Exemplo n.º 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",
Exemplo n.º 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
Exemplo n.º 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
Exemplo n.º 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
Exemplo n.º 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"))