This package provides denoising tools for M/EEG processing in Python.

Tensor-based Phase-Amplitude Coupling.

NeuroKit2 is a user-friendly package providing easy access to advanced biosignal processing routines. Researchers and clinicians without extensive knowledge of programming or biomedical signal processing can analyze physiological data with only two lines of code.

spike sorting pipeline.

pyRiemann is a Python machine learning package based on scikit-learn API. It provides a high-level interface for processing and classification of real (resp. complex)-valued multivariate data through the Riemannian geometry of symmetric (resp. Hermitian) positive definite (SPD) (resp. HPD) matrices.

AntroPy is a Python package providing several time-efficient algorithms for computing the complexity of time-series. It can be used for example to extract features from EEG signals.

mffpy is a lean reader for EGI's MFF file format. These files are directories containing several files of mostly xml files, but also binary files.

mne-icalabel is a Python package for labeling independent components that stem from an Independent Component Analysis (ICA).

MNE-CPP is an open-source, cross-platform C++ framework for real-time and offline processing of MEG, EEG, and related neurophysiological data.

Python library for reading, writing, and validating SNIRF files

deviceXlib is a library that wraps device-oriented routines and utilities, such as device data allocation, host-device data transfers. It supports CUDA language, together with OpenACC and OpenMP programming paradigms. It wraps a subset of functions from Nvidia cuBLAS, Intel oneMKL BLAS and AMD rocBLAS libraries.

Fortran Package Manager (fpm) is a package manager and build system for Fortran. Its key goal is to improve the user experience of Fortran programmers. It does so by making it easier to build your Fortran program or library, run the executables, tests, and examples, and distribute it as a dependency to other Fortran projects. Fpm's user interface is modeled after Rust's Cargo, so if you're familiar with that tool, you will feel at home with fpm. Fpm's long term vision is to nurture and grow the ecosystem of modern Fortran applications and libraries.

deviceXlib is a library that wraps device-oriented routines and utilities, such as device data allocation, host-device data transfers. It supports CUDA language, together with OpenACC and OpenMP programming paradigms. It wraps a subset of functions from Nvidia cuBLAS, Intel oneMKL BLAS and AMD rocBLAS libraries.

Fypp is a Python powered preprocessor. It can be used for any programming languages but its primary aim is to offer a Fortran preprocessor, which helps to extend Fortran with condititional compiling and template metaprogramming capabilities. Instead of introducing its own expression syntax, it uses Python expressions in its preprocessor directives, offering the consistency and versatility of Python when formulating metaprogramming tasks.

This package provides DLF as used in Geophysics for electromagnetic modelling.

This package provides a geospatial extension for xarray powered by rasterio.

This package provides programmatic access to the CDS, ADS and EWDS data catalogues from the ECMWF.

Pyresample is a python package for resampling geospatial image data. Resampling or reprojection is the process of mapping input geolocated data points to a new target geographic projection and area.

This package provides programmatic access to the data store catalogue of the Copernicus CDS.

PnetCDF is a high-performance parallel I/O library for accessing Unidata's NetCDF, files in classic formats, specifically the formats of CDF-1, 2, and 5.

This package provides discretization tools for finite volume and inverse problems.

The vision is to create a package for finite volume simulation with a focus on large scale inverse problems. This package has the following features:

• modular with respect to the spacial discretization

• built with the inverse problem in mind

• supports 1D, 2D and 3D problems

• access to sparse matrix operators

• access to derivatives to mesh variables

Currently, discretize supports:

• Tensor Meshes (1D, 2D and 3D)

• Cylindrically Symmetric Meshes

• QuadTree and OcTree Meshes (2D and 3D)

• Logically Rectangular Meshes (2D and 3D)

• Triangular (2D) and Tetrahedral (3D) Meshes

This package provides a collection of (mostly) analytic functions in geophysics. We take an object oriented approach with the aim of having users be able to readily interact with the functions using Jupyter.

Choclo is a Python library that hosts optimized kernel functions for running geophysical forward and inverse models, intended to be used by other libraries as the underlying layer of their computation.

This package provides a three-dimensional modeller for electromagnetic (EM) diffusion as used for instance in geophysical controlled-source EM (CSEM) surveys. This includes use cases in the search for resources such as groundwater, geothermal energy, hydrocarbons, and minerals, or civil engineering and environmental applications.