def main(ts, ns):
station = Station(501)
traces = station.event_trace(ts, ns, True)
dr = DataReduction()
reduced_traces, o = dr.reduce_traces(array(traces).T, return_offset=True)
reduced_traces = reduced_traces.T
plot = Plot()
t = arange(len(traces[0])) * 2.5
for i, trace in enumerate(traces):
plot.plot(t, trace, linestyle='%s, thin' % COLORS[i], mark=None)
plot.draw_vertical_line(o * 2.5, 'gray')
plot.draw_vertical_line((o + len(reduced_traces[0])) * 2.5, 'gray')
plot.set_axis_options('line join=round')
plot.set_xlabel(r'Event time [\si{\ns}]')
plot.set_ylabel(r'Signal strength [ADCcounts]')
plot.set_xlimits(t[0], t[-1])
plot.save_as_pdf('raw_traces_%d_%d' % (ts, ns))
t = arange(o, o + len(reduced_traces[0])) * 2.5
for i, trace in enumerate(reduced_traces):
plot.plot(t, trace, linestyle='%s, thin' % COLORS[i], mark=None)
plot.set_axis_options('line join=round')
plot.set_xlabel(r'Event time [\si{\ns}]')
plot.set_ylabel(r'Signal strength [ADCcounts]')
plot.set_xlimits(t[0], t[-1])
plot.save_as_pdf('reduced_traces_%d_%d' % (ts, ns))
def plot_traces():
with tables.open_file(DATA, 'r') as data:
for i, pre, coin, post in TIME_WINDOWS:
test_node = data.get_node('/t%d' % i)
events = test_node.events.read()
events.sort(order='ext_timestamp')
blobs = test_node.blobs
for e_idx in [0, 1]:
t_idx = events[e_idx]['traces'][1]
extts = events[e_idx]['ext_timestamp']
try:
trace = zlib.decompress(blobs[t_idx]).split(',')
except zlib.error:
trace = zlib.decompress(blobs[t_idx][1:-1]).split(',')
if trace[-1] == '':
del trace[-1]
trace = [int(x) for x in trace]
plot = Plot()
plot.plot(range(len(trace)), trace, mark=None)
plot.set_label('%d' % extts)
microsec_to_sample = 400
plot.draw_vertical_line(pre * microsec_to_sample,
linestyle='thick,red,semitransparent')
plot.draw_vertical_line((pre + coin) * microsec_to_sample,
linestyle='thick,blue,semitransparent')
plot.set_ylabel('Signal strength [ADCcounts]')
plot.set_xlabel('Sample [2.5ns]')
plot.set_ylimits(min=150, max=1500)
plot.set_xlimits(min=0, max=len(trace))
plot.save_as_pdf('trace_%d_%d' % (i, e_idx))
def plot_raw(raw_traces):
length = 2.5 * len(raw_traces[0])
plot = Plot()
max_signal = max(chain.from_iterable(raw_traces))
plot.add_pin_at_xy(500,
max_signal,
'pre-trigger',
location='above',
use_arrow=False)
plot.draw_vertical_line(1000, 'gray')
plot.add_pin_at_xy(1750,
max_signal,
'trigger',
location='above',
use_arrow=False)
plot.draw_vertical_line(2500, 'gray')
plot.add_pin_at_xy(4250,
max_signal,
'post-trigger',
location='above',
use_arrow=False)
for i, raw_trace in enumerate(raw_traces):
plot.plot(arange(0, length, 2.5),
raw_trace,
mark=None,
linestyle=COLORS[i])
plot.set_ylimits(min=0)
plot.set_xlimits(min=0, max=length)
plot.set_ylabel(r'Signal strength [ADC counts]')
plot.set_xlabel(r'Sample [\si{\nano\second}]')
plot.save_as_pdf('raw')
def plot_interaction_altitude_distribution(cq):
# altitudes = cq.sims.col('first_interaction_altitude') / 1e3
altitudes = cq.simulations(energy=15,
zenith=22.5)['first_interaction_altitude'] / 1e3
bins = arange(0, 100, 2)
counts, bins = histogram(altitudes, bins, density=True)
plot = Plot()
plot.histogram(counts, bins)
plot.draw_vertical_line(median(altitudes), linestyle='red')
plot.set_xlabel(r'First interaction altitude [m]')
plot.set_ylabel(r'Counts')
plot.save_as_pdf('plots/interaction_altitude_distribution')
def plot_traces(traces, label='', raw=False):
"""Plot traces
Does not take different mV/ADC for HiSPARC II-III into account!
:param traces: list of lists of trace values.
:param label: name (suffix) for the output pdf.
"""
colors = ['black', 'red', 'black!40!green', 'blue']
plot = Plot(width=r'.6\textwidth')
times = arange(0, len(traces[0]) * 2.5, 2.5)
for i, trace in enumerate(traces):
if not raw:
if max(trace) * 0.57 < 500:
use_milli = True
trace = [t * -0.57 for t in trace]
else:
use_milli = False
trace = [t * -0.57 / 1e3 for t in trace]
plot.plot(times, trace, linestyle='%s, thin' % colors[i], mark=None)
if len(traces[0]) == 2400 and raw:
plot.add_pin_at_xy(500,
10,
'pre-trigger',
location='below',
use_arrow=False)
plot.add_pin_at_xy(1750,
10,
'trigger',
location='below',
use_arrow=False)
plot.add_pin_at_xy(4250,
10,
'post-trigger',
location='below',
use_arrow=False)
plot.draw_vertical_line(1000, 'gray')
plot.draw_vertical_line(2500, 'gray')
if raw:
plot.set_ylabel(r'Signal strength [ADCcounts]')
elif use_milli:
plot.set_ylabel(r'Signal strength [\si{\milli\volt}]')
else:
plot.set_ylabel(r'Signal strength [\si{\volt}]')
plot.set_xlabel(r'Event time [\si{\ns}]')
plot.set_xlimits(0, times[-1])
plot.set_axis_options('line join=round')
plot.save_as_pdf('trace_' + label)
def plot_coincidence_intervals(coincidences):
plot = Plot(axis='semilogx')
bins = logspace(7, 15, 150)
minn, maxn = (2, 10)
for n in range(minn, maxn + 1):
dt = coincidence_interval(coincidences, n)
counts, bins = histogram(dt, bins=bins)
# The counts are multiplied by 3 ** n to make them more similar in size
# Difference are cause by energy spectrum, station uptime and positions
greyness = r'black!%d' % (n * 100 / maxn)
plot.histogram(counts * (3**n), bins, linestyle=greyness)
plot.draw_vertical_line(bins[counts.argmax()], linestyle=greyness)
plot.set_xlabel(r'Time between consecutive coincidences')
plot.set_ylabel(r'Counts')
plot.set_ylimits(min=0)
plot.set_xlimits(min=bins[0], max=bins[-1])
plot.save_as_pdf('coincidence_intervals_501')
def plot_contribution_station(self, n, ref_n):
plot = Plot('semilogy')
colors = [
'red', 'blue', 'green', 'purple', 'gray', 'brown', 'cyan',
'magenta', 'orange', 'teal'
]
padding = 0.25
bins = linspace(0, 20, 150)
plot.histogram(*histogram(n, bins=bins))
plot.draw_vertical_line(1)
for j, density in enumerate(range(1, 8) + [15] + [20]):
n_slice = n.compress(abs(ref_n - density) < padding)
counts, bins = histogram(n_slice, bins=bins)
plot.histogram(counts,
bins + (j / 100.),
linestyle=colors[j % len(colors)])
plot.set_ylimits(min=0.9, max=1e5)
plot.set_xlimits(min=bins[0], max=bins[-1])
plot.set_xlabel(r'HiSPARC detected density [\si{\per\meter\squared}]')
plot.set_ylabel(r'Counts')
return plot
def determine_detector_timing_offsets(s, events):
"""Determine the offsets between the station detectors.
ADL: Currently assumes detector 1 is a good reference.
But this is not always the best choice. Perhaps it should be
determined using more data (more than one day) to be more
accurate.
"""
bins = arange(-100 + 1.25, 100, 2.5)
col = (cl for cl in COLORS)
graph = Plot()
ids = range(1, 5)
reference = 2
for j in [1, 3, 4]:
if j == reference:
continue
tref = events.col('t%d' % reference)
tj = events.col('t%d' % j)
dt = (tj - tref).compress((tref >= 0) & (tj >= 0))
y, bins = histogram(dt, bins=bins)
c = col.next()
graph.histogram(y, bins, linestyle='%s' % c)
x = (bins[:-1] + bins[1:]) / 2
try:
popt, pcov = curve_fit(gauss, x, y, p0=(len(dt), 0., 10.))
graph.draw_vertical_line(popt[1], linestyle='%s' % c)
print '%d-%d: %f (%f)' % (j, reference, popt[1], popt[2])
except (IndexError, RuntimeError):
print '%d-%d: failed' % (j, reference)
graph.set_title('Time difference, station %d' % (s))
graph.set_xlimits(-100, 100)
graph.set_ylimits(min=0)
graph.set_xlabel('$\Delta t$')
graph.set_ylabel('Counts')
graph.save_as_pdf('detector_offsets_%s' % s)
def plot_times():
plot = Plot('semilogx')
data = read_times()
walltimes = data['walltime'] / 60. / 60. # To hours
print 'Total time: %d years.' % (sum(walltimes) / 24. / 365.)
print 'Longest job: %d hours.' % max(walltimes)
print 'Shortest job: %d seconds.' % (min(walltimes) * 60. * 60.)
counts, bins = histogram(log10(walltimes), bins=300)
plot.histogram(counts, 10**bins, linestyle='fill=black')
plot.add_pin_at_xy(4,
max(counts),
'short',
location='above left',
use_arrow=False)
plot.draw_vertical_line(4, 'gray')
plot.add_pin_at_xy(24,
max(counts),
'generic',
location='above left',
use_arrow=False)
plot.draw_vertical_line(24, 'gray')
plot.add_pin_at_xy(96,
max(counts),
'long',
location='above left',
use_arrow=False)
plot.draw_vertical_line(96, 'gray')
plot.add_pin_at_xy(2000,
max(counts),
'extra-long',
location='above left',
use_arrow=False)
plot.draw_vertical_line(2000, 'gray')
plot.set_ylabel(r'Count')
plot.set_xlabel(r'Walltime [\si{\hour}]')
plot.set_ylimits(min=0)
plot.set_xlimits(min=3e-3, max=3e3)
plot.save_as_pdf('shower_walltime')
def determine_station_timing_offsets(data):
"""Determine the offsets between the stations."""
c = .3
ref_station_number = 501
ref_d_off = DETECTOR_OFFSETS[ref_station_number]
ref_events = data.root.hisparc.cluster_amsterdam.station_501.events
ref_t = array([
where(
ref_events.col('t1') == -999, 9000,
ref_events.col('t1') - ref_d_off[0]),
where(
ref_events.col('t2') == -999, 9000,
ref_events.col('t2') - ref_d_off[1]),
where(
ref_events.col('t3') == -999, 9000,
ref_events.col('t3') - ref_d_off[2]),
where(
ref_events.col('t4') == -999, 9000,
ref_events.col('t4') - ref_d_off[3])
])
ref_min_t = ref_t.min(axis=0)
station_number = 510
d_off = DETECTOR_OFFSETS[station_number]
events = data.root.hisparc.cluster_amsterdam.station_510.events
t = array([
where(events.col('t1') == -999, 90000,
events.col('t1') - d_off[0]),
where(events.col('t2') == -999, 90000,
events.col('t2') - d_off[1]),
where(events.col('t3') == -999, 90000,
events.col('t3') - d_off[2]),
where(events.col('t4') == -999, 90000,
events.col('t4') - d_off[3])
])
min_t = t.min(axis=0)
dt = []
for event, ref_event in itertools.izip(events, ref_events):
if (ref_event['t_trigger'] in ERR or event['t_trigger'] in ERR):
dt.append(nan)
continue
dt.append((int(event['ext_timestamp']) -
int(ref_event['ext_timestamp'])) -
(event['t_trigger'] - ref_event['t_trigger']))
dt = array(dt)
dt = dt + (min_t - ref_min_t)
plot = Plot()
bins = linspace(-50, 50, 100)
y, bins = histogram(dt, bins=bins)
plot.histogram(y, bins)
x = (bins[:-1] + bins[1:]) / 2
try:
popt, pcov = curve_fit(gauss, x, y, p0=(len(dt), 0., 10))
station_offset = popt[1]
plot.draw_vertical_line(station_offset)
bins = linspace(-50, 50, 1000)
plot.plot(bins, gauss(bins, *popt), mark=None, linestyle='gray')
except RuntimeError:
station_offset = 0.
print station_offset
plot.set_title('Time difference, station 510-501')
plot.set_xlimits(-50, 50)
plot.set_ylimits(min=0)
plot.set_xlabel('$\Delta t$ [ns]')
plot.set_ylabel('Counts')
plot.save_as_pdf('station_offsets')
def plot_traces(traces1, traces2, overlap=0, label=''):
"""Plot traces
:param traces: list of lists of trace values.
:param label: name (suffix) for the output pdf.
"""
colors1 = ['black', 'red', 'black!40!green', 'blue']
colors2 = ['gray', 'black!40!red', 'black!60!green', 'black!40!blue']
plot = Plot(width=r'1.\textwidth', height=r'.3\textwidth')
times1 = arange(0, len(traces1[0]) * 2.5, 2.5)
times2 = arange((len(traces1[0]) - overlap) * 2.5,
(len(traces1[0]) + len(traces2[0]) - overlap) * 2.5, 2.5)
for i, trace in enumerate(traces1):
plot.plot(times1,
array(trace) + i * 20,
linestyle='%s, ultra thin' % colors1[i],
mark=None)
plot.draw_vertical_line(1000, 'gray, very thin')
plot.draw_vertical_line(2500, 'gray, very thin')
plot.draw_vertical_line(6000, 'pink, dashed, very thin')
plot.add_pin_at_xy(0,
450,
r'\tiny{pre-trigger}',
location='right',
use_arrow=False)
plot.add_pin_at_xy(1000,
450,
r'\tiny{trigger}',
location='right',
use_arrow=False)
plot.add_pin_at_xy(2500,
450,
r'\tiny{post-trigger}',
location='right',
use_arrow=False)
plot.add_pin_at_xy(6000,
450,
r'\tiny{end of first event}',
location='left',
use_arrow=True)
for i, trace in enumerate(traces2):
plot.plot(times2,
array(trace) + i * 20,
linestyle='%s, ultra thin' % colors2[i],
mark=None)
plot.draw_vertical_line(6000 - (overlap * 2.5), 'pink, very thin')
plot.draw_vertical_line(7000 - (overlap * 2.5), 'gray, very thin')
plot.draw_vertical_line(8500 - (overlap * 2.5), 'gray, very thin')
plot.add_pin_at_xy(6000 - (overlap * 2.5),
400,
r'\tiny{pre-trigger}',
location='right',
use_arrow=False)
plot.add_pin_at_xy(7000 - (overlap * 2.5),
400,
r'\tiny{trigger}',
location='right',
use_arrow=False)
plot.add_pin_at_xy(8500 - (overlap * 2.5),
400,
r'\tiny{post-trigger}',
location='right',
use_arrow=False)
plot.set_ylabel(r'Signal strength [ADCcounts]')
plot.set_xlabel(r'Event time [\si{\ns}]')
plot.set_ylimits(0, 500)
plot.set_xlimits(0, times2[-1])
plot.set_axis_options('line join=round')
plot.save_as_pdf('trace_' + label)