def boxplot_arrival_times(group, N):
table = group.E_1PeV.zenith_0
sel = table.readWhere('min_n134 >= N')
t1 = sel[:]['t1']
t3 = sel[:]['t3']
t4 = sel[:]['t4']
ts = concatenate([t1, t3, t4])
print "Median arrival time delay over all detected events", median(ts)
figure()
bin_edges = linspace(0, 100, 11)
x, arrival_times = [], []
t25, t50, t75 = [], [], []
for low, high in zip(bin_edges[:-1], bin_edges[1:]):
query = '(min_n134 >= N) & (low <= r) & (r < high)'
sel = table.readWhere(query)
t1 = sel[:]['t1']
t2 = sel[:]['t2']
ct1 = t1.compress((t1 > -999) & (t2 > -999))
ct2 = t2.compress((t1 > -999) & (t2 > -999))
ts = abs(ct2 - ct1)
t25.append(scoreatpercentile(ts, 25))
t50.append(scoreatpercentile(ts, 50))
t75.append(scoreatpercentile(ts, 75))
x.append((low + high) / 2)
fill_between(x, t25, t75, color='0.75')
plot(x, t50, 'o-', color='black')
xlabel("Core distance [m]")
ylabel("Arrival time delay [ns]")
#title(r"$N_{MIP} \geq %d, \quad \theta = 0^\circ$" % N)
xticks(arange(0, 100.5, 10))
utils.savedata((x, t25, t50, t75), N)
utils.saveplot(N)
graph = GraphArtist()
graph.shade_region(x, t25, t75)
graph.plot(x, t50, linestyle=None)
graph.set_xlabel(r"Core distance [\si{\meter}]")
graph.set_ylabel(
r"Arrival time difference $|t_2 - t_1|$ [\si{\nano\second}]")
graph.set_xlimits(0, 100)
graph.set_ylimits(min=0)
artist.utils.save_graph(graph, suffix=N, dirname='plots')
def boxplot_arrival_times(group, N):
table = group.E_1PeV.zenith_0
sel = table.read_where('min_n134 >= N')
t1 = sel[:]['t1']
t3 = sel[:]['t3']
t4 = sel[:]['t4']
ts = concatenate([t1, t3, t4])
print "Median arrival time delay over all detected events", median(ts)
figure()
bin_edges = linspace(0, 100, 11)
x, arrival_times = [], []
t25, t50, t75 = [], [], []
for low, high in zip(bin_edges[:-1], bin_edges[1:]):
query = '(min_n134 >= N) & (low <= r) & (r < high)'
sel = table.read_where(query)
t1 = sel[:]['t1']
t2 = sel[:]['t2']
ct1 = t1.compress((t1 > -999) & (t2 > -999))
ct2 = t2.compress((t1 > -999) & (t2 > -999))
ts = abs(ct2 - ct1)
t25.append(scoreatpercentile(ts, 25))
t50.append(scoreatpercentile(ts, 50))
t75.append(scoreatpercentile(ts, 75))
x.append((low + high) / 2)
fill_between(x, t25, t75, color='0.75')
plot(x, t50, 'o-', color='black')
xlabel("Core distance [m]")
ylabel("Arrival time delay [ns]")
#title(r"$N_{MIP} \geq %d, \quad \theta = 0^\circ$" % N)
xticks(arange(0, 100.5, 10))
utils.savedata((x, t25, t50, t75), N)
utils.saveplot(N)
graph = GraphArtist()
graph.shade_region(x, t25, t75)
graph.plot(x, t50, linestyle=None)
graph.set_xlabel(r"Core distance [\si{\meter}]")
graph.set_ylabel(r"Arrival time difference $|t_2 - t_1|$ [\si{\nano\second}]")
graph.set_xlimits(0, 100)
graph.set_ylimits(min=0)
artist.utils.save_graph(graph, suffix=N, dirname='plots')
def boxplot_phi_reconstruction_results_for_MIP(table, N):
figure()
THETA = deg2rad(22.5)
DTHETA = deg2rad(5.)
bin_edges = linspace(-180, 180, 18)
x, r_dphi = [], []
d25, d50, d75 = [], [], []
for low, high in zip(bin_edges[:-1], bin_edges[1:]):
rad_low = deg2rad(low)
rad_high = deg2rad(high)
query = '(min_n134 >= N) & (rad_low < reference_phi) & (reference_phi < rad_high) & (abs(reference_theta - THETA) <= DTHETA)'
sel = table.readWhere(query)
dphi = sel[:]['reconstructed_phi'] - sel[:]['reference_phi']
dphi = (dphi + pi) % (2 * pi) - pi
r_dphi.append(rad2deg(dphi))
d25.append(scoreatpercentile(rad2deg(dphi), 25))
d50.append(scoreatpercentile(rad2deg(dphi), 50))
d75.append(scoreatpercentile(rad2deg(dphi), 75))
x.append((low + high) / 2)
#boxplot(r_dphi, positions=x, widths=1 * (high - low), sym='')
fill_between(x, d25, d75, color='0.75')
plot(x, d50, 'o-', color='black')
xlabel(r"$\phi_K$ [deg]")
ylabel(r"$\phi_H - \phi_K$ [deg]")
title(r"$N_{MIP} \geq %d, \quad \theta = 22.5^\circ \pm %d^\circ$" %
(N, rad2deg(DTHETA)))
xticks(linspace(-180, 180, 9))
axhline(0, color='black')
utils.saveplot(N)
graph = GraphArtist()
graph.draw_horizontal_line(0, linestyle='gray')
graph.shade_region(x, d25, d75)
graph.plot(x, d50, linestyle=None)
graph.set_xlabel(r"$\phi_K$ [\si{\degree}]")
graph.set_ylabel(r"$\phi_H - \phi_K$ [\si{\degree}]")
graph.set_xticks([-180, -90, '...', 180])
graph.set_xlimits(-180, 180)
graph.set_ylimits(-23, 23)
artist.utils.save_graph(graph, suffix=N, dirname='plots')
def boxplot_phi_reconstruction_results_for_MIP(table, N):
figure()
THETA = deg2rad(22.5)
DTHETA = deg2rad(5.)
bin_edges = linspace(-180, 180, 18)
x, r_dphi = [], []
d25, d50, d75 = [], [], []
for low, high in zip(bin_edges[:-1], bin_edges[1:]):
rad_low = deg2rad(low)
rad_high = deg2rad(high)
query = '(min_n134 >= N) & (rad_low < reference_phi) & (reference_phi < rad_high) & (abs(reference_theta - THETA) <= DTHETA)'
sel = table.read_where(query)
dphi = sel[:]['reconstructed_phi'] - sel[:]['reference_phi']
dphi = (dphi + pi) % (2 * pi) - pi
r_dphi.append(rad2deg(dphi))
d25.append(scoreatpercentile(rad2deg(dphi), 25))
d50.append(scoreatpercentile(rad2deg(dphi), 50))
d75.append(scoreatpercentile(rad2deg(dphi), 75))
x.append((low + high) / 2)
#boxplot(r_dphi, positions=x, widths=1 * (high - low), sym='')
fill_between(x, d25, d75, color='0.75')
plot(x, d50, 'o-', color='black')
xlabel(r"$\phi_K$ [deg]")
ylabel(r"$\phi_H - \phi_K$ [deg]")
title(r"$N_{MIP} \geq %d, \quad \theta = 22.5^\circ \pm %d^\circ$" % (N, rad2deg(DTHETA)))
xticks(linspace(-180, 180, 9))
axhline(0, color='black')
utils.saveplot(N)
graph = GraphArtist()
graph.draw_horizontal_line(0, linestyle='gray')
graph.shade_region(x, d25, d75)
graph.plot(x, d50, linestyle=None)
graph.set_xlabel(r"$\phi_K$ [\si{\degree}]")
graph.set_ylabel(r"$\phi_H - \phi_K$ [\si{\degree}]")
graph.set_xticks([-180, -90, '...', 180])
graph.set_xlimits(-180, 180)
graph.set_ylimits(-23, 23)
artist.utils.save_graph(graph, suffix=N, dirname='plots')
def boxplot_phi_reconstruction_results_for_MIP(group, N):
table = group.E_1PeV.zenith_22_5
figure()
bin_edges = linspace(-180, 180, 18)
x, r_dphi = [], []
d25, d50, d75 = [], [], []
for low, high in zip(bin_edges[:-1], bin_edges[1:]):
rad_low = deg2rad(low)
rad_high = deg2rad(high)
query = '(min_n134 >= N) & (rad_low < reference_phi) & (reference_phi < rad_high)'
sel = table.read_where(query)
dphi = sel[:]['reconstructed_phi'] - sel[:]['reference_phi']
dphi = (dphi + pi) % (2 * pi) - pi
r_dphi.append(rad2deg(dphi))
d25.append(scoreatpercentile(rad2deg(dphi), 25))
d50.append(scoreatpercentile(rad2deg(dphi), 50))
d75.append(scoreatpercentile(rad2deg(dphi), 75))
x.append((low + high) / 2)
fill_between(x, d25, d75, color='0.75')
plot(x, d50, 'o-', color='black')
xlabel(r"$\phi_{simulated}$ [deg]")
ylabel(r"$\phi_{reconstructed} - \phi_{simulated}$ [deg]")
#title(r"$N_{MIP} \geq %d, \quad \theta = 22.5^\circ$" % N)
xticks(linspace(-180, 180, 9))
axhline(0, color='black')
ylim(-15, 15)
utils.saveplot(N)
graph = GraphArtist()
graph.draw_horizontal_line(0, linestyle='gray')
graph.shade_region(x, d25, d75)
graph.plot(x, d50, linestyle=None)
graph.set_xlabel(r"$\phi_\mathrm{sim}$ [\si{\degree}]")
graph.set_ylabel(r"$\phi_\mathrm{rec} - \phi_\mathrm{sim}$ [\si{\degree}]")
graph.set_title(r"$N_\mathrm{MIP} \geq %d$" % N)
graph.set_xticks([-180, -90, '...', 180])
graph.set_xlimits(-180, 180)
graph.set_ylimits(-17, 17)
artist.utils.save_graph(graph, suffix=N, dirname='plots')
def boxplot_phi_reconstruction_results_for_MIP(group, N):
table = group.E_1PeV.zenith_22_5
figure()
bin_edges = linspace(-180, 180, 18)
x, r_dphi = [], []
d25, d50, d75 = [], [], []
for low, high in zip(bin_edges[:-1], bin_edges[1:]):
rad_low = deg2rad(low)
rad_high = deg2rad(high)
query = '(min_n134 >= N) & (rad_low < reference_phi) & (reference_phi < rad_high)'
sel = table.readWhere(query)
dphi = sel[:]['reconstructed_phi'] - sel[:]['reference_phi']
dphi = (dphi + pi) % (2 * pi) - pi
r_dphi.append(rad2deg(dphi))
d25.append(scoreatpercentile(rad2deg(dphi), 25))
d50.append(scoreatpercentile(rad2deg(dphi), 50))
d75.append(scoreatpercentile(rad2deg(dphi), 75))
x.append((low + high) / 2)
fill_between(x, d25, d75, color='0.75')
plot(x, d50, 'o-', color='black')
xlabel(r"$\phi_{simulated}$ [deg]")
ylabel(r"$\phi_{reconstructed} - \phi_{simulated}$ [deg]")
#title(r"$N_{MIP} \geq %d, \quad \theta = 22.5^\circ$" % N)
xticks(linspace(-180, 180, 9))
axhline(0, color='black')
ylim(-15, 15)
utils.saveplot(N)
graph = GraphArtist()
graph.draw_horizontal_line(0, linestyle='gray')
graph.shade_region(x, d25, d75)
graph.plot(x, d50, linestyle=None)
graph.set_xlabel(r"$\phi_\mathrm{sim}$ [\si{\degree}]")
graph.set_ylabel(r"$\phi_\mathrm{rec} - \phi_\mathrm{sim}$ [\si{\degree}]")
graph.set_title(r"$N_\mathrm{MIP} \geq %d$" % N)
graph.set_xticks([-180, -90, '...', 180])
graph.set_xlimits(-180, 180)
graph.set_ylimits(-17, 17)
artist.utils.save_graph(graph, suffix=N, dirname='plots')
def boxplot_theta_reconstruction_results_for_MIP(table, N):
figure()
DTHETA = deg2rad(1.)
angles = [0, 5, 10, 15, 22.5, 35]
r_dtheta = []
x = []
d25, d50, d75 = [], [], []
for angle in angles:
theta = deg2rad(angle)
sel = table.readWhere(
'(min_n134 >= N) & (abs(reference_theta - theta) <= DTHETA)')
dtheta = rad2deg(sel[:]['reconstructed_theta'] -
sel[:]['reference_theta'])
r_dtheta.append(dtheta)
d25.append(scoreatpercentile(dtheta, 25))
d50.append(scoreatpercentile(dtheta, 50))
d75.append(scoreatpercentile(dtheta, 75))
x.append(angle)
#boxplot(r_dtheta, sym='', positions=angles, widths=2.)
fill_between(x, d25, d75, color='0.75')
plot(x, d50, 'o-', color='black')
xlabel(r"$\theta_K$ [deg]")
ylabel(r"$\theta_H - \theta_K$ [deg]")
title(r"$N_{MIP} \geq %d$" % N)
axhline(0, color='black')
ylim(-20, 25)
xlim(0, 35)
utils.saveplot(N)
graph = GraphArtist()
graph.draw_horizontal_line(0, linestyle='gray')
graph.shade_region(angles, d25, d75)
graph.plot(angles, d50, linestyle=None)
graph.set_xlabel(r"$\theta_K$ [\si{\degree}]")
graph.set_ylabel(r"$\theta_H - \theta_K$ [\si{\degree}]")
graph.set_ylimits(-5, 15)
artist.utils.save_graph(graph, suffix=N, dirname='plots')
def boxplot_theta_reconstruction_results_for_MIP(table, N):
figure()
DTHETA = deg2rad(1.)
angles = [0, 5, 10, 15, 22.5, 35]
r_dtheta = []
x = []
d25, d50, d75 = [], [], []
for angle in angles:
theta = deg2rad(angle)
sel = table.read_where('(min_n134 >= N) & (abs(reference_theta - theta) <= DTHETA)')
dtheta = rad2deg(sel[:]['reconstructed_theta'] - sel[:]['reference_theta'])
r_dtheta.append(dtheta)
d25.append(scoreatpercentile(dtheta, 25))
d50.append(scoreatpercentile(dtheta, 50))
d75.append(scoreatpercentile(dtheta, 75))
x.append(angle)
#boxplot(r_dtheta, sym='', positions=angles, widths=2.)
fill_between(x, d25, d75, color='0.75')
plot(x, d50, 'o-', color='black')
xlabel(r"$\theta_K$ [deg]")
ylabel(r"$\theta_H - \theta_K$ [deg]")
title(r"$N_{MIP} \geq %d$" % N)
axhline(0, color='black')
ylim(-20, 25)
xlim(0, 35)
utils.saveplot(N)
graph = GraphArtist()
graph.draw_horizontal_line(0, linestyle='gray')
graph.shade_region(angles, d25, d75)
graph.plot(angles, d50, linestyle=None)
graph.set_xlabel(r"$\theta_K$ [\si{\degree}]")
graph.set_ylabel(r"$\theta_H - \theta_K$ [\si{\degree}]")
graph.set_ylimits(-5, 15)
artist.utils.save_graph(graph, suffix=N, dirname='plots')
def boxplot_theta_reconstruction_results_for_MIP(group, N):
group = group.E_1PeV
figure()
angles = [0, 5, 10, 15, 22.5, 30, 35, 45]
r_dtheta = []
d25, d50, d75 = [], [], []
for angle in angles:
table = group._f_getChild('zenith_%s' % str(angle).replace('.', '_'))
sel = table.readWhere('min_n134 >= %d' % N)
dtheta = sel[:]['reconstructed_theta'] - sel[:]['reference_theta']
r_dtheta.append(rad2deg(dtheta))
d25.append(scoreatpercentile(rad2deg(dtheta), 25))
d50.append(scoreatpercentile(rad2deg(dtheta), 50))
d75.append(scoreatpercentile(rad2deg(dtheta), 75))
fill_between(angles, d25, d75, color='0.75')
plot(angles, d50, 'o-', color='black')
xlabel(r"$\theta_{simulated}$ [deg]")
ylabel(r"$\theta_{reconstructed} - \theta_{simulated}$ [deg]")
#title(r"$N_{MIP} \geq %d$" % N)
axhline(0, color='black')
ylim(-10, 25)
utils.saveplot(N)
graph = GraphArtist()
graph.draw_horizontal_line(0, linestyle='gray')
graph.shade_region(angles, d25, d75)
graph.plot(angles, d50, linestyle=None)
graph.set_xlabel(r"$\theta_\mathrm{sim}$ [\si{\degree}]")
graph.set_ylabel(
r"$\theta_\mathrm{rec} - \theta_\mathrm{sim}$ [\si{\degree}]")
graph.set_title(r"$N_\mathrm{MIP} \geq %d$" % N)
graph.set_ylimits(-8, 22)
artist.utils.save_graph(graph, suffix=N, dirname='plots')
def boxplot_theta_reconstruction_results_for_MIP(group, N):
group = group.E_1PeV
figure()
angles = [0, 5, 10, 15, 22.5, 30, 35, 45]
r_dtheta = []
d25, d50, d75 = [], [], []
for angle in angles:
table = group._f_get_child('zenith_%s' % str(angle).replace('.', '_'))
sel = table.read_where('min_n134 >= %d' % N)
dtheta = sel[:]['reconstructed_theta'] - sel[:]['reference_theta']
r_dtheta.append(rad2deg(dtheta))
d25.append(scoreatpercentile(rad2deg(dtheta), 25))
d50.append(scoreatpercentile(rad2deg(dtheta), 50))
d75.append(scoreatpercentile(rad2deg(dtheta), 75))
fill_between(angles, d25, d75, color='0.75')
plot(angles, d50, 'o-', color='black')
xlabel(r"$\theta_{simulated}$ [deg]")
ylabel(r"$\theta_{reconstructed} - \theta_{simulated}$ [deg]")
#title(r"$N_{MIP} \geq %d$" % N)
axhline(0, color='black')
ylim(-10, 25)
utils.saveplot(N)
graph = GraphArtist()
graph.draw_horizontal_line(0, linestyle='gray')
graph.shade_region(angles, d25, d75)
graph.plot(angles, d50, linestyle=None)
graph.set_xlabel(r"$\theta_\mathrm{sim}$ [\si{\degree}]")
graph.set_ylabel(r"$\theta_\mathrm{rec} - \theta_\mathrm{sim}$ [\si{\degree}]")
graph.set_title(r"$N_\mathrm{MIP} \geq %d$" % N)
graph.set_ylimits(-8, 22)
artist.utils.save_graph(graph, suffix=N, dirname='plots')
def boxplot_core_distance_vs_time():
plt.figure()
sim = data.root.showers.E_1PeV.zenith_0.shower_0
leptons = sim.leptons
#bins = np.logspace(0, 2, 25)
bins = np.linspace(0, 100, 15)
x, arrival_time, widths = [], [], []
t25, t50, t75 = [], [], []
for low, high in zip(bins[:-1], bins[1:]):
sel = leptons.readWhere(
'(low < core_distance) & (core_distance <= high)')
x.append(np.mean([low, high]))
arrival_time.append(sel[:]['arrival_time'])
widths.append((high - low) / 2)
ts = sel[:]['arrival_time']
t25.append(scoreatpercentile(ts, 25))
t50.append(scoreatpercentile(ts, 50))
t75.append(scoreatpercentile(ts, 75))
fill_between(x, t25, t75, color='0.75')
plot(x, t50, 'o-', color='black')
plt.xlabel("Core distance [m]")
plt.ylabel("Arrival time [ns]")
#utils.title("Shower front timing structure")
utils.saveplot()
graph = GraphArtist()
graph.plot(x, t50, linestyle=None)
graph.shade_region(x, t25, t75)
graph.set_xlabel(r"Core distance [\si{\meter}]")
graph.set_ylabel(r"Arrival time [\si{\nano\second}]")
graph.set_ylimits(0, 30)
graph.set_xlimits(0, 100)
graph.save('plots/front-passage-vs-R')
def boxplot_core_distance_vs_time():
plt.figure()
sim = data.root.showers.E_1PeV.zenith_0.shower_0
leptons = sim.leptons
#bins = np.logspace(0, 2, 25)
bins = np.linspace(0, 100, 15)
x, arrival_time, widths = [], [], []
t25, t50, t75 = [], [], []
for low, high in zip(bins[:-1], bins[1:]):
sel = leptons.read_where('(low < core_distance) & (core_distance <= high)')
x.append(np.mean([low, high]))
arrival_time.append(sel[:]['arrival_time'])
widths.append((high - low) / 2)
ts = sel[:]['arrival_time']
t25.append(scoreatpercentile(ts, 25))
t50.append(scoreatpercentile(ts, 50))
t75.append(scoreatpercentile(ts, 75))
fill_between(x, t25, t75, color='0.75')
plot(x, t50, 'o-', color='black')
plt.xlabel("Core distance [m]")
plt.ylabel("Arrival time [ns]")
#utils.title("Shower front timing structure")
utils.saveplot()
graph = GraphArtist()
graph.plot(x, t50, linestyle=None)
graph.shade_region(x, t25, t75)
graph.set_xlabel(r"Core distance [\si{\meter}]")
graph.set_ylabel(r"Arrival time [\si{\nano\second}]")
graph.set_ylimits(0, 30)
graph.set_xlimits(0, 100)
graph.save('plots/front-passage-vs-R')
def boxplot_core_distances_for_mips(group):
table = group.E_1PeV.zenith_22_5
figure()
r_list = []
r25, r50, r75 = [], [], []
x = []
for N in range(1, 5):
sel = table.read_where('min_n134 >= N')
r = sel[:]['r']
r_list.append(r)
x.append(N)
r25.append(scoreatpercentile(r, 25))
r50.append(scoreatpercentile(r, 50))
r75.append(scoreatpercentile(r, 75))
fill_between(x, r25, r75, color='0.75')
plot(x, r50, 'o-', color='black')
xticks(range(1, 5))
xlabel("Minimum number of particles")
ylabel("Core distance [m]")
#title(r"$\theta = 22.5^\circ$")
utils.saveplot()
graph = GraphArtist()
graph.shade_region(x, r25, r75)
graph.plot(x, r50, linestyle=None)
graph.set_xlabel("Minimum number of particles")
graph.set_ylabel(r"Core distance [\si{\meter}]")
graph.set_ylimits(min=0)
graph.set_xticks(range(5))
artist.utils.save_graph(graph, dirname='plots')
def boxplot_core_distances_for_mips(group):
table = group.E_1PeV.zenith_22_5
figure()
r_list = []
r25, r50, r75 = [], [], []
x = []
for N in range(1, 5):
sel = table.readWhere('min_n134 >= N')
r = sel[:]['r']
r_list.append(r)
x.append(N)
r25.append(scoreatpercentile(r, 25))
r50.append(scoreatpercentile(r, 50))
r75.append(scoreatpercentile(r, 75))
fill_between(x, r25, r75, color='0.75')
plot(x, r50, 'o-', color='black')
xticks(range(1, 5))
xlabel("Minimum number of particles")
ylabel("Core distance [m]")
#title(r"$\theta = 22.5^\circ$")
utils.saveplot()
graph = GraphArtist()
graph.shade_region(x, r25, r75)
graph.plot(x, r50, linestyle=None)
graph.set_xlabel("Minimum number of particles")
graph.set_ylabel(r"Core distance [\si{\meter}]")
graph.set_ylimits(min=0)
graph.set_xticks(range(5))
artist.utils.save_graph(graph, dirname='plots')
