nibabel 2.0.1-1 source package in Ubuntu
Changelog
nibabel (2.0.1-1) unstable; urgency=medium
* Fresh upstream release
* debian/rules
- First install for python3 and then for python2 to get correct
shebang in nib-ls (Closes: #784697)
-- Yaroslav Halchenko <email address hidden> Sun, 28 Jun 2015 01:06:52 -0400
Upload details
- Uploaded by:
- NeuroDebian Team
- Uploaded to:
- Sid
- Original maintainer:
- NeuroDebian Team
- Architectures:
- all
- Section:
- python
- Urgency:
- Medium Urgency
See full publishing history Publishing
| Series | Published | Component | Section |
|---|
Downloads
| File | Size | SHA-256 Checksum |
|---|---|---|
| nibabel_2.0.1-1.dsc | 2.2 KiB | d44916e3966ccdba433ff8cb5767808aa401cf663c6e7184a43a542b15d40a8c |
| nibabel_2.0.1.orig.tar.gz | 3.2 MiB | 29c7c371149079586c0cc6152a8dcfd32d1611d683a33306fa551cab93de23db |
| nibabel_2.0.1-1.debian.tar.xz | 5.9 KiB | 3d7d8f1c9b59b8877505376cbbd029850ea1d1eb79ccd8c9097d673b9e27c596 |
Available diffs
- diff from 1.3.0-2 to 2.0.1-1 (400.4 KiB)
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: No summary available for python-nibabel-doc in ubuntu wily.
No description available for python-nibabel-doc in ubuntu wily.
- 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.
