This is a repository containing code for the analyis of the LFV B2KTauMu decay.
Contact: luca.pescatore@cern.ch
Clone the repository.
git clone --recursive ssh://git@gitlab.cern.ch:7999/pluca/B2Ktaumu.git
If you want to run interactively in testing mode (normal way to run).
source setup.sh
Or if you want to run pipelines using Snakemake:
source setup.sh snake
N.B.: To work properly in "snake" mode you have to setup some dependencies (Snakemake) the first time you use it. Please read README_SNAKEMAKE.
- The
B2KTAUMUROOTvariable is now avilable pointing to the top folder of the repo. - ROOT, matplotlib, sklearn, etc are setup.
- Now code into the
pythonfolder should be automatically picked up if you try to import it. - At the beginning of each python file you should add
import B2KTauMu as an(see later)
- The analysis code should be contained into the
scriptsandpythonfolders.
N.B.: If you make subfolders of python put an empty __init__.py file inside each one.
Gangacontains Ganga options. In parituclar gangaoption.py where a function CreateDVJob() is defied.
Running ganga with runganga all functions defined in gangaoption.py will be available.
Optionscontains DaVinci options to create the tuples.Datacontains files with lists of LFNs used to make tuples.LHCbcontains generic LHCb stuff like the LHCb style file and the particle propeties.tablesis where you should put the output tables (see B2KTauMuEnv).
It also contains the templates folder which should contain latex templates to be filled automatically.
plotsis where you should put output splots (see B2KTauMuEnv).
All cuts should go into .py files in the folder python/B2KTauMu/cuts/. Mainly into __init__.py
These can be then used as e.g. :
data.Draw('Somevar',cuts.somecut)```
See also python environment paragraph.
### Access data
Raw data (the output of the stripping) can be accessed using a provided function:
```import B2KTauMu as an
files = an.utils.remote_ls_fromids(an.dataids['{some data label e.g. CL11}'])```
To see the available datasets:
```import B2KTauMu as an
print an.dataids.keys()
['CL16', 'CL15', 'CL12', 'CL11']```
## B2KTauMu python environment (important!!)
This module loads the python environment: `import B2KTauMuEnv as an`.
What will this do for you:
* Checking that you sourced the setup.sh file.
* Loading the LHCb style for plots.
* Make available any variable defined into B2KTauMu/__init__.py (e.g. se next point: loc)
* Make the locations easily available to your pathon scripts though the `loc` object. Sone already defined locations are the following (feel free to define more as you need them):
- loc.ROOT = $LB2LEMUANAROOT
- loc.PYTHON = $LB2LEMUANAROOT/python/
- loc.LHCB = $LB2LEMUANAROOT/LHCb/
- loc.PLOTS = $LB2LEMUANAROOT/plots/
- loc.TABS = $LB2LEMUANAROOT/tables/
- loc.TMPS = $LB2LEMUANAROOT/tables/templates/
- loc.TUPLE = /eos/lhcb/user/p/pluca/Analysis/B2KTauMu/Tuple/
* Provide a common database saved on disk to presist results, e.g.:.
import B2KTauMuEnv as an print an.db {'Test':True, ...} an.db['myeff'] = 0.99 dumpDB() ## Saves it to disk
* Provide easy handling of output files
```from Lb2LemuEnv import *
outfiles.create("yields") ## Will create (only first time) the $LB2LEMUROOT/tables/yields.txt file and remember that it exists
outfile.writeline("yields","N_B0 = 4000")```
Or even better you can do the same using templates!!! Crate a file in the templates folder. You can write whatever you want into it just put the values to substitute into {}
E.g.: `seleff = ${sel_eff} \pm {sel_eff_err}$`
And then use the `db` object to fill it!!
```from Lb2LemuEnv import *
outfile.fill_template("efficiencies","eff_tmp",db)```
This will look for the keys into the db, fill them into your template and same everything to $REPO/tables/efficiency.txt
* Make available to every script any other variable you wish to define into it.
## Snakemake
You can run the offline anaylsis (or parts of it) simply typing `snakemake`.
The steps are defined into `Snakefile` in the top folder. See README_SNAKEMAKE for more details.
To run snakemake from a clean shell:
source setup.ch snake snakemake
## Docker
Docker support is available for this repository to allow running the analysis on any machine anywhere in the world (with internet). Please have a look at the readme inside the Docker folder.
## Common utilities
The `pyutils` folder contains utilities which you may find useful. See pyutils/README.md.