def setUp(self):
self.d = [det.Detector(ifo)
for ifo, name in det.get_available_detectors()]
# not distributed sanely, but should provide some good coverage
N = 1000
self.ra = uniform(0, numpy.pi * 2, size=N)
self.dec = uniform(-numpy.pi, numpy.pi, size=N)
self.pol = uniform(0, numpy.pi * 2, size=N)
self.time = uniform(1126000000.0, 1336096017.0, size=N)
def __init__(self,
num_templates,
analysis_block,
background_statistic,
stat_files,
ifos,
ifar_limit=100,
timeslide_interval=.035,
ifar_remove_threshold=100,
coinc_threshold=0.002,
return_background=False,
save_background_on_interrupt=False):
"""
Parameters
----------
num_templates: int
The size of the template bank
analysis_block: int
The number of seconds in each analysis segment
background_statistic: str
The name of the statistic to rank coincident events.
stat_files: list of strs
List of filenames that contain information used to construct
various coincident statistics.
ifos: list of strs
List of ifo names that are being analyzed. At the moment this must
be two items such as ['H1', 'L1'].
ifar_limit: float
The largest inverse false alarm rate in years that we would like to
calculate.
timeslide_interval: float
The time in seconds between consecutive timeslide offsets.
ifar_remove_threshold: float
The inverse false alarm rate to assume a detection is made and remove
from the background estimate. !NOT IMPLEMENTED!
coinc_threshold: float
Amount of time allowed to form a coincidence in addition to the
time of flight in seconds.
return_background: boolean
If true, background triggers will also be included in the file
output.
save_background_on_interrupt: boolean
If true, an interrupt can be given to save a pickled version of
the background instance for later restoration. !NOT IMPLEMENTED!
"""
from pycbc import detector
from . import stat
self.num_templates = num_templates
self.analysis_block = analysis_block
self.stat_calculator = stat.get_statistic(background_statistic)(
stat_files)
self.timeslide_interval = timeslide_interval
self.return_background = return_background
self.ifar_remove_threshold = ifar_remove_threshold
self.ifos = ifos
if len(self.ifos) != 2:
raise ValueError(
"Only a two ifo analysis is supported at this time")
self.lookback_time = (ifar_limit * lal.YRJUL_SI *
timeslide_interval)**0.5
self.buffer_size = int(numpy.ceil(self.lookback_time / analysis_block))
det0, det1 = detector.Detector(ifos[0]), detector.Detector(ifos[1])
self.time_window = det0.light_travel_time_to_detector(
det1) + coinc_threshold
self.coincs = CoincExpireBuffer(self.buffer_size, self.ifos)
self.singles = {}
