Physics Performance and Datasets exercises

Overview

In this set of exercises you will learn how to look for the datasets and find out their key properties relevant for the analysis: how to navigate their parent-child relationship and determine the software release, production configuration, alignment-calibration conditions they've been produced with, e.g. cmsdrivers, global tags, production configuration files, gridpacks, cross section and more production details of samples. You'll be exposed to using the principal services providing status and details of datasets: *DAS*, brilcalc, McM, pMp, cmsDBbrowser. You'll also find out how to compute the integrated luminosity for your analysis.

Contact

Please contact Gurpreet Singh Chahal (gurpreet.singh@cernNOSPAMPLEASE.ch) and Tongguang Cheng (tongguang.cheng@cernNOSPAMPLEASE.ch) for questions, comments or suggestions about this exercise.

Introduction to datasets

Summarise there the content of the slides, add a pointer to them:

• For an introduction, please see the slides at PPD short exercises (XXX)
• Take note of these two documentation twiki: PdmVDataReprocessing: data reprocessing campaigns * PdmVMcCampaigns: Monte Carlo campaigns

Getting ready for these exercises

A bit of preparation will ease following this tutorial. Below a few concrete actions you can take before starting the hands-on session.

Prerequisites

In order to carry out the exercises of this session you need:

• a CMS account at CERN to access web services (you can access this twiki you have it) and log into lxplus
• a grid certicate installed on your favourite web browser
• read the XXX is beneficial

Setup a CMSSW area

Most of the exercises will be carried out using your web browser. A CMSSW work area will also be needed during the exercise.

Now you are ready to proceed to the exercises.

Exercise 1: Exploring dataset searching using DAS

Reminder about the general structure of a dataset name:

 dataset = /PrimaryDataset/ProcessingVersion/DataTier

Examples:

dataset = /BTagCSV/Run2015B-05Aug2015-v1/AOD

To start with, you need to establish the full dataset name "with single electron". Either you know it from a reference, or you need to construct a key elements of it, and put them together in a search. With the key elements at hand, you'll be able to use the *DAS* web interface and queries with wildcard in order to establish or confirm the complete dataset name.

1. what is the primary dataset name ? 1. what is the primary dataset name ?

2. what is the Processing Version ? 2. what is the Processing Version ?

3. what is the Data Tier ? 3. what is the Data Tier?

You can now place a query to DAS to find the dataset; using the wildcard increases the chances of finding at the first try what you're looking for with no need to remember the details of the naming conventions - of course, you ought to use the wildcard with a pinch of salt, not to be flooded with too many results matching your query.

dataset dataset=/SingleElectron*/*Run2017D*17Nov2017*/MINIAOD 

4. Is the dataset preset at a site which is accessible to cmsRun ? 4. Is the dataset preset at a site which is accessible to cmsRun?

• → check the Sites

• note that some sites are not accessible to the users (e.g. : tape storage)

Place your final query to DAS looking for the file you want at a site where the dataset has a presence. (note: the site where the dataset is present might change with time, thus the site chosen in detailed query which follows might need to be updated):

file dataset=/SingleElectron/Run2017D-17Nov2017-v1/MINIAOD site=T1_US_FNAL_Buffer
Does the query return a file ? If not, why and which site(s) we use to return a file ? 

You can now run on one of the files and find out its basic properties, exploiting the fact that xrootd will serve the file you've chosen from the CMS site where it's available on disk to your cmsRun process:

 edmFileUtil   --eventsInLumis  -P   root://xrootd.unl.edu//store/data/Run2017D/SingleElectron/MINIAOD/17Nov2017-v1/70000/FEDC8953-1ADA-E711-AC4E-02163E013395.root (*update with the actual file you've found*) 

Exercise 2: Explore information for a Monte Carlo miniAODSIM sample from DAS, McM and pMp

The sample we start from is the TTJets sample overlaid with the pile up which matches the profile of instantaneous luminosity of the 2016 data taking:

dataset dataset=/TT_TuneCUETP8M2T4_13TeV-powheg-pythia8/RunIISummer17MiniAOD-92X_upgrade2017_realistic_v7-v1/MINIAODSIM 

1. what is the global tag used for its digi-reco ? 1. what is the global tag used for its digi-reco ?

find with DAS the GEN-SIM parent of the MINIAOD dataset find with DAS the GEN-SIM parent of the MINIAODSIM dataset

• Click on the Parents link in the DAS presentation of the dataset

find with DAS the children of the GEN-SIM parent 6. find with DAS the children of the GEN-SIM parent

• Click on the Children link in the DAS presentation of the dataset

• Multiple children are found, spanning over 6 pile up scenario

Any Monte Carlo sample is associated to a prepID, a unique identifier of the production request which has produced it. prepID 's are strings like HCA-RunIIFall15DR76-00002, formed by the physics group which has placed the production request, the production campaign and an integer number.

prepID 's are used by the Monte Carlo Management Meeting, where production requests are notified and prioritized, and by the computing operation teams, and are the identifier used in its two key web based platforms: Monte Carlo Management (McM) and production Monitoring platform (pMp).

2. Find the prepID of the sample using DAS 2. Find the prepID using DAS

• TOP-RunIIFall17MiniAODv2-00002

3. Find in McM the request which has produced of the sample 3. Find in McM the request which has produced of the sample

4. Get the McM test command sequence with the full digi-reco configuration 4. Get the McM test command sequence with the full digi-reco configuration

5. Explore the request chain(s) 5. Explore the request chain(s)

Exercise 3: Generating MC miniAOD events from scratch

• Follow slides 24, 25, 26 from PPD short exercises slides.
  • Get test command for GEN-SIM or LHE request
  • Go to terminal, enter your work area
  • $> wget <URL>
  • Initialize your grid proxy certificate
  • $> voms-proxy-init -voms cms
  • Update the script in accord with your needs
  • Launch test command
  • $> source <filename>
  • Request.xml, Request.py, Request.root files will be created
  • Read logs and explore these files
  • If everything seems reasonable, you can also produce DIGI-RECO and miniAOD in same file by adding appropriate cmsdrivers, etc.

Exercise 4: Compute the integrated luminosity collected by CMS in 2017

The data collected by CMS are certified on a luminosity-section basis to determine which data is of good quality to be included in physics analyses. The data certification is carried out taking into account both the health in operation of the sub-detectors at and the scrutiny of the reconstructed physics objects by DPG and POG experts. The outcome of the certification process as more data gets collected and for each new version of the data processing is regularly updated by the DQM-DataCertification with reports at the PPD General Meeting and by means of json files, also available in this certification repository:

ls -ltrFh /afs/cern.ch/cms/CAF/CMSCOMM/COMM_DQM/certification/Collisions17/13TeV/ReReco/Cert_294927-306462_13TeV_EOY2017ReReco_Collisions17_JSON_v1.txt

The json files from the certification are used to restrict the events to be included in analysis, typically setting the lumiMask in the crab configuration.

You can see the run and luminosity section structure by opening one of the files:

cat  /afs/cern.ch/cms/CAF/CMSCOMM/COMM_DQM/certification/Collisions17/13TeV/ReReco/Cert_294927-306462_13TeV_EOY2017ReReco_Collisions17_JSON_v1.txt

Only successfully processed luminosity sections should be used to compute the integrated luminosity of your analysis: that's typically achieved by asking for the crab report, which is also in json format, and provides a summary file of the runs and luminosity sections processed by completed jobs. Here, for semplicity, we'll use directly the certification exercise for luminosity calculation, assuming all processing jobs for run 305842 have been successful.

The luminosity information can be accessed via the BRIL Work Suite , which needs a simple installation procedure:

pip install --install-option="--prefix=$HOME/.local" brilws
*bash* : export PATH=$HOME/.local/bin:/afs/cern.ch/cms/lumi/brilconda-1.0.3/bin:$PATH
*tcsh* : setenv PATH $HOME/.local/bin:/afs/cern.ch/cms/lumi/brilconda-1.0.3/bin:$PATH

The integrated luminosity as measured during the data taking (Norm tag:*onlineresult*), delivered and recored, is provided for the luminosity sections specified in the json, limiting to the run 305842:

brilcalc lumi --help
brilcalc lumi -b 'STABLE BEAMS'  -r 305842  -i  /afs/cern.ch/cms/CAF/CMSCOMM/COMM_DQM/certification/Collisions17/13TeV/ReReco/Cert_294927-306462_13TeV_EOY2017ReReco_Collisions17_JSON_v1.txt 

 --without-checkjson 

 -u /fb or /pb 

outcome for: Norm tag: onlineresult outcome for: Norm tag onlineresult

 
#Data tag : online , Norm tag: onlineresult
+-------------+-------------------+-----+------+----------------+---------------+
| run:fill    | time              | nls | ncms | delivered(/ub) | recorded(/ub) |
+-------------+-------------------+-----+------+----------------+---------------+
| 305842:6346 | 10/29/17 23:07:27 | 862 | 862  | 118945539.409 | 115950148.878  |
+-------------+-------------------+-----+------+----------------+---------------+
#Summary:
+-------+------+-----+------+-------------------+------------------+
| nfill | nrun | nls | ncms | totdelivered(/ub) | totrecorded(/ub) |
+-------+------+-----+------+-------------------+------------------+
| 1     | 1    | 862 | 862  | 118945539.409  | 15950148.878 |
+-------+------+-----+------+-------------------+------------------+

You can verify that you get the same output of you constrict yourself a json file limited to run 256843 and process it without run restrictions:

cd CMSSW_9_4_6_patch1/src 
cmsenv
filterJSON.py --min=305842 --max=305842 /afs/cern.ch/cms/CAF/CMSCOMM/COMM_DQM/certification/Collisions17/13TeV/ReReco/Cert_294927-306462_13TeV_EOY2017ReReco_Collisions17_JSON_v1.txt   | tee 305842.txt
cat 305842.txt
brilcalc lumi -b 'STABLE BEAMS'  -i  305842.txt

The luminosity measurement is updated and improved, after the first release of the online measurement, by taking into account all the luminometers available at CMS and the outcome of the Van der Meer scan analyses. A few weeks after the data taking, the Bril DPG and Luminosity POG release the best combination of luminometers in a Norm tag (e.g.: composite) json file available:

you should look here /afs/cern.ch/user/l/lumipro/public/normtag_file for most up to date file.

Therefore the recommended way of computing luminosity for your analysis is :

brilcalc lumi -help
brilcalc lumi -r 305842 --normtag /cvmfs/cms-bril.cern.ch/cms-lumi-pog/Normtags/normtag_BRIL.json -u /pb -i Cert_294927-306462_13TeV_EOY2017ReReco_Collisions17_JSON_v1.txt --without-checkjson [--byls]

outcome for: Norm tag composite outcome for: Norm tag composite

 
#Data tag : online , Norm tag: composite
+-------------+-------------------+-----+------+----------------+---------------+
| run:fill    | time              | nls | ncms | delivered(/ub) | recorded(/ub) |
+-------------+-------------------+-----+------+----------------+---------------+
| 305842:6346 | 10/29/17 23:07:26 | 862 | 862  | 117828014.670  | 114870230.725  |
+-------------+-------------------+-----+------+----------------+---------------+
#Summary:
+-------+------+-----+------+-------------------+------------------+
| nfill | nrun | nls | ncms | totdelivered(/ub) | totrecorded(/ub) |
+-------+------+-----+------+-------------------+------------------+
| 1     | 1    | 862 | 862  | 117828014.670     | 114870230.725     |
+-------+------+-----+------+-------------------+------------------+

Exercise 5: Explore GlobalTag through cmsDBbrowser

What is GlobalTag

The alignment and calibration conditions needed by all stages of the data production (SIM, DIGI: for simulated events) and processing (RECO, miniAOD: for simulation and reconstruction alike) in CMSSW are defined in the Offline Conditions Database, which is read in CMSSW applications via Frontier caching servers.

The set of database tags which together define the offline conditions data are collected together in a Global Tag, which is itself stored in the database. This removes the need for the list of database tags to be defined in separate CMSSW configuration fragments and therefore decouples the conditions database from the CMSSW release; different Global Tags can be used with a given CMSSW release, with the tag itself specified in the cfg file.

The following file should be included in the cfg for any CMSSW application for which needs to read conditions data:

from Configuration.AlCa.GlobalTag import GlobalTag

Conditions of different type are (e.g. : measured beamspot, HCAL intercalibrations, etc) are identified by a specific string called tag; a Global Tag is constructed aggregating a large set of tags (typically three to four hundred).

More information can be referred to SWGuideFrontierConditions

Explore GlobalTag through cmsDbBrowser service

Find the global tags used for the RunIIFall17DRPremix and RunIISummer17DRPremix campaigns Find the global tags used for the RunIIFall17DRPremix and RunIISummer17DRPremix campaigns

The cmsDbBrowser service is the web portal for administration and navigation of the existing global tag. You can find the description of your favorite global tag, all the tags it's made of, and you can explore both the meta-data and the content of tags.

Find the beamspot tag for 92X_upgrade2017_realistic_v7 Find the beamspot tag for 92X_upgrade2017_realistic_v7

Compare 94X_mc2017_realistic_v10 and 92X_upgrade2017_realistic_v7 Compare 102X_upgrade2018_realistic_v9 and 101X_upgrade2018_realistic_v7

Bonus Bonus

   const FooRecord& fooRecord = iEventSetup.get<FooRecord>();

  edm::ESHandle<Foo> fooH;
  fooRecord.get(fooH);

  edm::ESHandle<Foo> fooH;
  fooRecord.get("bar", fooH);