对13 TeV 的cross section测量,我们现在打算用某一些特定TCK取下的数据,这就要求在扫描数据的时候将不需要的TCK事例扔掉。如果依靠tuple level的筛选,那么最终的 integrated luminosity 很难确定出来。

在LHCb上,是依靠ganga来实现这个功能的。

在ganga的脚本里,关于dataset的定义修改为如下:

job=Job(
   name = Name,
   application = Application,
   splitter    = SplitByFiles ( filesPerJob = NFilePerJob, maxFiles = MaxFiles, ignoremissing = True ),
   merger      = RootMerger (files=[OutputTuple],overwrite=True,ignorefailed=True),
   inputsandbox = [],
   outputfiles = [LocalFile(OutputTuple)],
   backend     = Dirac(),
   inputdata = FilterTCKs (bkk_directory) )
job.submit() 

其中,

def FilterTCKs (path):
   badtcks=['0x10600a6', '0x10600a7', '0x10700a1']
   dataset = BKQuery(path, type = "Path", dqflag=['OK']).getDataset()
   datasetM = BKQuery(path, type = "Path", dqflag=['OK']).getDatasetMetadata()
   filteredFiles = []

   for f in dataset.files:
       if datasetM['Value'][f.localDir]['TCK'] in badtcks:
           filteredFiles.append(f)

   for f in filteredFiles:
       dataset.files.remove(f)

   return dataset

这样就能把A1,A6,A7取下的数据扔掉。

另外,2015年的MagUp没有用到到以上的TCK,所以只需要重新扫描一遍MagDown数据。

-- HangYin - 2016-06-06

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Topic revision: r1 - 2016-06-06 - HangYin
 
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