if abs(seg) > 2000:
longLen += abs(seg)
longNum += 1
print "For ifo %s there is %d seconds of data in %d segments, %d seconds (%d unique segments) in segments longer than 500s and %d seconds (%d unique segments) longer than 2000s." % (
ifo, fullLen, fullNum, shortLen, shortNum, longLen, longNum)
scienceSegs, segsList = _workflow.setup_segment_generation(workflow, segDir)
segment_report(scienceSegs)
print
print
print "RUNNING DATAFIND"
datafinds, scienceSegs = _workflow.setup_datafind_workflow(
workflow, scienceSegs, dfDir, segsList)
# This is needed to know what times will be analysed by daily ahope
# Template bank stuff
banks = _workflow.setup_tmpltbank_workflow(workflow, scienceSegs, datafinds,
dfDir)
# Do matched-filtering
insps = _workflow.setup_matchedfltr_workflow(workflow, scienceSegs, datafinds,
banks, dfDir)
# Now construct the summary XML file
outdoc = ligolw.Document()
outdoc.appendChild(ligolw.LIGO_LW())
# FIXME: PROGRAM NAME and dictionary of opts should be variables defined up above
proc_id = ligolw_process.register_to_xmldoc(outdoc, 'dayhopetest',
shortNum+=1
if abs(seg) > 2000:
longLen+=abs(seg)
longNum+=1
print "For ifo %s there is %d seconds of data in %d segments, %d seconds (%d unique segments) in segments longer than 500s and %d seconds (%d unique segments) longer than 2000s." %(ifo, fullLen, fullNum, shortLen, shortNum, longLen, longNum)
scienceSegs, segsList = _workflow.setup_segment_generation(workflow, segDir)
segment_report(scienceSegs)
print
print
print "RUNNING DATAFIND"
datafinds, scienceSegs = _workflow.setup_datafind_workflow(workflow, scienceSegs,
dfDir, segsList)
# This is needed to know what times will be analysed by daily ahope
# Template bank stuff
banks = _workflow.setup_tmpltbank_workflow(workflow, scienceSegs, datafinds,
dfDir)
# Do matched-filtering
insps = _workflow.setup_matchedfltr_workflow(workflow, scienceSegs, datafinds,
banks, dfDir)
# Now construct the summary XML file
outdoc = ligolw.Document()
outdoc.appendChild(ligolw.LIGO_LW())
# FIXME: PROGRAM NAME and dictionary of opts should be variables defined up above
proc_id = ligolw_process.register_to_xmldoc(outdoc, 'dayhopetest',
segment_report(scienceSegs)
print "STARTING DF"
print
# Start with SYR comparison
# FIXME: Used to use deecopy here, but now that seems to fail so repeating
# segment query calls with logging off. This may be slow!
logger.disabled = True
scienceSegsS, _ = _workflow.setup_segment_generation(workflow, segDir)
logger.disabled = False
print "RUNNING DATAFIND FOR SYR"
datafinds, scienceSegsS = _workflow.setup_datafind_workflow(workflow,
scienceSegsS,
dfDirSYR,
segsList,
tag="SYR")
segment_report(scienceSegsS)
print
print
print "RUNNING DATAFIND FOR CIT"
logger.disabled = True
scienceSegsC, _ = _workflow.setup_segment_generation(workflow, segDir)
logger.disabled = False
datafinds, scienceSegsC = _workflow.setup_datafind_workflow(workflow,
scienceSegsC,
dfDirCIT,
segsList,
longLen,
longNum,
)
scienceSegs, segsList = _workflow.setup_segment_generation(workflow, segDir)
segment_report(scienceSegs)
print
print
# Start with SYR comparison
scienceSegsS = copy.deepcopy(scienceSegs)
print "RUNNING DATAFIND FOR SYR"
datafinds, scienceSegsS = _workflow.setup_datafind_workflow(workflow, scienceSegsS, dfDirSYR, segsList, tag="SYR")
segment_report(scienceSegsS)
print
print
print "RUNNING DATAFIND FOR CIT"
scienceSegsC = copy.deepcopy(scienceSegs)
datafinds, scienceSegsC = _workflow.setup_datafind_workflow(workflow, scienceSegsC, dfDirCIT, segsList, tag="CIT")
segment_report(scienceSegsC)
print "Frames present a SYR and not at CIT:"
for ifo in scienceSegsS.keys():
print "For ifo", ifo
if ifo in scienceSegsC.keys():
# Retrieve segments ahope-style
currDir = os.getcwd()
segDir = os.path.join(currDir, "segments")
sciSegs, segsFileList = _workflow.setup_segment_generation(wflow, segDir)
# Make coherent network segments
onSrc, sciSegs = _workflow.get_triggered_coherent_segment(wflow, segDir,
sciSegs)
# FIXME: The following two lines are/were crude hacks.
ifo = sciSegs.keys()[0]
wflow.analysis_time = sciSegs[ifo][0]
# Datafind
dfDir = os.path.join(currDir, "datafind")
datafind_files, sciSegs = _workflow.setup_datafind_workflow(wflow, sciSegs,
dfDir,
segsFileList)
all_files.extend(datafind_files)
# Template bank and splitting the bank
# TODO: Move from pregenerated to generated coherent network bank
bank_files = _workflow.setup_tmpltbank_workflow(wflow, sciSegs,
datafind_files, dfDir)
splitbank_files = _workflow.setup_splittable_workflow(wflow, bank_files, dfDir)
all_files.extend(bank_files)
all_files.extend(splitbank_files)
# Injections
"""
injDir = os.path.join(currDir, "inj_files")
inj_files, inj_tags = ahope.setup_injection_workflow(wflow,
