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')
p_detection = np.vectorize(lambda x: 1 - np.exp(-.5 * x) if x >= 0 else 0.)
def conv_p_detection(self, x, sigma):
x_step = x[-1] - x[-2]
x2 = np.arange(-2 * max(x), 2 * max(x) + x_step / 2, x_step)
g = stats.norm(scale=sigma).pdf
y2 = landau.discrete_convolution(self.p_detection, g, x2)
y = np.interp(x, x2, y2)
return y
if __name__ == '__main__':
np.seterr(invalid='ignore', divide='ignore')
if 'data' not in globals():
data = tables.open_file('kascade.h5', 'r')
utils.set_prefix('EFF-')
artist.utils.set_prefix('EFF-')
efficiency = ReconstructionEfficiency(data)
efficiency.main()
graph.plot(x, rad2deg(f_y2), mark=None)
graph.plot(x, rad2deg(l_y2), mark=None, linestyle='dashed')
graph.set_xlabel(r"Shower zenith angle [\si{\degree}]")
graph.set_ylabel(r"Angle reconstruction uncertainty [\si{\degree}]")
artist.utils.save_graph(graph, dirname='plots')
if __name__ == '__main__':
# invalid values in arcsin will be ignored (nan handles the situation
# quite well)
np.seterr(invalid='ignore', divide='ignore')
try:
data
except NameError:
data = tables.open_file('kascade.h5', 'r')
artist.utils.set_prefix("KAS-")
utils.set_prefix("KAS-")
do_reconstruction_plots(data, data.root.reconstructions)
do_lint_comparison(data)
artist.utils.set_prefix("KAS-LINT-")
utils.set_prefix("KAS-LINT-")
do_reconstruction_plots(data, data.root.lint_reconstructions)
artist.utils.set_prefix("KAS-OFFSETS-")
utils.set_prefix("KAS-OFFSETS-")
do_reconstruction_plots(data, data.root.reconstructions_offsets)
artist.utils.set_prefix("KAS-LINT-OFFSETS-")
utils.set_prefix("KAS-LINT-OFFSETS-")
do_reconstruction_plots(data, data.root.lint_reconstructions_offsets)
graph1.set_xlabel(r'Shower azimuthal angle [\si{\degree}]')
graph1.set_ylabel('Count')
artist.utils.save_graph(graph1, suffix='phi', dirname='plots')
graph2.set_ylimits_for_all(None, 0, 2000)
graph2.set_xlimits_for_all(None, 0, 45)
graph2.show_yticklabels(0, 0)
graph2.show_xticklabels_for_all()
graph2.set_xticklabels_position(0, 1, 'right')
graph2.set_xlabel(r'Shower zenith angle [\si{\degree}]')
graph2.set_ylabel('Count')
artist.utils.save_graph(graph2, suffix='theta', dirname='plots')
if __name__ == '__main__':
if 'data' not in globals():
# For single station plots
#data = tables.open_file('month-single.h5')
# For station / cluster plots
#data = tables.open_file('new.h5')
#data = tables.open_file('newlarge.h5')
data = tables.open_file('master.h5')
# For N vs R plot
#data = tables.open_file('master-large.h5')
# No data
#data = None
artist.utils.set_prefix("SP-DIR-")
utils.set_prefix("SP-DIR-")
main(data)
graph1.set_xlabel(r'Shower azimuthal angle [\si{\degree}]')
graph1.set_ylabel('Count')
artist.utils.save_graph(graph1, suffix='phi', dirname='plots')
graph2.set_ylimits_for_all(None, 0, 2000)
graph2.set_xlimits_for_all(None, 0, 45)
graph2.show_yticklabels(0, 0)
graph2.show_xticklabels_for_all()
graph2.set_xticklabels_position(0, 1, 'right')
graph2.set_xlabel(r'Shower zenith angle [\si{\degree}]')
graph2.set_ylabel('Count')
artist.utils.save_graph(graph2, suffix='theta', dirname='plots')
if __name__ == '__main__':
if 'data' not in globals():
# For single station plots
#data = tables.open_file('month-single.h5')
# For station / cluster plots
#data = tables.open_file('new.h5')
#data = tables.open_file('newlarge.h5')
data = tables.open_file('master.h5')
# For N vs R plot
#data = tables.open_file('master-large.h5')
# No data
#data = None
artist.utils.set_prefix("SP-DIR-")
utils.set_prefix("SP-DIR-")
main(data)
graph.plot(x, rad2deg(f_y2), mark=None)
graph.plot(x, rad2deg(l_y2), mark=None, linestyle='dashed')
graph.set_xlabel(r"Shower zenith angle [\si{\degree}]")
graph.set_ylabel(r"Angle reconstruction uncertainty [\si{\degree}]")
artist.utils.save_graph(graph, dirname='plots')
if __name__ == '__main__':
# invalid values in arcsin will be ignored (nan handles the situation
# quite well)
np.seterr(invalid='ignore', divide='ignore')
try:
data
except NameError:
data = tables.open_file('kascade.h5', 'r')
artist.utils.set_prefix("KAS-")
utils.set_prefix("KAS-")
do_reconstruction_plots(data, data.root.reconstructions)
do_lint_comparison(data)
artist.utils.set_prefix("KAS-LINT-")
utils.set_prefix("KAS-LINT-")
do_reconstruction_plots(data, data.root.lint_reconstructions)
artist.utils.set_prefix("KAS-OFFSETS-")
utils.set_prefix("KAS-OFFSETS-")
do_reconstruction_plots(data, data.root.reconstructions_offsets)
artist.utils.set_prefix("KAS-LINT-OFFSETS-")
utils.set_prefix("KAS-LINT-OFFSETS-")
do_reconstruction_plots(data, data.root.lint_reconstructions_offsets)
#ylim(0, 100)
#legend(numpoints=1)
utils.saveplot()
artist.utils.save_graph(graph, dirname='plots')
print
if __name__ == '__main__':
# invalid values in arcsin will be ignored (nan handles the situation
# quite well)
np.seterr(invalid='ignore', divide='ignore')
try:
data
except NameError:
data = tables.open_file('master-ch4v2.h5', 'r')
if '/reconstructions' not in data:
print "Reconstructing shower direction..."
do_full_reconstruction(data)
else:
print "Skipping reconstruction!"
utils.set_prefix("DIR-")
artist.utils.set_prefix("DIR-")
do_reconstruction_plots(data)
# These currently don't work
# utils.set_prefix("WIP-")
# do_jos_plots(data)
#ylim(0, 100)
#legend(numpoints=1)
utils.saveplot()
artist.utils.save_graph(graph, dirname='plots')
print
if __name__ == '__main__':
# invalid values in arcsin will be ignored (nan handles the situation
# quite well)
np.seterr(invalid='ignore', divide='ignore')
try:
data
except NameError:
data = tables.open_file('master-ch4v2.h5', 'r')
if '/reconstructions' not in data:
print "Reconstructing shower direction..."
do_full_reconstruction(data)
else:
print "Skipping reconstruction!"
utils.set_prefix("DIR-")
artist.utils.set_prefix("DIR-")
do_reconstruction_plots(data)
# These currently don't work
# utils.set_prefix("WIP-")
# do_jos_plots(data)