Notebooks

Open Free Energy: An Open Source Ecosystem for Calculating Free Energies

Alyssa Travitz, Irfan Alibay, Hannah Baumann, David Dotson, James Eastwood, Mike Henry, Josh Horton, Ian Kenney, Iván Pulido, Benjamin Ries, and David Mobley

Alchemical free energy calculations are integral to state-of-the-art drug discovery pipelines, yet the need for domain expertise and reliance on closed-source software remain major barriers to their widespread use. The Open Free Energy (OpenFE) project is a pre-competitive collaboration between academic and industry partners to develop an ecosystem of extensible open-source tools for accessible and reproducible free energy calculations. OpenFE’s ecosystem includes Python-based tools for network planning, atom mapping, defining protocols for relative and absolute alchemical transformations, simulation execution, and data analysis. We will demonstrate how these tools can be used out of the box, adapted, or extended to create end-to-end workflows enabling robust free energy calculations at scale.

colab notebook: https://colab.research.google.com/github/OpenFreeEnergy/ExampleNotebooks/blob/main/showcase/openfe_showcase.ipynb

git repository: https://github.com/OpenFreeEnergy/ExampleNotebooks/tree/main/showcase

Undate: computing with uncertain and partially-unknown dates

Rebecca S. Koeser

This notebook provides a demonstration of the functionality of the Python library undate (https://github.com/dh-tech/undate-python/).

Undate is an ambitious, in-progress effort to develop a pragmatic Python library for computation and analysis of temporal information in humanistic and cultural data, with a particular emphasis on uncertain, incomplete, or imprecise dates and with support for multiple calendars.

Researchers in the humanities often work with historical or cultural data, and knowing when particular materials were created or events happened is important for understanding the context, interpreting correctly, and determining relationships and sequencing. However, these kind of materials rarely have full precision dates with known year, month, and day. In some contexts, scholars may be happy if they can determine even just a century based on handwriting or mentions of historic coins.

Humanistic and cultural data also often includes dates in different calendars, or even a mix of calendars within the same project or system. It’s important to preserve the original date and calendar information, but it’s also valuable to convert dates to a standard calendar so they can be compared and sorted together. Undate objects are calendar aware and calendar explicit, with a default of the Gregorian calendar. Currently, we support parsing and calendar conversion for dates in the Hebrew Anno Mundi calendar and Islamic Hijri calendar.

This notebook demonstrates current use and functionality of the core Undate and UndateInterval objects, along with some examples showing use-cases from two projects that fed into development on undate: Shakespeare and Company Project (https://shakespeareandco.princeton.edu/), and Princeton Geniza Project (https://geniza.princeton.edu/).

Repository URL: https://github.com/rlskoeser/undate-notebook-usrse25 Git ref: 1.0

Combining TIFF, HDF5, and Zarr into a Single Image File Format

Mark Kittisopikul

“Situation: There are 3 competing standards” the last card of a popular XKCD cartoon (#927) might read if applied to recent microscopy bioimaging formats. TIFF, HDF5, and Zarr have all been used to store images as part of popular standards and formats (OME-TIFF, BDV-HDF5, OME-Zarr). The cartoon humorously points out the tendency to create new standards while discounting prior efforts. To combat the proliferation of formats I examine similarities between TIFF, HDF5, and Zarr shard containers. I then exploit them to create a combined data container that is simultaneously a TIFF file, a HDF5 file, and a Zarr version 3 shard without duplicating the image pixel or volumetric voxel data. This combined format is compatible with multiple viewers and image analysis pipelines. Additionally, the techniques involved provide a path to convert between the formats with minimal processing or overhead. In practice, the combined format avoids redundant copies of data while providing great utility to the microscope user. The combined format is a great candidate for a microscope acquisition format as it satisfies both short term needs to view microscope output in traditional viewers while integrating into next generation image analysis pipelines.

https://github.com/mkitti/simple_image_formats/blob/main/header_formats.ipynb