def plot_densities(data):
"""Make particle count plots for each detector to compare densities/responses"""
e501 = data.get_node('/hisparc/cluster_amsterdam/station_501', 'events')
e510 = data.get_node('/hisparc/cluster_amsterdam/station_510', 'events')
sn501 = (e501.col('n1') + e501.col('n2') + e501.col('n3') +
e501.col('n4')) / 2
sn510 = (e510.col('n1') + e510.col('n2') + e510.col('n3') +
e510.col('n4')) / 2
n501 = [e501.col('n1'), e501.col('n2'), e501.col('n3'), e501.col('n4')]
n510 = [e510.col('n1'), e510.col('n2'), e510.col('n3'), e510.col('n4')]
n_min = 0.5 # remove peak at 0
n_max = 200
bins = np.logspace(np.log10(n_min), np.log10(n_max), 50)
for minn in [0, 1, 2, 4, 8, 16]:
# poisson_errors = np.sqrt(bins)
# filter = sn501 > minn
filter = (sn501 > minn) & (sn510 > minn)
plot = MultiPlot(4,
4,
'loglog',
width=r'.22\linewidth',
height=r'.22\linewidth')
for i in range(4):
for j in range(4):
ncounts, x, y = np.histogram2d(n501[i].compress(filter),
n510[j].compress(filter),
bins=bins)
subplot = plot.get_subplot_at(i, j)
subplot.histogram2d(ncounts,
x,
y,
type='reverse_bw',
bitmap=True)
# subplot.plot(bins - poisson_errors, bins + poisson_errors,
# mark=None, linestyle='red')
# subplot.plot(bins + poisson_errors, bins - poisson_errors,
# mark=None, linestyle='red')
plot.show_xticklabels_for_all([(3, 0), (3, 1), (3, 2), (3, 3)])
plot.show_yticklabels_for_all([(0, 3), (1, 3), (2, 3), (3, 3)])
# plot.set_title(0, 1, 'Particle counts for station 501 and 510')
for i in range(4):
plot.set_subplot_xlabel(0, i, 'detector %d' % (i + 1))
plot.set_subplot_ylabel(i, 0, 'detector %d' % (i + 1))
plot.set_xlabel('Number of particles 501')
plot.set_ylabel('Number of particles 510')
plot.save_as_pdf('n_minn%d_501_510_bins_log' % minn)
ncounts, x, y = np.histogram2d(sn501, sn510, bins=bins)
plot = Plot('loglog')
plot.set_axis_equal()
plot.histogram2d(ncounts, x, y, type='reverse_bw', bitmap=True)
# plot.set_title('Particle counts for station 501 and 510')
plot.set_xlabel('Particle density in 501')
plot.set_ylabel('Particle density in 510')
plot.save_as_pdf('n_501_510_sum_log')
def plot_densities(data):
"""Make particle count plots for each detector to compare densities/responses"""
n_min = 0.5 # remove gamma peak
n_max = 50
bins = np.linspace(np.log10(n_min), np.log10(n_max), 60)
for station_number in [501, 510]:
events = data.get_node('/s%d' % station_number, 'events')
average_n = (events.col('n1') + events.col('n2') + events.col('n3') + events.col('n4')) / 4.
n = [events.col('n1'), events.col('n2'), events.col('n3'), events.col('n4')]
for minn in [0, 1, 2, 4, 8, 16]:
filter = (average_n > minn) & (n[0] > 0) & (n[1] > 0) & (n[2] > 0) & (n[3] > 0)
plot = MultiPlot(4, 4, width=r'.25\linewidth',
height=r'.25\linewidth')
for i in range(4):
for j in range(4):
if i < j:
continue
elif i == j:
ncounts, x, y = np.histogram2d(np.log10(average_n.compress(filter)),
np.log10(n[i].compress(filter)),
bins=bins)
else:
ncounts, x, y = np.histogram2d(np.log10(n[i].compress(filter)),
np.log10(n[j].compress(filter)),
bins=bins)
subplot = plot.get_subplot_at(i, j)
subplot.histogram2d(ncounts, x, y, type='reverse_bw',
bitmap=True)
plot.set_xlimits_for_all(min=0, max=np.log10(n_max))
plot.set_ylimits_for_all(min=0, max=np.log10(n_max))
plot.show_xticklabels_for_all([(3, 0), (3, 1), (3, 2), (3, 3)])
plot.show_yticklabels_for_all([(0, 3), (1, 3), (2, 3), (3, 3)])
# plot.set_title(0, 1, 'Particle counts for station 501 and 510')
for i in range(4):
plot.set_subplot_xlabel(0, i, 'detector %d' % (i + 1))
plot.set_subplot_ylabel(i, 0, 'detector %d' % (i + 1))
plot.set_xlabel('Number of particles')
plot.set_ylabel('Number of particles')
plot.save_as_pdf('plots/n_minn%d_%d' % (minn, station_number))
