
#SNR_z = np.abs(V_z + np.random.normal(0., det.V_rms, len(V_x)))/det.V_rms
SNR_x = np.abs(V_x) / det.V_rms
SNR_y = np.abs(V_y) / det.V_rms
SNR_z = np.abs(V_z) / det.V_rms
cut_x = SNR_x > SNR_thresh
cut_y = SNR_y > SNR_thresh
#if evn%100 == 0:
# print evn, '%1.1f, %1.2e, %d, %d'%(np.min(det_arr.th_view*180./pi), max_val, np.sum(cut_x), np.sum(cut_y))
# print '\t %1.1f %1.1f'%(np.max(SNR_x), np.max(SNR_y))
#if( np.sum(cut_x)>=N_trig or np.sum(cut_y) >= N_trig):
event_trigger = 0
for FPGA in range(16):
if (np.sum(cut_x[FPGA * 16:(FPGA + 1) * 16]) +
np.sum(cut_y[FPGA * 16:(FPGA + 1) * 16]) >= N_trig):
#if( np.sum(cut_x[FPGA*16:(FPGA+1)*16])>=N_trig or np.sum(cut_y[FPGA*16:(FPGA+1)*16]) >= N_trig ):
event_trigger = 1
if verbose:
print '\t d_core %1.2f' % (np.sqrt(geom.x_pos[evn]**2 +
geom.y_pos[evn]**2))
print '\t th_view %1.2f %1.2f' % (
np.min(det_arr.th_view) * 180. / pi,
np.max(det_arr.th_view) * 180. / pi)
print '\t th_zen %1.2f' % (np.arccos(geom.k_z[evn]) *
180. / pi)
print '\t=================\n'
# Estimate Guassian power residual if the event triggers
if event_trigger == 1:
thz_array.append(th_z)
trig_evn.append(evn)
SNR_cut = 1.
min_x = np.max([np.min(1. + SNR_x**2), SNR_cut])
min_y = np.max([np.min((1. + SNR_y**2)), SNR_cut])
#print 'min_x, min_y', min_x, min_y, float(len(SNR_x[SNR_x**2>SNR_cut])), float(len(SNR_y[SNR_y**2>SNR_cut]))
res_x = 0.
res_y = 0.
if len(SNR_x[SNR_x**2 > SNR_cut]) > N_trig:
P_tot_x = np.sum((1. + SNR_x[SNR_x**2 > SNR_cut])**2)
P_min_x = min_x * float(len(SNR_x[SNR_x**2 > SNR_cut]))
#res_x = np.sum(((1.+SNR_x) - np.mean((1.+SNR_x)))**2)/np.sum((1.+SNR_x)**2)
res_x = np.sum(((1. + SNR_x**2) - np.mean(
(1. + SNR_x**2)))**2) / np.sum((1. + SNR_x**2)**2)
#res_x = P_min_x / P_tot_x
#res_x = np.sum(SNR_x[SNR_x**2>SNR_cut]**2 - min_x)/min_x/float(len(SNR_x[SNR_x**2>SNR_cut]))
if len(SNR_y[SNR_y**2 > SNR_cut]) > N_trig:
P_tot_y = np.sum((1. + SNR_y[SNR_y**2 > SNR_cut])**2)
P_min_y = min_y * float(len(SNR_y[SNR_y**2 > SNR_cut]))
#res_y = np.sum(((1.+SNR_y) - np.mean((1.+SNR_y)))**2)/np.sum((1.+SNR_y)**2)
res_y = np.sum(((1. + SNR_y**2) - np.mean(
(1. + SNR_y**2)))**2) / np.sum((1. + SNR_y**2)**2)
#res_y = P_min_y / P_tot_y
#res_y = np.sum(SNR_y[SNR_y**2>SNR_cut]**2 - min_y)/min_y/float(len(SNR_y[SNR_y**2>SNR_cut]))
flat_residual.append([res_x, res_y])
trigger += event_trigger
# will want to save events
#print '\t %1.2e %1.2e %1.2e'%(x_pol, y_pol, z_pol)
# then cute by maximum V_mag
#plot([np.min(det_arr.th_view)*180./pi], [max_val], 'k.')
#semilogy([np.min(det_arr.th_view)*180./pi], [max([max(SNR_x), max(SNR_y), max(SNR_z)])], 'k.')
#show()
#print 'trigger', trigger
return float(trigger) / float(num_particles), np.array(
thz_array), np.array(flat_residual)
#print 10**(log10_energy-17.)
#print 'det.V_rms', det.V_rms
'''
figure(1)
for evn in range(0, args.num_particles):
if evn%500 == 0: print evn
det_arr.get_distances_and_view_angles(XMC, geom, event=evn)
# first cut by minimum view angle here.
if np.min(det_arr.th_view*180./pi)> 10.: continue
th_z = np.arccos(geom.k_z[evn])*180./pi
E_field,dist = rad_em.radio_beam_model2(th_z, det_arr.th_view, 1.2) # 1.2 is the altitude
E_field *= 10**(args.log10_energy-17.)
x_pol, y_pol, z_pol = rad_em.get_pol(XMC.x_max[evn], XMC.y_max[evn], XMC.z_max[evn], geom.x_pos[evn], geom.y_pos[evn], geom.z_pos[evn])
max_val = vmax=np.max(np.array(E_field)*1.e6)
# then cut by maximum voltage here
V_x = det.Efield_2_Voltage(np.array(E_field*x_pol), th_z)
V_y = det.Efield_2_Voltage(np.array(E_field*y_pol), th_z)
V_z = det.Efield_2_Voltage(np.array(E_field*z_pol), th_z)
V_mag = np.sqrt(V_x**2 + V_y**2 + V_z**2)
max_val_V = np.max(V_mag)*1.e6
SNR_x = np.abs(V_x)/det.V_rms
SNR_y = np.abs(V_y)/det.V_rms
SNR_z = np.abs(V_z)/det.V_rms
cut_x = SNR_x>5.
cut_y = SNR_y>5.
#if evn%100 == 0:
def acceptance_sim(radius_km = 10.,
num_particles = 10000,
zenith_angle_deg = None,
log10_energy=17.,
SNR_thresh = 5.,
N_trig = 1,
trig_pol = 'hpol',
detector_mode = 'prototype_2019',
detector_altitude_km = 3.87553,
verbose = False):
'''
SETUP
'''
geom = Geometry(radius_km, num_particles, detector_altitude_km, zenith_angle_deg)
XMC = Xmax_calc()
# I want to provide the energy, cosmic ray ground position and direction, and get the Xmax position
XMC.get_Xmax_position(log10_energy, geom)
Xmax_altitude = np.sqrt(XMC.x_max**2 + XMC.y_max**2 + XMC.z_max**2) - XMC.Earth_radius - XMC.detector_altitude_km
det_arr = Detector_Array(mode=detector_mode)
rad_em = Radio_Emission(plots=False)
if detector_mode == 'prototype_2019':
antenna_type = 'dipole_2019'
elif detector_mode == 'prototype_2018':
antenna_type = 'lwa_2018'
else:
raise ValueError("Valid detector types are 'prototype_2019' and 'prototype_2018'. You requested '%s'"%detector_type)
det = Detector(antenna_type=antenna_type)
# loop through simulated events:
trigger = 0
trig_evn = []
thz_array = []
xmax_altitude_array = []
view_angle_array = []
for evn in range(0, num_particles):
if evn%500 == 0:
if verbose:
print(('%d of %d'%(evn, num_particles)))
det_arr.get_distances_and_view_angles(XMC, geom, event=evn)
# first cut by minimum view angle here.
if np.min(det_arr.th_view*180./pi)> 10.: continue
ph_xy = geom.phi_CR[evn]*180./pi
th_z = np.arccos(geom.k_z[evn])*180./pi
E_field,dist = rad_em.radio_beam_model2(th_z, det_arr.th_view, XMC.detector_altitude_km)
E_field *= 10**(log10_energy-17.)
x_pol, y_pol, z_pol = rad_em.get_pol(XMC.x_max[evn], XMC.y_max[evn], XMC.z_max[evn]-XMC.Earth_radius, geom.x_pos[evn], geom.y_pos[evn], geom.z_pos[evn])
max_val = np.max(np.array(E_field)*1.e6)
# then cut by maximum voltage here
V_x = det.Efield_2_Voltage(np.array(E_field*x_pol), th_z, ph_xy)
V_y = det.Efield_2_Voltage(np.array(E_field*y_pol), th_z, ph_xy)
V_z = det.Efield_2_Voltage(np.array(E_field*z_pol), th_z, ph_xy)
V_mag = np.sqrt(V_x**2 + V_y**2 + V_z**2)
max_val_V = np.max(V_mag)*1.e6
#SNR_x = np.abs(V_x + np.random.normal(0., det.V_rms, len(V_x)))/det.V_rms
#SNR_y = np.abs(V_y + np.random.normal(0., det.V_rms, len(V_x)))/det.V_rms
#SNR_z = np.abs(V_z + np.random.normal(0., det.V_rms, len(V_x)))/det.V_rms
#require that xmax is above the detector
cut_xmax = Xmax_altitude[evn] > detector_altitude_km
#require that the azimuthal direction is within 120 deg in azimuth
cut_phi = np.logical_or( ph_xy < 60., ph_xy > 300.)
SNR_x = np.abs(V_x)/det.V_rms
SNR_y = np.abs(V_y)/det.V_rms
SNR_z = np.abs(V_z)/det.V_rms
cut_x = SNR_x>SNR_thresh
cut_y = SNR_y>SNR_thresh
cut_z = SNR_z>SNR_thresh
if( trig_pol == 'hpol'):
cut_trig_pol = np.logical_or(cut_x, cut_y)
elif( trig_pol == 'vpol'):
cut_trig_pol = cut_z
else:
print("Warning: trigger must be 'hpol' or 'vpol'. Nothing will trigger")
cut_trig_pol = np.zeros(len(cut_x))
cut_trig = np.sum(cut_trig_pol) >= N_trig
cut_event = np.logical_and(cut_xmax, cut_trig)
cut_event = np.logical_and(cut_event, cut_phi)
event_trigger = 0
if cut_event:
event_trigger = 1
thz_array.append(th_z)
trig_evn.append(evn)
xmax_altitude_array.append(Xmax_altitude[evn])
view_angle_array.append(det_arr.th_view*180./np.pi)
if verbose:
print(('\t d_core %1.2f'%(np.sqrt(geom.x_pos[evn]**2 + geom.y_pos[evn]**2))))
print(('\t th_view %1.2f %1.2f'%(np.min(det_arr.th_view)*180./pi, np.max(det_arr.th_view)*180./pi)))
print(('\t th_zen %1.2f'%(np.arccos(geom.k_z[evn])*180./pi)))
print('\t=================\n')
trigger += event_trigger
# will want to save events
#print '\t %1.2e %1.2e %1.2e'%(x_pol, y_pol, z_pol)
# then cute by maximum V_mag
#plot([np.min(det_arr.th_view)*180./pi], [max_val], 'k.')
#semilogy([np.min(det_arr.th_view)*180./pi], [max([max(SNR_x), max(SNR_y), max(SNR_z)])], 'k.')
#show()
#print 'trigger', trigger
return float(trigger)/float(num_particles), np.array(thz_array), np.array(xmax_altitude_array), np.array(view_angle_array)
#print 10**(log10_energy-17.)
#print 'det.V_rms', det.V_rms
'''
figure(figsize=(4,4))
plot(geom.x_pos, geom.y_pos, '.', alpha=0.1)
xlabel('x, km')
ylabel('y, km')
figure()
hist(geom.x_pos)
figure()
hist(geom.th_CR*180./pi, bins=np.arange(0.,91., 5.))
xticks(np.arange(0.,91., 10.))
xlabel('CR Zenith Angle, deg')
show()
'''
