def plot_coinc_window(windows, counts, n_events=0):
plot = MultiPlot(2,
1,
axis='semilogx',
width=r'.8\linewidth',
height=r'.5\linewidth')
plot.set_title(0, 0,
'Number of coincidences as function of coincidence window')
plot.set_xlabel('Coincidence window (ns)')
plot.show_xticklabels(1, 0)
plot.show_yticklabels_for_all()
plot.set_xlimits_for_all(min=1e1, max=1e8)
plot.set_ylimits(1, 0, min=0)
counts = numpy.array(counts)
subplot = plot.get_subplot_at(0, 0)
subplot.set_ylabel('Found coincidences')
subplot.plot(windows, counts, mark=None)
subplot = plot.get_subplot_at(1, 0)
subplot.set_ylabel('Delta found coincidences')
subplot.plot(windows[:-1], counts[1:] - counts[:-1], mark=None)
plot.save_as_pdf('coincidence_window')
def plot_shower_profile(seeds):
with tables.open_file(PATH % seeds) as data:
gp = data.root.groundparticles
min_t = gp.col('t').min()
print 'Making plots for %s' % seeds
gamma = gp.read_where('particle_id == 1')
electrons = gp.read_where('(particle_id == 3) | (particle_id == 4)')
muons = gp.read_where('(particle_id == 5) | (particle_id == 6)')
for correction in ['none', 'median_self']:
plot = MultiPlot(3, 1, 'semilogx', height=r'.4\linewidth')
splot = plot.get_subplot_at(0, 0)
splot.set_ylabel('Gamma')
plot_statistics(seeds,
splot,
gamma['r'],
gamma['t'] - min_t,
'solid',
correction=correction)
splot = plot.get_subplot_at(1, 0)
splot.set_ylabel('Electrons')
plot_statistics(seeds,
splot,
electrons['r'],
electrons['t'] - min_t,
'solid',
correction=correction)
splot = plot.get_subplot_at(2, 0)
splot.set_ylabel('Muon')
plot_statistics(seeds,
splot,
muons['r'],
muons['t'] - min_t,
'solid',
correction=correction)
plot.set_xlimits_for_all(None, 1e0, 1e3)
if correction is 'median_self':
plot.set_ylimits_for_all(None, -120, 120)
else:
plot.set_ylimits_for_all(None, 0, 120)
plot.show_xticklabels(2, 0)
plot.show_yticklabels_for_all()
plot.set_ylabel(r'Arrival time [\si{\ns}]')
plot.set_xlabel(r'Core distance [\si{\meter}]')
plot.set_title(0, 0, get_info_string_tex(seeds))
plot.save_as_pdf('plots/time_profile/%s_%s.pdf' %
(get_info_string(seeds), correction))
def plot_detected_zenith_distribution():
plot = MultiPlot(2, 2, width=r'.3\textwidth', height=r'.3\textwidth')
for i, e in enumerate([16, 16.5, 17, 17.5]):
splot = plot.get_subplot_at(int(i / 2), int(i % 2))
c, b = histogram(zenith.compress(energy_in == e),
bins=arange(0, 65, 1))
splot.histogram(c, b)
plot.set_title('Reconstructed zeniths per shower energy')
plot.set_xlimits_for_all(None, 0, 65)
plot.set_ylimits_for_all(None, 0)
plot.save_as_pdf('zenith_reconstructed')
def plot_residual_time_differences(data):
global idxes, dts
events = data.root.kascade.events
c_index = data.root.kascade.c_index
t0 = make_timestamp(2008, 7, 2)
t1 = make_timestamp(2008, 7, 3)
idxes = events.get_where_list('(t0 <= timestamp) & (timestamp < t1)')
t0_idx = min(idxes)
t1_idx = max(idxes)
dts = c_index.read_where('(t0_idx <= k_idx) & (k_idx < t1_idx)',
field='dt')
all_dts = c_index.col('dt')
figure()
subplot(121)
hist(all_dts / 1e3, bins=arange(-10, 2, .01), histtype='step')
title("July 1 - Aug 6, 2008")
xlabel("Time difference [us]")
ylabel("Counts")
subplot(122)
hist(dts / 1e3, bins=arange(-8, -6, .01), histtype='step')
title("July 2, 2008")
xlabel("Time difference [us]")
utils.saveplot()
graph = MultiPlot(1, 2, width=r'.45\linewidth')
n, bins = histogram(all_dts / 1e3, bins=arange(-10, 2, .01))
graph.histogram(0, 1, n, bins)
graph.set_title(0, 1, "Jul 1 - Aug 6, 2008")
n, bins = histogram(dts / 1e3, bins=arange(-8, -6, .01))
graph.histogram(0, 0, n, bins)
graph.set_title(0, 0, "Jul 2, 2008")
graph.set_xlabel(r"Time difference [\si{\micro\second}]")
graph.set_ylabel("Counts")
graph.set_ylimits(min=0)
graph.show_xticklabels_for_all([(0, 0), (0, 1)])
graph.show_yticklabels_for_all([(0, 0), (0, 1)])
graph.save('plots/MAT-residual-time-differences')
graph.save_as_pdf('preview')
def plot_residual_time_differences(data):
global idxes, dts
events = data.root.kascade.events
c_index = data.root.kascade.c_index
t0 = make_timestamp(2008, 7, 2)
t1 = make_timestamp(2008, 7, 3)
idxes = events.get_where_list('(t0 <= timestamp) & (timestamp < t1)')
t0_idx = min(idxes)
t1_idx = max(idxes)
dts = c_index.read_where('(t0_idx <= k_idx) & (k_idx < t1_idx)',
field='dt')
all_dts = c_index.col('dt')
figure()
subplot(121)
hist(all_dts / 1e3, bins=arange(-10, 2, .01), histtype='step')
title("July 1 - Aug 6, 2008")
xlabel("Time difference [us]")
ylabel("Counts")
subplot(122)
hist(dts / 1e3, bins=arange(-8, -6, .01), histtype='step')
title("July 2, 2008")
xlabel("Time difference [us]")
utils.saveplot()
graph = MultiPlot(1, 2, width=r'.45\linewidth')
n, bins = histogram(all_dts / 1e3, bins=arange(-10, 2, .01))
graph.histogram(0, 1, n, bins)
graph.set_title(0, 1, "Jul 1 - Aug 6, 2008")
n, bins = histogram(dts / 1e3, bins=arange(-8, -6, .01))
graph.histogram(0, 0, n, bins)
graph.set_title(0, 0, "Jul 2, 2008")
graph.set_xlabel(r"Time difference [\si{\micro\second}]")
graph.set_ylabel("Counts")
graph.set_ylimits(min=0)
graph.show_xticklabels_for_all([(0, 0), (0, 1)])
graph.show_yticklabels_for_all([(0, 0), (0, 1)])
graph.save('plots/MAT-residual-time-differences')
graph.save_as_pdf('preview')
