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from django.db import models, IntegrityError

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from django.core.exceptions import ValidationError
from django.utils.translation import ugettext_lazy as _
from model_utils.managers import InheritanceManager

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#from django.contrib.auth.models import User as DjangoUser
#from django.contrib.auth.models import Group

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from django.contrib.auth import get_user_model

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from django.contrib.contenttypes.models import ContentType

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from guardian.models import GroupObjectPermission
import logging; log = logging.getLogger(__name__)
import glue
import glue.ligolw
import glue.ligolw.utils
import glue.ligolw.table
import glue.ligolw.lsctables
from glue.ligolw.ligolw import LIGOLWContentHandler

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import json, re

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from core.models import AutoIncrementModel, CleanSaveModel
from core.models import LogBase, m2mThroughBase
from django.conf import settings
import pytz
import calendar
from cStringIO import StringIO
from hashlib import sha1

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import shutil

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UserModel = get_user_model()
SERVER_TZ = pytz.timezone(settings.TIME_ZONE)
# Let's say we start here on schema versions
#
# 1.0 -> 1.1 changed EventLog.comment from CharField(length=200) -> TextField
#
schema_version = "1.1"
#class User(models.Model):
#name = models.CharField(max_length=100)
#email = models.EmailField()
#principal = models.CharField(max_length=100)
#dn = models.CharField(max_length=100)
#unixid = models.CharField(max_length=25)
#class Meta:
#ordering = ["name"]
#def __unicode__(self):
#return self.name
class Group(models.Model):
name = models.CharField(max_length=20)
def __unicode__(self):
return self.name
class Pipeline(models.Model):
name = models.CharField(max_length=100)
# XXX Need any additional fields? Like a librarian email? Or perhaps even fk?
def __unicode__(self):
return self.name
class Search(models.Model):
name = models.CharField(max_length=100)
description = models.TextField(blank=True)
# XXX Need any additional fields? Like a PI email? Or perhaps even fk?
def __unicode__(self):
return self.name
# Label color will be used in CSS, see
# https://www.w3schools.com/colors/colors_names.asp for
# allowed color choices
name = models.CharField(max_length=20, unique=True)
# XXX really, does this belong here? probably not.

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defaultColor = models.CharField(max_length=20, unique=False,
default="black")
description = models.TextField(blank=False)

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DEFAULT_PIPELINE_ID = 1
objects = InheritanceManager() # Queries can return subclasses, if available.
# ANALYSIS_TYPE_CHOICES = (
# ("LM", "LowMass"),
# ("HM", "HighMass"),
# ("GRB", "GRB"),
# ("RD", "Ringdown"),
# ("OM", "Omega"),
# ("Q", "Q"),
# ("X", "X"),
# ("CWB", "CWB"),
# ("MBTA", "MBTAOnline"),
# ("HWINJ", "HardwareInjection"),
# )
DEFAULT_EVENT_NEIGHBORHOOD = (-5,5)

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submitter = models.ForeignKey(UserModel)
created = models.DateTimeField(auto_now_add=True)
group = models.ForeignKey(Group)
#uid = models.CharField(max_length=20, default="") # XXX deprecated. should be removed.
#analysisType = models.CharField(max_length=20, choices=ANALYSIS_TYPE_CHOICES)

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# Events aren't required to be part of a superevent. If the superevent is
# deleted, don't delete the event; just set this FK to null.
superevent = models.ForeignKey('superevents.Superevent', null=True,
related_name='events', on_delete=models.SET_NULL)

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# Note: a default value is needed only during the schema migration
# that creates this column. After that, we can safely remove it.
# The presence or absence of the default value has no effect on the DB
# tables, so removing it does not necessitate a migration.
#pipeline = models.ForeignKey(Pipeline, default=DEFAULT_PIPELINE_ID)
pipeline = models.ForeignKey(Pipeline)
search = models.ForeignKey(Search, null=True)
instruments = models.CharField(max_length=20, default="")
nevents = models.PositiveIntegerField(null=True)
likelihood = models.FloatField(null=True)
# NOT from coinc_event, but so, so common.
# Note that the semantics for this is different depending
# on search type, so in some sense, querying on this may
# be considered, umm, wrong? But it is a starting point.
#gpstime = models.PositiveIntegerField(null=True)
gpstime = models.DecimalField(max_digits=16, decimal_places=6, null=True)
labels = models.ManyToManyField(Label, through="Labelling")

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# This field will store a JSON-serialized list of permissions, of the
# form <group name>_can_<permission codename>
# This obviously duplicates information that is already in the database
# in the form of GroupObjectPermission objects. Such duplication is
# normally a bad thing, as it can lead to divergence. But we're going
# to try really hard to avoid that. And it may help speed up the
# searches quite considerably.
perms = models.TextField(null=True)

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# Boolean which determines whether the event was submitted by an offline
# analysis (True) or an online/low-latency analysis (False). Because this
# is being implemented during a run (O2), we use a default value of False
# so as to ensure backwards-compatibility; i.e., all events treated as
# "online" by default.
offline = models.BooleanField(default=False)
class Meta:
ordering = ["-id"]
def graceid(self):
if self.group.name == "Test":
elif str(self.search) == str("MDC"):
return "M%04d" % self.id

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elif self.pipeline.name == "HardwareInjection":
return "H%04d" % self.id
elif self.group.name == "External":
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return "E%04d" % self.id
return "G%04d" % self.id
# XXX Not good. But then, it never was.
return reverse('file_list', args=[self.graceid()])
@property
def datadir(self):
# Create a file-like object which is the SHA-1 hexdigest of the Event's primary key
hdf = StringIO(sha1(str(self.id)).hexdigest())
# Build up the nodes of the directory structure
nodes = [hdf.read(i) for i in settings.GRACEDB_DIR_DIGITS]
# Read whatever is left over. This is the 'leaf' directory.
nodes.append(hdf.read())
return os.path.join(settings.GRACEDB_DATA_DIR, *nodes)
def reportingLatency(self):
if self.gpstime:
dt = self.created
if not dt.tzinfo:
dt = SERVER_TZ.localize(dt)
dt = dt.astimezone(pytz.utc)
posix_time = calendar.timegm(dt.timetuple())
gps_time = int(posixToGpsTime(posix_time))
return gps_time - self.gpstime
def neighbors(self, neighborhood=None):
if not self.gpstime:
return []
if self.group.name == 'Test':
nearby = Event.objects.filter(group__name='Test')
else:
nearby = Event.objects.exclude(group__name='Test')
delta1, delta2 = neighborhood or self.DEFAULT_EVENT_NEIGHBORHOOD
nearby = nearby.filter(gpstime__range=(self.gpstime+delta1, self.gpstime+delta2))
nearby = nearby.exclude(id=self.id)
nearby = nearby.distinct()
nearby = nearby.order_by('gpstime')
return nearby
@classmethod
def getTypeLabel(cls, code):
for key, label in cls.ANALYSIS_TYPE_CHOICES:
if (key == code) or (code == label):
return label
raise KeyError("Unknown analysis type code: %s" % code)
try:
e = cls.objects.filter(id=int(id[1:])).select_subclasses()[0]
except IndexError:
raise cls.DoesNotExist("Event matching query does not exist")
if (id[0] == "T") and (e.group.name == "Test"):
return e
if (id[0] == "H") and (e.pipeline.name == "HardwareInjection"):
if (id[0] == "E") and (e.group.name == "External"):
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return e
if (id[0] == "M") and (e.search and e.search.name == "MDC"):
if (id[0] == "G"):
return e
raise cls.DoesNotExist("Event matching query does not exist")
def __unicode__(self):
return self.graceid()
# Return a list of distinct tags associated with the log messages of this
# event.
def getAvailableTags(self):

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tagset_list = [log.tags.all() for log in self.eventlog_set.all()]
taglist = []
for tagset in tagset_list:
for tag in tagset:
taglist.append(tag)
# Eliminate duplicates
taglist = list(set(taglist))
# Ordering should match the ordering of blessed tags list.
# XXX Possibly, there are smarter ways of doing this.
if settings.BLESSED_TAGS:
availableTags = []
for blessed_tag in settings.BLESSED_TAGS:
for tag in taglist:
if tag.name == blessed_tag:
taglist.remove(tag)
availableTags.append(tag)
# Append any remaining tags at the end of the list
if len(taglist)>0:
for tag in taglist:
availableTags.append(tag)
else:
availableTags = taglist
return availableTags
def getLogsForTag(self,tagname):
loglist = []
for log in self.eventlog_set.all():

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for tag in log.tags.all():
if tag.name==tagname:
loglist.append(log)
return loglist

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# A method to update the permissions according to the permission objects in

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# the database.
def refresh_perms(self):
# Content type is 'Event', obvs.
content_type = ContentType.objects.get(app_label='events', model='event')

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# Get all of the GroupObjectPermissions for this object id and content type

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group_object_perms = GroupObjectPermission.objects.filter(object_pk=self.id,
content_type=content_type)
perm_strings = []
# Make a list of permission strings
for obj in group_object_perms:
perm_strings.append('%s_can_%s' % (obj.group.name, obj.permission.codename.split('_')[0]))
# Serialize as json.
self.perms = json.dumps(perm_strings)
# Fool! Save yourself!
self.save()

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def delete(self, purge=False, *args, **kwargs):
"""
Optionally override the delete method for Event models.
By default, deleting an Event deletes corresponding subclasses

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(GrbEvent, CoincInspiralEvent, etc.) and EventLogs, EMObservations,

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etc., but does not remove the data directory or the
GroupObjectPermissions corresponding to the Event or its subclasses.
Usage:
event.delete() will do the basic delete, just as before
event.delete(purge=True) will also remove the data directory
and GroupObjectPermissions for the Event and its subclasses
"""
if purge:
# Delete data directory
datadir = self.datadir

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if os.path.isdir(datadir):
shutil.rmtree(datadir)
# Delete any GroupObjectPermissions for this event and its
# subclasses (MultiBurstEvent, CoincInspiralEvent, etc.)
cls = self.__class__
subclasses = [f.related_model for f in cls._meta.get_fields()
if (f.one_to_one and f.auto_created and not f.concrete and
cls in f.related_model.__bases__)]
for m in subclasses + [cls]:
ctype = ContentType.objects.get_for_model(m)
gops = GroupObjectPermission.objects.filter(object_pk=self.id,
content_type=ctype)
gops.delete()
# Call base class delete
super(Event, self).delete(*args, **kwargs)

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class EventLog(CleanSaveModel, LogBase, AutoIncrementModel):

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"""

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Log message object attached to an Event. Uses the AutoIncrementModel
to handle log enumeration on a per-Event basis.

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"""

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AUTO_FIELD = 'N'
AUTO_CONSTRAINT = 'event'

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# Extra fields

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tags = models.ManyToManyField('Tag', related_name='event_logs')
class Meta(LogBase.Meta):
unique_together = (('event', 'N'),)
return reverse('file-download', args=[self.event.graceid(),

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class EMGroup(models.Model):
name = models.CharField(max_length=50, unique=True)

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# XXX what else? Possibly the liasons. These can be populated
# automatically from the gw-astronomy COManage-provisioned LDAP.

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# Let's leave this out for now. The submitter will be stored in
# the EMBB log record, and that should be enough for audit/blame
# purposes.

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#liasons = models.ManyToManyField(UserModel)
def __unicode__(self):
return self.name

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class EMObservationBase(models.Model):
"""Abstract base class for EM follow-up observation records"""
class Meta:

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abstract = True
ordering = ['-created', '-N']
N = models.IntegerField(null=False, editable=False)
created = models.DateTimeField(auto_now_add=True)

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submitter = models.ForeignKey(UserModel, null=False,
related_name='%(app_label)s_%(class)s_set')
# The MOU group responsible

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group = models.ForeignKey(EMGroup, null=False,
related_name='%(app_label)s_%(class)s_set')

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# The following fields should be calculated from the footprint info
# provided by the user. These fields are just for convenience and
# fast searching
# The center of the bounding box of the rectangular footprints ra,dec
# in J2000 in decimal degrees
ra = models.FloatField(null=True, blank=True)
dec = models.FloatField(null=True, blank=True)
# The width and height (RA range and Dec range) in decimal degrees
raWidth = models.FloatField(null=True, blank=True)
decWidth = models.FloatField(null=True, blank=True)
comment = models.TextField(blank=True)

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def calculateCoveringRegion(self, footprints=None):
# Implement most of the logic in the abstract class' method
# without needing to specify the footprints field
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if not footprints:
return
ramin = 360.0
ramax = 0.0
decmin = 90.0
decmax = -90.0
for f in footprints:
# evaluate bounding box
w = float(f.raWidth)/2
if f.ra-w < ramin: ramin = f.ra-w
if f.ra+w > ramax: ramax = f.ra+w
w = float(f.decWidth)/2
if f.dec-w < decmin: decmin = f.dec-w
if f.dec+w > decmax: decmax = f.dec+w
# Make sure the min/max ra and dec are within bounds:
ramin = max(0.0, ramin)
ramax = min(360.0, ramax)
decmin = max(-90.0, decmin)
decmax = min(90.0, decmax)
# Calculate sky rectangle bounds
self.ra = (ramin + ramax)/2
self.dec = (decmin + decmax)/2
self.raWidth = ramax-ramin
self.decWidth = decmax-decmin

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class EMObservation(EMObservationBase, AutoIncrementModel):
"""EMObservation class for events"""
AUTO_FIELD = 'N'
AUTO_CONSTRAINT = 'event'

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event = models.ForeignKey(Event, null=False, on_delete=models.CASCADE)
class Meta(EMObservationBase.Meta):
unique_together = (('event', 'N'),)
def __unicode__(self):
return "{event_id} | {group} | {N}".format(
event_id=self.event.graceid(), group=self.group.name, N=self.N)
def calculateCoveringRegion(self):
footprints = self.emfootprint_set.all()
super(EMObservation, self).calculateCoveringRegion(footprints)
class EMFootprintBase(models.Model):
"""

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Abstract base class for EM footprints:
Each EMObservation can have many footprints underneath.
None of the fields are optional here.
"""

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N = models.IntegerField(null=False, editable=False)
# The center of the rectangular footprint, right ascension and declination
# in J2000 in decimal degrees

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ra = models.FloatField(null=False, blank=False)
dec = models.FloatField(null=False, blank=False)
# The width and height (RA range and Dec range) in decimal degrees

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raWidth = models.FloatField(null=False, blank=False)
decWidth = models.FloatField(null=False, blank=False)
# The start time of the observation for this footprint

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start_time = models.DateTimeField(null=False, blank=False)
# The exposure time in seconds for this footprint

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exposure_time = models.PositiveIntegerField(null=False, blank=False)

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class Meta:

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abstract = True
ordering = ['-N']

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class EMFootprint(EMFootprintBase, AutoIncrementModel):
"""EMFootprint class for event EMObservations"""
# For AutoIncrementModel save
AUTO_FIELD = 'N'
AUTO_CONSTRAINT = 'observation'

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observation = models.ForeignKey(EMObservation, null=False,
on_delete=models.CASCADE)

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class Meta(EMFootprintBase.Meta):
unique_together = (('observation', 'N'),)

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class Labelling(m2mThroughBase):
"""
Model which provides the "through" relationship between Events and Labels.
"""
event = models.ForeignKey(Event)
label = models.ForeignKey(Label)
def __unicode__(self):
return "{graceid} | {label}".format(graceid=self.event.graceid(),
label=self.label.name)

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# XXX Deprecated? Is this used *anywhere*?
# Appears to only be used in models.py. Here and Event class as approval_set
class Approval(models.Model):
COLLABORATION_CHOICES = ( ('L','LIGO'), ('V','Virgo'), )
approver = models.ForeignKey(UserModel)
created = models.DateTimeField(auto_now_add=True)
approvedEvent = models.ForeignKey(Event, null=False)
approvingCollaboration = models.CharField(max_length=1, choices=COLLABORATION_CHOICES)

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## Analysis Specific Attributes.

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class GrbEvent(Event):
ivorn = models.CharField(max_length=200, null=True)
author_ivorn = models.CharField(max_length=200, null=True)
author_shortname = models.CharField(max_length=200, null=True)
observatory_location_id = models.CharField(max_length=200, null=True)
coord_system = models.CharField(max_length=200, null=True)
ra = models.FloatField(null=True)
dec = models.FloatField(null=True)
error_radius = models.FloatField(null=True)
how_description = models.CharField(max_length=200, null=True)
how_reference_url = models.URLField(null=True)
trigger_duration = models.FloatField(null=True)
t90 = models.FloatField(null=True)
designation = models.CharField(max_length=20, null=True)
redshift = models.FloatField(null=True)
trigger_id = models.CharField(max_length=25, null=True)

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class CoincInspiralEvent(Event):
ifos = models.CharField(max_length=20, default="")
end_time = models.PositiveIntegerField(null=True)
end_time_ns = models.PositiveIntegerField(null=True)
mass = models.FloatField(null=True)
mchirp = models.FloatField(null=True)
minimum_duration = models.FloatField(null=True)
snr = models.FloatField(null=True)
false_alarm_rate = models.FloatField(null=True)
combined_far = models.FloatField(null=True)

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class MultiBurstEvent(Event):
ifos = models.CharField(max_length=20, default="")
start_time = models.PositiveIntegerField(null=True)
start_time_ns = models.PositiveIntegerField(null=True)
duration = models.FloatField(null=True)
peak_time = models.PositiveIntegerField(null=True)
peak_time_ns = models.PositiveIntegerField(null=True)
central_freq = models.FloatField(null=True)
bandwidth = models.FloatField(null=True)
amplitude = models.FloatField(null=True)
snr = models.FloatField(null=True)
confidence = models.FloatField(null=True)
false_alarm_rate = models.FloatField(null=True)
ligo_axis_ra = models.FloatField(null=True)
ligo_axis_dec = models.FloatField(null=True)
ligo_angle = models.FloatField(null=True)
ligo_angle_sig = models.FloatField(null=True)
single_ifo_times = models.CharField(max_length=255, default="")

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class LalInferenceBurstEvent(Event):
bci = models.FloatField(null=True)
quality_mean = models.FloatField(null=True)
quality_median = models.FloatField(null=True)
bsn = models.FloatField(null=True)
omicron_snr_network = models.FloatField(null=True)
omicron_snr_H1 = models.FloatField(null=True)
omicron_snr_L1 = models.FloatField(null=True)
omicron_snr_V1 = models.FloatField(null=True)
hrss_mean = models.FloatField(null=True)
hrss_median = models.FloatField(null=True)
frequency_mean = models.FloatField(null=True)
frequency_median = models.FloatField(null=True)
class SingleInspiral(models.Model):
event = models.ForeignKey(Event, null=False)
ifo = models.CharField(max_length=20, null=True)
search = models.CharField(max_length=20, null=True)
channel = models.CharField(max_length=50, blank=True)
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end_time = models.IntegerField(null=True)
end_time_ns = models.IntegerField(null=True)
end_time_gmst = models.FloatField(null=True)
impulse_time = models.IntegerField(null=True)
impulse_time_ns = models.IntegerField(null=True)
template_duration = models.FloatField(null=True)
event_duration = models.FloatField(null=True)
amplitude = models.FloatField(null=True)
eff_distance = models.FloatField(null=True)
coa_phase = models.FloatField(null=True)
mass1 = models.FloatField(null=True)
mass2 = models.FloatField(null=True)
mchirp = models.FloatField(null=True)
mtotal = models.FloatField(null=True)
eta = models.FloatField(null=True)
kappa = models.FloatField(null=True)
chi = models.FloatField(null=True)
tau0 = models.FloatField(null=True)
tau2 = models.FloatField(null=True)
tau3 = models.FloatField(null=True)
tau4 = models.FloatField(null=True)
tau5 = models.FloatField(null=True)
ttotal = models.FloatField(null=True)
psi0 = models.FloatField(null=True)
psi3 = models.FloatField(null=True)
alpha = models.FloatField(null=True)
alpha1 = models.FloatField(null=True)
alpha2 = models.FloatField(null=True)
alpha3 = models.FloatField(null=True)
alpha4 = models.FloatField(null=True)
alpha5 = models.FloatField(null=True)
alpha6 = models.FloatField(null=True)
beta = models.FloatField(null=True)
f_final = models.FloatField(null=True)
snr = models.FloatField(null=True)
chisq = models.FloatField(null=True)
chisq_dof = models.IntegerField(null=True)
bank_chisq = models.FloatField(null=True)
bank_chisq_dof = models.IntegerField(null=True)
cont_chisq = models.FloatField(null=True)
cont_chisq_dof = models.IntegerField(null=True)
sigmasq = models.FloatField(null=True)
rsqveto_duration = models.FloatField(null=True)
Gamma0 = models.FloatField(null=True)
Gamma1 = models.FloatField(null=True)
Gamma2 = models.FloatField(null=True)
Gamma3 = models.FloatField(null=True)
Gamma4 = models.FloatField(null=True)
Gamma5 = models.FloatField(null=True)
Gamma6 = models.FloatField(null=True)
Gamma7 = models.FloatField(null=True)
Gamma8 = models.FloatField(null=True)
Gamma9 = models.FloatField(null=True)

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spin1x = models.FloatField(null=True)
spin1y = models.FloatField(null=True)
spin1z = models.FloatField(null=True)
spin2x = models.FloatField(null=True)
spin2y = models.FloatField(null=True)
spin2z = models.FloatField(null=True)
def end_time_full(self):
return LIGOTimeGPS(self.end_time, self.end_time_ns)
def impulse_time_full(self):
return LIGOTimeGPS(self.impulse_time, self.impulse_time_ns)
@classmethod
def create_events_from_ligolw_table(cls, table, event):
"""For an Event, given a table (loaded by ligolw.utils.load_filename or similar) create SingleEvent tables for the event"""
created_events = []
#log.debug("Single/create from table/fields: " + str(field_names))
#log.debug("Single/creating event")
for f in [cls._meta.get_field(f) for f in cls.field_names()]:
value = getattr(row, f.attname, f.default)
# Awful kludge for handling nan for eff_distance
try:
if (f.attname == 'eff_distance' and
isinstance(value, numbers.Number) and isnan(value)):
value = None
except Exception as e:
pass
# Only set value of class instance member if
# value is not None or if field is nullable.
# Otherwise we could overwrite non-nullable fields
# which have default values with None.
if value is not None or f.null:
#log.debug("Setting column '%s' with value '%s'" % (f.attname, value))
setattr(e, f.attname, value)
e.save()
created_events.append(e)
return created_events
@classmethod
def update_event(cls, event, datafile=None):
"""Given an Event (and optional location of coinc.xml) update SingleInspiral data"""
# XXX Need a better way to find original data.
if datafile is None:
datafile = os.path.join(event.datadir, 'coinc.xml')
xmldoc = glue.ligolw.utils.load_filename(datafile, contenthandler=LIGOLWContentHandler)
except IOError:
return None
# Extract Single Inspiral Information
s_inspiral_tables = glue.ligolw.lsctables.SnglInspiralTable.get_table(xmldoc)
# Concatentate the tables' rows into a single table
table = sum(s_inspiral_tables, [])
event.singleinspiral_set.all().delete()
return cls.create_events_from_ligolw_table(table, event)
@classmethod
def field_names(cls):
try:
return cls._field_names
except AttributeError: pass
model_field_names = set([ x.name for x in cls._meta.get_fields(include_parents=False) ])
ligolw_field_names = set(
glue.ligolw.lsctables.SnglInspiralTable.validcolumns.keys())
cls._field_names = model_field_names.intersection(ligolw_field_names)
return cls._field_names
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# Event subclass for injections
class SimInspiralEvent(Event):
mass1 = models.FloatField(null=True)
mass2 = models.FloatField(null=True)
eta = models.FloatField(null=True)
amp_order = models.IntegerField(null=True)
coa_phase = models.FloatField(null=True)
mchirp = models.FloatField(null=True)
spin1y = models.FloatField(null=True)
spin1x = models.FloatField(null=True)
spin1z = models.FloatField(null=True)
spin2x = models.FloatField(null=True)
spin2y = models.FloatField(null=True)
spin2z = models.FloatField(null=True)
geocent_end_time = models.IntegerField(null=True)
geocent_end_time_ns = models.IntegerField(null=True)
end_time_gmst = models.FloatField(null=True)
f_lower = models.FloatField(null=True)
f_final = models.FloatField(null=True)
distance = models.FloatField(null=True)
latitude = models.FloatField(null=True)
longitude = models.FloatField(null=True)
polarization = models.FloatField(null=True)
inclination = models.FloatField(null=True)
theta0 = models.FloatField(null=True)
phi0 = models.FloatField(null=True)
waveform = models.CharField(max_length=50, blank=True, default="")
numrel_mode_min = models.IntegerField(null=True)
numrel_mode_max = models.IntegerField(null=True)
numrel_data = models.CharField(max_length=50, blank=True, default="")
source = models.CharField(max_length=50, blank=True, default="")
taper = models.CharField(max_length=50, blank=True, default="")
bandpass = models.IntegerField(null=True)
alpha = models.FloatField(null=True)
beta = models.FloatField(null=True)
psi0 = models.FloatField(null=True)
psi3 = models.FloatField(null=True)
alpha1 = models.FloatField(null=True)
alpha2 = models.FloatField(null=True)
alpha3 = models.FloatField(null=True)
alpha4 = models.FloatField(null=True)
alpha5 = models.FloatField(null=True)
alpha6 = models.FloatField(null=True)
g_end_time = models.IntegerField(null=True)
g_end_time_ns = models.IntegerField(null=True)
h_end_time = models.IntegerField(null=True)
h_end_time_ns = models.IntegerField(null=True)
l_end_time = models.IntegerField(null=True)
l_end_time_ns = models.IntegerField(null=True)
t_end_time = models.IntegerField(null=True)
t_end_time_ns = models.IntegerField(null=True)
v_end_time = models.IntegerField(null=True)
v_end_time_ns = models.IntegerField(null=True)
eff_dist_g = models.FloatField(null=True)
eff_dist_h = models.FloatField(null=True)
eff_dist_l = models.FloatField(null=True)
eff_dist_t = models.FloatField(null=True)
eff_dist_v = models.FloatField(null=True)
# Additional desired attributes that are not in the SimInspiral table
source_channel = models.CharField(max_length=50, blank=True, default="")
destination_channel = models.CharField(max_length=50, blank=True, default="")
@classmethod
def field_names(cls):
try:
return cls._field_names
except AttributeError: pass
# We only care about the model field names in this particular case.
cls._field_names = [ x.name for x in cls._meta.get_fields(include_parents=False) ]
return cls._field_names

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# Tags (user-defined log message attributes)
class Tag(CleanSaveModel):
"""
Model for tags attached to EventLogs.
We don't use an explicit through model to track relationship creators and
time of relationship creation since we generally create a log message
whenever another log is tagged. Not sure that it's good to make the
assumption that this will always be done. But is it really important to
track those things? Doesn't seem like it.
"""
name = models.CharField(max_length=100, null=False, blank=False,
unique=True,
validators=[
models.fields.validators.RegexValidator(
regex=r'^[0-9a-zA-Z_\-]*$',
message="Tag names can only include [0-9a-zA-z_-]",
code="invalid_tag_name",
)
])

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displayName = models.CharField(max_length=200, null=True, blank=True)

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return self.displayName if self.displayName else self.name

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class VOEventBase(models.Model):
"""Abstract base model for VOEvents"""
class Meta:

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abstract = True
ordering = ['-created', '-N']
# VOEvent type choices
VOEVENT_TYPE_PRELIMINARY = 'PR'
VOEVENT_TYPE_INITIAL = 'IN'
VOEVENT_TYPE_UPDATE = 'UP'
VOEVENT_TYPE_RETRACTION = 'RE'
VOEVENT_TYPE_CHOICES = (
(VOEVENT_TYPE_PRELIMINARY, 'preliminary'),
(VOEVENT_TYPE_INITIAL, 'initial'),
(VOEVENT_TYPE_UPDATE, 'update'),
(VOEVENT_TYPE_RETRACTION, 'retraction'),
)
# Fields
created = models.DateTimeField(auto_now_add=True)

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issuer = models.ForeignKey(UserModel, null=False,
related_name='%(app_label)s_%(class)s_set')
ivorn = models.CharField(max_length=200, default="", blank=True)
filename = models.CharField(max_length=100, default="", blank=True)
file_version = models.IntegerField(null=True, default=None, blank=True)
N = models.IntegerField(null=False, editable=False)
voevent_type = models.CharField(max_length=2, choices=VOEVENT_TYPE_CHOICES)

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def fileurl(self):
# Override this method on derived classes
return NotImplemented
class VOEvent(VOEventBase, AutoIncrementModel):
"""VOEvent class for events"""
AUTO_FIELD = 'N'
AUTO_CONSTRAINT = 'event'

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event = models.ForeignKey(Event, null=False, on_delete=models.CASCADE)
class Meta(VOEventBase.Meta):
unique_together = (('event', 'N'),)
def fileurl(self):
if self.filename:
actual_filename = self.filename
if self.file_version >= 0:
actual_filename += ',%d' % self.file_version
return reverse('file-download', args=[self.event.graceid(),
actual_filename])
else:
return None

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class SignoffBase(models.Model):
"""Abstract base model for operator and advocate signoffs"""
# Instrument choices
INSTRUMENT_H1 = 'H1'
INSTRUMENT_L1 = 'L1'
INSTRUMENT_V1 = 'V1'
INSTRUMENT_CHOICES = (
(INSTRUMENT_H1, 'LHO'),
(INSTRUMENT_L1, 'LLO'),
(INSTRUMENT_V1, 'Virgo'),
)
# Operator status choices
OPERATOR_STATUS_OK = 'OK'
OPERATOR_STATUS_NOTOK = 'NO'
OPERATOR_STATUS_CHOICES = (
(OPERATOR_STATUS_OK, 'OKAY'),
(OPERATOR_STATUS_NOTOK, 'NOT OKAY'),
)
# Signoff type choices
SIGNOFF_TYPE_OPERATOR = 'OP'
SIGNOFF_TYPE_ADVOCATE = 'ADV'
SIGNOFF_TYPE_CHOICES = (
(SIGNOFF_TYPE_OPERATOR, 'operator'),
(SIGNOFF_TYPE_ADVOCATE, 'advocate'),
)
# Field definitions
submitter = models.ForeignKey(UserModel, related_name=
'%(app_label)s_%(class)s_set')
comment = models.TextField(blank=True)
instrument = models.CharField(max_length=2, blank=True,
choices=INSTRUMENT_CHOICES)
status = models.CharField(max_length=2, blank=False,
choices=OPERATOR_STATUS_CHOICES)
signoff_type = models.CharField(max_length=3, blank=False,
choices=SIGNOFF_TYPE_CHOICES)

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abstract = True
def clean(self, *args, **kwargs):
"""Custom clean method for signoffs"""
# Make sure instrument is non-blank if this is an operator signoff
if (self.signoff_type == self.SIGNOFF_TYPE_OPERATOR and

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not self.instrument):
raise ValidationError({'instrument':
_('Instrument must be specified for operator signoff')})
super(SignoffBase, self).clean(*args, **kwargs)
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def get_req_label_name(self):
if self.signoff_type == 'OP':
return self.instrument + 'OPS'
elif self.signoff_type == 'ADV':
return 'ADVREQ'
def get_status_label_name(self):
if self.signoff_type == 'OP':
return self.instrument + self.status
elif self.signoff_type == 'ADV':
return 'ADV' + self.status
@property
def opposite_status(self):
if self.status == 'OK':
return 'NO'
elif self.status == 'NO':
return 'OK'
def get_opposite_status_label_name(self):
if self.signoff_type == 'OP':
return self.instrument + self.opposite_status
elif self.signoff_type == 'ADV':
return 'ADV' + self.opposite_status

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class Signoff(SignoffBase):
"""Class for Event signoffs"""
event = models.ForeignKey(Event)

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class Meta:
unique_together = ('event', 'instrument')
def __unicode__(self):
return "%s | %s | %s" % (self.event.graceid(), self.instrument,
self.status)
EMSPECTRUM = (
('em.gamma', 'Gamma rays part of the spectrum'),
('em.gamma.soft', 'Soft gamma ray (120 - 500 keV)'),
('em.gamma.hard', 'Hard gamma ray (>500 keV)'),
('em.X-ray', 'X-ray part of the spectrum'),
('em.X-ray.soft', 'Soft X-ray (0.12 - 2 keV)'),
('em.X-ray.medium', 'Medium X-ray (2 - 12 keV)'),
('em.X-ray.hard', 'Hard X-ray (12 - 120 keV)'),
('em.UV', 'Ultraviolet part of the spectrum'),
('em.UV.10-50nm', 'Ultraviolet between 10 and 50 nm'),
('em.UV.50-100nm', 'Ultraviolet between 50 and 100 nm'),
('em.UV.100-200nm', 'Ultraviolet between 100 and 200 nm'),
('em.UV.200-300nm', 'Ultraviolet between 200 and 300 nm'),
('em.UV.FUV', 'Far-Infrared, 30-100 microns'),
('em.opt', 'Optical part of the spectrum'),
('em.opt.U', 'Optical band between 300 and 400 nm'),
('em.opt.B', 'Optical band between 400 and 500 nm'),
('em.opt.V', 'Optical band between 500 and 600 nm'),
('em.opt.R', 'Optical band between 600 and 750 nm'),
('em.opt.I', 'Optical band between 750 and 1000 nm'),
('em.IR', 'Infrared part of the spectrum'),
('em.IR.NIR', 'Near-Infrared, 1-5 microns'),
('em.IR.J', 'Infrared between 1.0 and 1.5 micron'),
('em.IR.H', 'Infrared between 1.5 and 2 micron'),
('em.IR.K', 'Infrared between 2 and 3 micron'),
('em.IR.MIR', 'Medium-Infrared, 5-30 microns'),
('em.IR.3-4um', 'Infrared between 3 and 4 micron'),
('em.IR.4-8um', 'Infrared between 4 and 8 micron'),
('em.IR.8-15um', 'Infrared between 8 and 15 micron'),
('em.IR.15-30um', 'Infrared between 15 and 30 micron'),
('em.IR.30-60um', 'Infrared between 30 and 60 micron'),
('em.IR.60-100um', 'Infrared between 60 and 100 micron'),
('em.IR.FIR', 'Far-Infrared, 30-100 microns'),
('em.mm', 'Millimetric part of the spectrum'),
('em.mm.1500-3000GHz', 'Millimetric between 1500 and 3000 GHz'),
('em.mm.750-1500GHz', 'Millimetric between 750 and 1500 GHz'),
('em.mm.400-750GHz', 'Millimetric between 400 and 750 GHz'),
('em.mm.200-400GHz', 'Millimetric between 200 and 400 GHz'),
('em.mm.100-200GHz', 'Millimetric between 100 and 200 GHz'),
('em.mm.50-100GHz', 'Millimetric between 50 and 100 GHz'),
('em.mm.30-50GHz', 'Millimetric between 30 and 50 GHz'),
('em.radio', 'Radio part of the spectrum'),
('em.radio.12-30GHz', 'Radio between 12 and 30 GHz'),
('em.radio.6-12GHz', 'Radio between 6 and 12 GHz'),
('em.radio.3-6GHz', 'Radio between 3 and 6 GHz'),
('em.radio.1500-3000MHz','Radio between 1500 and 3000 MHz'),
('em.radio.750-1500MHz','Radio between 750 and 1500 MHz'),
('em.radio.400-750MHz', 'Radio between 400 and 750 MHz'),
('em.radio.200-400MHz', 'Radio between 200 and 400 MHz'),
('em.radio.100-200MHz', 'Radio between 100 and 200 MHz'),
('em.radio.20-100MHz', 'Radio between 20 and 100 MHz'),
)
# TP (2 Apr 2018): pretty sure this class is deprecated - most recent
# production use is T137114 = April 2015.
class EMBBEventLog(AutoIncrementModel):
"""EMBB EventLog: A multi-purpose annotation for EM followup.
A rectangle on the sky, equatorially aligned,
that has or will be imaged that is related to an event"""
class Meta:
ordering = ['-created', '-N']
unique_together = ("event","N")

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return "%s-%s-%d" % (self.event.graceid(), self.group.name, self.N)
# A counter for Eels associated with a given event. This is
# important for addressibility.
N = models.IntegerField(null=False)
# The time at which this Eel was created. Important for event auditing.
created = models.DateTimeField(auto_now_add=True)
# The gracedb event that this Eel relates to
event = models.ForeignKey(Event)
# The responsible author of this communication
submitter = models.ForeignKey(UserModel) # from a table of people
# The MOU group responsible
group = models.ForeignKey(EMGroup) # from a table of facilities
# The instrument used or intended for the imaging implied by this footprint
instrument = models.CharField(max_length=200, blank=True)
# Facility-local identifier for this footprint
footprintID= models.TextField(blank=True)
# Now the global ID is a concatenation: facilityName#footprintID
# the EM waveband used for the imaging as below
waveband = models.CharField(max_length=25, choices=EMSPECTRUM)
# The center of the bounding box of the rectangular footprints, right ascension and declination
# in J2000 in decimal degrees
ra = models.FloatField(null=True)
dec = models.FloatField(null=True)
# The width and height (RA range and Dec range) in decimal degrees of each image
raWidth = models.FloatField(null=True)
decWidth = models.FloatField(null=True)
# The GPS time of the middle of the bounding box of the imaging time
gpstime = models.PositiveIntegerField(null=True)
# The duration of each image in seconds
duration = models.PositiveIntegerField(null=True)
# The lists of RA and Dec of the centers of the images
raList = models.TextField(blank=True)
decList = models.TextField(blank=True)
# The width and height of each individual image
raWidthList = models.TextField(blank=True)
decWidthList = models.TextField(blank=True)
# The list of GPS times of the images
gpstimeList = models.TextField(blank=True)
# The duration of each individual image
durationList = models.TextField(blank=True)
# Event Log status
EEL_STATUS_CHOICES = (('FO','FOOTPRINT'), ('SO','SOURCE'), ('CO','COMMENT'), ('CI','CIRCULAR'))
eel_status = models.CharField(max_length=2, choices=EEL_STATUS_CHOICES)
# Observation status. If OBSERVATION, then there is a good chance of good image
OBS_STATUS_CHOICES = (('NA', 'NOT APPLICABLE'), ('OB','OBSERVATION'), ('TE','TEST'), ('PR','PREDICTION'))
obs_status = models.CharField(max_length=2, choices=OBS_STATUS_CHOICES)
# This field is natural language for human
comment = models.TextField(blank=True)

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# This field is formal struct by a syntax TBD
# for example {"phot.mag.limit": 22.3}
extra_info_dict = models.TextField(blank=True)
# For AutoIncrementModel save
AUTO_FIELD = 'N'
AUTO_CONSTRAINT = 'event'

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# Validates the input and builds bounding box in RA/Dec/GPS
def validateMakeRects(self):
# get all the list based position and times and their widths
raRealList = []
rawRealList = []
# add a [ and ] to convert the input csv list to a json parsable text
if self.raList: raRealList = json.loads('['+self.raList+']')
if self.raWidthList: rawRealList = json.loads('['+self.raWidthList+']')
if self.decList: decRealList = json.loads('['+self.decList+']')
if self.decWidthList: decwRealList = json.loads('['+self.decWidthList+']')
if self.gpstimeList: gpstimeRealList = json.loads('['+self.gpstimeList+']')
if self.durationList: durationRealList = json.loads('['+self.durationList+']')
# is there anything in the ra list?
nList = len(raRealList)
if nList > 0:
if decRealList and len(decRealList) != nList:
raise ValueError('RA and Dec lists are different lengths.')
if gpstimeRealList and len(gpstimeRealList) != nList:
raise ValueError('RA and GPS lists are different lengths.')
# is there anything in the raWidth list?
mList = len(rawRealList)
if mList > 0:
if decwRealList and len(decwRealList) != mList:
raise ValueError('RAwidth and Decwidth lists are different lengths.')
if durationRealList and len(durationRealList) != mList:
raise ValueError('RAwidth and Duration lists are different lengths.')
# There can be 1 width for the whole list, or one for each ra/dec/gps
if mList != 1 and mList != nList:
raise ValueError('Width and duration lists must be length 1 or same length as coordinate lists')
else:
mList = 0
ramin = 360.0
ramax = 0.0
decmin = 90.0
decmax = -90.0
gpsmin = 100000000000
gpsmax = 0
for i in range(nList):
try:
ra = float(raRealList[i])
except:
raise ValueError('Cannot read RA list element %d of %s'%(i, self.raList))
try:
dec = float(decRealList[i])
except:
raise ValueError('Cannot read Dec list element %d of %s'%(i, self.decList))
try:
gps = int(gpstimeRealList[i])
except:
raise ValueError('Cannot read GPStime list element %d of %s'%(i, self.gpstimeList))
# the widths list can have 1 member to cover all, or one for each
if mList==1: j=0
else : j=i
try:
w = float(rawRealList[j])/2
except:
raise ValueError('Cannot read raWidth list element %d of %s'%(i, self.raWidthList))
# evaluate bounding box
if ra-w < ramin: ramin = ra-w
if ra+w > ramax: ramax = ra+w
try:
w = float(decwRealList[j])/2
except:
raise ValueError('Cannot read raWidth list element %d of %s'%(i, self.decWidthList))
# evaluate bounding box
if dec-w < decmin: decmin = dec-w
if dec+w > decmax: decmax = dec+w
try:
w = int(durationRealList[j])/2
except:
raise ValueError('Cannot read duration list element %d of %s'%(i, self.durationList))
# evaluate bounding box
if gps-w < gpsmin: gpsmin = gps-w
if gps+w > gpsmax: gpsmax = gps+w
# Make sure the min/max ra and dec are within bounds:
ramin = max(0.0, ramin)
ramax = min(360.0, ramax)
decmin = max(-90.0, decmin)
decmax = min(90.0, decmax)
if nList>0:
self.ra = (ramin + ramax)/2
self.dec = (decmin + decmax)/2
self.gpstime = (gpsmin+gpsmax)/2
if mList>0:
self.raWidth = ramax-ramin
self.decWidth = decmax-decmin
self.duration = gpsmax-gpsmin
return True