Skip to main content

scikit autoregressive models for functional connectivity

Project description

CI Documentation codecov Ruff Python3 License

skarf (scikit autoregressive models for functional connectivity) is a Python package for regularized vector autoregressive (VAR) time series modeling built on top of scikit-learn. It is built for functional connectivity analyses of fMRI data.

Installation

You can install the latest release from PyPI with

pip install skarf

The latest development version can be installed with

pip install git+https://github.com/childmindresearch/skarf.git

Documentation

Package documentation is available here.

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

skarf-0.1.0.tar.gz (256.2 kB view details)

Uploaded Source

Built Distribution

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

skarf-0.1.0-py3-none-any.whl (21.7 kB view details)

Uploaded Python 3

File details

Details for the file skarf-0.1.0.tar.gz.

File metadata

  • Download URL: skarf-0.1.0.tar.gz
  • Upload date:
  • Size: 256.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.12.9

File hashes

Hashes for skarf-0.1.0.tar.gz
Algorithm Hash digest
SHA256 9d762d74bf3c7bb227c9ea3f8d1b1de4eee2b64a81cd49901662b45c055c2194
MD5 a44e6787aa04d6cf8021350dbcbf964e
BLAKE2b-256 d806808f7104254519ab71a2c21c09ac96f77009e623feb1fdbb351d11063615

See more details on using hashes here.

Provenance

The following attestation bundles were made for skarf-0.1.0.tar.gz:

Publisher: release.yaml on childmindresearch/skarf

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

File details

Details for the file skarf-0.1.0-py3-none-any.whl.

File metadata

  • Download URL: skarf-0.1.0-py3-none-any.whl
  • Upload date:
  • Size: 21.7 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.12.9

File hashes

Hashes for skarf-0.1.0-py3-none-any.whl
Algorithm Hash digest
SHA256 673fff1d47d3348b2192d805c2e297fdc08ee62aaad5bc96ddcc4701e3b5ae20
MD5 5a0f825175d17f36828bb75410b953ff
BLAKE2b-256 75a5b31b71e626adc84efa9eca20c2cc90da9655ca08f24b49a35a8b9fb376f8

See more details on using hashes here.

Provenance

The following attestation bundles were made for skarf-0.1.0-py3-none-any.whl:

Publisher: release.yaml on childmindresearch/skarf

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