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Source: python-numpy-groupies
Maintainer: Debian Python Team <team+python@tracker.debian.org>
Uploaders: Steffen Moeller <moeller@debian.org>
Section: science
Priority: optional
Testsuite: autopkgtest-pkg-pybuild
Build-Depends: debhelper-compat (= 13),
dh-python,
dh-sequence-python3,
pybuild-plugin-pyproject,
python3-all,
python3-numpy <!nocheck>,
python3-pandas <!nocheck>,
python3-pytest <!nocheck>,
python3-scipy <!nocheck>,
python3-setuptools,
python3-setuptools-scm
Standards-Version: 4.6.2
Vcs-Browser: https://salsa.debian.org/python-team/packages/numpy-groupies
Vcs-Git: https://salsa.debian.org/python-team/packages/numpy-groupies.git
Homepage: https://github.com/ml31415/numpy-groupies
Rules-Requires-Root: no
Package: python3-numpy-groupies
Architecture: all
Section: python
Depends: ${python3:Depends},
${misc:Depends}
Description: performs operations on/with subsets of n-dim arrays
This package consists of a couple of optimised tools for doing things
that can roughly be considered "group-indexing operations". The most
prominent tool is `aggregate`.
.
`aggregate` takes an array of values, and an array giving the group
number for each of those values. It then returns the sum (or mean, or
std, or any, ...etc.) of the values in each group. You have probably
come across this idea before, using `matlab` accumarray, `pandas`
groupby, or generally MapReduce algorithms and histograms.
.
There are different implementations of `aggregate` provided, based on
plain `numpy`, `numba` and `weave`. Performance is a main concern, and
so far this implementation comfortably beats similar implementations in
other packages (check the benchmarks).
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