pymvpa2 2.2.0-4 source package in Ubuntu
Changelog
pymvpa2 (2.2.0-4) unstable; urgency=low * debian/control: - specify git branch for debian packaging of pymvpa2. Thanks Julien Cristau for the report - build-depends on python-numpydoc - recommend python-pprocess (removed from the Debian archive since we missed a dependency on it and otherwise was unused, but is present from NeuroDebian ) - policy boosted to 3.9.5 (no changes) * debian/rules: - mkdir target -lib directories before moving .so files. It should resolve FTBFS with debhelper 9.20130507 and robustify build - quote paths with globs to avoid their expansion in find command. Thanks Julien Cristau for the hint -- Yaroslav Halchenko <email address hidden> Thu, 12 Dec 2013 08:55:02 -0500
Upload details
- Uploaded by:
- NeuroDebian Team
- Uploaded to:
- Sid
- Original maintainer:
- NeuroDebian Team
- Architectures:
- any all
- Section:
- python
- Urgency:
- Low Urgency
See full publishing history Publishing
Series | Published | Component | Section |
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Downloads
File | Size | SHA-256 Checksum |
---|---|---|
pymvpa2_2.2.0-4.dsc | 1.6 KiB | e3792f75360a499a103120864c5ecfa6bbae049ea91b65420a0b4d94dfd4cf30 |
pymvpa2_2.2.0.orig.tar.gz | 4.7 MiB | baf18427cc87610b4afa30d98168cd7acabad026e8c0758b5f5bcf18f1739559 |
pymvpa2_2.2.0-4.debian.tar.gz | 11.1 KiB | b24b4b948756b66395b00d993195523d8fc0274c22415dbdaa8d6a9626da4319 |
Available diffs
- diff from 2.2.0-3 to 2.2.0-4 (1.5 KiB)
No changes file available.
Binary packages built by this source
- python-mvpa2: multivariate pattern analysis with Python v. 2
PyMVPA eases pattern classification analyses of large datasets, with an
accent on neuroimaging. It provides high-level abstraction of typical
processing steps (e.g. data preparation, classification, feature selection,
generalization testing), a number of implementations of some popular
algorithms (e.g. kNN, Ridge Regressions, Sparse Multinomial Logistic
Regression), and bindings to external machine learning libraries (libsvm,
shogun).
.
While it is not limited to neuroimaging data (e.g. fMRI, or EEG) it
is eminently suited for such datasets.
.
This is a package of PyMVPA v.2. Previously released stable version
is provided by the python-mvpa package.
- python-mvpa2-doc: documentation and examples for PyMVPA v. 2
This is an add-on package for the PyMVPA framework. It provides a
HTML documentation (tutorial, FAQ etc.), and example scripts.
In addition the PyMVPA tutorial is also provided as IPython notebooks.
- python-mvpa2-lib: low-level implementations and bindings for PyMVPA v. 2
This is an add-on package for the PyMVPA framework. It provides a low-level
implementation of an SMLR classifier and custom Python bindings for the LIBSVM
library.
.
This is a package of a development snapshot. The latest released version is
provided by the python-mvpa-lib package.