Fast Hierarchical Clustering Routines for R and 'Python'

This is a two-in-one package which provides interfaces to both R and 'Python'. It 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. Based on the present package, Christoph Dalitz also wrote a pure 'C++' interface to 'fastcluster': < http://informatik.hsnr.de/~dalitz/data/hclust>.


News

fastcluster: Fast hierarchical clustering routines for R and Python

Copyright: • Until package version 1.1.23: © 2011 Daniel Müllner http://danifold.net • All changes from version 1.1.24 on: © Google Inc. http://google.com

Version history ‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾ Version 1.0.0, 03/14/2011:

• Initial release, dependent on Rcpp. Not available on CRAN.

Version 1.0.1, 03/15/2011:

• Removed the dependence on Rcpp; only R's original C interface is used.

Version 1.0.2, 03/17/2011:

• File DESCRIPTION: Fixed a typo

Version 1.0.3, 03/20/2011:

• File README: Removed the warning about false results from the flashClust package since the new flashClust version 1.01 has this error corrected.

• Cleaned the test file fastcluster_test.R up. (No dependence on the MASS package any more)

Version 1.0.4, 03/21/2011:

• Changed the name of the external function from the outdated "Rcpp_linkage" to "fastcluster".

• Registered the external function "fastcluster" in R.

• Configured the C header inclusions to work on Fedora (thanks to Peter Langfelder).

Version 1.1.0, 08/21/2011

• Routines for clustering vector data.

• Added a User's manual

• Revision of all files

Version 1.1.1, 10/08/2011

• Fixed test scripts, which indicated an error on some architectures, even if results were correct. (The assumption was that ties in single linkage clustering are resolved in the same way, both for dissimilarity input and for vector input. This is not necessarily true if the floating point unit uses "excess precision". Now the test scripts are content with arbitrary resolution of ties and do not assume a specific scheme.)

• Bug fix: uninitialized function pointer in Version 1.1.0

Version 1.1.2, 10/11/2011

• Fix for Solaris: replaced ssize_t by ptrdiff_t in the C++ code.

• Removed the NN-chain algorithm for vector input: it was not clear that it would work under all circumstances with the intricacies of floating- point arithmetic. Especially the effects of the excess precision on the x87 are impossible to control in a portable way. Now, the memory-saving routines for the “Ward” linkage use the generic algorithm, as “centroid” and “median” linkage do.

Version 1.1.3, 12/10/2011

• Replaced ptrdiff_t by std::ptrdiff_t, as GCC 4.6.1 complains about this.

Version 1.1.4, 02/01/2012

• Release the GIL in the Python package, so that it can be used efficiently in multithreaded applications.

• Improved performance for the "Ward" method with vector input.

• The "members" parameter in the R interface is now treated as a double array, not an integer array as before. This was a slight incompatibility with the stats::hclust function. Thanks to Matthias Studer, University of Geneva, for pointing this out.

Version 1.1.5, 02/14/2012

• Updated the "members" specification in the User's manual to reflect the recent change.

Version 1.1.6, 03/12/2012

• Bug fix related to GIL release in the Python wrapper. Thanks to Massimo Di Stefano for the bug report.

• Small compatibility changes in the Python test scripts (again thanks to Massimo Di Stefano for the report).

Version 1.1.7, 09/17/2012

• Scipy import is now optional (suggested by Forest Gregg)

• Compatibility fix for NumPy 1.7. Thanks to Semihcan Doken for the bug report.

Version 1.1.8, 08/28/2012

• Test for NaN dissimilarity values: Now the algorithms produce an error message instead of silently giving false results. The documentation was updated accordingly. This is the final design as intended: the fastcluster package handles infinity values correctly but complains about NaNs.

• The Python interface now works with both Python 2 and Python 3.

• Changed the license to BSD.

Version 1.1.9, 03/15/2013

• Compatibility fix for the MSVC compilers on Windows.

• Simplified GIL release in the Python interface.

Version 1.1.10, 05/22/2013

• Updated citation information (JSS paper).

• Suppress warnings where applicable. Compilation with GCC should not produce any warning at all, even if all compiler warnings are enabled. (The switch -pedantic still does not work, but this is due to the Python headers.)

• Optimization: Hidden symbols. Only the interface functions are exported to the symbol table with GCC.

Version 1.1.11, 05/23/2013

• Compatibility fix for Solaris.

Version 1.1.12, 12/10/2013

• Tiny maintenance updates: new author web page and e-mail address, new location for R vignette.

Version 1.1.13, 12/17/2013

• Moved the "python" directory due to CRAN requirements.

Version 1.1.14, 01/02/2015

• Updated the DESCRIPTION file according to CRAN rules. • Renamed the “ward” method for dissimilarity input to “ward.D” in the R interface and created a new method “ward.D2”, following changes in R's hclust package.

Version 1.1.15, 01/05/2015

• Fixed the unit test to work with old and new R versions (see the changes in stats::hclust in R 3.1.0).

Version 1.1.16, 01/07/2015

• Support for large distance matrices (more than 2^31 entries, R's long vector support since version 3.0.0).

Version 1.1.17, 07/03/2015

• Resolved MSVC compiler warnings.

Version 1.1.18, 07/16/2015

• Fixed missing NumPy header include path.

Version 1.1.19, 07/19/2015

• Fixed unit tests. They can be run with "python setup.py test" now.

Version 1.1.20, 07/19/2015

• New version number due to PyPI upload error.

Version 1.1.21, 09/18/2016

• Appropiate use of std namespace, as required by CRAN.

Version 1.1.22, 06/12/2016

• No fenv header usage if software floating-point emulation is used (bug report: NaN test failed on Debian armel).

Version 1.1.23, 03/24/2017

• setup.py: Late NumPy import for better dependency management.

Version 1.1.24, 08/04/2017

• R 3.5 corrects the formula for the “Canberra” metric. See https://bugs.r-project.org/bugzilla/show_bug.cgi?id=17285. The formula in the fastcluster package was changed accordingly. This concerns only the R interface. SciPy and fastcluster's Python interface always had the correct formula.

Version 1.1.25, 05/27/2018

• Removed all “#pragma GCC diagnostic” directives in .cpp files due to changed CRAN requirements (CRAN repository only, not the GitHub repository).

Reference manual

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install.packages("fastcluster")

1.1.25 by Daniel Müllner, 2 years ago


http://danifold.net/fastcluster.html


Browse source code at https://github.com/cran/fastcluster


Authors: Daniel Müllner [aut, cph, cre] , Google Inc. [cph]


Documentation:   PDF Manual  


Task views: Cluster Analysis & Finite Mixture Models


FreeBSD | GPL-2 | file LICENSE license


Enhances stats, flashClust


Imported by MLGL, MRPC, MetProc, NPflow, SpatialVx, VoxR, cstab, disto, heatmap3, hypervolume, iheatmapr, maotai, mousetrap, pinbasic, propr, vanddraabe.

Depended on by PropClust, WGCNA, bahc.

Suggested by FCPS, IncDTW, TDAmapper, hyperSpec, linkcomm.


See at CRAN