nibabel 2.5.1-1 source package in Ubuntu
Changelog
nibabel (2.5.1-1) unstable; urgency=medium
* Fresh 2.5.1 release (2.5.x series is the last one to support python2)
* debian/control
- boosted policy to 4.4.1
- Stripped XS- for Testsuite
* debian/copyright
- removed obsolete paragraph for no longer included
doc/sphinxext/autosummary
* rm debian/patches/lenny-dsc-patch_numpy_testing - no backports for lenny
were built for years
-- Yaroslav Halchenko <email address hidden> Sun, 10 Nov 2019 18:09:36 -0500
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_2.5.1-1.dsc | 2.5 KiB | e68cf8817aa0872964ccaa1991fe9e879b4b4be837f8bece585a091dc7f3217b |
| nibabel_2.5.1.orig.tar.gz | 4.1 MiB | a75e15577b9f783e09f48ab42799f3265b7a674f051be118d5f1186a7413bbcd |
| nibabel_2.5.1-1.debian.tar.xz | 7.6 KiB | f1b1b066eb8e616f098bf483e8272f7164a902fa5070433b38edca6ffab33a56 |
Available diffs
- diff from 2.5.0-1 to 2.5.1-1 (10.3 KiB)
No changes file available.
Binary packages built by this source
- python-nibabel: No summary available for python-nibabel in ubuntu focal.
No description available for python-nibabel in ubuntu focal.
- 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.
