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 in objectPerformance.

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.