def create_dag_node(self): """ Return a CondorDAGNode that represents this entire DAG. """ dir, fname = os.path.split(self.get_dag_path()) job = pipeline.CondorDAGManJob(fname, dir) node = pipeline.CondorDAGNode(job) return node
def finalise_DAG(dag, parents=[]):
dag.write_sub_files()
dag.write_dag()
dag.write_script()
dagfile = os.path.split(dag.get_dag_file())
DAGManJob = pipeline.CondorDAGManJob(dagfile[1], dagfile[0])
DAGManNode = pipeline.CondorDAGManNode(DAGManJob)
for node in parents:
DAGManNode.add_parent(node)
return DAGManNode
.format(myinjpath, injpath)))
sys.exit(1)
else:
# The link doens't exist, so create it and update config
try:
os.link(os.path.abspath(injpath), myinjpath)
except:
from shutil import copyfile
copyfile(injpath, myinjpath)
cp.set('input', 'injection-file', myinjpath)
for this_cp in setup_roq(cp):
# Create the DAG from the configparser object
dag = pipe_utils.LALInferencePipelineDAG(this_cp, dax=False)
dagjob = pipeline.CondorDAGManJob(
os.path.join(this_cp.get('paths', 'basedir'), dag.get_dag_file()),
this_cp.get('paths', 'basedir'))
dagnode = pipeline.CondorDAGManNode(dagjob)
outerdag.add_node(dagnode)
dag.write_sub_files()
dag.write_dag()
dag.write_script()
outerdag.write_sub_files()
outerdag.write_dag()
outerdag.write_script()
# End of program
print('Successfully created DAG file.')
if opts.condor_submit:
with open('sites.xml','w') as fout:
for line in lines:
fout.write(line)
if cp.has_option('analysis','accounting_group_user'):
lines=[]
with open('sites.xml') as fin:
for line in fin:
if '<profile namespace="condor" key="getenv">True</profile>' in line:
line=line+' <profile namespace="condor" key="accounting_group_user">'+cp.get('analysis','accounting_group_user')+'</profile>\n'
lines.append(line)
with open('sites.xml','w') as fout:
for line in lines:
fout.write(line)
full_dag_path=os.path.join(cp.get('paths','basedir'),dag.get_dag_file())
dagjob=pipeline.CondorDAGManJob(full_dag_path,dir=rundir_root)
dagnode=pipeline.CondorDAGManNode(dagjob)
outerdag.add_node(dagnode)
dag.write_sub_files()
dag.write_dag()
dag.write_script()
os.chdir(olddir)
if(opts.dax):
# Create a text file with the frames listed
pfnfile = outerdag.create_frame_pfn_file()
peg_frame_cache = inspiralutils.create_pegasus_cache_file(pfnfile)
outerdag.write_sub_files()
outerdag.write_dag()
daglogdir, 'lalinference_injection_test_' + str(uuid.uuid1()) + '.log')
outerdag = pipeline.CondorDAG(outerdaglog)
outerdag.set_dag_file(os.path.join(rundir, 'priortest'))
# Run code with prior sampling
trig_time = 1085855789
fake_event = pipe_utils.Event(trig_time=trig_time)
tfpath = os.path.join(rundir, 'time.txt')
tfile = open(tfpath, 'w')
print('%i\n' % (trig_time), file=tfile)
tfile.close()
prior_cp.set('input', 'gps-time-file', tfpath)
priordag = pipe_utils.LALInferencePipelineDAG(prior_cp)
priordag.set_dag_file(os.path.join(priordir, 'lalinference_priorsample'))
priordagjob = pipeline.CondorDAGManJob(priordag.get_dag_file(), dir=priordir)
priordagnode = pipeline.CondorDAGManNode(priordagjob)
# Find the output file
pagenode = filter(lambda n: isinstance(n, pipe_utils.ResultsPageNode),
priordag.get_nodes())[0]
priorfile = pagenode.get_pos_file()
# Convert prior samples to injections
convertsub = os.path.join(rundir, 'samples2injections.sub')
converterr = os.path.join(
outerlogdir, 'samples2injection-$(cluster)-$(process)-$(node).err')
convertout = os.path.join(
outerlogdir, 'samples2injection-$(cluster)-$(process)-$(node).out')
if opts.injections:
injfile = os.path.abspath(opts.injections)
############################################################################
# MVSC Calculation
if 'FULL_DATA' in tag and veto_cat in sim_caches:
print "\tsetting up MVSC dag..."
mvsc_dag_name = options.config_file.replace('.ini','')+'_mvsc_'+tag+'_n'+cp.get("mvsc_dag","number-of-trees")+'_l'+cp.get("mvsc_dag","leaf-size")+'_s'+cp.get("mvsc_dag","sampled-parameters")+'_c'+cp.get("mvsc_dag","criterion-for-optimization")+'.dag'
mvsc_dag_generator_job = inspiral.MVSCDagGenerationJob(cp)
for key,val in cp.items("mvsc_dag"):
mvsc_dag_generator_job.add_opt(key,val)
mvsc_dag_generator_job.add_opt("ini-file", options.config_file)
mvsc_dag_generator_node = inspiral.MVSCDagGenerationNode(mvsc_dag_generator_job)
mvsc_dag_generator_node.set_user_tag(tag)
mvsc_dag_generator_node.set_database(result_db.path)
mvsc_dag_generator_node.add_parent(comp_durs_node)
dag.add_node(mvsc_dag_generator_node)
mvsc_dag_job = pipeline.CondorDAGManJob(mvsc_dag_name, os.getcwd(), None)
mvsc_dag_node = pipeline.CondorDAGManNode(mvsc_dag_job)
mvsc_dag_node.add_parent(mvsc_dag_generator_node)
dag.add_node(mvsc_dag_node)
############################################################################
# Compute the uncombined false alarm rates
print "\tsetting up cfar nodes:"
print "\t\tfor uncombined false alarm rates..."
# set node options: output database is same as input
ucfar_node = inspiral.CFarNode( ucfar_job )
ucfar_node.set_category('cfar')
ucfar_node.set_tmp_space( tmp_space )
ucfar_node.set_input( result_db.path )
