openmedical/registry
← registry

wonambi

imported

software/wonambi

Package to analyze EEG, ECoG and other electrophysiology formats. It allows for visualization of the results and for a GUI that can be used to score sleep stages.

Machine-generated from the listed sources and not yet reviewed by a human.

record
Category
Software & Systems
Subcategory
unknown
License
BSD-3-Clause(osi)
Status
active
Maturity
deployed
Organization
wonambi-python
Country
unknown
Documentation
unknown
Tags
ecog · eeg · electrocorticography · periodogram · sleep · visualization · wavelet
Regulatory
unknown
built by · 6

Top contributors by commit count, from the project’s public repository. Avatars are served by their origin, not stored here. To be removed from this list, open an issue.

similar by tags

Computed from shared tags, weighted so a rare tag counts for more than a common one. These are suggestions, not curated relationships.

  • braindecodeecog · eeg · electrocorticography

    Deep learning software to decode EEG, ECG or MEG signals

  • mne-pythonecog · eeg · electrocorticography

    MNE: Magnetoencephalography (MEG) and Electroencephalography (EEG) in Python

  • AccuSleepeeg · sleep

    Automatically score rodent sleep using EEG and EMG recordings

  • deepsleepneteeg · sleep

    DeepSleepNet: a Model for Automatic Sleep Stage Scoring based on Raw Single-Channel EEG

  • mne-arieeg · electrocorticography

    All-resolutions Inference for M/EEG in Python

  • NeuroRAecog · eeg

    A Python Toolbox for Multimode Neural Data Representation Analysis - A Representational Analysis Toolbox for Neuroscience, including Representational Similarity Analysis (RSA), & Inter-Subject…

sources
  1. api.github.com/repos/wonambi-python/wonambi
    retrieved 2026-08-05 · via github-api

    Machine-imported from GitHub search. Last push 2026-04-29, 100 stars, license reported as BSD-3-Clause. Category and schematic were assigned by keyword heuristics and are unreviewed.

Not yet verified by a human. Correct this record →

machine-readable

/v1/entries/4.json→ .entries["wonambi"]

Entries are sharded 64 ways by a stable hash of the id, so a consumer can find any record without an index.