Installation#

Warning

Pre-alpha software

VneuroTK is under active development. Public APIs and storage details may change before the first stable release; pin versions in reproducible work.

Install from PyPI#

Install the core package when you only need neural-data I/O and analysis:

uv add vneurotk

Or with pip:

pip install vneurotk

The core installation does not install PyTorch, Transformers, or Matplotlib. Visualization and DNN vision are separate optional features: viz installs Matplotlib for plotting recordings, while the vision-related extras install model backends for extracting representations from images.

Optional dependencies#

Install the extra that matches the features or model backend you need:

Extra

Installs

Use for

vision

torch, transformers

DNN vision-model and feature-extraction support

viz

matplotlib

Neural-recording and stimulus-timing visualization

timm

torch, transformers, timm

timm model backend, including the shared vision stack

thingsvision

torch, transformers, numba, thingsvision (Python 3.11–3.12)

thingsvision backend, including the shared vision stack

mne

mne, mne-bids

M/EEG analysis and BIDS support

notebook

ipykernel, ipywidgets

Jupyter notebooks

cebra

cebra, trialcebra

CEBRA integration

For example:

uv add "vneurotk[vision]"       # DNN vision extraction: PyTorch + Transformers
uv add "vneurotk[viz]"          # recording visualization: Matplotlib
uv add "vneurotk[timm]"         # timm + shared vision dependencies
uv add "vneurotk[thingsvision]" # thingsvision + shared vision dependencies
uv add "vneurotk[mne]"          # M/EEG analysis
uv add "vneurotk[notebook]"     # Jupyter support
uv add "vneurotk[cebra]"        # CEBRA support

Multiple real extras can be installed together. For example, this installs M/EEG support, Jupyter, and recording visualization; it does not install DNN vision extraction:

uv add "vneurotk[mne,notebook,viz]"

The thingsvision extra is currently constrained to Python 3.11–3.12. ThingsVision 1.4.4 imports TensorFlow eagerly, and its current dependency stack is not runtime-compatible with Python 3.13 in this project; on newer Python versions the extra intentionally installs no backend dependencies rather than presenting an untested installation as supported.

The torch requirement in the vision-related extras is installable on CPU-only systems. If you need a CUDA- or accelerator-specific PyTorch build, follow the PyTorch installation selector for your platform before or while resolving the extra.

From source#

git clone https://github.com/colehank/vneurotk.git
cd vneurotk
uv sync

uv sync installs the core package only. Add the extras needed for local work:

uv sync --extra vision       # DNN vision extraction stack
uv sync --extra viz          # recording visualization
uv sync --extra timm         # timm backend + shared vision stack
uv sync --extra thingsvision # thingsvision backend + shared vision stack

For contributors#

Clone the repository and install the development tools:

git clone https://github.com/colehank/vneurotk.git
cd vneurotk
uv sync --group dev

The development group contains Ruff, pytest, coverage, ty, Sphinx, MyST-NB, numpydoc, and the PyData Sphinx Theme. Dependency groups and package extras can be combined:

uv sync --group dev --extra vision --extra viz

Next steps#