def plot_azimuths(azimuth, name=''): plot = PolarPlot(use_radians=True) n, bins = histogram(azimuth, bins=linspace(-pi, pi, 21)) plot.histogram(n, bins) plot.set_title('Azimuth distribution') plot.set_ylimits(min=0) plot.set_xlabel('Azimuth [rad]') plot.set_ylabel('Counts') plot.save_as_pdf('azimuths_%s' % name)
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))