The ProcessMCRaT library is a python package that can be used to process the output of the MCRaT code.
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The ProcessMCRaT package allows for the outputs of the MCRaT simulations to be processed in a number of different ways. The package allows the user to quickly analyze the MCRaT simulation by conveniently creating a number of mock observations for a variety of observer viewing angles and then use those observations to calculate spectra, light curves, and polarizations. The package also includes convenience plotting functions that allow quick, convenient plotting of these various quantities to fully explore the MCRaT results. These functions are also meant to be examples of how to work with the outputs of the ProcessMCRaT library. Additionally, the package also includes support for analyzing the position of photons in a given hydrodynamic simulation, allowing for analysis of hydrodynamic structures and mock observables at the same time.

There is also a Jupyter notebook that is included on Github that outlines the usage of the library, and many functionalities that the library offers. This notebook can be accessed by cloning the repository or loading the notebook in Binder (see the Usage section). The detailed documentation for each function is still under development, but the Jupyter notebook covers the ways that each function can be used.

• Python

To get a local copy up and running follow these simple steps.

The following are necessary to use the ProcessMCRaT code :

• The output of a MCRaT simulation
• Python -- we recommend installing Python 3 using Anaconda
  • Necessary packages under Python are numpy, scipy, matplotlib, h5py, pickle, tables and random -- many of these will be included in the base installation if using Anaconda and those that are not can easily be installed using the conda command line interface

1. Use pip install

   pip install ProcessMCRaT

2. Test the installation by running python -c "import processmcrat as pm" or by trying the Jupyter documentation notebook included in the github
   • To gain access to the Jupyter notebook, either clone the repo with git clone https://github.com/parsotat/ProcessMCRaT.git and run Jupyter notebook at the comand line in the notebooks directory

The typical steps in using the ProcessMCRaT library is shown in the included Jupyter notebook, with explainations of the many functions that are included in the package. To access the notebook, either:

• To gain access to the Jupyter notebook, either clone the repo with git clone https://github.com/parsotat/ProcessMCRaT.git and run Jupyter notebook at the comand line in the notebooks directory Or
• Access the notebook interactively online via Binder. You can click the launch Binder link at the top of the ReadMe or go directly to https://mybinder.org/v2/gh/parsotat/ProcessMCRaT/HEAD?filepath=notebooks%2Fprocessmcrat_example.ipynb

1. The code will include the means to include various instrument response functions in the creation of mock observed light curves, spectra, and polarizations.

See the open issues for a list of proposed features (and known issues).

Contributions are what make the open source community such an amazing place to be learn, inspire, and create. Any contributions you make are greatly appreciated.

1. Fork the Project
2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
3. Commit your Changes (git commit -m 'Add some AmazingFeature')
4. Push to the Branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

Distributed under the MIT License. See LICENSE for more information.

Tyler Parsotan - Personal Website - parsotat@umbc.edu

Project Link: https://github.com/parsotat/ProcessMCRaT

• In using ProcessMCRaT and the MCRaT codes, we ask that you cite the following papers:
  • Lazzati (2016)
  • Parsotan & Lazzati (2018)
  • Parsotan et al. (2018)
  • Parsotan et. al. (2020)
  • Parsotan & Lazzati (2021)
  • Parsotan & Lazzati (2022)
• README Template from: othneildrew/Best-README-Template