This package provides an electrophysiological data analysis library for Python.

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.

A Python package to handle the layout, geometry, and wiring of silicon probes for extracellular electrophysiology experiments.

This is a Python package for performing representational similarity analysis (RSA) using MNE-Python data structures. The main use-case is to perform RSA using a “searchlight” approach through time and/or a volumetric or surface source space.

This library implements a simple lossless compression scheme adapted to time-dependent high-frequency, high-dimensional signals. It is being developed within the International Brain Laboratory with the aim of being the compression library used for all large-scale electrophysiological recordings based on Neuropixels. The signals are typically recorded at 30 kHz and 10 bit depth, and contain several hundreds of channels.

This package provides code for feature extraction with M/EEG data.

This package provides a Python implementation of a multitaper window method for estimating Wigner spectra for certain locally stationary processes.

Tensor-based Phase-Amplitude Coupling.

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

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

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.

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.

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 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.

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

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.

This packge provides utilities to retrieve tile maps from the internet. It can add those tiles as basemap to matplotlib figures or write tile maps to disk into geospatial raster files. Bounding boxes can be passed in both WGS84 (EPSG:4326) and Spheric Mercator (EPSG:3857).

This package provides methods for simulation and gradient-based parameter estimation in the context of geophysical applications.

The vision is to create a package for finite volume simulation with applications to geophysical imaging and subsurface flow. To enable the understanding of the many different components, this package has the following features:

• modular with respect to the spacial discretization, optimization routine, and geophysical problem

• built with the inverse problem in mind

• provides a framework for geophysical and hydrogeologic problems

• supports 1D, 2D and 3D problems

• designed for large-scale inversions

The electromagnetic modeller empymod can model electric or magnetic responses due to a three-dimensional electric or magnetic source in a layered-earth model with vertical transverse isotropic (VTI) resistivity, VTI electric permittivity, and VTI magnetic permeability, from very low frequencies (DC) to very high frequencies (GPR). The computation is carried out in the wavenumber-frequency domain, and various Hankel- and Fourier-transform methods are included to transform the responses into the space-frequency and space-time domains.

PyGMT is a library for processing geospatial and geophysical data and making publication-quality maps and figures. It provides a Pythonic interface for the Generic Mapping Tools (GMT), a command-line program widely used across the Earth, Ocean, and Planetary sciences and beyond.

This package provides a Python wrapper for solid to compute solid Earth tides.

Provides a high-level interface to the ECWMF ECCODES C library for reading GRIB files. There are limited capabilities for writing GRIB files (you can modify the contents of an existing file, but you can't create one from scratch).