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Online new extinction

Merged Prathamesh Joshi requested to merge o4b-online-new-extinction into o4b-online
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@@ -253,10 +253,6 @@ def main():
data = pdf.new_with_extinction()
else:
logging.warning(f'Skipping first-round extinction for {pdfs[svd_bin].files[0]}')
if data:
data += pdf
else:
data = pdf
# while looping through registries
# send heartbeat messages
@@ -264,7 +260,8 @@ def main():
kafka_processor.heartbeat()
# zero out the zerolag after the first round of extinction is finished
data.zero_lag_lr_lnpdf.count.array[:] = 0
if data:
data.zero_lag_lr_lnpdf.count.array[:] = 0
# if we fail to complete more than 1% of the bins,
# this is a serious problem and we should just quit
@@ -284,6+281,6 @@
# zero-lag counts files downloaded from the jobs must be all 0, and
# the zero-lag counts in the output generated by
# gstlal_inspiral_calc_rank_pdfs must be 0. NOTE: this is where
# the zero-lag counts have the density estimation transform
# applied.
zerolag_counts_url = url_from_registry("gstlal_ll_inspiral_trigger_counter_registry.txt", zerolag_counts_path)
# add zerolag counts url to marginalized data
data += far.RankingStatPDF.from_xml(ligolw_utils.load_url(zerolag_counts_url, verbose = options.verbose, contenthandler = far.RankingStat.LIGOLWContentHandler), u"gstlal_inspiral_likelihood")
if data:
data += far.RankingStatPDF.from_xml(ligolw_utils.load_url(zerolag_counts_url, verbose = options.verbose, contenthandler = far.RankingStat.LIGOLWContentHandler), u"gstlal_inspiral_likelihood")
else:
data = far.RankingStatPDF.from_xml(ligolw_utils.load_url(zerolag_counts_url, verbose = options.verbose, contenthandler = far.RankingStat.LIGOLWContentHandler), u"gstlal_inspiral_likelihood")
if kafka_processor:
kafka_processor.heartbeat()
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