GHDL analyses, elaborates and simulates VHDL sources. It may also be used as an experimental synthesizer backend.

This package gathers GNAT binaries from FSF GCC releases of the Alire Project.

This plugin provides a shared library module for Yosys to implement logical synthesis of VHDL designs.

pyVHDLModel provides an unified abstract language model for VHDL written in Python.

GHDL Language Server Protocol (LSP) is a server for VHDL based on GHDL.

UVVM Light is a low threshold version of UVVM and is intended for developers who want to start using UVVM Utilty library and Bus Functional Models.

nwb2bids reorganizes NWB files into a BIDS directory layout.

Features:

• Automatically renames NWB files and their directories to conform to BIDS conventions.

• Extracts relevant metadata from NWB files to populate BIDS sidecar TSV & JSON files.

• Currently supports BEP32 (micro-electrode electrophysiology) data types, such as extracellular (ecephys) and intracellular (icephys) electrophysiology, as well as associated behavioral events.

This package provides a library for sleep stage classification using ECG data.

Meggie is an open-source software designed for intuitive MEG and EEG analysis. With its user-friendly graphical interface, Meggie brings the powerful analysis methods of MNE-Python to researchers without requiring programming skills.

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

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-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 denoising tools for M/EEG processing in Python.

klusta is an open source package for automatic spike sorting of multielectrode neurophysiological recordings made with probes containing up to a few dozens of sites.

FASTER is a fully automated, unsupervised method for processing of high density EEG data.

The NIX data model allows to store fully annotated scientific dataset, i.e. the data together with its metadata within the same container. The current implementations store the actual data using the HDF5 file format as a storage backend.

This inspector is meant as a companion to the PyNWB validator, which checks for strict schema compliance. This tool attempts to apply some common sense to find components of the file that are technically compliant, but possibly incorrect, suboptimal in their representation, or deviate from best practices.

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

MNE-LSL (Documentation website) provides a real-time brain signal streaming framework. MNE-LSL contains an improved python-binding for the Lab Streaming Layer C++ library, mne_lsl.lsl, replacing pylsl. This low-level binding is used in high-level objects to interact with LSL streams.

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

pyABF is a Python package for reading electrophysiology data from ABF files. It was created with the goal of providing a Pythonic API to access the content of ABF files which is so intuitive to use (with a predictive IDE) that documentation is largely unnecessary.

YASA is a Python package to analyze polysomnographic sleep recordings.

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

Tensor-based Phase-Amplitude Coupling.