Skip to main content

Neuroimaging in Python: Pipelines and Interfaces

Project description

Current neuroimaging software offer users an incredible opportunity to analyze data using a variety of different algorithms. However, this has resulted in a heterogeneous collection of specialized applications without transparent interoperability or a uniform operating interface.

Nipype, an open-source, community-developed initiative under the umbrella of NiPy, is a Python project that provides a uniform interface to existing neuroimaging software and facilitates interaction between these packages within a single workflow. Nipype provides an environment that encourages interactive exploration of algorithms from different packages (e.g., AFNI, ANTS, BRAINS, BrainSuite, Camino, FreeSurfer, FSL, MNE, MRtrix, MNE, Nipy, Slicer, SPM), eases the design of workflows within and between packages, and reduces the learning curve necessary to use different packages. Nipype is creating a collaborative platform for neuroimaging software development in a high-level language and addressing limitations of existing pipeline systems.

Nipype allows you to:

  • easily interact with tools from different software packages

  • combine processing steps from different software packages

  • develop new workflows faster by reusing common steps from old ones

  • process data faster by running it in parallel on many cores/machines

  • make your research easily reproducible

  • share your processing workflows with the community

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

nipype-1.3.0.tar.gz (2.7 MB view details)

Uploaded Source

Built Distribution

nipype-1.3.0-py2.py3-none-any.whl (3.2 MB view details)

Uploaded Python 2 Python 3

File details

Details for the file nipype-1.3.0.tar.gz.

File metadata

  • Download URL: nipype-1.3.0.tar.gz
  • Upload date:
  • Size: 2.7 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/2.0.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.6.0 requests-toolbelt/0.9.1 tqdm/4.38.0 CPython/3.6.5

File hashes

Hashes for nipype-1.3.0.tar.gz
Algorithm Hash digest
SHA256 53724e2762f1926db127eb9aa8a768d7086a60ab6daa44c679a3519faeee78ef
MD5 884875e8b1e111c5656e6b6cbe1b53ba
BLAKE2b-256 245220cf5bd944bdbae46810a3fd914343aca9265cf94291d97513e40a4965c4

See more details on using hashes here.

Provenance

File details

Details for the file nipype-1.3.0-py2.py3-none-any.whl.

File metadata

  • Download URL: nipype-1.3.0-py2.py3-none-any.whl
  • Upload date:
  • Size: 3.2 MB
  • Tags: Python 2, Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/2.0.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.6.0 requests-toolbelt/0.9.1 tqdm/4.38.0 CPython/3.6.5

File hashes

Hashes for nipype-1.3.0-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 f15a0c5ce31d5d3ef024135c0f3036dd62bee0ba95f3bf63e7eed5a40c005d91
MD5 f92d23bdd486c161b508fbd88878240d
BLAKE2b-256 0292633a6ace9a82003030240b03a4b0f320c08d7b40a70375554225a3e75565

See more details on using hashes here.

Provenance

Supported by

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