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-1.1.1.tar.gz (3.2 MB view details)

Uploaded Source

Built Distribution

nipype-1.1.1-py2.py3-none-any.whl (3.2 MB view details)

Uploaded Python 2 Python 3

File details

Details for the file nipype-1.1.1.tar.gz.

File metadata

  • Download URL: nipype-1.1.1.tar.gz
  • Upload date:
  • Size: 3.2 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.11.0 pkginfo/1.4.2 requests/2.19.1 setuptools/20.10.1 requests-toolbelt/0.8.0 tqdm/4.24.0 CPython/2.7.12

File hashes

Hashes for nipype-1.1.1.tar.gz
Algorithm Hash digest
SHA256 e2b526d4eea0614734d389635e3909e180985cf4b17a9878d20fc8e992a5c83b
MD5 94084c9abb598fcb27d1cc3731751b0e
BLAKE2b-256 cd623caff5d083673997e5271978edbd64ced7ecf4ef64a30326da5299ac7988

See more details on using hashes here.

Provenance

File details

Details for the file nipype-1.1.1-py2.py3-none-any.whl.

File metadata

  • Download URL: nipype-1.1.1-py2.py3-none-any.whl
  • Upload date:
  • Size: 3.2 MB
  • Tags: Python 2, Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.11.0 pkginfo/1.4.2 requests/2.19.1 setuptools/20.10.1 requests-toolbelt/0.8.0 tqdm/4.24.0 CPython/2.7.12

File hashes

Hashes for nipype-1.1.1-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 33bb93eac3e3351778bd182050d9442670e40bd47f7a530b9a7e65d970e0a815
MD5 0e5cfa34074f997b335b47802e7fa85a
BLAKE2b-256 3b2a8487f6b8f041887a4a445e9c317daea4bedfcdfa6604350daa1015f020b9

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