HyperSpy Software Package for Multi-Dimensional Data Analysis

This seminar introduces HyperSpy, an open-source Python package for multi-dimensional data analysis, with a focus on its application in electron microscopy. Driven by the increasing need to handle large datasets, HyperSpy provides a user-friendly syntax for visualizing, analyzing, and storing complex datasets, regardless of size. We will discuss HyperSpy's key features, including out-of-memory computation and parallel processing, and its seamless integration with the broader scientific Python ecosystem. We will also cover HyperSpy's open development model, its thriving software ecosystem and community, and future plans for addressing evolving data challenges in electron microscopy.

Bio
Francisco de la Peña is lecturer in Physics at the University of Lille. He obtained his Ph.D in Physics in 2010 from the Paris-Sud University working on EELS quantification. From 2010 to 2011 he was a postdoctoral fellow at CEA-LETI Grenoble where he worked on EELS applications to semiconductor devices. From 2011 to 2017 he was a Postdoctoral Research Associate at the University of Cambridge working on analytical tomography. He is particularly interested in open and reproducible science and the application and development of innovative data analysis methods for multi-dimensional microscopy. During his Ph.D he created EELSLab, an open source Python programme for EELS data analysis that later, with the contributions of tens of researchers from multiple institutions, became the HyperSpy software package for multi-dimensional data analysis.