Python parser for Igor Binary Waves (.ibw) and Packed Experiment (.pxp) files written by WaveMetrics' IGOR Pro software.

This package provides a full-flegded processing pipeline for your MEG and EEG data. It operates on data stored according to the BIDS format.

spike sorting pipeline.

track_linearization is a Python package for mapping animal movement on complex track environments (mazes, figure-8s, T-mazes) into simplified 1D representations. It uses Hidden Markov Models to handle noisy position data and provides powerful tools for analyzing spatial behavior in neuroscience experiments.

This package provides tools for calculating smoothed 2D position, speed, head direction.

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.

This package implements both parametric and permutation-based ARI, and is meant to be compatible with the MNE-Python ecosystem.

pybv is a lightweight I/O utility for the BrainVision data format. The BrainVision data format is a recommended data format for use in the Brain Imaging Data Structure.

XDF is a general-purpose container format for multi-channel time series data with extensive associated meta information. XDF is tailored towards biosignal data such as EEG, EMG, EOG, ECG, GSR, MEG, but it can also handle data with high sampling rate (like audio) or data with a high number of channels (like fMRI or raw video). Meta information is stored as XML.

This package provides a new backend based on pyqtgraph for the 2D-Data-Browser in MNE-Python.

MNE-Python is an open-source Python package for exploring, visualizing, and analyzing human neurophysiological data such as MEG, EEG, sEEG, ECoG, and more. It includes modules for data input/output, preprocessing, visualization, source estimation, time-frequency analysis, connectivity analysis, machine learning, statistics, and more.

This package provides a C++ library for multi-modal time-synched data transmission over the local network.

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.

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.

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.

This package provides a Python library for manipulation and storage of a wide range of geoscientific data (points, curve, surface, 2D and 3D grids) in *.geoh5 file format.

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).

Harmonica is a Python library for processing and modeling gravity and magnetic data. It includes common processing steps, like calculation of Bouguer and terrain corrections, reduction to the pole, upward continuation, equivalent sources, and more. There are forward modeling functions for basic geometric shapes, like point sources, prisms and tesseroids.

This package provides a set of sparse matrix solvers used in geoscience.

All solvers work with scipy.sparse matricies, and a single or multiple right hand sides using numpy:

• L/U Triangular Solves

• Wrapping of SciPy matrix solvers (direct and indirect)

• Pardiso solvers now that MKL comes with conda!

• Mumps solver with nice error messages

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 powerful tools for geospatial data manipulation in Python, including working with coordinate reference systems, grid definitions, and spatial transformations.

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

This package provides conversion functions between UTM and WGS84 coordinates.