# GolemFlavor [![Build Status](https://api.travis-ci.org/ShiveshM/GolemFlavor.svg?branch=master)](https://travis-ci.org/ShiveshM/GolemFlavor) ![Python Version](https://img.shields.io/badge/python-2.7+|3.4+-blue.svg) [![license](https://img.shields.io/github/license/ShiveshM/GolemFlavor 'license')](https://github.com/ShiveshM/GolemFlavor/blob/master/LICENSE) GolemFlavor is a Python package for running an analysis pipeline using `GolemFit`. ![GolemFlavor Logo](logo.png) ## Installation GolemFlavor can be installed using `pip` ``` pip install git+https://github.com/ShiveshM/GolemFlavor.git ``` This installs GolemFlavor, along with all the necessary dependencies such as NumPy and SciPy. GolemFlavor uses the IceCube software [`GolemFit: The HESE fitter`](https://github.com/IceCubeOpenSource/GolemFit) to fit with IceCube HESE data. Current access is limited to IceCube collaborators. A simple Gaussian likelihood can be used instead for test purposes if this requirement is not found. ### Dependencies GolemFlavor has the following dependencies: * [`Python`](https://www.python.org/) >= 2.7 or >= 3.4 * [`NumPy`](http://www.numpy.org/) * [`SciPy`](https://www.scipy.org/) * [`Six`](https://six.readthedocs.io/) * [`mpmath`](http://mpmath.org/) * [`emcee`](https://emcee.readthedocs.io/en/stable/) * [`PyMultiNest`](https://johannesbuchner.github.io/PyMultiNest/) * [`tqdm`](https://tqdm.github.io/) * [`Shapely`](https://shapely.readthedocs.io/en/latest/manual.html) * [`Matplotlib`](https://matplotlib.org/) * [`python-ternary`](https://github.com/marcharper/python-ternary) * [`GetDist`](https://getdist.readthedocs.io/en/latest/) You can use `pip` to install the above automatically. Note that `PyMultiNest` requires the `MultiNest` Bayesian inference library, see [the `PyMultiNest` documentation](https://johannesbuchner.github.io/PyMultiNest/install.html#prerequisites-for-building-the-libraries) for install instructions. Additional dependencies: * [`GolemFit`](https://github.com/IceCubeOpenSource/GolemFit) ## License [MIT License](LICENSE) Copyright (c) 2020 Shivesh Mandalia