nibabel 2.3.2-1 source package in Ubuntu

Changelog

nibabel (2.3.2-1) unstable; urgency=medium

  * Fresh upstream release

 -- Yaroslav Halchenko <email address hidden>  Fri, 04 Jan 2019 23:35:50 -0500

Upload details

Uploaded by:
NeuroDebian Team on 2019-01-08
Uploaded to:
Sid
Original maintainer:
NeuroDebian Team
Architectures:
all
Section:
python
Urgency:
Medium Urgency

See full publishing history Publishing

Series Pocket Published Component Section

Builds

Disco: [FULLYBUILT] amd64

Downloads

File Size SHA-256 Checksum
nibabel_2.3.2-1.dsc 2.5 KiB 8e50ad11d27e62bc7dcfe4d6089d3fe2936fed5411f1d6fc90ed58891ff6b4ff
nibabel_2.3.2.orig.tar.gz 4.0 MiB b982d839490157a05f82d1e5a136ac44288f8a604242de506d45219a49b4d9f0
nibabel_2.3.2-1.debian.tar.xz 8.0 KiB 4b8c56a9036a906ec22eeb5b595e44e070ca73d73eda66c4fbd4e051f750e639

Available diffs

No changes file available.

Binary packages built by this source

python-nibabel: Python bindings to various neuroimaging data formats

 NiBabel provides read and write access to some common medical and
 neuroimaging file formats, including: ANALYZE (plain, SPM99, SPM2), GIFTI,
 NIfTI1, MINC, as well as PAR/REC. The various image format classes give full
 or selective access to header (meta) information and access to the image data
 is made available via NumPy arrays. NiBabel is the successor of PyNIfTI.
 .
 This package also provides a commandline tools:
 .
  - dicomfs - FUSE filesystem on top of a directory with DICOMs
  - nib-ls - 'ls' for neuroimaging files
  - parrec2nii - for conversion of PAR/REC to NIfTI images

python-nibabel-doc: documentation for NiBabel

 NiBabel provides read and write access to some common medical and
 neuroimaging file formats, including: ANALYZE (plain, SPM99, SPM2), GIFTI,
 NIfTI1, MINC, as well as PAR/REC. The various image format classes give full
 or selective access to header (meta) information and access to the image data
 is made available via NumPy arrays. NiBabel is the successor of PyNIfTI.
 .
 This package provides the documentation in HTML format.

python3-nibabel: Python3 bindings to various neuroimaging data formats

 NiBabel provides read and write access to some common medical and
 neuroimaging file formats, including: ANALYZE (plain, SPM99, SPM2), GIFTI,
 NIfTI1, MINC, as well as PAR/REC. The various image format classes give full
 or selective access to header (meta) information and access to the image data
 is made available via NumPy arrays. NiBabel is the successor of PyNIfTI.