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-1.1.4.tar.gz (2.8 MB view details)

Uploaded Source

Built Distribution

nipype-1.1.4-py2.py3-none-any.whl (3.2 MB view details)

Uploaded Python 2 Python 3

File details

Details for the file nipype-1.1.4.tar.gz.

File metadata

  • Download URL: nipype-1.1.4.tar.gz
  • Upload date:
  • Size: 2.8 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.12.1 pkginfo/1.4.2 requests/2.20.0 setuptools/40.5.0 requests-toolbelt/0.8.0 tqdm/4.28.1 CPython/2.7.12

File hashes

Hashes for nipype-1.1.4.tar.gz
Algorithm Hash digest
SHA256 bfed0d6d905e5fc73d5b9513b4381b9025977e3c8544dd012d2775735456298c
MD5 7ea1d7582910fa1d1919e79638f7f788
BLAKE2b-256 e02e113fe7bf03c3e8a5c58347c72d6f0365eefbb6ea74c6aa083946bf637bd0

See more details on using hashes here.

Provenance

File details

Details for the file nipype-1.1.4-py2.py3-none-any.whl.

File metadata

  • Download URL: nipype-1.1.4-py2.py3-none-any.whl
  • Upload date:
  • Size: 3.2 MB
  • Tags: Python 2, Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.12.1 pkginfo/1.4.2 requests/2.20.0 setuptools/40.5.0 requests-toolbelt/0.8.0 tqdm/4.28.1 CPython/2.7.12

File hashes

Hashes for nipype-1.1.4-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 9fb6376324c95866843316b27f066a3f57453c941ef75e7e82a232dedec0ae44
MD5 7a7006fcc3511e0c90c9e3549a7f810a
BLAKE2b-256 059b75aaea188f5fc26c40de25d59ab2eb44fa37fa314f3ebf267e255b770f66

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