EuroSciPy 2024

Kushal Kolar

PhD Candidate in Biomedical Engineering at the Flatiron Institute for Computational Neuroscience and NYU. 10+ years of experience using Python for data analysis and machine learning with neuroscience datasets. Core developer of fastplotlib and maintainer of several Python libraries in neuroscience with significant user bases, and a contributor to other libraries such as tslearn and CaImAn.


Institute / Company

NYU Engineering and Flatiron Institute

Homepage

https://www.simonsfoundation.org/flatiron/center-for-computational-neuroscience/

Twitter handle

https://twitter.com/kushalkolar

Git*hub|lab

https://github.com/kushalkolar


Session

08-29
13:55
30min
fastplotlib: A high-level library for ultra fast visualization of large datasets using modern graphics APIs
Kushal Kolar, Caitlin Lewis

Fast interactive visualization remains a considerable barrier in analyses pipelines for large neuronal datasets. Here, we present fastplotlib, a scientific plotting library featuring an expressive API for very fast visualization of scientific data. Fastplotlib is built upon pygfx which utilizes the GPU via WGPU, allowing it to interface with modern graphics APIs such as Vulkan for fast rendering of objects. Fastplotlib is non-blocking, allowing for interactivity with data after plot generation. Ultimately, fastplotlib is a general purpose scientific plotting library that is useful for the fast and live visualization and analysis of complex datasets.

Data Science and Visualisation
Room 7