working release

.gitignore

@@ -3,4 +3,7 @@ env/
 .ipynb_checkpoints/
 .idea/
 dist/
-MANIFEST
+MANIFEST
+build/
+test.py
+space_time_astar.egg-info/

setup.py

@@ -1,21 +1,18 @@
-from distutils.core import setup
+import setuptools
 
 # read the contents of your README file
-from os import path
-this_directory = path.abspath(path.dirname(__file__))
-with open(path.join(this_directory, 'README.md'), encoding='utf-8') as f:
-    long_description = f.read()
+with open("README.md", "r") as fh:
+    long_description = fh.read()
 
-setup(
+setuptools.setup(
   name = 'space-time-astar',         # How you named your package folder (MyLib)
-  packages = ['stastar'],   # Chose the same as "name"
-  version = '0.2',      # Start with a small number and increase it with every change you make
+  packages=setuptools.find_packages(),
+  version = '0.3.4',      # Start with a small number and increase it with every change you make
   license='MIT',        # Chose a license from here: https://help.github.com/articles/licensing-a-repository
   description = 'A* search algorithm with an added time dimension to deal with dynamic obstacles.',   # Give a short description about your library
   author = 'Haoran Peng',                   # Type in your name
   author_email = '[email protected]',      # Type in your E-Mail
   url = 'https://github.com/GavinPHR/Space-Time-AStar',   # Provide either the link to your github or to your website
-  download_url = 'https://github.com/GavinPHR/Space-Time-AStar/archive/v0.1-alpha.tar.gz',    # I explain this later on
   keywords = ['astar-algorithm', 'obstacle-avoidance', 'time-dimension'],   # Keywords that define your package best
   install_requires=[            # I get to this in a second
           'numpy',
@@ -26,14 +23,12 @@
     'Intended Audience :: Developers',      # Define that your audience are developers
     'Topic :: Software Development :: Build Tools',
     'License :: OSI Approved :: MIT License',   # Again, pick a license
-    'Programming Language :: Python :: 3',      #Specify which pyhton versions that you want to support
-    'Programming Language :: Python :: 3.4',
-    'Programming Language :: Python :: 3.5',
-    'Programming Language :: Python :: 3.6',
-    'Programming Language :: Python :: 3.7',
   ],
+  python_requires='>=3.5',
   long_description=long_description,
   long_description_content_type='text/markdown'
 )
 
+# python3 setup.py sdist bdist_wheel
+# twine upload dist/*
 # Tutorial at https://medium.com/@joel.barmettler/how-to-upload-your-python-package-to-pypi-65edc5fe9c56

stastar/__init__.py

@@ -1 +1,9 @@
-from space-time-astar.planner import Planner
+#!/usr/bin/env python3
+'''
+Author: Haoran Peng
+Email: [email protected]
+'''
+from . import planner
+from . import neighbour_table
+from . import grid
+from . import state

stastar/planner.py

@@ -8,9 +8,9 @@
 import numpy as np
 from scipy.spatial import KDTree
 
-from neighbour_table import NeighbourTable
-from grid import Grid
-from state import State
+from .neighbour_table import NeighbourTable
+from .grid import Grid
+from .state import State
 
 
 # static obstacles must include the boundary
@@ -120,12 +120,4 @@ def reconstruct_path(self, came_from: Dict[State, State], current: State) -> np.
         return np.array(total_path[::-1])
 
 
-if __name__ == '__main__':
-    grid_size = 1
-    robot_radius = 2
-    start = (2, 2)
-    goal = (50, 50)
-    static_obstacles = [(0, 0), (60, 70)]
-    dynamic_obstacles = {0: [(5, 16)], 1: [(5, 17)], 2: [(5, 18), (11, 20)]}
-    planner = Planner(grid_size, robot_radius, start, goal, static_obstacles, dynamic_obstacles)
-    print(planner.plan())
+