def main():
directions = np.genfromtxt('data/discrete-directions.txt',
names=['azimuth', 'zenith'])
plot = PolarPlot(use_radians=True)
plot.scatter(directions['azimuth'], directions['zenith'],
markstyle='mark size=.75pt')
plot.set_xlabel('Azimuth [rad]')
plot.set_ylabel('Zenith [rad]')
plot.save('discrete_directions')
def plot_discrete(angles):
theta, phi = zip(*angles)
graph = PolarPlot(use_radians=True)
graph.scatter(phi, theta, markstyle='mark size=.5pt')
graph.set_ylimits(0, np.pi / 2)
graph.set_yticks([0, np.pi / 6, np.pi / 3, np.pi / 2])
graph.set_ytick_labels([
r'$0$',
r'$\frac{1}{6}\pi$',
r'$\frac{2}{6}\pi$',
r'$\frac{1}{2}\pi$',
])
graph.set_ylabel('Zenith [rad]')
graph.set_xlabel('Azimuth [rad]')
graph.save_as_pdf('discrete_directions')
def plot_reconstruction_accuracy(data, d):
station_path = '/cluster_simulations/station_%d'
cluster = cluster_501_510()
coincidences = data.root.coincidences.coincidences
recs501 = data.root.hisparc.cluster_amsterdam.station_501.reconstructions
recs510 = data.root.hisparc.cluster_amsterdam.station_510.reconstructions
graph = Plot()
ids = set(recs501.col('id')).intersection(recs510.col('id'))
filtered_501 = [(row['zenith'], row['azimuth']) for row in recs501
if row['id'] in ids]
filtered_510 = [(row['zenith'], row['azimuth']) for row in recs510
if row['id'] in ids]
zen501, azi501 = zip(*filtered_501)
zen510, azi510 = zip(*filtered_510)
zen501 = array(zen501)
azi501 = array(azi501)
zen510 = array(zen510)
azi510 = array(azi510)
da = angle_between(zen501, azi501, zen510, azi510)
n, bins = histogram(da, bins=arange(0, pi, .1))
graph.histogram(n, bins)
failed = coincidences.nrows - len(ids)
graph.set_ylimits(min=0)
graph.set_xlimits(min=0, max=pi)
graph.set_ylabel('Count')
graph.set_xlabel('Angle between 501 and 510 [rad]')
graph.set_title('Coincidences between 501 and 510')
graph.set_label('Failed to reconstruct %d events' % failed)
graph.save_as_pdf('coincidences_%s' % d)
graph_recs = PolarPlot()
azimuth = degrees(recs501.col('azimuth'))
zenith = degrees(recs501.col('zenith'))
graph_recs.scatter(azimuth[:5000],
zenith[:5000],
mark='*',
markstyle='mark size=.2pt')
graph_recs.set_ylimits(min=0, max=90)
graph_recs.set_ylabel('Zenith [degrees]')
graph_recs.set_xlabel('Azimuth [degrees]')
graph_recs.set_title('Reconstructions by 501')
graph_recs.save_as_pdf('reconstructions_%s' % d)
def discrete_directions():
graph = PolarPlot(use_radians=True)
times = generate_discrete_times(station, detector_ids=[0, 1, 2])
detectors = [station.detectors[id].get_coordinates() for id in [0, 1, 2]]
x, y, z = zip(*detectors)
theta, phi = itertools.izip(*(dirrec.reconstruct_common((0,) + t, x, y, z)
for t in times))
thetaa = [t for t in theta if not np.isnan(t)]
phia = [p for p in phi if not np.isnan(p)]
graph.scatter(phia, thetaa, markstyle='mark size=1pt', mark='*')
graph.set_ylimits(0, np.pi / 2)
graph.set_yticks([0, np.pi / 6, np.pi / 3, np.pi / 2])
graph.set_ytick_labels([r'$0$', r'$\frac{1}{6}\pi$',
r'$\frac{2}{6}\pi$', r'$\frac{1}{2}\pi$', ])
graph.set_ylabel('Zenith [rad]')
graph.set_xlabel('Azimuth [rad]')
graph.save_as_pdf('discrete_directions')
def reconstruct_for_detectors(ids):
graph = PolarPlot(use_radians=True)
times = generate_discrete_times(station, detector_ids=ids)
detectors = [station.detectors[id].get_coordinates() for id in ids]
x, y, z = zip(*detectors)
theta, phi = itertools.izip(*(dirrec.reconstruct_common((0,) + t, x, y, z)
for t in times))
thetaa = [t for t in theta if not np.isnan(t)]
phia = [p for p in phi if not np.isnan(p)]
graph.scatter(phia, thetaa, markstyle='mark size=.5pt', mark='*')
# Add curved lines where detector 0 and 2 have fixed but different times
# and a straight line where detector 0 and 2 have equal times
times = np.arange(-60, 60, TIME_RESOLUTION)
for dt in (-2.5, 0, 2.5, 7.5, 15, 22.5, 30, 45):
theta, phi = itertools.izip(*(dirrec.reconstruct_common((t, 0, dt), x, y, z)
for t in times))
thetaa = [t for t in theta if not np.isnan(t)]
phia = [p for p in phi if not np.isnan(p)]
graph.plot(phia, thetaa, mark=None, linestyle='solid,' + COLORS[ids[0]])
theta, phi = itertools.izip(*(dirrec.reconstruct_common((0, t, dt), x, y, z)
for t in times))
thetaa = [t for t in theta if not np.isnan(t)]
phia = [p for p in phi if not np.isnan(p)]
graph.plot(phia, thetaa, mark=None, linestyle='solid,' + COLORS[ids[1]])
theta, phi = itertools.izip(*(dirrec.reconstruct_common((0, dt, t), x, y, z)
for t in times))
thetaa = [t for t in theta if not np.isnan(t)]
phia = [p for p in phi if not np.isnan(p)]
graph.plot(phia, thetaa, mark=None, linestyle='solid,' + COLORS[ids[2]])
graph.set_ylimits(0, np.pi / 2)
graph.set_yticks([0, np.pi / 6, np.pi / 3, np.pi / 2])
graph.set_ytick_labels([r'$0$', r'$\frac{1}{6}\pi$',
r'$\frac{2}{6}\pi$', r'$\frac{1}{2}\pi$', ])
graph.set_ylabel('Zenith [rad]')
graph.set_xlabel('Azimuth [rad]')
graph.save_as_pdf('discrete_directions_%s' % '_'.join(str(i) for i in ids))
