Metadata-Version: 2.1
Name: km3irf
Version: 0.4.0
Summary: KM3NeT instrument response functions
Home-page: https://git.km3net.de/km3py/km3irf
Author: Tamas Gal
Author-email: tgal@km3net.de
Maintainer: Tamas Gal
Maintainer-email: tgal@km3net.de
License: MIT
Description: .. image:: https://git.km3net.de/km3py/km3irf/badges/main/pipeline.svg
            :target: https://git.km3net.de/km3py/km3irf/pipelines
        
        .. image:: https://git.km3net.de/km3py/km3irf/badges/main/coverage.svg
            :target: https://km3py.pages.km3net.de/km3irf/coverage
        
        .. image:: https://git.km3net.de/examples/km3badges/-/raw/master/docs-latest-brightgreen.svg
            :target: https://km3py.pages.km3net.de/km3irf
        
        .. image:: https://git.km3net.de/km3py/km3irf/-/badges/release.svg
            :target: https://git.km3net.de/km3py/km3irf/-/releases
        
        .. image:: https://img.shields.io/badge/License-BSD_3--Clause-blueviolet.svg
            :target: https://opensource.org/licenses/BSD-3-Clause
        
        KM3NeT instrument response functions
        ====================================
        
        This project provides a versatile tool that can be used to quickly analyze the sensitivity of the **KM3NeT** detector for various source models.
        Currently it considers only point-like sources. The main feature of the tool is deep targeting to ``gammapy`` software.
        At same time it is independent from installation of ``gammapy`` software.
        For further analysis in ``gammapy``, ``km3irf`` provides next modules:
        
        * Instrument response function (IRF)
        
          * Effective area (Aeff)
        
          * Energy dispertion (Edisp)
        
          * Point spread function (PSF)
        
        * Data set (*in progress*)
        
        * Event list (*in progress*)
        
        Installation
        ------------
        
        It is recommended to create an isolated virtualenvironment to not interfere
        with other Python projects, preferably inside the project's folder. First clone
        the repository with::
        
          git clone git@git.km3net.de:km3py/km3irf.git
        
        or::
        
          git clone https://git.km3net.de/km3py/km3irf.git
        
        Create and acitvate a virtual environment::
        
          cd km3irf
          python3 -m venv venv
          . venv/bin/activate
        
        Install the package with::
        
          make install
        
        You can also install the package directly from ``Pypi`` via ``pip`` package manager (no cloning needed).
        It can easily be done into any Python environment with next command::
        
          pip install km3irf
        
        To install all the development dependencies, in case you want to contribute or
        run the test suite::
        
          make install-dev
          make test
        
        
        ---
        
        *Created with ``cookiecutter https://git.km3net.de/templates/python-project``*
        
Keywords: neutrino,astroparticle,physics,HEP
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: BSD License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Topic :: Scientific/Engineering
Requires-Python: >=3.6
Description-Content-Type: text/x-rst
Provides-Extra: all
Provides-Extra: dev
Provides-Extra: test
