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.
1 maintainer
Metadata
1 maintainer
Release files for skarf 0.1.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| skarf-0.1.0.tar.gz | 256.2 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| skarf-0.1.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 277.9 kB
Release files / skarf-0.1.0.tar.gz
| Download URL | skarf-0.1.0.tar.gz |
|---|---|
| Size | 256.2 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
9d762d74bf3c7bb227c9ea3f8d1b1de4eee2b64a81cd49901662b45c055c2194
|
|
BLAKE2b-256 checksum How to use checksums |
d806808f7104254519ab71a2c21c09ac96f77009e623feb1fdbb351d11063615
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/6.1.0 CPython/3.12.9
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on May 29, 2025.
Transparency logRelease files / skarf-0.1.0-py3-none-any.whl
| Download URL | skarf-0.1.0-py3-none-any.whl |
|---|---|
| Size | 21.7 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
673fff1d47d3348b2192d805c2e297fdc08ee62aaad5bc96ddcc4701e3b5ae20
|
|
BLAKE2b-256 checksum How to use checksums |
75a5b31b71e626adc84efa9eca20c2cc90da9655ca08f24b49a35a8b9fb376f8
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/6.1.0 CPython/3.12.9
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on May 29, 2025.
Transparency log
