1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62
|
Source: nitime
Maintainer: Debian Med Packaging Team <debian-med-packaging@lists.alioth.debian.org>
Uploaders: Yaroslav Halchenko <debian@onerussian.com>,
Michael Hanke <mih@debian.org>,
Nilesh Patra <nilesh@debian.org>,
Étienne Mollier <emollier@debian.org>
Section: python
Testsuite: autopkgtest-pkg-pybuild
Priority: optional
Build-Depends: debhelper-compat (= 13),
python3-all,
dh-sequence-python3,
pybuild-plugin-pyproject,
python3-numpy,
python3-scipy,
python3-matplotlib,
python3-tk,
python3-sphinx,
python3-networkx,
python3-nibabel,
python3-setuptools,
python3-setuptools-scm,
python3-pytest,
graphviz
Standards-Version: 4.7.0
Vcs-Browser: https://salsa.debian.org/med-team/nitime
Vcs-Git: https://salsa.debian.org/med-team/nitime.git
Homepage: https://nipy.org/nitime
Rules-Requires-Root: no
Package: python3-nitime
Architecture: all
Depends: ${python3:Depends},
${shlibs:Depends},
${misc:Depends},
python3-numpy,
python3-scipy
Recommends: python3-matplotlib,
python3-nibabel,
python3-networkx
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.
Package: python-nitime-doc
Architecture: all
Section: doc
Depends: ${misc:Depends},
libjs-jquery,
libjs-underscore
Suggests: python3-nitime
Multi-Arch: foreign
Description: timeseries analysis for neuroscience data (nitime) -- documentation
Nitime is a Python module for time-series analysis of data from
neuroscience experiments.
.
This package provides the documentation in HTML format.
|