def setUpSearch(cls):
     search = Expando()
     search.maze = [[1, 1, 1, 1], [1, 1, 1, 1], [1, 1, 1, 1], [1, 1, 1, 1]]
     search.totalNodes = 16
     search.startPosition = (0, 0)
     search.endPosition = (1, 3)
     search.astar = AStar(heuristicFunction)
     search.pathMap = search.astar.findPath(search.maze,
                                            search.startPosition,
                                            search.endPosition)
     search.path = search.astar.pathToNode(search.pathMap,
                                           search.endPosition)
     cls.search = search
Example #2
0
 def setUpSearch(cls):
     search = Expando()
     search.maze = [[1, 1, 1, 1, 1], [1, 0, 1, 0, 1], [1, 1, 0, 1, 1],
                    [0, 1, 0, 1, 0], [1, 1, 1, 1, 1]]
     search.totalNodes = 20
     search.startPosition = (0, 0)
     search.endPosition = (4, 4)
     search.astar = AStar()
     search.pathMap = search.astar.findPath(search.maze,
                                            search.startPosition,
                                            search.endPosition)
     search.path = search.astar.pathToNode(search.pathMap,
                                           search.endPosition)
     cls.search = search
Example #3
0
from astar.AStar import AStar
from astar.HeuristicFunctions import manhattan as heuristicFunction
from my_logger import astar_logger as logger

# import logging
# logger.setLevel(logging.DEBUG)

maze = [[1, 1, 1, 1, 1], [1, 0, 0, 0, 1], [1, 1, 0, 1, 1], [1, 0, 0, 0, 1],
        [6, 1, 1, 1, 1]]
startPosition = (0, 2)
endPosition = (4, 4)

# Dijkstra
dijkstra = AStar()
searchMap = dijkstra.findPath(maze, startPosition, endPosition)
shortestPath = dijkstra.pathToNode(searchMap, endPosition)

# logger.info(f"{searchMap}")
logger.info(f"{shortestPath}")

# Astar
astar = AStar(heuristicFunction)
searchMap = astar.findPath(maze, startPosition, endPosition)
shortestPath = astar.pathToNode(searchMap, endPosition)

# logger.info(f"{searchMap}")
logger.info(f"{shortestPath}")