skyllh 24.1.0

The SkyLLH framework is an open-source Python3-based package licensed under the GPLv3 license. It provides a modular framework for implementing custom likelihood functions and executing log-likelihood ratio hypothesis tests. The idea is to provide a class structure tied to the mathematical objects of the likelihood functions.

SkyLLH

[Full documentation].

The SkyLLH framework is an open-source Python3-based package licensed under the GPLv3 license. It provides a modular framework for implementing custom likelihood functions and executing log-likelihood ratio hypothesis tests. The idea is to provide a class structure tied to the mathematical objects of the likelihood functions, rather than to entire abstract likelihood models.

The math formalism used in SkyLLH is described in the [math formalism document].

Installation

Using pip

The latest skyllh release can be installed from PyPI repository:

pip install skyllh

The current development version can be installed using pip:

pip install git+https://github.com/icecube/skyllh.git#egg=skyllh

Optionally, the editable package version with a specified reference can be installed by:

pip install -e git+https://github.com/icecube/skyllh.git@[ref]#egg=skyllh

where

• -e is an editable flag
• [ref] is an optional argument containing a specific commit hash, branch name or tag

Cloning from GitHub

The skyllh (and an optional private i3skyllh) package can be installed by cloning the GitHub repository and adding it to the Python path:

import sys

sys.path.insert(0, '/path/to/skyllh')
sys.path.insert(0, '/path/to/i3skyllh')  # optional

Publications

Several publications about the SkyLLH software are available:

• IceCube Collaboration, C. Bellenghi, M. Karl, M. Wolf, et al. PoS ICRC2023 (2023) 1061 DOI
• IceCube Collaboration, T. Kontrimas, M. Wolf, et al. PoS ICRC2021 (2022) 1073 DOI
• IceCube Collaboration, M. Wolf, et al. PoS ICRC2019 (2020) 1035 DOI

Developer Guidelines

These guidelines should help new developers of SkyLLH to join the development process easily.

Code style

• The code follows PEP8 coding style guidelines as close as possible.

• Code lines are maximum 80 characters wide.

• 4 spaces are used as one indentation level.

Branching

• When implementing a new feature / change, first an issue must be created describing the new feature / change. Then a branch must be created referring to this issue. We recommend the branch name fix<ISSUE_NUMBER>, where <ISSUE_NUMBER> is the number of the created issue for this feature / change.

• In cases when SkyLLH needs to be updated because of a change in the i3skyllh package (see below), we recommend the branch name i3skyllh_<ISSUE_NUMBER>, where <ISSUE_NUMBER> is the number of the issue created in the i3skyllh repository. That way the analysis unit tests workflow will be able to find the correct skyllh branch corresponding to the i3skyllh change automatically.

Releases and Versioning

• Release version numbers follow the format v<YY>.<MAJOR>.<MINOR>, where <YY> is the current year, <MAJOR> and <MINOR> are the major and minor version numbers of type integer. Example: v23.2.0.

• Release candidates follow the same format as releases, but have the additional suffix .rc<NUMBER>, where <NUMBER> is an integer starting with 1. Example: v23.2.0.rc1

• Before creating the release on github, the version number needs to be updated in the Sphinx documentation: doc/sphinx/conf.py.

i3skyllh

The i3skyllh package provides complementary pre-defined common analyses and datasets for the IceCube Neutrino Observatory detector in a private repository.