fastcluster: Fast hierarchical clustering routines for R and Python

Copyright © 2011 Daniel Müllner
<http://math.stanford.edu/~muellner>


Installation
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Installation procedures were tested under 64-bit Ubuntu. In principle, it should
be possible to install the fastcluster package on any system that has a C++
compiler and R respectively Python with NumPy.  There are no unusual libraries
needed to compile the package, only the STL library, which every C++ compiler
should have by default.

Please send me feedback if you accomplish to install the fastcluster package
under a different operating system from Linux or if you had to tweak the
configuration!  I will the update the installation instructions and modify the
package if needed (eg.  include the right compiler flags for various operating
systems).


Installation for R
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Open a terminal, go to the directory with the downloaded archive file and type:

  R CMD INSTALL fastcluster_1.0.2.tar.gz

You may need to precede the above command with sudo to gain administrator
privileges. There are ways to install R packages without administrator
privileges in your user directories. See this help page for example:

  http://csg.sph.umich.edu/docs/R/localpackages.html

If you need further help with the installation procedure, please consult R's
help function by typing ?INSTALL from within R.


Installation for Python
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Make sure that you have Python and NumPy installed. Open a terminal, go to the
directory with the downloaded file and extract the contents of the archive with:

    tar -xvf fastcluster_1.0.2.tar.gz

This will generate a new directory fastcluster. Switch to its python
subdirectory:

    cd fastcluster/python/

Now compile and install the Python module by:

    python setup.py install

Again, you may need to precede this command with sudo or install the package in
your home directory. For example, the line

    python setup.py install --home=~

installs the package in the path lib/python/ under your home directory. See the
chapter “Installing Python modules” in the Python documentation for further
help.
