SkyLLH documentation

SkyLLH is a Python based framework to develop and to perform general maximum likelihood ratio hypothesis testing. The idea of SkyLLH is to provide a framework with a class structure that is tied to the mathematical objects of the likelihood functions, rather than to entire abstract likelihood models. Hence with SkyLLH it is supposed to be easy to perform an entire maximum likelihood ratio test once the user (likelihood developer) defined the mathematical likelihood function.

User Documentation

• Installation
  • Prerequisites
  • Setup
• Tutorials
  • Getting started
    • SkyLLH’s analysis workflow
  • Time-integrated point source search analysis example
    • Software setup
    • Create datasets object
    • Create the analysis object
    • Some utility functions
    • Pseudo data example
  • IC170922A_wGFU
    • Introduction
    • Setup
• Hypothesis Definition
• Unit tests
• skyllh package
  • Subpackages
    • skyllh.cluster package
    • skyllh.core package
    • skyllh.i3 package
    • skyllh.physics package
    • skyllh.plotting package
    • skyllh.utils package
• Notes
  • Docstrings

Developer Documentation

• Logging

Indices and tables

• Index

• Module Index

• Search Page