--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/README	Sat Jun 20 12:33:19 2009 -0700
@@ -0,0 +1,86 @@
+pyANN
+=====
+
+pyANN provides Python bindings for David Mount and Sunil Arya's ANN_ library for
+approximate nearest neighbor searching.
+
+.. _ANN:        http://www.cs.umd.edu/~mount/ANN/
+
+
+Example
+-------
+
+.. parsed-literal::
+
+    >>> import pyANN
+    >>> kdtree = pyANN.KDTree([[1,1,1], [1,2,3], [4,5,6]])
+    >>> kdtree.kSearch([0,0,0], 2, 0)
+    ([0, 1], [3.0, 14.0])
+
+
+Download
+--------
+
+The easiest way to obtain pyANN is to check it out from my Mercurial_
+repository:
+
+.. parsed-literal::
+
+    hg clone http://hg.mrzv.org/pyANN
+
+Alternatively, one can download the tarball_.
+
+.. _Mercurial:  http://www.selenic.com/mercurial/wiki/
+.. _tarball:    http://hg.mrzv.org/pyANN/archive/tip.tar.gz
+
+
+Building and Installing
+-----------------------
+
+First of all, one needs to patch ANN_ to make it compile with more recent
+versions of GCC_ and to make it build shared libraries under Linux. If you are
+not under Linux and have an older version of GCC_ (below 4.3), you can safely
+skip these steps.
+
+.. _GCC:                    http://gcc.gnu.org/
+
+Download the gcc43.patch_ and shared-libs.patch_. Within the directory where
+you've extracted ANN_, run::
+
+    patch -p1 < .../gcc43.patch   
+    patch -p1 < .../shared-libs.patch
+    make linux-g++-sl
+
+(assuming you are on Linux).    
+
+.. _gcc43.patch:            http://aur.archlinux.org/packages/ann/ann/gcc43.patch
+.. _shared-libs.patch:      http://aur.archlinux.org/packages/ann/ann/shared-libs.patch
+
+Besides ANN_, pyANN **depends** on Boost.Python_. To compile and install the
+bindings, if you have waf_ installed, run::
+
+    waf configure
+    waf build
+    waf install
+
+Otherwise, there is the original simple ``Makefile``, which you can tweak (e.g.,
+adjust paths), and then ``make`` will compile the bindings. You will have to
+manually put them somewhere on your ``PYTHONPATH``.
+
+.. _Boost.Python:           http://www.boost.org/doc/libs/1_39_0/libs/python/doc/index.html
+.. _waf:                    http://code.google.com/p/waf/
+
+
+KDTree class
+------------
+
+The main content of pyANN is the class `KDTree`. The class is initialized with a
+list of points, and provides three key methods:
+
+    :kSearch:
+    :kPriSearch:
+    :kFRSearch:
+
+Additional auxiliary methods mimick ANN's functionality:
+
+