A package for computing data-driven approximations to the Koopman operator.

Wind farm tools based in Julia

Sparsity-promoting Kernel Dynamic Mode Decomposition for Nonlinear Dynamical Systems

A Python package for spectral proper orthogonal decomposition (SPOD).

Codes for Linear and Nonlinear Disambiguation Optimization (LANDO)

A collection of spectral collocation differentiation matrices

Code for conducting eigenvalue and resolvent analyses using the python bindings for PETSc and SLEPc.

Tools for building fast, hackable, pseudospectral partial differential equation solvers on periodic domains

Companion code for Data-Driven Resolvent Analysis

Artificial Intelligence Research for Science (AIRS)

Source code to perform Lagrangian modal analysis (LMA). The case study comprises a double-gyre flow pattern subjected to LMA, computing Lagrangian proper orthogonal decomposition (LPOD) modes.

Machine learning from scratch in Julia

a scaffolding for building inviscid flow models

Python Dynamic Mode Decomposition

GPU Programming with Julia - course at the Swiss National Supercomputing Centre (CSCS), ETH Zurich

Matplotlib styles for scientific plotting

Fast and simple fluid simulator in Julia