Matthew Andres Moreno

Packaging Composable Research Software Libraries

include graph for DISHTINY software 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
2024 Phylotrack: C++ and Python libraries for in silico phylogenetic tracking
arXiv
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Authors
Date May 15th, 2024
DOI 10.48550/arXiv.2405.09389
Venue arXiv
Abstract

In silico evolution instantiates the processes of heredity, variation, and differential reproductive success (the three “ingredients” for evolution by natural selection) within digital populations of computational agents. Consequently, these populations undergo evolution, and can be used as virtual model systems for studying evolutionary dynamics. This experimental paradigm — used across biological modeling, artificial life, and evolutionary computation — complements research done using in vitro and in vivo systems by enabling experiments that would be impossible in the lab or field. One key benefit is complete, exact observability. For example, it is possible to perfectly record all parent-child relationships across simulation history, yielding complete phylogenies (ancestry trees). This information reveals when traits were gained or lost, and also facilitates inference of underlying evolutionary dynamics.

The Phylotrack project provides libraries for tracking and analyzing phylogenies in in silico evolution. The project is composed of 1) Phylotracklib: a header-only C++ library, developed under the umbrella of the Empirical project, and 2) Phylotrackpy: a Python wrapper around Phylotracklib, created with Pybind11. Both components supply a public-facing API to attach phylogenetic tracking to digital evolution systems, as well as a stand-alone interface for measuring a variety of popular phylogenetic topology metrics. Underlying design and C++ implementation prioritizes efficiency, allowing for fast generational turnover for agent populations numbering in the tens of thousands. Several explicit features (e.g., phylogeny pruning and abstraction, etc.) are provided for reducing the memory footprint of phylogenetic information.

BibTeX
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@misc{dolson2024phylotrack,
      doi={10.48550/arXiv.2405.09389},
      url={https://arxiv.org/abs/2405.09389},
      title={Phylotrack: C++ and Python libraries for in silico phylogenetic tracking},
      author={Emily Dolson and Santiago Rodriguez-Papa and Matthew Andres Moreno},
      year={2024},
      eprint={2405.09389},
      archivePrefix={arXiv},
      primaryClass={q-bio.PE}
}
Citation
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Dolson, E., Rodriguez-Papa, S., & Moreno, M. A. (2024). Phylotrack: C++ and Python libraries for in silico phylogenetic tracking. arXiv preprint arXiv:2405.09389.

Supporting Materials

2023 outset
Python package published via PyPI
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Date December 22nd, 2023
Venue Python package published via PyPI

add zoom indicators, insets, and magnified panels to matplotlib/seaborn visualizations with ease!

BibTeX
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@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
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Matthew Andres Moreno. (2023). mmore500/outset. Zenodo. https://doi.org/10.5281/zenodo.10426106

Supporting Materials

2022 phylotrackpy
Python package published via PyPI
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Authors
Date January 1st, 2022
Venue Python package published via PyPI

phylotrackpy is a Python phylogeny tracker.


2022 opytional
Python package published via PyPI
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Date January 1st, 2022
Venue Python package published via PyPI

opytional makes working with values that might be None safer and easier.


2022 interval-search
Python package published via PyPI
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Authors
Date January 1st, 2022
Venue Python package published via PyPI

interval-search provides predicate-based binary and doubling search implementations.


2022 hstrat
Python package published via PyPI
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Authors
Date January 1st, 2022
Venue Python package published via PyPI

hstrat enables phylogenetic inference on distributed digital evolution populations.

BibTeX
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@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
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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


2022 alifedata-phyloinformatics-convert
Python package published via PyPI
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Date January 1st, 2022
Venue Python package published via PyPI

alifedata-phyloinformatics-convert helps apply traditional phyloinformatics software to alife standardized data.


2020 Zero to Sixty: Onboarding Tutorials for Native & Web Software Development with C++
Workshop for Avida-ED Software Development
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Authors
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.


2020 teeplot
Python package published via PyPI
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Date January 1st, 2020
Venue Python package published via PyPI

teeplot wrangles your data visualizations out of notebooks for you.

BibTeX
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@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
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Matthew Andres Moreno. (2023). mmore500/teeplot. Zenodo. https://doi.org/10.5281/zenodo.10440670


2020 signalgp-lite
header-only C++ library
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Authors
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.


2020 conduit
header-only C++ library
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Authors
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.


2020 dishtiny
header-only C++ library
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Authors
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.


2019 keyname
Python package published via PyPI
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Authors
Date January 1st, 2019
Venue Python package published via PyPI

keyname helps easily pack and unpack metadata in a filename.


2018 Empirical
header-only C++ library
View on GitHub
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
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@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
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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

Supporting Materials