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README update with pyOpenSci review suggestions: repotatus badge; target-audience paragraph; Fortran/CMake dependency mentioned earlier on
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README.md

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PyPartMC is a Python interface to [PartMC](https://lagrange.mechse.illinois.edu/partmc/),
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a particle-resolved Monte-Carlo code for atmospheric aerosol simulation.
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Development of PyPartMC has been intended to remove limitations to the use of Fortran-implemented PartMC.
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PyPartMC facilitates the dissemination of computational research results by streamlining independent execution
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of PartMC simulations (also during peer-review processes).
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Additionally, the ability to easily package examples, simple simulations, and results in a web-based notebook
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allows PyPartMC to support the efforts of many members of the scientific community, including researchers,
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instructors, and students, with nominal software and hardware requirements.
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PyPartMC is implemented in C++ and it also constitutes a C++ API to the PartMC Fortran internals.
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The Python API can facilitate using PartMC from other environments - see, e.g., Julia and Matlab examples below.
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[![API docs](https://shields.mitmproxy.org/badge/docs-pdoc.dev-brightgreen.svg)](https://open-atmos.github.io/PyPartMC/)
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[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.7662635.svg)](https://doi.org/10.5281/zenodo.7662635)
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[![PyPI version](https://badge.fury.io/py/PyPartMC.svg)](https://pypi.org/p/PyPartMC)
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[![Project Status: Active – The project has reached a stable, usable state and is being actively developed.](https://www.repostatus.org/badges/latest/active.svg)](https://www.repostatus.org/#active)
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## TL;DR (try in a Jupyter notebook)
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import PyPartMC
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```
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Note that, depending on the environment (OS, hardware, Python version), the pip-install invocation
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may either trigger a download of a pre-compiled binary, or trigger compilation of PyPartMC.
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In the former case, all dependencies will be resolved by pip.
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In the latter case, a Fortran compiler and some development tools includiong CMake, m4 and perl
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are required.
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#### Jupyter notebooks with examples
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Note: clicking the badges below redirects to cloud-computing platforms. The mybinder.org links allow anonymous execution, Google Colab requires logging in with a Google account, ARM JupyerHub requires logging in with an ARM account (and directing Jupyter to a particular notebook within the `examples` folder).
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