Metadata-Version: 2.1
Name: fastcluster
Version: 1.2.3
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>
Description: 
        This library provides Python functions for hierarchical clustering. It
        generates hierarchical clusters from distance matrices or from vector data.
        
        This module is intended to replace the functions
        ```
            linkage, single, complete, average, weighted, centroid, median, ward
        ```
        in the module [`scipy.cluster.hierarchy`](
        https://docs.scipy.org/doc/scipy/reference/cluster.hierarchy.html) 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).
        
        The “Yule” distance function changed in fastcluster version 1.2.0. This is
        following a [change in SciPy 1.6.3](
        https://github.com/scipy/scipy/commit/3b22d1da98dc1b5f64bc944c21f398d4ba782bce).
        It is recommended to use fastcluster version 1.1.x together with SciPy versions
        before 1.6.3 and fastcluster 1.2.x with SciPy ≥1.6.3.
        
        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.
        
        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).
        
        Christoph Dalitz wrote a pure [C++ interface to fastcluster](
        https://lionel.kr.hs-niederrhein.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, https://www.jstatsoft.org/v53/i09/.
        
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 :: 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
Requires-Python: >=3
Description-Content-Type: text/markdown
Provides-Extra: test
