rr = np.random.triangular(rmin, rmax, rmax, n_events)
phiphi = np.random.uniform(0, 2 * np.pi, n_events)
xx = rr * np.cos(phiphi)
yy = rr * np.sin(phiphi)
zz = np.random.uniform(zmin, zmax, n_events)
points = np.array([xx, yy, zz]).T
x_receiver = np.array([0., 0., -5.])
results_C0s_cpp = np.zeros((n_events, 2))
n_freqs = 256//2 + 1
# n_freqs = 5
results_A_cpp = np.zeros((n_events, 2, n_freqs))
t_start = time.time()
ff = np.linspace(0, 500*units.MHz, n_freqs)
# tt = 0
for iX, x in enumerate(points):
# t_start2 = time.time()
r = ray.ray_tracing(ice)
r.set_start_and_end_point(x, x_receiver)
# tt += (time.time() - t_start2)
r.find_solutions()
if(r.has_solution()):
for iS in range(r.get_number_of_solutions()):
results_C0s_cpp[iX, iS] = r.get_results()[iS]['C0']
results_C0s_cpp_ref = io_utilities.read_pickle("reference_C0.pkl", encoding='latin1')
testing.assert_allclose(results_C0s_cpp, results_C0s_cpp_ref)
print('T05unit_test_c0_SP passed without issues')
rr = np.random.triangular(rmin, rmax, rmax, n_events)
phiphi = np.random.uniform(0, 2 * np.pi, n_events)
xx = rr * np.cos(phiphi)
yy = rr * np.sin(phiphi)
zz = np.random.uniform(zmin, zmax, n_events)
points = np.array([xx, yy, zz]).T
x_receiver = np.array([0., 0., -5.])
results_C0s_cpp = np.zeros((n_events, 10))
n_freqs = 256 // 2 + 1
# n_freqs = 5
results_A_cpp = np.zeros((n_events, 2, n_freqs))
t_start = time.time()
ff = np.linspace(0, 500 * units.MHz, n_freqs)
# tt = 0
for iX, x in enumerate(points):
# t_start2 = time.time()
r = ray.ray_tracing(x, x_receiver, ice, n_reflections=2)
# tt += (time.time() - t_start2)
r.find_solutions()
if (r.has_solution()):
for iS in range(r.get_number_of_solutions()):
results_C0s_cpp[iX, iS] = r.get_results()[iS]['C0']
results_C0s_cpp_ref = io_utilities.read_pickle("reference_C0_MooresBay.pkl",
encoding='latin1')
testing.assert_allclose(results_C0s_cpp, results_C0s_cpp_ref, rtol=1.e-6)
print('T06unit_test_C0_mooresbay passed without issues')
continue
vertex = np.array([fin['xx'][iE], fin['yy'][iE], fin['zz'][iE]])
# print(fin.keys())
# l1 = fin['launch_vectors'][iE][3] / units.deg
l2 = fin['station_101']['launch_vectors'][iE][j * 4 + 3]
# r1 = ray.ray_tracing(vertex, x1, med, log_level=logging.DEBUG)
# # r1.find_solutions()
# r1.set_solution(fin['ray_tracing_C0'][iE][3], fin['ray_tracing_C1'][iE][3], fin['ray_tracing_solution_type'][iE][3])
# path1 = r1.get_path(0)
zen, az = fin['zeniths'][iE], fin['azimuths'][iE]
v = hp.spherical_to_cartesian(zen, az)
if (plot):
r2 = ray.ray_tracing(vertex, x2, med, log_level=logging.INFO)
r2.set_solution(
fin['station_101']['ray_tracing_C0'][iE][iC],
fin['station_101']['ray_tracing_C1'][iE][iC],
fin['station_101']['ray_tracing_solution_type'][iE][iC])
path2 = r2.get_path(0)
# ax.plot3D(path1.T[0], path1.T[1], path1.T[2], label='path 1')
ax.plot3D(path2.T[0],
path2.T[1],
path2.T[2],
label='path {}'.format(j))
ax.plot3D([vertex[0], vertex[0] + 500 * v[0]],
[vertex[1], vertex[1] + 500 * v[1]],
[vertex[2], vertex[2] + 500 * v[2]],
'--',
label='shower direction')
cmap=plt.get_cmap('Blues'), weights=weights)
cb = plt.colorbar(h[3], ax=ax)
cb.set_label("weighted number of events")
ax.set_aspect('equal')
ax.set_xlabel("r [m]")
ax.set_ylabel("z [m]")
fig.tight_layout()
mask = (zz < -2000 * units.m) & (rr < 5000 * units.m)
for i in np.array(range(len(xx)))[mask]:
# C0 = fin['ray_tracing_C0'][i][0][0]
# C1 = fin['ray_tracing_C1'][i][0][0]
print('weight = {:.2f}'.format(weights[i]))
x1 = np.array([xx[i], yy[i], zz[i]])
x2 = np.array([0, 0, -5])
r = ray.ray_tracing(x1, x2, medium.southpole_simple())
r.find_solutions()
C0 = r.get_results()[0]['C0']
x1 = np.array([-rr[i], zz[i]])
x2 = np.array([0, -5])
r2 = ray.ray_tracing_2D(medium.southpole_simple())
yyy, zzz = r2.get_path(x1, x2, C0)
launch_vector = fin['launch_vectors'][i][0][0]
print(launch_vector)
zenith_nu = fin['zeniths'][i]
print(zenith_nu / units.deg)
fig, ax = plt.subplots(1, 1)
ax.plot(-rr[i], zz[i], 'o')
ax.plot([-rr[i], -rr[i] + 100 * np.cos(zenith_nu)], [zz[i], zz[i] + 100 * np.sin(zenith_nu)], '-C0')
phiphi = np.random.uniform(0, 2 * np.pi, n_events)
xx = rr * np.cos(phiphi)
yy = rr * np.sin(phiphi)
zz = np.random.uniform(zmin, zmax, n_events)
points = np.array([xx, yy, zz]).T
x_receiver = np.array([0., 0., -5.])
results_C0s_cpp = np.zeros((n_events, 10))
n_freqs = 256 // 2 + 1
# n_freqs = 5
results_A_cpp = np.zeros((n_events, 2, n_freqs))
t_start = time.time()
ff = np.linspace(0, 500 * units.MHz, n_freqs)
# tt = 0
for iX, x in enumerate(points):
# t_start2 = time.time()
r = ray.ray_tracing(ice, n_reflections=2)
r.set_start_and_end_point(x, x_receiver)
# tt += (time.time() - t_start2)
r.find_solutions()
if (r.has_solution()):
for iS in range(r.get_number_of_solutions()):
results_C0s_cpp[iX, iS] = r.get_results()[iS]['C0']
results_C0s_cpp_ref = io_utilities.read_pickle("reference_C0_MooresBay.pkl",
encoding='latin1')
testing.assert_allclose(results_C0s_cpp, results_C0s_cpp_ref, rtol=1.e-6)
print('T06unit_test_C0_mooresbay passed without issues')
points = np.array([xx, yy, zz]).T
x_receiver = np.array([0., 0., -5.])
nsol = 6
results_D = np.zeros((n_events, nsol))
results_D_analytic = np.zeros((n_events, nsol))
results_T = np.zeros((n_events, nsol))
results_T_analytic = np.zeros((n_events, nsol))
d_numeric = 0
d_analytic = 0
t_numeric = 0
t_analytic = 0
for iX, x in enumerate(points):
r = ray.ray_tracing(x, x_receiver, ice, log_level=logging.WARNING, n_reflections=1)
r.find_solutions()
if(r.has_solution()):
for iS in range(r.get_number_of_solutions()):
t_start = time.time()
results_D[iX, iS] = r.get_path_length(iS, analytic=False)
d_numeric += time.time() - t_start
t_start = time.time()
results_D_analytic[iX, iS] = r.get_path_length(iS, analytic=True)
d_analytic += time.time() - t_start
t_start = time.time()
results_T[iX, iS] = r.get_travel_time(iS, analytic=False)
t_numeric += time.time() - t_start
t_start = time.time()
receive_vectors = np.zeros((4, 2, 3)) * np.nan
ray_tracing_C0 = np.zeros((4, 2)) * np.nan
ray_tracing_C1 = np.zeros((4, 2)) * np.nan
ray_tracing_solution_type = np.zeros((4, 2), dtype=np.int) * np.nan
travel_times = np.zeros((4, 2)) * np.nan
travel_distances = np.zeros((4, 2)) * np.nan
ice = medium.southpole_simple()
lss = ['-', '--', ':']
colors = ['b','g','r']
fig, ax = plt.subplots(1, 1)
ax.plot(x1[0], x1[2], 'ko')
for i, x in enumerate([x2, x3, x4, x5]):
print('finding solutions for ', x)
r = ray.ray_tracing(x1,x,ice)
r.find_solutions()
if(r.has_solution()):
for iS in range(r.get_number_of_solutions()):
ray_tracing_C0[i, iS] = r.get_results()[iS]['C0']
ray_tracing_solution_type[i, iS] = r.get_solution_type(iS)
print(" Solution %d, Type %d: "%(iS,ray_tracing_solution_type[i, iS]))
R = r.get_path_length(iS) # calculate path length
T = r.get_travel_time(iS) # calculate travel time
print(" Ray Distance %.3f and Travel Time %.3f"%(R/units.m,T/units.ns))
receive_vector = r.get_receive_vector(iS)
receive_vectors[i, iS] = receive_vector
zenith, azimuth = hp.cartesian_to_spherical(*receive_vector)
print(" Receiving Zenith %.3f and Azimuth %.3f "%(zenith/units.deg, azimuth/units.deg))
#to readout the actual trace, we have to flatten to 2D
yy = rr * np.sin(phiphi)
zz = np.random.uniform(zmin, zmax, n_events)
points = np.array([xx, yy, zz]).T
x_receiver = np.array([0., 0., -5.])
results_C0s_cpp = np.zeros((n_events, 2))
n_freqs = 256 // 2 + 1
# n_freqs = 5
results_A_cpp = np.zeros((n_events, 2, n_freqs))
t_start = time.time()
ff = np.linspace(0, 500 * units.MHz, n_freqs)
# tt = 0
for iX, x in enumerate(points):
# t_start2 = time.time()
r = ray.ray_tracing(x, x_receiver, ice)
# tt += (time.time() - t_start2)
r.find_solutions()
if (r.has_solution()):
for iS in range(r.get_number_of_solutions()):
results_C0s_cpp[iX, iS] = r.get_results()[iS]['C0']
results_A_cpp[iX, iS] = r.get_attenuation(iS, ff)
t_cpp = time.time() - t_start
print("CPP time = {:.1f} seconds = {:.2f}ms/event".format(
t_cpp, 1000. * t_cpp / n_events))
# print("CPP time = {:.1f} seconds = {:.2f}ms/event".format(tt, 1000. * tt / n_events))
results_C0s_python = np.zeros((n_events, 2))
results_A_python = np.zeros((n_events, 2, n_freqs))
ray.cpp_available = False
t_start = time.time()
for evt in eventReader.run():
for station in evt.get_stations():
station_id = station.get_id()
t = station.get_station_time()
det.update(t)
d = evt.get_first_sim_shower().get_parameter(shp.vertex)[2]
if (np.any(np.isclose(d, dds, atol=5))):
dds = np.delete(dds, np.argwhere(np.isclose(d, dds, atol=5)))
else:
continue
# if(d > -800):
# continue
# calcualte expected angles
r = ray.ray_tracing(pos_spice + np.array([0, 0, d]),
pos_SP1,
medium.southpole_simple(),
log_level=logging.WARNING)
r.find_solutions()
if (not r.has_solution()):
continue
results['depth'].append(d)
rvec = r.get_receive_vector(0)
zen, az = hp.cartesian_to_spherical(*rvec)
az = hp.get_normalized_angle(az)
results['exp'].append((zen, az))
print("{} depth = {:.1f}m -> {:.2f} {:.2f} (solution type {})".format(
t, d, zen / units.deg, az / units.deg, r.get_solution_type(0)))
channelResampler.run(evt, station, det, 50 * units.GHz)
channelBandPassFilter.run(evt,
points = np.array([xx, yy, zz]).T
x_receiver = np.array([0., 0., -5.])
nsol = 6
results_D = np.zeros((n_events, nsol))
results_D_analytic = np.zeros((n_events, nsol))
results_T = np.zeros((n_events, nsol))
results_T_analytic = np.zeros((n_events, nsol))
d_numeric = 0
d_analytic = 0
t_numeric = 0
t_analytic = 0
for iX, x in enumerate(points):
r = ray.ray_tracing(ice, log_level=logging.WARNING, n_reflections=1)
r.set_start_and_end_point(x, x_receiver)
r.find_solutions()
if (r.has_solution()):
for iS in range(r.get_number_of_solutions()):
t_start = time.time()
results_D[iX, iS] = r.get_path_length(iS, analytic=False)
d_numeric += time.time() - t_start
t_start = time.time()
results_D_analytic[iX, iS] = r.get_path_length(iS, analytic=True)
d_analytic += time.time() - t_start
t_start = time.time()
results_T[iX, iS] = r.get_travel_time(iS, analytic=False)
t_numeric += time.time() - t_start
t_start = time.time()
dds = -1 * np.arange(500, 1800, 100)
for evt in eventReader.run():
for station in evt.get_stations():
station_id = station.get_id()
t = station.get_station_time()
det.update(t)
d = evt.get_first_sim_shower().get_parameter(shp.vertex)[2]
if (np.any(np.isclose(d, dds, atol=5))):
dds = np.delete(dds, np.argwhere(np.isclose(d, dds, atol=5)))
else:
continue
# if(d > -800):
# continue
# calcualte expected angles
r = ray.ray_tracing(medium.southpole_simple(),
log_level=logging.WARNING)
r.set_start_and_end_point(pos_spice + np.array([0, 0, d]), pos_SP1)
r.find_solutions()
if (not r.has_solution()):
continue
results['depth'].append(d)
rvec = r.get_receive_vector(0)
zen, az = hp.cartesian_to_spherical(*rvec)
az = hp.get_normalized_angle(az)
results['exp'].append((zen, az))
print("{} depth = {:.1f}m -> {:.2f} {:.2f} (solution type {})".format(
t, d, zen / units.deg, az / units.deg, r.get_solution_type(0)))
channelResampler.run(evt, station, det, 50 * units.GHz)
channelBandPassFilter.run(evt,