xPDT : a Toolkit for Persistent Data Topology

xPDT is the third volume of this ‘Machine Learning Tools in Fluids Mechanics’ Series and focuses on Persistent Data Topology (PDT). The objectives of this book are twofold: First, provide an introduction to PDT for students, researchers, and newcomers on the field; and second, share an open-source code, xPDT, to automatically extract the topological features in the data. The presented PDT algorithm makes the identification of extrema by persistent discrete scalar-field topology computationally manageable for high dimensions. We give a step-by-step guide that shall help new users to run the code within few minutes. The code is open-source and a GitHub version is available for future updates, options, and add-ons.