def cluster(self, window):
""" Cluster the dict array, assuming it has the relevant Coinc colums,
time1, time2, stat, and timeslide_id
"""
from pycbc.events import cluster_coincs
interval = self.attrs["timeslide_interval"]
cid = cluster_coincs(self.stat, self.time1, self.time2, self.timeslide_id, interval, window)
return self.select(cid)
def cluster(self, window):
""" Cluster the dict array, assuming it has the relevant Coinc colums,
time1, time2, stat, and timeslide_id
"""
# If no events, do nothing
if len(self.time1) == 0 or len(self.time2) == 0:
return self
from pycbc.events import cluster_coincs
interval = self.attrs['timeslide_interval']
cid = cluster_coincs(self.stat, self.time1, self.time2,
self.timeslide_id, interval, window)
return self.select(cid)
def cluster(self, window):
""" Cluster the dict array, assuming it has the relevant Coinc colums,
time1, time2, stat, and timeslide_id
"""
# If no events, do nothing
if len(self.time1) == 0 or len(self.time2) == 0:
return self
from pycbc.events import cluster_coincs
interval = self.attrs['timeslide_interval']
cid = cluster_coincs(self.stat, self.time1, self.time2,
self.timeslide_id, interval, window)
return self.select(cid)
def cluster(self, window):
""" Cluster the dict array, assuming it has the relevant Coinc colums,
time1, time2, stat, and timeslide_id
"""
# If no events, do nothing
pivot_ifo = self.attrs['pivot']
fixed_ifo = self.attrs['fixed']
if len(self.data['%s/time' % pivot_ifo]) == 0 or len(
self.data['%s/time' % fixed_ifo]) == 0:
return self
from pycbc.events import cluster_coincs
interval = self.attrs['timeslide_interval']
cid = cluster_coincs(self.stat, self.data['%s/time' % pivot_ifo],
self.data['%s/time' % fixed_ifo],
self.timeslide_id, interval, window)
return self.select(cid)
def cluster(self, window):
""" Cluster the dict array, assuming it has the relevant Coinc colums,
time1, time2, stat, and timeslide_id
"""
# If no events, do nothing
pivot_ifo = self.attrs['pivot']
fixed_ifo = self.attrs['fixed']
if len(self.data['%s/time' % pivot_ifo]) == 0 or len(self.data['%s/time' % fixed_ifo]) == 0:
return self
from pycbc.events import cluster_coincs
interval = self.attrs['timeslide_interval']
cid = cluster_coincs(self.stat,
self.data['%s/time' % pivot_ifo],
self.data['%s/time' % fixed_ifo],
self.timeslide_id,
interval,
window)
return self.select(cid)
