Skip to main content

DARTsort

Project description

badge coveralls Zenodo DOI

dartsort

:warning: Work in progress code repository

We do not currently recommend DARTsort for production spike sorting purposes. We are in the process of implementing a robust and documented pipeline in src/dartsort, and we will update this page accordingly.

A workflow described in our preprint (https://www.biorxiv.org/content/10.1101/2023.08.11.553023v1) is in uhd_pipeline.py, which is implemented using the legacy code in src/spike_psvae.

Suggested install steps

If you don't already have Python and PyTorch 2 installed, we recommend doing this with the Miniforge distribution of conda. You can find info and installers for your platform at Miniforge's GitHub repository. After installing Miniforge, conda will be available on your computer for installing Python packages, as well as the newer and faster conda replacement tool mamba. We recommend using mamba instead of conda below, since the installation tends to be a lot faster with mamba.

To install DARTsort, first clone this GitHub repository.

After cloning the repository, create and activate the mamba/conda environment from the configuration file provided as follows:

$ mamba env create -f environment.yml
$ mamba activate dartsort

Next, visit https://pytorch.org/get-started/locally/ and follow the PyTorch install instructions for your specific OS and hardware needs. We also need to install linear_operator from the gpytorch channel. For example, on a Linux workstation or cluster with NVIDIA GPUs available, one might use (dropping in mamba for conda commands):

# Example -- see https://pytorch.org/get-started/locally/ to find your platform's command.
(dartsort) $ mamba install pytorch torchvision torchaudio pytorch-cuda=11.8 linear_operator -c pytorch -c nvidia -c gpytorch

Finally, install the remaining pip dependencies and dartsort itself:

(dartsort) $ pip install -r requirements-full.txt
(dartsort) $ pip install -e .

To enable DARTsort's default motion correction algorithm DREDge, clone its GitHub repository, and then cd dredge/ and install the DREDge package with pip install -e ..

Soon we will have a package on PyPI so that these last steps will be just a pip install dartsort.

To make sure everything is working:

$ (dartsort) pytest tests/*

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

dartsort-0.4.0.tar.gz (4.1 MB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

dartsort-0.4.0-py3-none-any.whl (2.5 MB view details)

Uploaded Python 3

File details

Details for the file dartsort-0.4.0.tar.gz.

File metadata

  • Download URL: dartsort-0.4.0.tar.gz
  • Upload date:
  • Size: 4.1 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for dartsort-0.4.0.tar.gz
Algorithm Hash digest
SHA256 576d0309ca1c91abff0d0927e8d68bb836b4d65016c518bd45b80da7a68e5b01
MD5 5521e9df0b980b332b5fc74990670371
BLAKE2b-256 0bd32802dd3000fd7d8610e79594419bd0f402fb226c9f2253e225981c1207bb

See more details on using hashes here.

Provenance

The following attestation bundles were made for dartsort-0.4.0.tar.gz:

Publisher: deploy.yml on cwindolf/dartsort

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file dartsort-0.4.0-py3-none-any.whl.

File metadata

  • Download URL: dartsort-0.4.0-py3-none-any.whl
  • Upload date:
  • Size: 2.5 MB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for dartsort-0.4.0-py3-none-any.whl
Algorithm Hash digest
SHA256 af58ca14cba5e4aec68babda5328c26fa704341c56cf40ab7067ca6272d86e89
MD5 b8011ede73e0c8d46154ea2a2e176d29
BLAKE2b-256 cd0019f1899fb64847d28f031f8e6245e728a5a280149472afdaef8c0e9f4cbf

See more details on using hashes here.

Provenance

The following attestation bundles were made for dartsort-0.4.0-py3-none-any.whl:

Publisher: deploy.yml on cwindolf/dartsort

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page