Exemplo n.º 1
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]
Exemplo n.º 2
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]
Exemplo n.º 3
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.")