update repo for packaging

.travis.yml

@@ -2,14 +2,14 @@ language: python
 
 python:
   - "2.7"
-  - "3.5"
+  - "3.6"
 
 install:
   - pip install codecov
   - pip install -r requirements.txt
 
 script:
-  - coverage run test_entropy.py
+  - coverage run tests/test_entropy.py
 
 after_success:
   - codecov

README.md

@@ -3,7 +3,7 @@
 [![Build Status](https://travis-ci.org/nikdon/pyEntropy.svg?branch=master)](https://travis-ci.org/nikdon/pyEntropy)
 [![codecov](https://codecov.io/gh/nikdon/pyEntropy/branch/master/graph/badge.svg)](https://codecov.io/gh/nikdon/pyEntropy)
 ![py27 status](https://img.shields.io/badge/python2.7-supported-green.svg)
-![py35 status](https://img.shields.io/badge/python3.5.2-supported-green.svg)
+![py36 status](https://img.shields.io/badge/python3.6.1-supported-green.svg)
 
 This is a small set of functions on top of NumPy that help to compute different types of entropy for time series analysis.
 

requirements.txt

@@ -1 +1 @@
-numpy>=1.9.0
+numpy>=1.7.0

setup.cfg

@@ -0,0 +1,8 @@
+[bdist_wheel]
+# This flag says that the code is written to work on both Python 2 and Python
+# 3. If at all possible, it is good practice to do this. If you cannot, you
+# will need to generate wheels for each Python version that you support.
+universal=1
+
+[metadata]
+description-file = README.md

setup.py

@@ -0,0 +1,40 @@
+from distutils.core import setup
+
+setup(
+    name='pyentrp',
+    version='0.1.0',
+    description='Functions on top of NumPy for computing different types of entropy',
+    long_description=open("README.md").read(),
+    url='https://github.com/nikdon/pyEntropy',
+    download_url='github.com/nikdon/pyEntropy/tarball/0.1.0.tar.gz',
+    author='Nikolay Donets',
+    author_email='nd.startup@gmail.com',
+    maintainer='Nikolay Donets',
+    maintainer_email='nd.startup@gmail.com',
+    license='Apache-2.0',
+    packages=['pyentrp'],
+
+    install_requires=[
+        'numpy>=1.7.0 ',
+    ],
+    test_suite="tests.test_entropy",
+
+    keywords=['entropy', 'python', 'sample entropy', 'multiscale entropy', 'permutation entropy',
+              'composite multiscale entropy'],
+
+    classifiers=[
+        'Environment :: Console',
+        'Intended Audience :: Science/Research',
+        'Operating System :: OS Independent',
+        'Programming Language :: Python :: 2',
+        'Programming Language :: Python :: 2.7',
+        'Programming Language :: Python :: 3',
+        'Programming Language :: Python :: 3.3',
+        'Programming Language :: Python :: 3.4',
+        'Programming Language :: Python :: 3.5',
+        'Programming Language :: Python :: 3.6',
+        'Topic :: Scientific/Engineering :: Bio-Informatics',
+        'Topic :: Scientific/Engineering :: Information Analysis',
+        'Topic :: Scientific/Engineering :: Mathematics',
+    ],
+)

test_entropy.py → tests/test_entropy.py

@@ -2,10 +2,10 @@
 
 from __future__ import unicode_literals
 
+import numpy as np
 import unittest
 
-import numpy as np
-import entropy as ent
+from pyentrp import entropy as ent
 
 TIME_SERIES = [1, 1, 1, 2, 3, 4, 5]
 TIME_SERIES_STRING = '1112345'