def to_coinc_xml_object(self, file_name):
outdoc = ligolw.Document()
outdoc.appendChild(ligolw.LIGO_LW())
ifos = list(self.sngl_files.keys())
proc_id = ligolw_process.register_to_xmldoc(
outdoc,
'pycbc', {},
ifos=ifos,
comment='',
version=pycbc_version.git_hash,
cvs_repository='pycbc/' + pycbc_version.git_branch,
cvs_entry_time=pycbc_version.date).process_id
search_summ_table = lsctables.New(lsctables.SearchSummaryTable)
coinc_h5file = self.coinc_file.h5file
try:
start_time = coinc_h5file['segments']['coinc']['start'][:].min()
end_time = coinc_h5file['segments']['coinc']['end'][:].max()
except KeyError:
start_times = []
end_times = []
for ifo_comb in coinc_h5file['segments']:
if ifo_comb == 'foreground_veto':
continue
seg_group = coinc_h5file['segments'][ifo_comb]
start_times.append(seg_group['start'][:].min())
end_times.append(seg_group['end'][:].max())
start_time = min(start_times)
end_time = max(end_times)
num_trigs = len(self.sort_arr)
search_summary = return_search_summary(start_time, end_time, num_trigs,
ifos)
search_summ_table.append(search_summary)
outdoc.childNodes[0].appendChild(search_summ_table)
sngl_inspiral_table = lsctables.New(lsctables.SnglInspiralTable)
coinc_def_table = lsctables.New(lsctables.CoincDefTable)
coinc_event_table = lsctables.New(lsctables.CoincTable)
coinc_inspiral_table = lsctables.New(lsctables.CoincInspiralTable)
coinc_event_map_table = lsctables.New(lsctables.CoincMapTable)
time_slide_table = lsctables.New(lsctables.TimeSlideTable)
# Set up time_slide table
time_slide_id = lsctables.TimeSlideID(0)
for ifo in ifos:
time_slide_row = lsctables.TimeSlide()
time_slide_row.instrument = ifo
time_slide_row.time_slide_id = time_slide_id
time_slide_row.offset = 0
time_slide_row.process_id = proc_id
time_slide_table.append(time_slide_row)
# Set up coinc_definer table
coinc_def_id = lsctables.CoincDefID(0)
coinc_def_row = lsctables.CoincDef()
coinc_def_row.search = "inspiral"
coinc_def_row.description = \
"sngl_inspiral<-->sngl_inspiral coincidences"
coinc_def_row.coinc_def_id = coinc_def_id
coinc_def_row.search_coinc_type = 0
coinc_def_table.append(coinc_def_row)
bank_col_names = ['mass1', 'mass2', 'spin1z', 'spin2z']
bank_col_vals = {}
for name in bank_col_names:
bank_col_vals[name] = self.get_bankfile_array(name)
coinc_event_names = ['ifar', 'time', 'fap', 'stat']
coinc_event_vals = {}
for name in coinc_event_names:
if name == 'time':
coinc_event_vals[name] = self.get_end_time()
else:
coinc_event_vals[name] = self.get_coincfile_array(name)
sngl_col_names = [
'snr', 'chisq', 'chisq_dof', 'bank_chisq', 'bank_chisq_dof',
'cont_chisq', 'cont_chisq_dof', 'end_time', 'template_duration',
'coa_phase', 'sigmasq'
]
sngl_col_vals = {}
for name in sngl_col_names:
sngl_col_vals[name] = self.get_snglfile_array_dict(name)
sngl_event_count = 0
for idx in range(len(self.sort_arr)):
# Set up IDs and mapping values
coinc_id = lsctables.CoincID(idx)
# Set up sngls
# FIXME: As two-ifo is hardcoded loop over all ifos
sngl_combined_mchirp = 0
sngl_combined_mtot = 0
net_snrsq = 0
for ifo in ifos:
# If this ifo is not participating in this coincidence then
# ignore it and move on.
if not sngl_col_vals['snr'][ifo][1][idx]:
continue
event_id = lsctables.SnglInspiralID(sngl_event_count)
sngl_event_count += 1
sngl = return_empty_sngl()
sngl.event_id = event_id
sngl.ifo = ifo
net_snrsq += sngl_col_vals['snr'][ifo][0][idx]**2
for name in sngl_col_names:
val = sngl_col_vals[name][ifo][0][idx]
if name == 'end_time':
sngl.set_end(LIGOTimeGPS(val))
else:
setattr(sngl, name, val)
for name in bank_col_names:
val = bank_col_vals[name][idx]
setattr(sngl, name, val)
sngl.mtotal, sngl.eta = pnutils.mass1_mass2_to_mtotal_eta(
sngl.mass1, sngl.mass2)
sngl.mchirp, _ = pnutils.mass1_mass2_to_mchirp_eta(
sngl.mass1, sngl.mass2)
sngl.eff_distance = (sngl.sigmasq)**0.5 / sngl.snr
sngl_combined_mchirp += sngl.mchirp
sngl_combined_mtot += sngl.mtotal
sngl_inspiral_table.append(sngl)
# Set up coinc_map entry
coinc_map_row = lsctables.CoincMap()
coinc_map_row.table_name = 'sngl_inspiral'
coinc_map_row.coinc_event_id = coinc_id
coinc_map_row.event_id = event_id
coinc_event_map_table.append(coinc_map_row)
sngl_combined_mchirp = sngl_combined_mchirp / len(ifos)
sngl_combined_mtot = sngl_combined_mtot / len(ifos)
# Set up coinc inspiral and coinc event tables
coinc_event_row = lsctables.Coinc()
coinc_inspiral_row = lsctables.CoincInspiral()
coinc_event_row.coinc_def_id = coinc_def_id
coinc_event_row.nevents = len(ifos)
coinc_event_row.instruments = ','.join(ifos)
coinc_inspiral_row.set_ifos(ifos)
coinc_event_row.time_slide_id = time_slide_id
coinc_event_row.process_id = proc_id
coinc_event_row.coinc_event_id = coinc_id
coinc_inspiral_row.coinc_event_id = coinc_id
coinc_inspiral_row.mchirp = sngl_combined_mchirp
coinc_inspiral_row.mass = sngl_combined_mtot
coinc_inspiral_row.set_end(
LIGOTimeGPS(coinc_event_vals['time'][idx]))
coinc_inspiral_row.snr = net_snrsq**0.5
coinc_inspiral_row.false_alarm_rate = coinc_event_vals['fap'][idx]
coinc_inspiral_row.combined_far = 1. / coinc_event_vals['ifar'][idx]
# Transform to Hz
coinc_inspiral_row.combined_far = \
coinc_inspiral_row.combined_far / YRJUL_SI
coinc_event_row.likelihood = coinc_event_vals['stat'][idx]
coinc_inspiral_row.minimum_duration = 0.
coinc_event_table.append(coinc_event_row)
coinc_inspiral_table.append(coinc_inspiral_row)
outdoc.childNodes[0].appendChild(coinc_def_table)
outdoc.childNodes[0].appendChild(coinc_event_table)
outdoc.childNodes[0].appendChild(coinc_event_map_table)
outdoc.childNodes[0].appendChild(time_slide_table)
outdoc.childNodes[0].appendChild(coinc_inspiral_table)
outdoc.childNodes[0].appendChild(sngl_inspiral_table)
ligolw_utils.write_filename(outdoc, file_name)
for key, psd in psds.items() if psd is not None
}
# Read injection file.
progress.update(-1, 'reading ' + opts.input.name)
xmldoc, _ = ligolw_utils.load_fileobj(
opts.input, contenthandler=ligolw_bayestar.LSCTablesContentHandler)
# Extract simulation table from injection file.
sim_inspiral_table = ligolw_table.get_table(
xmldoc, lsctables.SimInspiralTable.tableName)
# Create a SnglInspiral table and initialize its row ID counter.
sngl_inspiral_table = lsctables.New(lsctables.SnglInspiralTable)
out_xmldoc.childNodes[0].appendChild(sngl_inspiral_table)
sngl_inspiral_table.set_next_id(lsctables.SnglInspiralID(0))
# Create a time slide entry. Needed for coinc_event rows.
time_slide_table = lsctables.New(lsctables.TimeSlideTable)
out_xmldoc.childNodes[0].appendChild(time_slide_table)
time_slide_id = time_slide_table.get_time_slide_id(
{ifo: 0
for ifo in opts.detector}, create_new=process)
# Create a CoincDef table and record a CoincDef row for
# sngl_inspiral <-> sngl_inspiral coincidences.
coinc_def_table = lsctables.New(lsctables.CoincDefTable)
out_xmldoc.childNodes[0].appendChild(coinc_def_table)
coinc_def = InspiralCoincDef
coinc_def_id = coinc_def_table.get_next_id()
coinc_def.coinc_def_id = coinc_def_id
def __init__(self, ifos, coinc_results, **kwargs):
"""Initialize a ligolw xml representation of a zerolag trigger
for upload from pycbc live to gracedb.
Parameters
----------
ifos: list of strs
A list of the ifos pariticipating in this trigger
coinc_results: dict of values
A dictionary of values. The format is defined in
pycbc/events/coinc.py and matches the on disk representation
in the hdf file for this time.
psds: dict of FrequencySeries
Dictionary providing PSD estimates for all involved detectors.
low_frequency_cutoff: float
Minimum valid frequency for the PSD estimates.
followup_data: dict of dicts, optional
Dictionary providing SNR time series for each detector,
to be used in sky localization with BAYESTAR. The format should
be `followup_data['H1']['snr_series']`. More detectors can be
present than given in `ifos`. If so, the extra detectors will only
be used for sky localization.
channel_names: dict of strings, optional
Strain channel names for each detector.
Will be recorded in the sngl_inspiral table.
"""
self.template_id = coinc_results['foreground/%s/template_id' % ifos[0]]
self.coinc_results = coinc_results
self.ifos = ifos
# remember if this should be marked as HWINJ
self.is_hardware_injection = ('HWINJ' in coinc_results
and coinc_results['HWINJ'])
if 'followup_data' in kwargs:
fud = kwargs['followup_data']
assert len({fud[ifo]['snr_series'].delta_t for ifo in fud}) == 1, \
"delta_t for all ifos do not match"
self.snr_series = {ifo: fud[ifo]['snr_series'] for ifo in fud}
usable_ifos = fud.keys()
followup_ifos = list(set(usable_ifos) - set(ifos))
else:
self.snr_series = None
usable_ifos = ifos
followup_ifos = []
# Set up the bare structure of the xml document
outdoc = ligolw.Document()
outdoc.appendChild(ligolw.LIGO_LW())
proc_id = ligolw_process.register_to_xmldoc(
outdoc, 'pycbc', {}, ifos=usable_ifos, comment='',
version=pycbc_version.git_hash,
cvs_repository='pycbc/'+pycbc_version.git_branch,
cvs_entry_time=pycbc_version.date).process_id
# Set up coinc_definer table
coinc_def_table = lsctables.New(lsctables.CoincDefTable)
coinc_def_id = lsctables.CoincDefID(0)
coinc_def_row = lsctables.CoincDef()
coinc_def_row.search = "inspiral"
coinc_def_row.description = "sngl_inspiral<-->sngl_inspiral coincs"
coinc_def_row.coinc_def_id = coinc_def_id
coinc_def_row.search_coinc_type = 0
coinc_def_table.append(coinc_def_row)
outdoc.childNodes[0].appendChild(coinc_def_table)
# Set up coinc inspiral and coinc event tables
coinc_id = lsctables.CoincID(0)
coinc_event_table = lsctables.New(lsctables.CoincTable)
coinc_event_row = lsctables.Coinc()
coinc_event_row.coinc_def_id = coinc_def_id
coinc_event_row.nevents = len(usable_ifos)
coinc_event_row.instruments = ','.join(usable_ifos)
coinc_event_row.time_slide_id = lsctables.TimeSlideID(0)
coinc_event_row.process_id = proc_id
coinc_event_row.coinc_event_id = coinc_id
coinc_event_row.likelihood = 0.
coinc_event_table.append(coinc_event_row)
outdoc.childNodes[0].appendChild(coinc_event_table)
# Set up sngls
sngl_inspiral_table = lsctables.New(lsctables.SnglInspiralTable)
coinc_event_map_table = lsctables.New(lsctables.CoincMapTable)
sngl_populated = None
network_snrsq = 0
for sngl_id, ifo in enumerate(usable_ifos):
sngl = return_empty_sngl(nones=True)
sngl.event_id = lsctables.SnglInspiralID(sngl_id)
sngl.process_id = proc_id
sngl.ifo = ifo
names = [n.split('/')[-1] for n in coinc_results
if 'foreground/%s' % ifo in n]
for name in names:
val = coinc_results['foreground/%s/%s' % (ifo, name)]
if name == 'end_time':
sngl.set_end(lal.LIGOTimeGPS(val))
else:
try:
setattr(sngl, name, val)
except AttributeError:
pass
if sngl.mass1 and sngl.mass2:
sngl.mtotal, sngl.eta = pnutils.mass1_mass2_to_mtotal_eta(
sngl.mass1, sngl.mass2)
sngl.mchirp, _ = pnutils.mass1_mass2_to_mchirp_eta(
sngl.mass1, sngl.mass2)
sngl_populated = sngl
if sngl.snr:
sngl.eff_distance = (sngl.sigmasq)**0.5 / sngl.snr
network_snrsq += sngl.snr ** 2.0
if 'channel_names' in kwargs and ifo in kwargs['channel_names']:
sngl.channel = kwargs['channel_names'][ifo]
sngl_inspiral_table.append(sngl)
# Set up coinc_map entry
coinc_map_row = lsctables.CoincMap()
coinc_map_row.table_name = 'sngl_inspiral'
coinc_map_row.coinc_event_id = coinc_id
coinc_map_row.event_id = sngl.event_id
coinc_event_map_table.append(coinc_map_row)
if self.snr_series is not None:
snr_series_to_xml(self.snr_series[ifo], outdoc, sngl.event_id)
# for subthreshold detectors, respect BAYESTAR's assumptions and checks
bayestar_check_fields = ('mass1 mass2 mtotal mchirp eta spin1x '
'spin1y spin1z spin2x spin2y spin2z').split()
subthreshold_sngl_time = numpy.mean(
[coinc_results['foreground/{}/end_time'.format(ifo)]
for ifo in ifos])
for sngl in sngl_inspiral_table:
if sngl.ifo in followup_ifos:
for bcf in bayestar_check_fields:
setattr(sngl, bcf, getattr(sngl_populated, bcf))
sngl.set_end(lal.LIGOTimeGPS(subthreshold_sngl_time))
outdoc.childNodes[0].appendChild(coinc_event_map_table)
outdoc.childNodes[0].appendChild(sngl_inspiral_table)
# Set up the coinc inspiral table
coinc_inspiral_table = lsctables.New(lsctables.CoincInspiralTable)
coinc_inspiral_row = lsctables.CoincInspiral()
# This seems to be used as FAP, which should not be in gracedb
coinc_inspiral_row.false_alarm_rate = 0
coinc_inspiral_row.minimum_duration = 0.
coinc_inspiral_row.set_ifos(usable_ifos)
coinc_inspiral_row.coinc_event_id = coinc_id
coinc_inspiral_row.mchirp = sngl_populated.mchirp
coinc_inspiral_row.mass = sngl_populated.mtotal
coinc_inspiral_row.end_time = sngl_populated.end_time
coinc_inspiral_row.end_time_ns = sngl_populated.end_time_ns
coinc_inspiral_row.snr = network_snrsq ** 0.5
far = 1.0 / (lal.YRJUL_SI * coinc_results['foreground/ifar'])
coinc_inspiral_row.combined_far = far
coinc_inspiral_table.append(coinc_inspiral_row)
outdoc.childNodes[0].appendChild(coinc_inspiral_table)
# append the PSDs
self.psds = kwargs['psds']
psds_lal = {}
for ifo in self.psds:
psd = self.psds[ifo]
kmin = int(kwargs['low_frequency_cutoff'] / psd.delta_f)
fseries = lal.CreateREAL8FrequencySeries(
"psd", psd.epoch, kwargs['low_frequency_cutoff'], psd.delta_f,
lal.StrainUnit**2 / lal.HertzUnit, len(psd) - kmin)
fseries.data.data = psd.numpy()[kmin:] / pycbc.DYN_RANGE_FAC ** 2.0
psds_lal[ifo] = fseries
make_psd_xmldoc(psds_lal, outdoc)
self.outdoc = outdoc
self.time = sngl_populated.get_end()
def __init__(self, ifos, coinc_results):
"""Initialize a ligolw xml representation of a zerolag trigger
for upload from pycbc live to gracedb.
Parameters
----------
ifos: list of strs
A list of the ifos pariticipating in this trigger
coinc_results: dict of values
A dictionary of values. The format is define
in pycbc/events/coinc.py
and matches the on disk representation in the hdf file for this time.
"""
# remember if this should be marked as HWINJ
self.is_hardware_injection = False
if 'HWINJ' in coinc_results:
self.is_hardware_injection = True
# Set up the bare structure of the xml document
outdoc = ligolw.Document()
outdoc.appendChild(ligolw.LIGO_LW())
proc_id = ligolw_process.register_to_xmldoc(
outdoc,
'pycbc', {},
ifos=ifos,
comment='',
version=pycbc_version.git_hash,
cvs_repository='pycbc/' + pycbc_version.git_branch,
cvs_entry_time=pycbc_version.date).process_id
# Set up coinc_definer table
coinc_def_table = lsctables.New(lsctables.CoincDefTable)
coinc_def_id = lsctables.CoincDefID(0)
coinc_def_row = lsctables.CoincDef()
coinc_def_row.search = "inspiral"
coinc_def_row.description = "sngl_inspiral<-->sngl_inspiral coincs"
coinc_def_row.coinc_def_id = coinc_def_id
coinc_def_row.search_coinc_type = 0
coinc_def_table.append(coinc_def_row)
outdoc.childNodes[0].appendChild(coinc_def_table)
# Set up coinc inspiral and coinc event tables
coinc_id = lsctables.CoincID(0)
coinc_event_table = lsctables.New(lsctables.CoincTable)
coinc_event_row = lsctables.Coinc()
coinc_event_row.coinc_def_id = coinc_def_id
coinc_event_row.nevents = len(ifos)
coinc_event_row.instruments = ','.join(ifos)
coinc_event_row.time_slide_id = lsctables.TimeSlideID(0)
coinc_event_row.process_id = proc_id
coinc_event_row.coinc_event_id = coinc_id
coinc_event_row.likelihood = 0.
coinc_event_table.append(coinc_event_row)
outdoc.childNodes[0].appendChild(coinc_event_table)
# Set up sngls
sngl_inspiral_table = lsctables.New(lsctables.SnglInspiralTable)
coinc_event_map_table = lsctables.New(lsctables.CoincMapTable)
sngl_id = 0
for ifo in ifos:
names = [
n.split('/')[-1] for n in coinc_results
if 'foreground/%s' % ifo in n
]
sngl_id += 1
sngl = return_empty_sngl()
sngl.event_id = lsctables.SnglInspiralID(sngl_id)
sngl.ifo = ifo
for name in names:
val = coinc_results['foreground/%s/%s' % (ifo, name)]
if name == 'end_time':
sngl.set_end(LIGOTimeGPS(val))
else:
try:
setattr(sngl, name, val)
except AttributeError:
pass
sngl.mtotal, sngl.eta = pnutils.mass1_mass2_to_mtotal_eta(
sngl.mass1, sngl.mass2)
sngl.mchirp, _ = pnutils.mass1_mass2_to_mchirp_eta(
sngl.mass1, sngl.mass2)
sngl.eff_distance = (sngl.sigmasq)**0.5 / sngl.snr
sngl_inspiral_table.append(sngl)
# Set up coinc_map entry
coinc_map_row = lsctables.CoincMap()
coinc_map_row.table_name = 'sngl_inspiral'
coinc_map_row.coinc_event_id = coinc_id
coinc_map_row.event_id = sngl.event_id
coinc_event_map_table.append(coinc_map_row)
outdoc.childNodes[0].appendChild(coinc_event_map_table)
outdoc.childNodes[0].appendChild(sngl_inspiral_table)
# Set up the coinc inspiral table
coinc_inspiral_table = lsctables.New(lsctables.CoincInspiralTable)
coinc_inspiral_row = lsctables.CoincInspiral()
# This seems to be used as FAP, which should not be in gracedb
coinc_inspiral_row.false_alarm_rate = 0
coinc_inspiral_row.minimum_duration = 0.
coinc_inspiral_row.set_ifos(ifos)
coinc_inspiral_row.coinc_event_id = coinc_id
coinc_inspiral_row.mchirp = sngl.mchirp
coinc_inspiral_row.mass = sngl.mtotal
coinc_inspiral_row.end_time = sngl.end_time
coinc_inspiral_row.end_time_ns = sngl.end_time_ns
coinc_inspiral_row.snr = coinc_results['foreground/stat']
far = 1.0 / (YRJUL_SI * coinc_results['foreground/ifar'])
coinc_inspiral_row.combined_far = far
coinc_inspiral_table.append(coinc_inspiral_row)
outdoc.childNodes[0].appendChild(coinc_inspiral_table)
self.outdoc = outdoc
def new(self, row):
self.n += 1
a = self.n // 100000
b = self.n % 100000
return lsctables.SnglInspiralID(a * 1000000000 +
row.get_id_parts()[1] * 100000 + b)
def __init__(self, ifos, coinc_results, **kwargs):
"""Initialize a ligolw xml representation of a zerolag trigger
for upload from pycbc live to gracedb.
Parameters
----------
ifos: list of strs
A list of the ifos pariticipating in this trigger
coinc_results: dict of values
A dictionary of values. The format is defined in
pycbc/events/coinc.py and matches the on disk representation
in the hdf file for this time.
"""
self.ifos = ifos
if 'followup_ifos' in kwargs and kwargs['followup_ifos'] is not None:
self.followup_ifos = kwargs['followup_ifos']
else:
self.followup_ifos = []
self.template_id = coinc_results['foreground/%s/template_id' %
self.ifos[0]]
# remember if this should be marked as HWINJ
self.is_hardware_injection = ('HWINJ' in coinc_results)
# Set up the bare structure of the xml document
outdoc = ligolw.Document()
outdoc.appendChild(ligolw.LIGO_LW())
proc_id = ligolw_process.register_to_xmldoc(
outdoc,
'pycbc', {},
ifos=ifos,
comment='',
version=pycbc_version.git_hash,
cvs_repository='pycbc/' + pycbc_version.git_branch,
cvs_entry_time=pycbc_version.date).process_id
# Set up coinc_definer table
coinc_def_table = lsctables.New(lsctables.CoincDefTable)
coinc_def_id = lsctables.CoincDefID(0)
coinc_def_row = lsctables.CoincDef()
coinc_def_row.search = "inspiral"
coinc_def_row.description = "sngl_inspiral<-->sngl_inspiral coincs"
coinc_def_row.coinc_def_id = coinc_def_id
coinc_def_row.search_coinc_type = 0
coinc_def_table.append(coinc_def_row)
outdoc.childNodes[0].appendChild(coinc_def_table)
# Set up coinc inspiral and coinc event tables
coinc_id = lsctables.CoincID(0)
coinc_event_table = lsctables.New(lsctables.CoincTable)
coinc_event_row = lsctables.Coinc()
coinc_event_row.coinc_def_id = coinc_def_id
coinc_event_row.nevents = len(ifos)
coinc_event_row.instruments = ','.join(ifos)
coinc_event_row.time_slide_id = lsctables.TimeSlideID(0)
coinc_event_row.process_id = proc_id
coinc_event_row.coinc_event_id = coinc_id
coinc_event_row.likelihood = 0.
coinc_event_table.append(coinc_event_row)
outdoc.childNodes[0].appendChild(coinc_event_table)
# Set up sngls
sngl_inspiral_table = lsctables.New(lsctables.SnglInspiralTable)
coinc_event_map_table = lsctables.New(lsctables.CoincMapTable)
sngl_event_id_map = {}
sngl_populated = None
for sngl_id, ifo in enumerate(ifos + self.followup_ifos):
sngl = return_empty_sngl(nones=True)
sngl.event_id = lsctables.SnglInspiralID(sngl_id)
sngl_event_id_map[ifo] = sngl.event_id
sngl.process_id = proc_id
sngl.ifo = ifo
names = [
n.split('/')[-1] for n in coinc_results
if 'foreground/%s' % ifo in n
]
for name in names:
val = coinc_results['foreground/%s/%s' % (ifo, name)]
if name == 'end_time':
sngl.set_end(lal.LIGOTimeGPS(val))
else:
try:
setattr(sngl, name, val)
except AttributeError:
pass
if sngl.mass1 and sngl.mass2:
sngl.mtotal, sngl.eta = pnutils.mass1_mass2_to_mtotal_eta(
sngl.mass1, sngl.mass2)
sngl.mchirp, _ = pnutils.mass1_mass2_to_mchirp_eta(
sngl.mass1, sngl.mass2)
sngl_populated = sngl
if sngl.snr:
sngl.eff_distance = (sngl.sigmasq)**0.5 / sngl.snr
sngl_inspiral_table.append(sngl)
# Set up coinc_map entry
coinc_map_row = lsctables.CoincMap()
coinc_map_row.table_name = 'sngl_inspiral'
coinc_map_row.coinc_event_id = coinc_id
coinc_map_row.event_id = sngl.event_id
coinc_event_map_table.append(coinc_map_row)
# for subthreshold detectors, respect BAYESTAR's assumptions and checks
bayestar_check_fields = ('mass1 mass2 mtotal mchirp eta spin1x '
'spin1y spin1z spin2x spin2y spin2z').split()
subthreshold_sngl_time = numpy.mean(
[coinc_results['foreground/%s/end_time' % ifo] for ifo in ifos])
for sngl in sngl_inspiral_table:
if sngl.ifo in self.followup_ifos:
for bcf in bayestar_check_fields:
setattr(sngl, bcf, getattr(sngl_populated, bcf))
sngl.set_end(lal.LIGOTimeGPS(subthreshold_sngl_time))
outdoc.childNodes[0].appendChild(coinc_event_map_table)
outdoc.childNodes[0].appendChild(sngl_inspiral_table)
# Set up the coinc inspiral table
coinc_inspiral_table = lsctables.New(lsctables.CoincInspiralTable)
coinc_inspiral_row = lsctables.CoincInspiral()
# This seems to be used as FAP, which should not be in gracedb
coinc_inspiral_row.false_alarm_rate = 0
coinc_inspiral_row.minimum_duration = 0.
coinc_inspiral_row.set_ifos(ifos)
coinc_inspiral_row.coinc_event_id = coinc_id
coinc_inspiral_row.mchirp = sngl_populated.mchirp
coinc_inspiral_row.mass = sngl_populated.mtotal
coinc_inspiral_row.end_time = sngl_populated.end_time
coinc_inspiral_row.end_time_ns = sngl_populated.end_time_ns
coinc_inspiral_row.snr = coinc_results['foreground/stat']
far = 1.0 / (lal.YRJUL_SI * coinc_results['foreground/ifar'])
coinc_inspiral_row.combined_far = far
coinc_inspiral_table.append(coinc_inspiral_row)
outdoc.childNodes[0].appendChild(coinc_inspiral_table)
self.outdoc = outdoc
self.time = sngl_populated.get_end()
# compute SNR time series
self.upload_snr_series = kwargs['upload_snr_series']
if self.upload_snr_series:
htilde = kwargs['bank'][self.template_id]
self.snr_series = {}
self.snr_series_psd = {}
for ifo in self.ifos + self.followup_ifos:
if ifo in ifos:
trig_time = coinc_results['foreground/%s/end_time' % ifo]
else:
trig_time = subthreshold_sngl_time
self.snr_series[ifo], self.snr_series_psd[ifo] = \
compute_followup_snr_series(
kwargs['data_readers'][ifo], htilde,
trig_time)
snr_series_to_xml(self.snr_series[ifo], outdoc,
sngl_event_id_map[ifo])
def find_slide_coincs(htrigs, ltrigs, min_mchirp, max_mchirp, ethinca, slide,
threshold):
""" Calculate coincs from single detector triggers. We window based on
mchirp, apply a new snr threshold, and only keep triggers that lie on a
slide boundary.
"""
coinc_sngls = lsctables.New(lsctables.SnglInspiralTable)
num_trig = 0
t_snrsq = float(threshold)**2
# Collect the mchirp, new snr, and end time of the second detector's
# triggers into numpy arrays for faster math operations later.
l_ends = []
lt_mc = []
lt_sn = []
lt_en = []
for l in ltrigs:
lt_mc.append(l.mchirp)
lt_sn.append(l.get_new_snr()**2)
lt_en.append(float(l.get_end()))
lt_mc = numpy.array(lt_mc)
lt_sn = numpy.array(lt_sn)
lt_en = numpy.array(lt_en)
# The list of index location of "good" triggers in the second detector
# good triggers are ones that might possibly still form coincs with the
# first detector's triggers. Initially, this is all of them.
loc = numpy.arange(0, len(ltrigs))
# Sort the first detector's triggers by newsnr ascending
stats = []
htrigs.sort(lambda a, b: cmp(a.get_new_snr(), b.get_new_snr()),
reverse=True)
# Iterate over each of the first detector's triggers and calculate what
# coincs it will generate with the second detector's triggers
for h in htrigs:
h_end = float(h.get_end())
h_mchirp = h.mchirp
h_max_td = max_dt(h, ethinca)
h_snrsq = h.get_new_snr()**2
r_snrsq = t_snrsq - h_snrsq
lind = 0
# Grab only the information about triggers that could still form
# coincs
lt_snl = lt_sn[loc]
lt_mcl = lt_mc[loc]
lt_enl = lt_en[loc]
# Determine the time difference between these triggers and the
# considered "h" trigger
num_slides = numpy.round((h_end - lt_enl) / slide)
lt_en_tmp = lt_enl + num_slides * slide
td = abs(h_end - lt_en_tmp)
# Get location of coincs that are above the coinc new snr threshold
# Triggers that fall below this threshold are never considered again
goods = (lt_snl >= r_snrsq)
# Get the location of coincs that pass the rough time coincidence
# and are within the mchirp bin. We calculate ethinca only for these.
good = goods & (td <= h_max_td) & (
lt_mcl >= 2 * min_mchirp - h_mchirp) & (lt_mcl <=
2 * max_mchirp - h_mchirp)
# For each remaining trigger we calculate the ethinca test and add
# to the list of coincs if they pass
for lind, ns in zip(loc[good], num_slides[good]):
# don't allow zerolag or offsets too close to it!
if abs(slide * ns) < 0.1:
continue
# Get the single inspiral trigger and apply the time offset
# so that we can perform coincidence
l = ltrigs[lind]
l_end_old = l.get_end()
l_end_tmp = l_end_old + float(slide * ns)
l.set_end(l_end_tmp)
epar = XLALCalculateEThincaParameter(h, l)
# If we pass coincidence we add the first and second detector
# trigger pair to the output list
if epar < ethinca:
# This should never happen
if abs(slide * ns) < 0.1:
print 'I USED ZEROLAG!!'
exit(1)
hcopy = copy.deepcopy(h)
l.set_end(h.get_end())
lcopy = copy.deepcopy(l)
hcopy.event_id = lsctables.SnglInspiralID(num_trig)
lcopy.event_id = lsctables.SnglInspiralID(num_trig)
num_trig += 1
coinc_sngls.append(hcopy)
coinc_sngls.append(lcopy)
l.set_end(l_end_old)
# Finally set the list of second triggers to consider to the reduced
# set that are still above the coinc new snr threshold
loc = loc[goods]
# No more triggers to consider
if len(loc) == 0:
break
return (coinc_sngls)
def __init__(self, ifos, coinc_results, **kwargs):
"""Initialize a ligolw xml representation of a zerolag trigger
for upload from pycbc live to gracedb.
Parameters
----------
ifos: list of strs
A list of the ifos pariticipating in this trigger
coinc_results: dict of values
A dictionary of values. The format is define
in pycbc/events/coinc.py
and matches the on disk representation in the hdf file for this time.
"""
self.ifos = ifos
self.template_id = coinc_results['foreground/%s/template_id' %
self.ifos[0]]
# remember if this should be marked as HWINJ
self.is_hardware_injection = False
if 'HWINJ' in coinc_results:
self.is_hardware_injection = True
# Set up the bare structure of the xml document
outdoc = ligolw.Document()
outdoc.appendChild(ligolw.LIGO_LW())
proc_id = ligolw_process.register_to_xmldoc(
outdoc,
'pycbc', {},
ifos=ifos,
comment='',
version=pycbc_version.git_hash,
cvs_repository='pycbc/' + pycbc_version.git_branch,
cvs_entry_time=pycbc_version.date).process_id
# Set up coinc_definer table
coinc_def_table = lsctables.New(lsctables.CoincDefTable)
coinc_def_id = lsctables.CoincDefID(0)
coinc_def_row = lsctables.CoincDef()
coinc_def_row.search = "inspiral"
coinc_def_row.description = "sngl_inspiral<-->sngl_inspiral coincs"
coinc_def_row.coinc_def_id = coinc_def_id
coinc_def_row.search_coinc_type = 0
coinc_def_table.append(coinc_def_row)
outdoc.childNodes[0].appendChild(coinc_def_table)
# Set up coinc inspiral and coinc event tables
coinc_id = lsctables.CoincID(0)
coinc_event_table = lsctables.New(lsctables.CoincTable)
coinc_event_row = lsctables.Coinc()
coinc_event_row.coinc_def_id = coinc_def_id
coinc_event_row.nevents = len(ifos)
coinc_event_row.instruments = ','.join(ifos)
coinc_event_row.time_slide_id = lsctables.TimeSlideID(0)
coinc_event_row.process_id = proc_id
coinc_event_row.coinc_event_id = coinc_id
coinc_event_row.likelihood = 0.
coinc_event_table.append(coinc_event_row)
outdoc.childNodes[0].appendChild(coinc_event_table)
# Set up sngls
sngl_inspiral_table = lsctables.New(lsctables.SnglInspiralTable)
coinc_event_map_table = lsctables.New(lsctables.CoincMapTable)
sngl_id = 0
sngl_event_id_map = {}
for ifo in ifos:
names = [
n.split('/')[-1] for n in coinc_results
if 'foreground/%s' % ifo in n
]
sngl_id += 1
sngl = return_empty_sngl()
sngl.event_id = lsctables.SnglInspiralID(sngl_id)
sngl_event_id_map[ifo] = sngl.event_id
sngl.ifo = ifo
for name in names:
val = coinc_results['foreground/%s/%s' % (ifo, name)]
if name == 'end_time':
sngl.set_end(lal.LIGOTimeGPS(val))
else:
try:
setattr(sngl, name, val)
except AttributeError:
pass
sngl.mtotal, sngl.eta = pnutils.mass1_mass2_to_mtotal_eta(
sngl.mass1, sngl.mass2)
sngl.mchirp, _ = pnutils.mass1_mass2_to_mchirp_eta(
sngl.mass1, sngl.mass2)
sngl.eff_distance = (sngl.sigmasq)**0.5 / sngl.snr
sngl_inspiral_table.append(sngl)
# Set up coinc_map entry
coinc_map_row = lsctables.CoincMap()
coinc_map_row.table_name = 'sngl_inspiral'
coinc_map_row.coinc_event_id = coinc_id
coinc_map_row.event_id = sngl.event_id
coinc_event_map_table.append(coinc_map_row)
outdoc.childNodes[0].appendChild(coinc_event_map_table)
outdoc.childNodes[0].appendChild(sngl_inspiral_table)
# Set up the coinc inspiral table
coinc_inspiral_table = lsctables.New(lsctables.CoincInspiralTable)
coinc_inspiral_row = lsctables.CoincInspiral()
# This seems to be used as FAP, which should not be in gracedb
coinc_inspiral_row.false_alarm_rate = 0
coinc_inspiral_row.minimum_duration = 0.
coinc_inspiral_row.set_ifos(ifos)
coinc_inspiral_row.coinc_event_id = coinc_id
coinc_inspiral_row.mchirp = sngl.mchirp
coinc_inspiral_row.mass = sngl.mtotal
coinc_inspiral_row.end_time = sngl.end_time
coinc_inspiral_row.end_time_ns = sngl.end_time_ns
coinc_inspiral_row.snr = coinc_results['foreground/stat']
far = 1.0 / (lal.YRJUL_SI * coinc_results['foreground/ifar'])
coinc_inspiral_row.combined_far = far
coinc_inspiral_table.append(coinc_inspiral_row)
outdoc.childNodes[0].appendChild(coinc_inspiral_table)
self.outdoc = outdoc
self.time = sngl.get_end()
# compute SNR time series
self.upload_snr_series = kwargs['upload_snr_series']
if self.upload_snr_series:
data_readers = kwargs['data_readers']
bank = kwargs['bank']
htilde = bank[self.template_id]
self.snr_series = {}
self.snr_series_psd = {}
for ifo in self.ifos:
stilde = data_readers[ifo].overwhitened_data(htilde.delta_f)
norm = 4.0 * htilde.delta_f / (htilde.sigmasq(stilde.psd)**0.5)
qtilde = zeros((len(htilde) - 1) * 2, dtype=htilde.dtype)
correlate(htilde, stilde, qtilde)
snr = qtilde * 0
ifft(qtilde, snr)
valid_end = int(len(qtilde) - data_readers[ifo].trim_padding)
valid_start = int(valid_end - data_readers[ifo].blocksize *
data_readers[ifo].sample_rate)
seg = slice(valid_start, valid_end)
snr = snr[seg]
snr *= norm
delta_t = 1.0 / data_readers[ifo].sample_rate
start = data_readers[ifo].start_time
snr = TimeSeries(snr, delta_t=delta_t, epoch=start)
self.snr_series[ifo] = snr
self.snr_series_psd[ifo] = stilde.psd
# store the on-source slice of the series into the XML doc
snr_onsource_time = coinc_results['foreground/%s/end_time' %
ifo] - snr.start_time
snr_onsource_dur = lal.REARTH_SI / lal.C_SI
onsource_idx = round(snr_onsource_time * snr.sample_rate)
onsource_start = onsource_idx - int(
snr.sample_rate * snr_onsource_dur / 2)
onsource_end = onsource_idx + int(
snr.sample_rate * snr_onsource_dur / 2)
onsource_slice = slice(onsource_start, onsource_end + 1)
snr_lal = snr[onsource_slice].lal()
snr_lal.name = 'snr'
snr_lal.sampleUnits = ''
snr_xml = _build_series(snr_lal,
(u'Time', u'Time,Real,Imaginary'),
None, 'deltaT', 's')
snr_node = outdoc.childNodes[-1].appendChild(snr_xml)
eid_param = ligolw_param.new_param(
u'event_id', u'ilwd:char', unicode(sngl_event_id_map[ifo]))
snr_node.appendChild(eid_param)
