Add README.md to package manifest ; update setup.py to reflect best p…

…ackaging know-how to date.

MANIFEST.in

@@ -0,0 +1 @@
+include README.md

README.rst → README.md

@@ -1,3 +1,5 @@
+# py-kohonen
+
 This module contains some basic implementations of Kohonen-style vector
 quantizers: Self-Organizing Map (SOM), Neural Gas, and Growing Neural Gas.
 Kohonen-style vector quantizers use some sort of explicitly specified topology
@@ -9,8 +11,8 @@ distribution. This process is also generally known as density estimation.
 
 The source distribution includes an interactive test module that uses PyGTK and
 Cairo to render a set of quantizers that move around in real time as samples are
-drawn from a known distribution and fed to the quantizers. Run this test with ::
+drawn from a known distribution and fed to the quantizers. Run this test with :
 
-  python kohonen_test.py
+    python kohonen_test.py
 
 Have fun !

setup.py

@@ -1,23 +1,24 @@
+import os
 import setuptools
 
 setuptools.setup(
     name='lmj.kohonen',
-    version='1.1.1',
-    install_requires=['numpy'],
+    version='1.1.2',
     namespace_packages=['lmj'],
-    py_modules=['lmj.kohonen'],
+    packages=setuptools.find_packages(),
     author='Leif Johnson',
     author_email='leif@leifjohnson.net',
-    description='A small library of Kohonen-style vector quantizers.',
-    long_description=open('README.rst').read(),
+    description='A library of vector quantizers',
+    long_description=open(os.path.join(os.path.dirname(os.path.abspath(__file__)), 'README.md')).read(),
     license='MIT',
+    url='http://github.com/lmjohns3/py-kohonen',
     keywords=('kohonen '
               'self-organizing-map '
               'neural-gas '
               'growing-neural-gas '
               'vector-quantization '
               'machine-learning'),
-    url='http://github.com/lmjohns3/py-kohonen',
+    install_requires=['numpy'],
     classifiers=[
         'Development Status :: 5 - Production/Stable',
         'Intended Audience :: Science/Research',