def __loadChain(self):
''' Load the TChain. Private.
'''
if len(self.files) == 0:
raise helpers.EmptySampleError("Sample {name} has no input files! Can not load.".format(name = self.name) )
else:
self._chain = ROOT.TChain(self.treeName)
counter = 0
for f in self.files:
logger.debug("Now adding file %s to sample '%s'", f, self.name)
try:
if helpers.checkRootFile(f, checkForObjects=[self.treeName]):
self._chain.Add(f)
counter+=1
else:
logger.error( "Check of root file failed. Skipping. File: %s", f )
except IOError as e:
logger.error( "Could not load file %s", f )
#raise e
logger.debug( "Loaded %i files for sample '%s'.", counter, self.name )
# Add friends
if hasattr( self, 'friends'): # Catch cases where cached samples have no default value for friends attribute
for friend_sample, friend_treeName in self.friends:
self.chain.AddFriend(friend_sample.chain, friend_treeName)
def __loadChain(self):
''' Load the TChain. Private.
'''
if len(self.files) == 0:
raise helpers.EmptySampleError("Sample {name} has no input files! Can not load.".format(name = self.name) )
else:
self._chain = ROOT.TChain(self.treeName)
counter = 0
for f in self.files:
logger.debug("Now adding file %s to sample '%s'", f, self.name)
try:
if helpers.checkRootFile(f, checkForObjects=[self.treeName]):
self._chain.Add(f)
counter+=1
else:
logger.error( "Check of root file failed. Skipping. File: %s", f )
except IOError as e:
logger.error( "Could not load file %s", f )
#raise e
logger.debug( "Loaded %i files for sample '%s'.", counter, self.name )
# Add friends
if hasattr( self, 'friends'): # Catch cases where cached samples have no default value for friends attribute
for friend_sample, friend_treeName in self.friends:
self.chain.AddFriend(friend_sample.chain, friend_treeName)
def __loadChain(self):
''' Load the TChain. Private.
'''
if len(self.files) == 0:
raise helpers.EmptySampleError("Sample {name} has no input files! Can not load.".format(name = self.name) )
else:
self._chain = ROOT.TChain(self.treeName)
counter = 0
for f in self.files:
logger.debug("Now adding file %s to sample '%s'", f, self.name)
try:
if helpers.checkRootFile(f, checkForObjects=[self.treeName]):
self._chain.Add(f)
counter+=1
except IOError:
pass
logger.warning( "Could not load file %s", f )
logger.debug( "Loaded %i files for sample '%s'.", counter, self.name )
def __init__(self,
heppy_samples,
dpm_directories,
cache_file,
multithreading=True):
# Read cache file, if exists
if os.path.exists(cache_file) and not overwrite:
self.sample_map = pickle.load(file(cache_file))
logger.info("Loaded cache file %s" % cache_file)
else:
logger.info("Cache file %s not found. Recreate map.", cache_file)
logger.info("Check proxy.")
# Proxy certificate
from RootTools.core.helpers import renew_proxy
# Make proxy in afs to allow batch jobs to run
proxy_path = os.path.expandvars('$HOME/private/.proxy')
proxy = renew_proxy(proxy_path)
logger.info("Using proxy %s" % proxy)
# Read dpm directories
self.cmg_directories = {}
for data_path in dpm_directories:
logger.info("Walking dpm directory %s", data_path)
walker = walk_dpm(data_path)
self.cmg_directories[
data_path] = walker.walk_dpm_cmgdirectories('.', maxN=maxN)
#del walker
logger.info("Now mapping directories to heppy samples")
for heppy_sample in heppy_samples:
heppy_sample.candidate_directories = []
pd, era = heppy_sample.dataset.split('/')[1:3]
for data_path in self.cmg_directories.keys():
for dpm_directory in self.cmg_directories[data_path].keys(
):
if not ('/%s/' % pd in dpm_directory):
logger.debug("/%s/ not in dpm_directory %s", pd,
dpm_directory)
continue
if not ('/' + era in dpm_directory):
logger.debug("/%s not in dpm_directory %s", era,
dpm_directory)
continue
heppy_sample.candidate_directories.append(
[data_path, dpm_directory])
logger.debug("heppy sample %s in %s",
heppy_sample.name, dpm_directory)
logger.info("Found heppy sample %s in %i directories.",
heppy_sample.name,
len(heppy_sample.candidate_directories))
# Merge
from RootTools.core.Sample import Sample
logger.info(
"Now making new sample map from %i directories and for %i heppy samples to be stored in %s",
len(dpm_directories), len(heppy_samples), cache_file)
self.sample_map = {}
for heppy_sample in heppy_samples:
if len(heppy_sample.candidate_directories) == 0:
logger.info("No directory found for %s", heppy_sample.name)
else:
normalization, files = walker.combine_cmg_directories(\
cmg_directories = {dpm_directory:self.cmg_directories[data_path][dpm_directory] for data_path, dpm_directory in heppy_sample.candidate_directories },
multithreading = multithreading,
)
logger.info(
"Sample %s: Found a total of %i files with normalization %3.2f",
heppy_sample.name, len(files), normalization)
tmp_files = []
for f in files:
isGoodFile = False
try:
isGoodFile = checkRootFile(
"root://hephyse.oeaw.ac.at/" + os.path.join(f))
logger.debug("File %s got added", f)
except IOError:
logger.info("File %s is corrupted, skipping", f)
if isGoodFile: tmp_files.append(f)
self.sample_map[heppy_sample] = Sample.fromFiles(
heppy_sample.name,
files=[
'root://hephyse.oeaw.ac.at/' + f for f in tmp_files
],
normalization=normalization,
treeName='tree',
isData=heppy_sample.isData,
maxN=maxN)
logger.info(
"Combined %i directories for sample %s to a total of %i files with normalization %3.2f",
len(heppy_sample.candidate_directories),
heppy_sample.name, len(files), normalization)
# Store cache file
dir_name = os.path.dirname(cache_file)
if len(self.sample_map.keys()) > 0:
if not os.path.exists(dir_name): os.makedirs(dir_name)
pickle.dump(self.sample_map, file(cache_file, 'w'))
logger.info("Created MC sample cache %s", cache_file)
else:
logger.info("Skipping to write %s because map is empty.",
cache_file)
def fromDAS(cls, name, dataset, instance = 'global', prefix='root://cms-xrd-global.cern.ch/', texName = None, maxN = None, dbFile=None, overwrite=False, skipCheck = False):
''' Make sample from DAS.
'''
# https://github.com/CERN-PH-CMG/cmg-cmssw/blob/0f1d3bf62e7ec91c2e249af1555644b7f414ab50/CMGTools/Production/python/dataset.py#L437
maxN = maxN if maxN is not None and maxN>0 else None
limit = maxN if maxN else 0
DASname = dataset.rstrip('/')
n_cache_files = 0
# Don't use the cache on partial queries
if dbFile is not None and ( maxN<0 or maxN is None ):
cache = Database(dbFile, "fileCache", ["name"])
n_cache_files = cache.contains({'name':name})
else:
cache = None
if n_cache_files and not overwrite:
files = [ f["value"] for f in cache.getDicts({'name':name}) ]
logger.info('Found sample %s in cache %s, return %i files.', name, dbFile, len(files))
else:
# def _dasPopen(dbs):
# if 'LSB_JOBID' in os.environ:
# raise RuntimeError, "Trying to do a DAS query while in a LXBatch job (env variable LSB_JOBID defined)\nquery was: %s" % dbs
# if 'X509_USER_PROXY' in os.environ:
# dbs += " --key {0} --cert {0}".format(os.environ['X509_USER_PROXY'])
# logger.info('DAS query\t: %s', dbs)
# return os.popen(dbs)
#
# sampleName = dataset.rstrip('/')
# query, qwhat = sampleName, "dataset"
# if "#" in sampleName: qwhat = "block"
#
# dbs='das_client --query="file %s=%s instance=prod/%s" --limit %i'%(qwhat,query, instance, limit)
# dbsOut = _dasPopen(dbs).readlines()
if overwrite:
cache.removeObjects({"name":name})
def _dasPopen(dbs):
if 'LSB_JOBID' in os.environ:
raise RuntimeError, "Trying to do a DAS query while in a LXBatch job (env variable LSB_JOBID defined)\nquery was: %s" % dbs
logger.info('DAS query\t: %s', dbs)
return os.popen(dbs)
query, qwhat = DASname, "dataset"
if "#" in DASname: qwhat = "block"
dbs='dasgoclient -query="file %s=%s instance=prod/%s" --limit %i'%(qwhat,query, instance, limit)
dbsOut = _dasPopen(dbs).readlines()
files = []
for line in dbsOut:
if line.startswith('/store/'):
line = line.rstrip()
filename = line
try:
if skipCheck or helpers.checkRootFile(prefix+filename):
files.append(filename)
except IOError:
logger.warning( "IOError for file %s. Skipping.", filename )
if cache is not None:
cache.add({"name":name}, filename, save=True)
if limit>0: files=files[:limit]
result = cls(name, files=[prefix+file for file in files], texName = texName)
result.DASname = DASname
return result
def fromCMGCrabDirectory(cls, name, baseDirectory, treeFilename = 'tree.root', treeName = 'tree', maxN = None, \
selectionString = None, weightString = None,
isData = False, color = 0, texName = None):
'''Load a CMG crab output directory
'''
import tarfile
from cmg_helpers import read_cmg_normalization
maxN = maxN if maxN is not None and maxN>0 else None
# Walk through all subdirectories and pick up pairs of files '..._n.root and ..._n.tgz where n is the job number'
treeFiles = {}
zipFiles = {}
for root, subFolders, filenames in os.walk( baseDirectory ):
for filename in filenames:
base, ext = os.path.splitext( filename )
try:
n = int(base.split('_')[-1])
except:
# filename is not of the form 'xyz_n' where n is the job number
continue
# add the tgz and files to the dict.
filename_ = os.path.join(root, filename)
if ext=='.root':
treeFiles[n] = filename_
if ext=='.tgz':
zipFiles[n] = filename_
# Find pairs of zip and root files
pairs = set(zipFiles.keys()) & set(treeFiles.keys())
n_jobs = len( set(zipFiles.keys()) | set(treeFiles.keys()) )
normalization = 0
files = []
failedJobs = []
for n in pairs:
sumW = None
tf = tarfile.open( zipFiles[n], 'r:gz' )
for f in tf.getmembers():
if "SkimReport.txt" in f.name:
sumW = read_cmg_normalization(tf.extractfile(f))
if sumW is not None: break
if sumW is None:
logger.warning( "No normalization found when reading tar file %s", zipFiles[n] )
tf.close()
# Check treefile for whether the tree 'treeName' can be found.
# This is an implicit check for broken, recovered or otherwise corrupted root files.
treeFile = treeFiles[n] if helpers.checkRootFile(treeFiles[n], checkForObjects = [treeName] ) else None
if treeFile is None: logger.warning( "File %s looks broken. Checked for presence of tree %s.", treeFiles[n] , treeName )
# If both, normalization and treefile are OK call it successful.
if sumW and treeFile:
files.append( treeFile )
normalization += sumW
logger.debug( "Successfully read job %i and incremented normalization by %7.2f", n, sumW )
else:
failedJobs.append( n )
# Don't allow empty samples
if len(files) == 0:
raise helpers.EmptySampleError("Could not find valid crab CMG output for sample {0}. Total number of jobs: {1}. baseDirectory: {2}"\
.format(name, len(pairs), baseDirectory))
# Log statements
eff = 100*len(failedJobs)/float( n_jobs )
logger.debug("Loaded CMGOutput sample %s. Total number of jobs: %i, both tgz and root: %i. Normalization: %7.2f Bad: %i. Inefficiency: %3.3f", \
name, len(pairs), n_jobs, normalization, len(failedJobs), eff)
logger.debug( "Read %i chunks and total normalization of %f", len(files), normalization )
return cls( name = name, treeName = treeName, files = files, normalization = normalization,
selectionString = selectionString, weightString = weightString,
isData = isData, color = color, texName = texName )
def fromCMGOutput(cls, name, baseDirectory, treeFilename = 'tree.root', chunkString = None, treeName = 'tree', maxN = None, \
selectionString = None, weightString = None,
isData = False, color = 0, texName = None):
'''Load a CMG output directory from e.g. unzipped crab output in the 'Chunks' directory structure.
Expects the presence of the tree root file and the SkimReport.txt
'''
from cmg_helpers import read_cmg_normalization
maxN = maxN if maxN is not None and maxN>0 else None
# Reading all subdirectories in base directory. If chunkString != None, require cmg output name formatting
chunkDirectories = []
# FIXME: Better to loop only over subdirectories in base directory?
for x in os.listdir(baseDirectory):
if os.path.isdir(os.path.join(baseDirectory, x)):
if not chunkString or (x.startswith(chunkString) and x.endswith('_Chunk')) or x==chunkString:
chunkDirectories.append(os.path.join(baseDirectory, x))
if len(chunkDirectories)==maxN:break
logger.debug( "Found %i chunk directories with chunkString %s in base directory %s", \
len(chunkDirectories), chunkString, baseDirectory )
normalization = 0
files = []
failedChunks=[]
goodChunks =[]
for i, chunkDirectory in enumerate( chunkDirectories ):
success = False
logger.debug("Reading chunk %s", chunkDirectory)
# Find normalization
sumW = None
for root, subFolders, filenames in os.walk( chunkDirectory ):
# Determine normalization constant
if 'SkimReport.txt' in filenames:
skimReportFilename = os.path.join(root, 'SkimReport.txt')
with open(skimReportFilename, 'r') as fin:
sumW = read_cmg_normalization(fin)
if not sumW:
logger.warning( "Read chunk %s and found report '%s' but could not read normalization.",
chunkDirectory, skimReportFilename )
# Find treefile
treeFile = None
for root, subFolders, filenames in os.walk( chunkDirectory ):
# Load tree file
if treeFilename in filenames:
treeFile = os.path.join(root, treeFilename)
# Checking whether root file is OG and contains a tree
if not helpers.checkRootFile(treeFile, checkForObjects=[treeName] ):
logger.warning( "Read chunk %s and found tree file '%s' but file looks broken.", chunkDirectory, treeFile )
# If both, normalization and treefile are OK call it successful.
if sumW and treeFile:
files.append( treeFile )
normalization += sumW
logger.debug( "Successfully read chunk %s and incremented normalization by %7.2f", chunkDirectory, sumW )
success = True
goodChunks.append( chunkDirectory )
if not success:
failedChunks.append( chunkDirectory )
# Don't allow empty samples
if len(goodChunks) == 0:
raise helpers.EmptySampleError("Could not find good CMGOutput chunks for sample {0}. Total number of chunks: {1}. baseDirectory: {2}"\
.format(name, len(chunkDirectories), baseDirectory))
# Log statements
eff = 100*len(failedChunks)/float( len(chunkDirectories) )
logger.debug("Loaded CMGOutput sample %s. Total number of chunks : %i. Normalization: %7.2f Bad: %i. Inefficiency: %3.3f", \
name, len(chunkDirectories), normalization, len(failedChunks), eff)
for chunk in failedChunks:
logger.debug( "Failed to load chunk %s", chunk)
logger.debug( "Read %i chunks and total normalization of %f", len(files), normalization )
return cls( name = name, treeName = treeName, files = files, normalization = normalization,
selectionString = selectionString, weightString = weightString,
isData = isData, color = color, texName = texName )
argParser.add_argument('--logLevel', action='store', nargs='?', choices=['CRITICAL', 'ERROR', 'WARNING', 'INFO', 'DEBUG', 'TRACE', 'NOTSET'], default='INFO', help="Log level for logging" )
args = argParser.parse_args()
logger = logger.get_logger(args.logLevel, logFile = None)
# Check if the gridpack exists
if not os.path.exists( args.gridpack ):
logger.error( "Gridpack %s not found. Exit", args.gridpack )
sys.exit(0)
gp = os.path.basename(args.gridpack).rstrip('.tar.xz')
# Check if the output is there
out_file = os.path.join( skim_output_directory, 'gen', args.outDir, gp, gp+'.root')
if os.path.exists( out_file ) and checkRootFile( out_file, checkForObjects=["Events"] ):
logger.info( "Found output file %s.", out_file )
if args.overwrite:
os.remove( out_file )
logger.info( "Deleted, because I overwrite." )
else:
sys.exit(0)
else:
logger.info( "Did not find output file %s. Look for gen sample. ", out_file )
# Check if the intermediate gen file is there
gen_file = os.path.join( args.genSampleDir, gp, 'events.root' )
if os.path.exists( gen_file ) and checkEDMRootFile( gen_file ):
logger.info( "Found edm gen file %s.", gen_file)
if args.overwriteGenFile:
os.remove( gen_file )
def fromDPMDirectory(cls,
name,
directory,
prefix='root://hephyse.oeaw.ac.at/',
texName=None,
maxN=None,
dbFile=None,
overwrite=False,
skipCheck=False):
maxN = maxN if maxN is not None and maxN > 0 else None
limit = maxN if maxN else 0
n_cache_files = 0
# Don't use the cache on partial queries
if dbFile is not None and (maxN < 0 or maxN is None):
cache = Database(dbFile, "fileCache", ["name"])
n_cache_files = cache.contains({'name': name})
else:
cache = None
if n_cache_files and not overwrite:
files = [f["value"] for f in cache.getDicts({'name': name})]
logger.info('Found sample %s in cache %s, return %i files.', name,
dbFile, len(files))
else:
if overwrite:
cache.removeObjects({"name": name})
def _dasPopen(dbs):
if 'LSB_JOBID' in os.environ:
raise RuntimeError, "Trying to do a DAS query while in a LXBatch job (env variable LSB_JOBID defined)\nquery was: %s" % dbs
logger.info('DAS query\t: %s', dbs)
return os.popen(dbs)
files = []
dbs = 'xrdfs %s ls %s' % (prefix, directory)
dbsOut = _dasPopen(dbs).readlines()
for line in dbsOut:
if line.startswith('/store/'):
line = line.rstrip()
filename = line
try:
if skipCheck or helpers.checkRootFile(prefix +
filename):
files.append(filename)
except IOError:
logger.warning("IOError for file %s. Skipping.",
filename)
if cache is not None:
cache.add({"name": name}, filename, save=True)
if limit > 0: files = files[:limit]
result = cls(name,
files=[prefix + file for file in files],
texName=texName)
result.DASname = prefix + directory.rstrip("/")
return result
def fromCMGCrabDirectory(cls, name, baseDirectory, treeFilename = 'tree.root', treeName = 'tree', maxN = None, xSection = -1,\
selectionString = None, weightString = None,
isData = False, color = 0, texName = None):
'''Load a CMG crab output directory
'''
import tarfile
from cmg_helpers import read_cmg_normalization
maxN = maxN if maxN is not None and maxN>0 else None
# Walk through all subdirectories and pick up pairs of files '..._n.root and ..._n.tgz where n is the job number'
treeFiles = {}
zipFiles = {}
for root, subFolders, filenames in os.walk( baseDirectory ):
for filename in filenames:
base, ext = os.path.splitext( filename )
try:
n = int(base.split('_')[-1])
except:
# filename is not of the form 'xyz_n' where n is the job number
continue
# add the tgz and files to the dict.
filename_ = os.path.join(root, filename)
if ext=='.root':
treeFiles[n] = filename_
if ext=='.tgz':
zipFiles[n] = filename_
# Find pairs of zip and root files
pairs = set(zipFiles.keys()) & set(treeFiles.keys())
n_jobs = len( set(zipFiles.keys()) | set(treeFiles.keys()) )
normalization = 0
files = []
failedJobs = []
for n in pairs:
sumW = None
tf = tarfile.open( zipFiles[n], 'r:gz' )
for f in tf.getmembers():
if "SkimReport.txt" in f.name:
sumW = read_cmg_normalization(tf.extractfile(f))
if sumW is not None: break
if sumW is None:
logger.warning( "No normalization found when reading tar file %s", zipFiles[n] )
tf.close()
# Check treefile for whether the tree 'treeName' can be found.
# This is an implicit check for broken, recovered or otherwise corrupted root files.
treeFile = treeFiles[n] if helpers.checkRootFile(treeFiles[n], checkForObjects = [treeName] ) else None
if treeFile is None: logger.warning( "File %s looks broken. Checked for presence of tree %s.", treeFiles[n] , treeName )
# If both, normalization and treefile are OK call it successful.
if sumW and treeFile:
files.append( treeFile )
normalization += sumW
logger.debug( "Successfully read job %i and incremented normalization by %7.2f", n, sumW )
else:
failedJobs.append( n )
# Don't allow empty samples
if len(files) == 0:
raise helpers.EmptySampleError("Could not find valid crab CMG output for sample {0}. Total number of jobs: {1}. baseDirectory: {2}"\
.format(name, len(pairs), baseDirectory))
# Log statements
eff = 100*len(failedJobs)/float( n_jobs )
logger.debug("Loaded CMGOutput sample %s. Total number of jobs: %i, both tgz and root: %i. Normalization: %7.2f Bad: %i. Inefficiency: %3.3f", \
name, len(pairs), n_jobs, normalization, len(failedJobs), eff)
logger.debug( "Read %i chunks and total normalization of %f", len(files), normalization )
return cls( name = name, treeName = treeName, files = files, normalization = normalization, xSection = xSection,
selectionString = selectionString, weightString = weightString,
isData = isData, color = color, texName = texName )
def fromCMGOutput(cls, name, baseDirectory, treeFilename = 'tree.root', chunkString = None, treeName = 'tree', maxN = None, \
selectionString = None, xSection = -1, weightString = None,
isData = False, color = 0, texName = None):
'''Load a CMG output directory from e.g. unzipped crab output in the 'Chunks' directory structure.
Expects the presence of the tree root file and the SkimReport.txt
'''
from cmg_helpers import read_cmg_normalization
maxN = maxN if maxN is not None and maxN>0 else None
# Reading all subdirectories in base directory. If chunkString != None, require cmg output name formatting
chunkDirectories = []
# FIXME: Better to loop only over subdirectories in base directory?
for x in os.listdir(baseDirectory):
if os.path.isdir(os.path.join(baseDirectory, x)):
if not chunkString or (x.startswith(chunkString) and x.endswith('_Chunk')) or x==chunkString:
chunkDirectories.append(os.path.join(baseDirectory, x))
if len(chunkDirectories)==maxN:break
logger.debug( "Found %i chunk directories with chunkString %s in base directory %s", \
len(chunkDirectories), chunkString, baseDirectory )
normalization = 0
files = []
failedChunks=[]
goodChunks =[]
for i, chunkDirectory in enumerate( chunkDirectories ):
success = False
logger.debug("Reading chunk %s", chunkDirectory)
# Find normalization
sumW = None
for root, subFolders, filenames in os.walk( chunkDirectory ):
# Determine normalization constant
if 'SkimReport.txt' in filenames:
skimReportFilename = os.path.join(root, 'SkimReport.txt')
with open(skimReportFilename, 'r') as fin:
sumW = read_cmg_normalization(fin)
if not sumW:
logger.warning( "Read chunk %s and found report '%s' but could not read normalization.",
chunkDirectory, skimReportFilename )
# Find treefile
treeFile = None
for root, subFolders, filenames in os.walk( chunkDirectory ):
# Load tree file
if treeFilename in filenames:
treeFile = os.path.join(root, treeFilename)
# Checking whether root file is OG and contains a tree
if not helpers.checkRootFile(treeFile, checkForObjects=[treeName] ):
logger.warning( "Read chunk %s and found tree file '%s' but file looks broken.", chunkDirectory, treeFile )
# If both, normalization and treefile are OK call it successful.
if sumW and treeFile:
files.append( treeFile )
normalization += sumW
logger.debug( "Successfully read chunk %s and incremented normalization by %7.2f", chunkDirectory, sumW )
success = True
goodChunks.append( chunkDirectory )
if not success:
failedChunks.append( chunkDirectory )
# Don't allow empty samples
if len(goodChunks) == 0:
raise helpers.EmptySampleError("Could not find good CMGOutput chunks for sample {0}. Total number of chunks: {1}. baseDirectory: {2}"\
.format(name, len(chunkDirectories), baseDirectory))
# Log statements
eff = 100*len(failedChunks)/float( len(chunkDirectories) )
logger.debug("Loaded CMGOutput sample %s. Total number of chunks : %i. Normalization: %7.2f Bad: %i. Inefficiency: %3.3f", \
name, len(chunkDirectories), normalization, len(failedChunks), eff)
for chunk in failedChunks:
logger.debug( "Failed to load chunk %s", chunk)
logger.debug( "Read %i chunks and total normalization of %f", len(files), normalization )
return cls( name = name, treeName = treeName, files = files, normalization = normalization,
selectionString = selectionString, weightString = weightString, xSection = xSection,
isData = isData, color = color, texName = texName )
