exttrigInjections = [startExttrig, stopExttrig]
# check the values given
if startExttrig < 1:
print >> sys.stderr, "exttrig-inj-start must be larger than 0."
sys.exit(1)
if startExttrig > stopExttrig:
print >> sys.stderr, "exttrig-inj-stop must be larger than "\
"exttrig-inj-start."
sys.exit(1)
else:
exttrigInjections = [0, 0]
doSlides = cp.has_option('input', 'do-long-slides')
tmplt_job = inspiral.TmpltBankJob(cp, opts.dax)
# spinchecker
spincheck_job = inspiral.PTFSpinCheckerJob(cp, opts.dax)
# inspiral:
insp_jobs = inspiral.PTFInspiralJob(cp, opts.dax)
if doExtTrig:
insp_jobs.add_opt('analyze-inj-segs-only', '')
for ifo1 in ifo_list:
if do[ifo1]:
ifo1 = ifo1.upper()
spincheck_job.add_opt(ifo1.lower() + '-data', '')
insp_jobs.add_opt(ifo1.lower() + '-data', '')
if not cp.has_option('segments', ifo.lower() + '-analyze'):
continue
# decide if we need to segment the data
available_segments = get_valid_segments(
cp.get('segfind', 'segment-url'), cp.get('framefind', 'base-dir'), ifo,
cp.get('segments',
ifo.lower() + '-analyze'), gps_start_time, gps_end_time)
if not available_segments:
print("No available segments for %s, skipping" % ifo)
continue
# create the Condor jobs that will be used in the DAG
df_job = pipeline.LSCDataFindJob('cache', 'logs', cp)
tmplt_job = inspiral.TmpltBankJob(cp)
# Based on S6A results ttrigscan clustering has
# been replaced with 30-ms window clustering
# ts_job = TrigscanJob(cp)
si_job_coarse = SiClusterJobCoarse(cp)
si_job_fine = SiClusterJobFine(cp)
cp_job = FilesystemJob('cp')
# Add ifo-specific template config
if cp.has_section(ifo.lower() + '-tmpltbank'):
tmplt_job.add_ini_opts(cp, ifo.lower() + '-tmpltbank')
# Create a job to split the template into parallelization pieces
split_job = inspiral.SplitBankJob(cp)
try: frame_types.append(cp.get('input','virgo-type'))
except: pass
try: frame_types.append(cp.get('input','geo-type'))
except: pass
frame_types = [t for t in frame_types if t]
except:
lsync_file = None
df_job = pipeline.LSCDataFindJob(
'cache','logs',cp,opts.dax,lsync_file,'|'.join(frame_types))
df_job.set_sub_file( basename + '.datafind'+ subsuffix )
# tmpltbank:
tmplt_jobs = {}
for ifo in ifo_list:
tmplt_jobs[ifo] = inspiral.TmpltBankJob(cp,opts.dax)
tmplt_jobs[ifo].set_sub_file( basename + '.tmpltbank_' + ifo + subsuffix )
# inspinj:
inspinj_job = inspiral.InspInjJob(cp)
inspinj_job.set_sub_file( basename + '.inspinj' + subsuffix )
if opts.noop_inspinj:
inspinj_job.add_condor_cmd("noop_job", "true")
# inspiral:
insp_jobs = {}
for ifo in ifo_list:
insp_jobs[ifo] = inspiral.InspiralJob(cp,opts.dax)
insp_jobs[ifo].set_sub_file( basename + '.inspiral_' + ifo + subsuffix )