Metadata-Version: 2.1
Name: fastcluster
Version: 1.1.26
Summary: Fast hierarchical clustering routines for R and Python.
Home-page: http://danifold.net
Author: Daniel Müllner
Author-email: daniel@danifold.net
License: BSD <http://opensource.org/licenses/BSD-2-Clause>
Keywords: dendrogram,linkage,cluster,agglomerative,hierarchical,hierarchy,ward
Platform: UNKNOWN
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Classifier: Topic :: Scientific/Engineering :: Mathematics
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: C++
Classifier: Operating System :: OS Independent
Classifier: License :: OSI Approved :: BSD License
Classifier: License :: OSI Approved :: GNU General Public License v2 (GPLv2)
Classifier: Intended Audience :: Science/Research
Classifier: Development Status :: 5 - Production/Stable
Requires: numpy
Provides: fastcluster
Description-Content-Type: text/x-rst
Provides-Extra: test
License-File: COPYING.txt


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.

**User manual:** `fastcluster.pdf
<https://github.com/dmuellner/fastcluster/raw/master/docs/fastcluster.pdf>`_.

Installation files for Windows are provided on `PyPI
<https://pypi.org/project/fastcluster/#files>`__ and on `Christoph Gohlke's
web page <http://www.lfd.uci.edu/~gohlke/pythonlibs/#fastcluster>`_.

**The fastcluster package is considered stable and will undergo few changes
from now on. If some years from now there have not been any updates, this
does not necessarily mean that the package is unmaintained but maybe it just
was not necessary to correct anything. Of course, please still report potential
bugs and incompatibilities to daniel@danifold.net. You may also use**
`my GitHub repository <https://github.com/dmuellner/fastcluster/>`_
**for bug reports, pull requests etc.**

Note that `PyPI <https://pypi.org/project/fastcluster/>`__ and `my GitHub
repository <https://github.com/dmuellner/fastcluster/>`_ host the source code
for the Python interface only. The archive with both the R and the Python
interface is available on `CRAN
<https://CRAN.R-project.org/package=fastcluster>`_ and the GitHub repository
`“cran/fastcluster” <https://github.com/cran/fastcluster>`_. Even though I
appear as the author also of this second GitHub repository, this is just an
automatic, read-only mirror of the CRAN archive, so please do not attempt to
report bugs or contact me via this repository.

Christoph Dalitz wrote a pure `C++ interface to fastcluster
<http://informatik.hsnr.de/~dalitz/data/hclust>`_.

Reference: Daniel Müllner, *fastcluster: Fast Hierarchical, Agglomerative
Clustering Routines for R and Python*, Journal of Statistical Software, **53**
(2013), no. 9, 1–18, http://www.jstatsoft.org/v53/i09/.


