[Blends-commit] r2751 - in /projects/med/trunk/debian-med/tasks: imaging imaging-dev

[tille at users.alioth.debian.org]

Author: tille
Date: Sun Apr 10 19:56:37 2011
New Revision: 2751

URL: http://svn.debian.org/wsvn/blends/?sc=1&rev=2751
Log:
python-dipy and python-nitime now official packages

Modified:
    projects/med/trunk/debian-med/tasks/imaging
    projects/med/trunk/debian-med/tasks/imaging-dev

Modified: projects/med/trunk/debian-med/tasks/imaging
URL: http://svn.debian.org/wsvn/blends/projects/med/trunk/debian-med/tasks/imaging?rev=2751&op=diff
==============================================================================
--- projects/med/trunk/debian-med/tasks/imaging (original)
+++ projects/med/trunk/debian-med/tasks/imaging Sun Apr 10 19:56:37 2011
@@ -975,31 +975,9 @@
  pyxid handles all of the low level device handling for XID devices in
  python projects.
 
- ; Added by blends-inject 0.0.7. [Please note here if modified manually]
 Recommends: python-dipy
 Why: Although listed in -dev task, it also has a strong focus on interactive
  data analysis.
-Homepage: http://nipy.org/dipy
-Language: Python
-WNPP: 610347
-Responsible: NeuroDebian Team <team at neuro.debian.net>
-License: BSD
-Vcs-Browser: http://github.com/neurodebian/dipy
-Vcs-Git: git://github.com/neurodebian/dipy.git
-Pkg-Description: toolbox for analysis of MR diffusion imaging data
- Dipy is a toolbox for the analysis of diffusion magnetic resonance
- imaging data. It features:
-  - Reconstruction algorithms, e.g. GQI, DTI
-  - Tractography generation algorithms, e.g. EuDX
-  - Intelligent downsampling of tracks
-  - Ultra fast tractography clustering
-  - Resampling datasets with anisotropic voxels to isotropic
-  - Visualizing multiple brains simultaneously
-  - Finding track correspondence between different brains
-  - Warping tractographies into another space, e.g. MNI space
-  - Reading many different file formats, e.g. Trackvis or NIfTI
-  - Dealing with huge tractographies without memory restrictions
-  - Playing with datasets interactively without storing
 Published-Authors: Garyfallidis E, Brett M, Tsiaras V, Vogiatzis G, Nimmo-Smith I
 Published-In: Proc. Intl. Soc. Mag. Reson. Med. 18
 Published-Title: Identification of corresponding tracks in diffusion MRI tractographies

Modified: projects/med/trunk/debian-med/tasks/imaging-dev
URL: http://svn.debian.org/wsvn/blends/projects/med/trunk/debian-med/tasks/imaging-dev?rev=2751&op=diff
==============================================================================
--- projects/med/trunk/debian-med/tasks/imaging-dev (original)
+++ projects/med/trunk/debian-med/tasks/imaging-dev Sun Apr 10 19:56:37 2011
@@ -40,23 +40,7 @@
 Published-URL: https://github.com/satra/ohbm2010/raw/master/NIPYPE/POSTER/poster_nipype.pdf
 Published-Year: 2010
 
- ; Added by blends-inject 0.0.2. [Please note here if modified manually]
 Depends: python-nitime
-Homepage: http://nipy.org/nitime
-Language: Python
-WNPP: 600714
-Responsible: NeuroDebian Team <team at neuro.debian.net>
-License: BSD-3
-Vcs-Browser: http://github.com/yarikoptic/nitime
-Vcs-Git: git://github.com/yarikoptic/nitime.git
-Pkg-Description: timeseries analysis for neuroscience data (nitime)
- Nitime is a Python module for time-series analysis of data from
- neuroscience experiments.  It contains a core of numerical algorithms
- for time-series analysis both in the time and spectral domains, a set
- of container objects to represent time-series, and auxiliary objects
- that expose a high level interface to the numerical machinery and
- make common analysis tasks easy to express with compact and
- semantically clear code.
 
 Depends: libvia-dev
 
@@ -194,29 +178,7 @@
   - complex searches
   - disk-caching of requested files and resources
 
- ; Added by blends-inject 0.0.7. [Please note here if modified manually]
 Depends: python-dipy
-Homepage: http://nipy.org/dipy
-Language: Python
-WNPP: 610347
-Responsible: NeuroDebian Team <team at neuro.debian.net>
-License: BSD
-Vcs-Browser: http://github.com/neurodebian/dipy
-Vcs-Git: git://github.com/neurodebian/dipy.git
-Pkg-Description: toolbox for analysis of MR diffusion imaging data
- Dipy is a toolbox for the analysis of diffusion magnetic resonance
- imaging data. It features:
-  - Reconstruction algorithms, e.g. GQI, DTI
-  - Tractography generation algorithms, e.g. EuDX
-  - Intelligent downsampling of tracks
-  - Ultra fast tractography clustering
-  - Resampling datasets with anisotropic voxels to isotropic
-  - Visualizing multiple brains simultaneously
-  - Finding track correspondence between different brains
-  - Warping tractographies into another space, e.g. MNI space
-  - Reading many different file formats, e.g. Trackvis or NIfTI
-  - Dealing with huge tractographies without memory restrictions
-  - Playing with datasets interactively without storing
 Published-Authors: Garyfallidis E, Brett M, Tsiaras V, Vogiatzis G, Nimmo-Smith I
 Published-In: Proc. Intl. Soc. Mag. Reson. Med. 18
 Published-Title: Identification of corresponding tracks in diffusion MRI tractographies