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PE Automator is a Python package for automating the setup and execution of parameter estimation (PE) runs using Bilby Pipe.

Project description

PE Automator

Installation

conda create -n pe_automator python=3.10 setuptools_scm
conda activate pe_automator
make install

Usage

Setup a run with the PE Automator:

pe_automator setup GW231123_135430 --data_path ./data --run_label run1 --account uib107 --partition gpp --qos gp_resa --approximant IMRPhenomXPNR --user resh000428 --conda_env parallel_bilby --private_token <token> --allocation AECT-2025-2-0029

The --data_path should point to data directory of this repo. The framefiles are stored as git-lfs files, so you need to have git-lfs installed and initialized in the repository. To install git-lfs, run the following command:

git lfs install

How to apply for a private token? See here. You should select the api scope to allow the PE Automator to access the GitLab repository and create issues.

Monitor and update the status of the runs (Should be run from a daemon or a cron job):

pe_automator monitor --private_token <token> --data_dir=./data

Update the conda evironment:

pe_automator setup_env pe-0.0.1beta1 --source_env=my_env.tar.gz --source_remote=resh000428@picasso.scbi.uma.es --data_dir=./data

pe-0.0.1beta1 will be the tagged conda environment name, --source_env= is the packed conda environment file, and --source_remote= is the remote server where the conda environment is stored. The --data_dir should point to the data directory of this repo.

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