This repository contains the python-based framework for the measurement of matching efficiencies, trigger turn-on curves, and scalings for the assessment of the physics performance of the CMS Phase-2 L1 Menu.
The repository is organized as follows:
-
objectPerformance
: tools for the measurement of the performance (matching efficiency, L1 turn-on efficiency curves, and online-to-offline scalings) of L1 objects. The definition of the L1 objects should follow the recommendations detailed here. -
rates
: tools for the measurement of trigger rates starting from the scalings derived with the tools inobjectPerformance
.
Detailed instructions on how to run each step of the workflow are provided in each folder.
Note: The code should run without any setup on lxplus
.
In the event of failure of the central setup, the following steps are required to install a new Python environment.
To install miniconda
run the following commands:
cd ~
wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh
bash Miniconda3-latest-Linux-x86_64.sh
Specify the path to your miniconda3
installation under prefix
in environment.yml
(working examples of environment.yml
files
are provided in the objectPerformance
and rates
folders) and run
conda env create -f environment.yml
This will create a new environment named py310
.
To execute the scripts in the repo you need to modify the shebang
(the very first line of the executable .py
files which starts
with #!
) to point
to your newly set up Python installation. To find the path run
conda activate py310
which python
and replace the current path in the shebang with the output.
More details on how to set up a conda
environment using a shared
.yml
file can be found
here.