r-cran-fastcluster 1.1.25-3build4 source package in Ubuntu


r-cran-fastcluster (1.1.25-3build4) hirsute; urgency=medium

  * No-change rebuild to drop python3.8 extensions.

 -- Matthias Klose <email address hidden>  Mon, 07 Dec 2020 18:25:11 +0100

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Matthias Klose on 2020-12-07
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Debian R Packages Maintainers
Medium Urgency

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Series Pocket Published Component Section
Impish release on 2021-04-23 universe misc
Hirsute release on 2020-12-09 universe misc


File Size SHA-256 Checksum
r-cran-fastcluster_1.1.25.orig.tar.gz 184.3 KiB f3661def975802f3dd3cec5b2a1379f3707eacff945cf448e33aec0da1ed4205
r-cran-fastcluster_1.1.25-3build4.debian.tar.xz 4.3 KiB d02d5f67ad9c5b865b942aa130e6e24aee0e2f3badd7c0c08be0567c03960f0b
r-cran-fastcluster_1.1.25-3build4.dsc 2.2 KiB 8cfdf1baaffdc451d567424b55662c05dfad924da2ae836dbb79a47946812bfe

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python3-fastcluster: Fast hierarchical clustering routines for Python 3

 This library provides Python functions for hierarchical
 clustering. It generates hierarchical clusters from distance matrices
 or from vector data.
 Part of this module is intended to replace the functions
     linkage, single, complete, average, weighted, centroid, median, ward
 in the module scipy.cluster.hierarchy with the same functionality but
 much faster algorithms. Moreover, the function 'linkage_vector'
 provides memory-efficient clustering for vector data.
 The interface is very similar to MATLAB's Statistics Toolbox API to
 make code easier to port from MATLAB to Python/Numpy. The core
 implementation of this library is in C++ for efficiency.
 This package provides the package's Python 3 interface.

python3-fastcluster-dbgsym: debug symbols for python3-fastcluster
r-cran-fastcluster: Fast hierarchical clustering routines for GNU R

 Fastcluster implements fast hierarchical, agglomerative clustering
 routines. Part of the functionality is designed as drop-in replacement
 for existing routines: “linkage” in the SciPy package
 “scipy.cluster.hierarchy”, “hclust” in R's “stats” package, and the
 “flashClust” package. It provides the same functionality with the
 benefit of a much faster implementation. Moreover, there are
 memory-saving routines for clustering of vector data, which go beyond
 what the existing packages provide. For information on how to install
 the Python files, see the file INSTALL in the source distribution.

r-cran-fastcluster-dbgsym: debug symbols for r-cran-fastcluster