def test_runReco_tf(self):
cmd = ['Reco_tf.py']
cmd.extend(['--AMI', 'q222'])
cmd.extend(['--maxEvents', '24'])
cmd.append('--athenaopts=--nprocs=4')
cmd.extend(['--athenaMPMergeTargetSize', 'ESD:0'])
msg.info('Will run this transform: {0}'.format(cmd))
p = subprocess.Popen(cmd, shell = False, stdout = subprocess.PIPE, stderr = subprocess.STDOUT, bufsize = 1)
while p.poll() is None:
line = p.stdout.readline()
sys.stdout.write(line)
# Hoover up remaining buffered output lines
for line in p.stdout:
sys.stdout.write(line)
self.assertEqual(p.returncode, 0)
# Now load metadata and test a few important values
with open('jobReport.json') as jr:
md = json.load(jr)
self.assertEqual(isinstance(md, dict), True)
dataDict = pyJobReportToFileDict(md)
self.assertTrue('ESD' in dataDict.keys())
self.assertTrue('AOD' in dataDict.keys())
self.assertTrue('HIST' in dataDict.keys())
self.assertTrue(len(dataDict['ESD']['subFiles']), 4)
self.assertEqual(dataDict['AOD']['subFiles'][0]['nentries'], 24)
self.assertEqual(dataDict['HIST']['subFiles'][0]['nentries'], 24)
def test_runReco_tf(self):
cmd = ['FullChain_tf.py', '--inputEVNTFile', sourceFile]
cmd.extend(['--outputAODFile', 'test.AOD.pool.root'])
cmd.extend(['--geometryVersion', 'ATLAS-GEO-20-00-01'])
cmd.extend(['--conditionsTag', 'OFLCOND-MC12-SIM-00'])
cmd.extend(['--randomSeed', '10'])
cmd.extend(['--skipEvents', '0'])
cmd.extend(['--maxEvents', '2']) # 2 events - this is a slow job in G4
## Event counting currently broken for multi-step transforms
msg.info('Will run this transform: {0}'.format(cmd))
p = subprocess.Popen(cmd, shell = False, stdout = subprocess.PIPE, stderr = subprocess.STDOUT, bufsize = 1)
while p.poll() is None:
line = p.stdout.readline()
sys.stdout.write(line)
# Hoover up remaining buffered output lines
for line in p.stdout:
sys.stdout.write(line)
self.assertEqual(p.returncode, 0)
# Now load metadata and test a few important values
with open('jobReport.json') as jr:
md = json.load(jr)
self.assertEqual(isinstance(md, dict), True)
dataDict = pyJobReportToFileDict(md)
self.assertEqual(dataDict["AOD"]['subFiles'][0]['nentries'], 2)
def test_runReco_tf(self):
inputs = glob.glob(sourceFiles)
self.assertEqual(len(inputs), 1)
cmd = ['Reco_tf.py', '--inputRDOFile']
cmd.extend(inputs)
cmd.extend([
'--outputESDFile', 'my.ESD.pool.root', '--autoConfiguration',
'everything'
])
cmd.extend(['--outputAODFile', 'my.AOD.pool.root'])
cmd.extend(['--outputHISTFile', 'my.HIST.root'])
cmd.extend(['--maxEvents', '10'])
#cmd.extend(['--preExec', 'rec.doTrigger=False']) # This is temporary while trigger doesn't work in r19
msg.info('Will run this transform: {0}'.format(cmd))
p = subprocess.Popen(cmd,
shell=False,
stdout=subprocess.PIPE,
stderr=subprocess.STDOUT,
bufsize=1)
while p.poll() is None:
line = p.stdout.readline()
sys.stdout.write(line.decode())
# Hoover up remaining buffered output lines
for line in p.stdout:
sys.stdout.write(line)
self.assertEqual(p.returncode, 0)
# Now load metadata and test a few important values
with open('jobReport.json') as jr:
md = json.load(jr)
self.assertEqual(isinstance(md, dict), True)
dataDict = pyJobReportToFileDict(md)
self.assertTrue('ESD' in dataDict)
self.assertTrue('AOD' in dataDict)
self.assertTrue('HIST' in dataDict)
self.assertEqual(dataDict['ESD']['subFiles'][0]['nentries'], 10)
self.assertEqual(dataDict['ESD']['subFiles'][0]['geometry'],
'ATLAS-GEO-20-00-01')
self.assertEqual(dataDict['ESD']['subFiles'][0]['conditions_tag'],
'COMCOND-BLKPA-006-01')
self.assertEqual(dataDict['ESD']['subFiles'][0]['beam_type'],
['collisions'])
self.assertEqual(dataDict['ESD']['subFiles'][0]['name'],
'my.ESD.pool.root')
self.assertEqual(dataDict['AOD']['subFiles'][0]['nentries'], 10)
self.assertEqual(dataDict['AOD']['subFiles'][0]['geometry'],
'ATLAS-GEO-20-00-01')
self.assertEqual(dataDict['AOD']['subFiles'][0]['conditions_tag'],
'COMCOND-BLKPA-006-01')
self.assertEqual(dataDict['AOD']['subFiles'][0]['beam_type'],
['collisions'])
self.assertEqual(dataDict['AOD']['subFiles'][0]['name'],
'my.AOD.pool.root')
self.assertEqual(dataDict['HIST']['subFiles'][0]['nentries'], 10)
def test_Reco_Tier0_tf(self):
pFile = 'job.pkl'
cmd = "Reco_tf.py --inputBSFile /afs/cern.ch/atlas/project/rig/referencefiles/dataStreams_high_mu/data12_8TeV/data12_8TeV.00201556.physics_JetTauEtmiss.merge.RAW._lb0423._SFO-1._0001.1 --maxEvents 5 --autoConfiguration everything --preExec 'rec.doDetailedAuditor=True' 'rec.doNameAuditor=True' 'rec.doCalo=False' 'rec.doInDet=False' 'rec.doMuon=False' 'rec.doJetMissingETTag=False' 'rec.doEgamma=False' 'rec.doMuonCombined=False' 'rec.doTau=False' 'rec.doTrigger=False' --outputESDFile myESD.pool.root --dumpPickle {0}".format(
pFile).split()
msg.info('Will run this transform: {0}'.format(cmd))
p = subprocess.Popen(cmd,
shell=False,
stdout=subprocess.PIPE,
stderr=subprocess.STDOUT,
bufsize=1)
while p.poll() is None:
line = p.stdout.readline()
sys.stdout.write(line)
# Hoover up remaining buffered output lines
for line in p.stdout:
sys.stdout.write(line)
self.assertEqual(p.returncode, 0)
# Check the pickle was produced
self.assertEqual(os.access(pFile, os.R_OK), True)
unpickleFile = open(pFile, 'r')
contents = pickle.load(unpickleFile)
unpickleFile.close()
self.assertEqual(isinstance(contents, dict), True)
# Now configure and run the transform from the pickle file
cmd = "Reco_tf.py --argdict {0} --outputESDFile newESD.pool.root".format(
pFile).split()
msg.info('Will run this transform: {0}'.format(cmd))
p = subprocess.Popen(cmd,
shell=False,
stdout=subprocess.PIPE,
stderr=subprocess.STDOUT,
bufsize=1)
while p.poll() is None:
line = p.stdout.readline()
sys.stdout.write(line)
# Hoover up remaining buffered output lines
for line in p.stdout:
sys.stdout.write(line)
self.assertEqual(p.returncode, 0)
# Now load metadata and test a few important values
with open('jobReport.json') as jr:
md = json.load(jr)
self.assertEqual(isinstance(md, dict), True)
dataDict = pyJobReportToFileDict(md)
self.assertTrue('ESD' in dataDict.keys())
self.assertEqual(dataDict['ESD']['subFiles'][0]['nentries'], 5)
self.assertEqual(dataDict['ESD']['subFiles'][0]['name'],
'newESD.pool.root')
def test_runReco_tf(self):
inputs = glob.glob(sourceFiles)
self.assertEqual(len(inputs), 1)
cmd = ['Reco_tf.py', '--inputBSFile']
cmd.extend(inputs)
cmd.extend([
'--outputESDFile', 'my.ESD.pool.root', '--autoConfiguration',
'everything'
])
cmd.extend(['--outputAODFile', 'my.AOD.pool.root'])
cmd.extend(['--outputHISTFile', 'my.HIST.root'])
cmd.extend(['--outputTAGFile', 'my.TAG.pool.root'])
cmd.extend(['--maxEvents', '10'])
cmd.extend(['--preExec', 'rec.doTrigger=False'
]) # This is temporary while trigger doesn't work in r19
## Event counting currently broken for multi-step transforms
cmd.extend(['--checkEventCount', 'true'])
msg.info('Will run this transform: {0}'.format(cmd))
p = subprocess.Popen(cmd,
shell=False,
stdout=subprocess.PIPE,
stderr=subprocess.STDOUT,
bufsize=1)
while p.poll() is None:
line = p.stdout.readline()
sys.stdout.write(line)
# Hoover up remaining buffered output lines
for line in p.stdout:
sys.stdout.write(line)
self.assertEqual(p.returncode, 0)
# Now load metadata and test a few important values
with open('jobReport.json') as jr:
md = json.load(jr)
self.assertEqual(isinstance(md, dict), True)
dataDict = pyJobReportToFileDict(md)
self.assertTrue('ESD' in dataDict.keys())
self.assertTrue('AOD' in dataDict.keys())
self.assertTrue('HIST' in dataDict.keys())
self.assertTrue('TAG' in dataDict.keys())
self.assertEqual(dataDict['ESD']['subFiles'][0]['nentries'], 10)
self.assertEqual(dataDict['ESD']['subFiles'][0]['name'],
'my.ESD.pool.root')
self.assertEqual(dataDict['AOD']['subFiles'][0]['nentries'], 10)
self.assertEqual(dataDict['AOD']['subFiles'][0]['name'],
'my.AOD.pool.root')
self.assertEqual(dataDict['HIST']['subFiles'][0]['nentries'], 10)
self.assertEqual(dataDict['TAG']['subFiles'][0]['nentries'], 10)
def test_runReco_tf(self):
cmd = ['AtlasG4_tf.py', '--inputEvgenFile', sourceFile]
cmd.extend(['--outputHITSFile', 'test.HITS.pool.root'])
cmd.extend(['--geometryVersion', 'ATLAS-GEO-20-00-01'])
cmd.extend(['--conditionsTag', 'OFLCOND-MC12-SIM-00'])
cmd.extend(['--randomSeed', '10'])
cmd.extend(['--skipEvents', '0'])
cmd.extend(['--maxEvents', '2']) # 2 events - this is a slow job
## Event counting currently broken for multi-step transforms
msg.info('Will run this transform: {0}'.format(cmd))
p = subprocess.Popen(cmd,
shell=False,
stdout=subprocess.PIPE,
stderr=subprocess.STDOUT,
bufsize=1)
while p.poll() is None:
line = p.stdout.readline()
sys.stdout.write(line.decode())
# Hoover up remaining buffered output lines
for line in p.stdout:
sys.stdout.write(line)
self.assertEqual(p.returncode, 0)
# Now load metadata and test a few important values
with open('jobReport.json') as jr:
md = json.load(jr)
self.assertEqual(isinstance(md, dict), True)
dataDict = pyJobReportToFileDict(md)
# Change in SimuJobTransforms, but be compatible with type = hits and HITS
dataKey = None
if 'hits' in dataDict:
dataKey = 'hits'
elif 'HITS' in dataDict:
dataKey = 'HITS'
self.assertNotEqual(dataKey, None)
self.assertEqual(dataDict[dataKey]['subFiles'][0]['nentries'], 2)
self.assertEqual(dataDict[dataKey]['subFiles'][0]['geometry'],
'ATLAS-GEO-20-00-01')
self.assertEqual(
dataDict[dataKey]['subFiles'][0]['conditions_tag'],
'OFLCOND-MC12-SIM-00')
