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',
vars(args) ).process_id
for ifo in workflow.ifos:
# Lets get the segment lists we need
segIfoFiles = segsList.find_output_with_ifo(ifo)
# SCIENCE
sciSegFile = segIfoFiles.find_output_with_tag('SCIENCE')
assert(len(sciSegFile) == 1)
sciSegFile = sciSegFile[0]
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',
vars(args)).process_id
for ifo in workflow.ifos:
# Lets get the segment lists we need
segIfoFiles = segsList.find_output_with_ifo(ifo)
# SCIENCE
sciSegFile = segIfoFiles.find_output_with_tag('SCIENCE')
assert (len(sciSegFile) == 1)
sciSegFile = sciSegFile[0]
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,
output_dir=injDir)
all_files.extend(inj_files)
"""
# Matched-filtering
# TODO: Write coherent matched filtering code
inspDir = os.path.join(currDir, "inspiral")
inspiral_files = _workflow.setup_matchedfltr_workflow(wflow, sciSegs,
datafind_files,
splitbank_files, inspDir)
all_files.extend(inspiral_files)
# Compile workflow and write DAX
wflow.save()
logging.info("Written dax.")
