Skip to main content

Python interface to the Fabber toolkit for Bayesian model fitting

Project description

PYFAB - Python interface to the Fabber Bayesian model fitting tool

Fabber is a Bayesian model-fitting framework designed to fit nonlinear parameterised models to timeseries data, particularly 4D fMRI data such as ASL, CEST, DCE, DSC, etc.

PYFAB offers a Python interface to the tool which can work with the command line Fabber tool, or the shared library version, depending on which is installed.

Fabber must be installed before use - See https://fabber_core.readthedocs.io/. Fabber and a selection of models will be available in the upcoming FSL 6.0.1 release

Full documentation at https://pyfab.readthedocs.io/

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

pyfab-0.3.3.post13.tar.gz (22.3 kB view details)

Uploaded Source

File details

Details for the file pyfab-0.3.3.post13.tar.gz.

File metadata

  • Download URL: pyfab-0.3.3.post13.tar.gz
  • Upload date:
  • Size: 22.3 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.13.0 pkginfo/1.5.0.1 requests/2.21.0 setuptools/41.0.1 requests-toolbelt/0.9.1 tqdm/4.32.2 CPython/2.7.15

File hashes

Hashes for pyfab-0.3.3.post13.tar.gz
Algorithm Hash digest
SHA256 fc92158f6457898f41fbc6aea2f81cc66ceefa71492a8fe3ac94e49c10067f55
MD5 36609ef34c4b0a63f82f6284a7e20f30
BLAKE2b-256 5b1d2043f36b1fd0b5d703565286aa89f892333f34bcd56b5e844552a6db5265

See more details on using hashes here.

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