Beispiel #1
0
class SimInspiral(lsctables.SimInspiral):
    pass


lsctables.SimInspiralTable.RowType = lsctables.SimInspiral = SimInspiral

#
# =============================================================================
#
#                              Document Interface
#
# =============================================================================
#

ExcessPowerSBBCoincDef = lsctables.CoincDef(
    search=u"excesspower",
    search_coinc_type=1,
    description=u"sim_burst<-->sngl_burst coincidences")
ExcessPowerSIBCoincDef = lsctables.CoincDef(
    search=u"excesspower",
    search_coinc_type=4,
    description=u"sim_inspiral<-->sngl_burst coincidences")
ExcessPowerSBCCoincDef = lsctables.CoincDef(
    search=u"excesspower",
    search_coinc_type=2,
    description=u"sim_burst<-->coinc_event coincidences (exact)")
ExcessPowerSBCNearCoincDef = lsctables.CoincDef(
    search=u"excesspower",
    search_coinc_type=3,
    description=u"sim_burst<-->coinc_event coincidences (nearby)")
ExcessPowerSICCoincDef = lsctables.CoincDef(
    search=u"excesspower",
Beispiel #2
0
@lsctables.use_in
class LIGOLWContentHandler(ligolw.LIGOLWContentHandler):
	pass


#
# =============================================================================
#
#                              Document Interface
#
# =============================================================================
#


InspiralSICoincDef = lsctables.CoincDef(search = u"inspiral", search_coinc_type = 1, description = u"sim_inspiral<-->sngl_inspiral coincidences")
InspiralSCNearCoincDef = lsctables.CoincDef(search = u"inspiral", search_coinc_type = 2, description = u"sim_inspiral<-->coinc_event coincidences (nearby)")
InspiralSCExactCoincDef = lsctables.CoincDef(search = u"inspiral", search_coinc_type = 3, description = u"sim_inspiral<-->coinc_event coincidences (exact)")
InspiralSTCoincDef = lsctables.CoincDef(search = u"inspiral", search_coinc_type = 4, description = u"sim_inspiral<-->sngl_inspiral template coincidences")


class DocContents(object):
	"""
	A wrapper interface to the XML document.
	"""
	def __init__(self, xmldoc, bbdef, sbdef, scedef, scndef, process, end_time_bisect_window):
		#
		# store the process row
		#

		self.process = process
Beispiel #3
0
    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 participating 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.
        high_frequency_cutoff: float, optional
            Maximum frequency considered for the PSD estimates. Default None.
        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.
        mc_area_args: dict of dicts, optional
            Dictionary providing arguments to be used in source probability
            estimation with pycbc/mchirp_area.py
        """
        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'])

        # Check if we need to apply a time offset (this may be permerger)
        self.time_offset = 0
        rtoff = 'foreground/{}/time_offset'.format(ifos[0])
        if rtoff in coinc_results:
            self.time_offset = coinc_results[rtoff]

        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))

            for ifo in self.snr_series:
                self.snr_series[ifo].start_time += self.time_offset
        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())

        # FIXME is it safe (in terms of downstream operations) to let
        # `program_name` default to the actual script name?
        proc_id = create_process_table(outdoc,
                                       program_name='pycbc',
                                       detectors=usable_ifos).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':
                    val += self.time_offset
                    sngl.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)

        # set merger time to the average of the ifo peaks
        self.merger_time = numpy.mean([
            coinc_results['foreground/{}/end_time'.format(ifo)] for ifo in ifos
        ]) + self.time_offset

        # for subthreshold detectors, respect BAYESTAR's assumptions and checks
        bayestar_check_fields = ('mass1 mass2 mtotal mchirp eta spin1x '
                                 'spin1y spin1z spin2x spin2y spin2z').split()
        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.end = lal.LIGOTimeGPS(self.merger_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.instruments = tuple(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)

        # source probabilities estimation
        if 'mc_area_args' in kwargs:
            eff_distances = [sngl.eff_distance for sngl in sngl_inspiral_table]
            probabilities = calc_probabilities(coinc_inspiral_row.mchirp,
                                               coinc_inspiral_row.snr,
                                               min(eff_distances),
                                               kwargs['mc_area_args'])
            self.probabilities = probabilities
        else:
            self.probabilities = None

        self.outdoc = outdoc
        self.time = sngl_populated.end
Beispiel #4
0
#
# =============================================================================
#
#                          CoincTables Customizations
#
# =============================================================================
#


#
# The sngl_inspiral <--> sngl_inspiral coinc type.
#


InspiralCoincDef = lsctables.CoincDef(search = u"inspiral", search_coinc_type = 0, description = u"sngl_inspiral<-->sngl_inspiral coincidences")


#
# Definition of coinc_inspiral.end_time
#


def coinc_inspiral_end_time(events, offset_vector):
	"""
	Compute the end time of an inspiral coincidence.  events is an
	iterable of sngl_inspiral triggers, offset_vector is a dictionary
	mapping instrument to offset.

	This function returns the time shifted end time of the trigger with
	the highest SNR.  The end time reported by this function gets used
Beispiel #5
0

#
# =============================================================================
#
#                          CoincTables Customizations
#
# =============================================================================
#

#
# For use with excess power.
#

ExcessPowerBBCoincDef = lsctables.CoincDef(
    search=u"excesspower",
    search_coinc_type=0,
    description=u"sngl_burst<-->sngl_burst coincidences")


class ExcessPowerCoincTables(snglcoinc.CoincTables):
    def __init__(self, xmldoc):
        super(ExcessPowerCoincTables, self).__init__(xmldoc)

        # find the multi_burst table or create one if not found
        try:
            self.multibursttable = lsctables.MultiBurstTable.get_table(xmldoc)
        except ValueError:
            self.multibursttable = lsctables.New(
                lsctables.MultiBurstTable,
                ("process_id", "duration", "central_freq", "bandwidth", "snr",
                 "confidence", "amplitude", "coinc_event_id"))