Skip to main content

Project with code used to ease data manipulation tasks

Project description

Description

This project is used to carry out checks on Run3 data. Check this for installation instructions and for instructions on how to setup an environment to use this project.

Specifying configuration for filtering and slimming

For this to work, configs need to be uploaded to the grid with the scripts below. The scripts need to know the place in the grid where the user LFNs live.

Once the config files have been updated, they have to be uploaded to the grid with:

update_config -u 1 -p /path/to/config.yaml

The -u flag will update the config file if its LFN is already in the grid. The -p flat passes the path to the config to be uploaded.

Save lists of PFNs

The PFNs to be processed will be stored once with the AP api and will be read as package data when processing ntuples. The list of PFNs is created with, e.g.:

save_pfns -c dt_2024_turbo_comp

where -c will correspond to the config file.

Submitting jobs


All the jobs below require code that lives in a virtual environment, there should be multiple versions of this environment and the latest one should be obtained by running:

dirac-dms-user-lfns -w dcheck.tar -b /lhcb/user/${LXNAME:0:1}/$LXNAME/run3/venv

currently, the latest

The instructions below need to be done outside the virtual environment in an environment with access to dirac and in the post_ap_grid directory.

First run a test job with:

job_filter -d dt_2024_turbo -c comp -j 1211 -e 003 -m local -n test_flt -u acampove

where -u specifies the user who authored the environment that the job will use. The flag -j specifies the number of jobs. For tests, this is the number of files to process, thus, the test job does only one file. The -n flag is the name of the job, for tests it will do/send only one job if either:

  1. Its name has the substring test.
  2. It is a local job.

Thus one can do local or grid tests running over a single file.

For real jobs:

job_filter -d dt_2024_turbo -c comp -j 200 -e 003 -m wms -n flt_001 -u acampove

Downloading ntuples

A test would look like:

run3_download_ntuples -j flt_004 -n 3 [-d $PWD/files]

where:

-j: Is the name of the job, which has to coincide with the directory name, where the ntuples are in EOS, e.g. /eos/lhcb/grid/user/lhcb/user/a/acampove/flt_004. -n: Number of ntuples to download, if not pased, will download everything. -d: Directory where output ntuples will go, if not passed, directory pointed by DOWNLOAD_NTUPPATH will be used.

A real download would look like:

run3_download_ntuples -j flt_001 -m 40

Where -m denotes the number of threads used to download, -j the name of the job.

Notes

  • The downloads can be ran many times, if a file has been downloaded already, it will not be downloaded again.

Linking and merging

Once the ntuples are downloaded these need to be linked and merged with:

link_merge -j flt_002 -v v1

where -j is the name of the job and the files are linked to a directory named as -v v1. For tests run:

link_merge -j flt_002 -d 1 -m 10 -v v1

which will do the same with at most 10 files, can use debug messages with -l 10.

Making basic plots

For this run:

plot_vars -y 2024 -v v2 -c bukee_opt -d data_ana_cut_bp_ee:Data ctrl_BuToKpEE_ana_ee:Simulation

which will run the plotting of the variables in a config specified by bukee_opt where also axis, names, ranges, etc are specified. This config is in post_ap_data. The script above will overlay data and MC.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

post_ap-0.0.7.tar.gz (53.5 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

post_ap-0.0.7-py3-none-any.whl (57.8 kB view details)

Uploaded Python 3

File details

Details for the file post_ap-0.0.7.tar.gz.

File metadata

  • Download URL: post_ap-0.0.7.tar.gz
  • Upload date:
  • Size: 53.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/5.1.1 CPython/3.12.7

File hashes

Hashes for post_ap-0.0.7.tar.gz
Algorithm Hash digest
SHA256 460abe7a7f277e762aa673387eed9898e6d63e7f88bd3c2174a1018ab2925445
MD5 f10efc3800eb502d820a7da6776d0ad2
BLAKE2b-256 87e0b50dd0211a7c1e8e4846006594fe1e0cefcb800cec0743244a750df93232

See more details on using hashes here.

Provenance

The following attestation bundles were made for post_ap-0.0.7.tar.gz:

Publisher: publish.yaml on acampove/post_ap

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file post_ap-0.0.7-py3-none-any.whl.

File metadata

  • Download URL: post_ap-0.0.7-py3-none-any.whl
  • Upload date:
  • Size: 57.8 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/5.1.1 CPython/3.12.7

File hashes

Hashes for post_ap-0.0.7-py3-none-any.whl
Algorithm Hash digest
SHA256 dd6a70cf7bc6f8fb66602bd1ba680305544669ca69a7f8cf50a885b7c5e67e5d
MD5 c67bcf78151a4b31773b105a6b08a070
BLAKE2b-256 d47cf5b73dbeec7ae8b8ce5843f3b8341adc2c1814de8a23fd921fd3d29954c1

See more details on using hashes here.

Provenance

The following attestation bundles were made for post_ap-0.0.7-py3-none-any.whl:

Publisher: publish.yaml on acampove/post_ap

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page