Packaging Composable Research Software Libraries
Include graph for DISHTINY software.
Packaging and distribution of software multiplies the impact of research, both by opening the door to follow-on research within the scientific community and by facilitating direct real-world applications. However, realizing this goal requires special attention to organization, documentation, and reliability. Many of my research projects are organized so to maximize contribution of general-purpose library software back to the community. This usually involves adding software features to an existing project or publishing a standalone Python or C++ library.
Publications & Software
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| Authors | Matthew Andres Moreno |
| Date | December 22nd, 2023 |
| Venue | Python package published via PyPI |
add zoom indicators, insets, and magnified panels to matplotlib/seaborn visualizations with ease!
BibTeX
@software{moreno2023outset,
author = {Matthew Andres Moreno},
title = {mmore500/outset},
month = dec,
year = 2023,
publisher = {Zenodo},
doi = {10.5281/zenodo.10426106},
url = {https://doi.org/10.5281/zenodo.10426106}
}
Citation
Matthew Andres Moreno. (2023). mmore500/outset. Zenodo. https://doi.org/10.5281/zenodo.10426106
Supporting Materials
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| Authors | Matthew Andres Moreno, Emily Dolson |
| Date | January 1st, 2022 |
| Venue | Python package published via PyPI |
phylotrackpy is a Python phylogeny tracker.
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| Authors | Matthew Andres Moreno |
| Date | January 1st, 2022 |
| Venue | Python package published via PyPI |
opytional makes working with values that might be None safer and easier.
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| Authors | Matthew Andres Moreno |
| Date | January 1st, 2022 |
| Venue | Python package published via PyPI |
interval-search provides predicate-based binary and doubling search implementations.
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| Authors | Matthew Andres Moreno, Emily Dolson, Charles Ofria |
| Date | January 1st, 2022 |
| Venue | Python package published via PyPI |
hstrat enables phylogenetic inference on distributed digital evolution populations.
BibTeX
@article{moreno2022hereditary,
author = {Moreno, Matthew Andres and Dolson, Emily and Ofria, Charles},
doi = {https://doi.org/10.1162/isal_a_00550},
journal = {Proceedings of the ALIFE 2022: The 2022 Conference on Artificial Life},
month = {7},
pages = {64--74},
title = {{Hereditary Stratigraphy: Genome Annotations to Enable Phylogenetic Inference over Distributed Populations}},
volume = {Proceedings of the ALIFE 2022: The 2022 Conference on Artificial Life},
year = {2022}
}
Citation
Moreno, M. A., Dolson, E., & Ofria, C. (2022). Hereditary Stratigraphy: Genome Annotations to Enable Phylogenetic Inference over Distributed Populations. Proceedings of the ALIFE 2022: The 2022 Conference on Artificial Life, Proceedings of the ALIFE 2022: The 2022 Conference on Artificial Life(), 64–74. https://doi.org/https://doi.org/10.1162/isal_a_00550
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| Authors | Matthew Andres Moreno, Emily Dolson |
| Date | January 1st, 2022 |
| Venue | Python package published via PyPI |
alifedata-phyloinformatics-convert helps apply traditional phyloinformatics software to alife standardized data.
| Authors | Matthew Andres Moreno, Santiago Rodriguez Papa |
| Date | May 26th, 2020 |
| Venue | Workshop for Avida-ED Software Development |
Hands-on, asynchronous 4 day tutorial series covering foundational web development competencies, C++ development with the Empirical library, and compiling for the web with Emscripten.
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| Authors | Matthew Andres Moreno |
| Date | January 1st, 2020 |
| Venue | Python package published via PyPI |
teeplot wrangles your data visualizations out of notebooks for you.
BibTeX
@software{moreno2023teeplot,
author = {Matthew Andres Moreno},
title = {mmore500/teeplot},
month = dec,
year = 2023,
publisher = {Zenodo},
doi = {10.5281/zenodo.10440670},
url = {https://doi.org/10.5281/zenodo.10440670}
}
Citation
Matthew Andres Moreno. (2023). mmore500/teeplot. Zenodo. https://doi.org/10.5281/zenodo.10440670
| Authors | Matthew Andres Moreno, Santiago Rodriguez Papa, Alexander Lalejini, Charles Ofria |
| Date | January 1st, 2020 |
| Venue | header-only C++ library |
A genetic programming implementation designed for large-scale artificial life applications. Organized as a header-only C++ library. Inspired by Alex Lalejini’s SignalGP.
| Authors | Matthew Andres Moreno, Santiago Rodriguez Papa, Charles Ofria |
| Date | January 1st, 2020 |
| Venue | header-only C++ library |
C++ library that wraps intra-thread, inter-thread, and inter-process communication in a uniform, modular, object-oriented interface, with a focus on asynchronous high-performance computing applications.
| Authors | Matthew Andres Moreno, Santiago Rodriguez Papa, Katherine Perry, Charles Ofria |
| Date | January 1st, 2020 |
| Venue | header-only C++ library |
C++ library for digital evolution simulations studying digital multicellularity and fraternal major evolutionary transitions in individuality.
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| Authors | Matthew Andres Moreno |
| Date | January 1st, 2019 |
| Venue | Python package published via PyPI |
keyname helps easily pack and unpack metadata in a filename.
| Date | January 1st, 2018 |
| Venue | header-only C++ library |
Empirical is a library of tools for developing useful, efficient, reliable, and available scientific software. The provided code is header-only and encapsulated into the emp namespace, so it is simple to incorporate into existing projects.
BibTeX
@software{Ofria_Empirical_C_library_2020,
author = {Ofria, Charles and Moreno, Matthew Andres and Dolson, Emily and Lalejini, Alex and Rodriguez Papa, Santiago and Fenton, Jake and Perry, Katherine and Jorgensen, Steven and hoffmanriley and grenewode and Baldwin Edwards, Oliver and Stredwick, Jason and cgnitash and theycallmeHeem and Vostinar, Anya and Moreno, Ryan and Schossau, Jory and Zaman, Luis and djrain},
doi = {10.5281/zenodo.4141943},
license = {MIT},
month = {10},
title = {{Empirical: C++ library for efficient, reliable, and accessible scientific software}},
url = {https://github.com/devosoft/Empirical},
version = {0.0.4},
year = {2020}
}
Citation
Ofria, C., Moreno, M. A., Dolson, E., Lalejini, A., Rodriguez Papa, S., Fenton, J., Perry, K., Jorgensen, S., , H., , G., Baldwin Edwards, O., Stredwick, J., , C., , T., Vostinar, A., Moreno, R., Schossau, J., Zaman, L., & , D. (2020). Empirical: C++ library for efficient, reliable, and accessible scientific software (Version 0.0.4) [Computer software]. https://doi.org/10.5281/zenodo.4141943