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 plot_full_spectrum_fit_in_density_range(self, sel, popt, low, high):
bins = np.linspace(0, RANGE_MAX, N_BINS + 1)
n, bins = np.histogram(sel, bins=bins)
x = (bins[:-1] + bins[1:]) / 2
p_gamma, p_landau = self.constrained_full_spectrum_fit(
x, n, popt[:2], popt[2:])
plt.figure()
plt.plot(x * VNS, n, label='data')
self.plot_landau_and_gamma(x, p_gamma, p_landau)
y_charged = self.calc_charged_spectrum(x, n, p_gamma, p_landau)
plt.plot(x * VNS, y_charged, label='charged particles')
plt.yscale('log')
plt.xlim(0, 50)
plt.ylim(ymin=1)
plt.xlabel("Pulse integral [V ns]")
plt.ylabel("Count")
plt.legend()
suffix = '%.1f-%.1f' % (low, high)
suffix = suffix.replace('.', '_')
utils.saveplot(suffix)
n = np.where(n > 0, n, 1e-99)
y_charged = np.where(y_charged > 0, y_charged, 1e-99)
graph = GraphArtist('semilogy')
graph.histogram(n, bins * VNS, linestyle='gray')
self.artistplot_alt_landau_and_gamma(graph, x, p_gamma, p_landau)
graph.histogram(y_charged, bins * VNS)
graph.set_xlabel(r"Pulse integral [\si{\volt\nano\second}]")
graph.set_ylabel("Count")
graph.set_title(
r"$\SI{%.1f}{\per\square\meter} \leq \rho_\mathrm{charged}$ < $\SI{%.1f}{\per\square\meter}$"
% (low, high))
graph.set_xlimits(0, 30)
graph.set_ylimits(1e0, 1e4)
artist.utils.save_graph(graph, suffix, 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 plot_full_spectrum_fit_in_density_range(self, sel, popt, low, high):
bins = np.linspace(0, RANGE_MAX, N_BINS + 1)
n, bins = np.histogram(sel, bins=bins)
x = (bins[:-1] + bins[1:]) / 2
p_gamma, p_landau = self.constrained_full_spectrum_fit(x, n, popt[:2], popt[2:])
plt.figure()
plt.plot(x * VNS, n, label="data")
self.plot_landau_and_gamma(x, p_gamma, p_landau)
y_charged = self.calc_charged_spectrum(x, n, p_gamma, p_landau)
plt.plot(x * VNS, y_charged, label="charged particles")
plt.yscale("log")
plt.xlim(0, 50)
plt.ylim(ymin=1)
plt.xlabel("Pulse integral [V ns]")
plt.ylabel("Count")
plt.legend()
suffix = "%.1f-%.1f" % (low, high)
suffix = suffix.replace(".", "_")
utils.saveplot(suffix)
n = np.where(n > 0, n, 1e-99)
y_charged = np.where(y_charged > 0, y_charged, 1e-99)
graph = GraphArtist("semilogy")
graph.histogram(n, bins * VNS, linestyle="gray")
self.artistplot_alt_landau_and_gamma(graph, x, p_gamma, p_landau)
graph.histogram(y_charged, bins * VNS)
graph.set_xlabel(r"Pulse integral [\si{\volt\nano\second}]")
graph.set_ylabel("Count")
graph.set_title(
r"$\SI{%.1f}{\per\square\meter} \leq \rho_\mathrm{charged}$ < $\SI{%.1f}{\per\square\meter}$" % (low, high)
)
graph.set_xlimits(0, 30)
graph.set_ylimits(1e0, 1e4)
artist.utils.save_graph(graph, suffix, dirname="plots")
