forked from s434673/AI_Waiter
Zaktualizuj 'src/waiter.py'
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4e763004f6
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1ee56bf721
102
src/waiter.py
102
src/waiter.py
@ -55,23 +55,30 @@ class Waiter(pygame.sprite.Sprite):
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# AStar
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def findPath(self, goal):
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#Stworzenie startowego i koncowego wierzcholka
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startNode = self.matrix.matrix[self.X][self.Y]
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goalNode = self.matrix.matrix[goal[5]][goal[7]]
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#Inicjalizacja list
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# Stworzenie startowego i koncowego wierzcholka
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startNode = self.matrix.matrix[self.X][self.Y]
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goalNode = self.matrix.matrix[goal[0]][goal[1]]
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# Inicjalizacja list
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openList = []
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closedList = []
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openList.append(startNode)
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parentNode = startNode
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while len(openList) > 0:
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openList.sort(key=self.tile.totalCost)
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openList.sort(key=getTotalCost)
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currentNode = openList.pop(0)
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if currentNode != parentNode:
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currentNode.parent = parentNode
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parentNode = currentNode
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closedList.append(currentNode)
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#Tutaj odbywac sie bedzie budowanie sciezki gdy algorytm osiagnie cel
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# Tutaj odbywac sie bedzie budowanie sciezki gdy algorytm osiagnie cel
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if currentNode == goalNode:
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path = []
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current = currentNode
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@ -81,52 +88,71 @@ class Waiter(pygame.sprite.Sprite):
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return path[::-1]
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children = []
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if currentNode.X >= 0:
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if currentNode.Y + 1 < len(self.matrix.matrix[0]):
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if self.matrix.matrix[currentNode.X][currentNode.Y + 1].walk_through == 1:
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children.append(self.matrix.matrix[currentNode.X][currentNode.Y + 1])
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if currentNode.Y - 1 >= 0:
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if self.matrix.matrix[currentNode.X][currentNode.Y - 1].walk_through == 1:
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children.append(self.matrix.matrix[currentNode.X][currentNode.Y - 1])
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if currentNode.X + 1 < len(self.matrix.matrix):
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if currentNode.Y + 1 < len(self.matrix.matrix[0]):
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if self.matrix.matrix[currentNode.X + 1][currentNode.Y + 1].walk_through == 1:
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children.append(self.matrix.matrix[currentNode.X + 1][currentNode.Y + 1])
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if currentNode.Y - 1 >= 0:
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if self.matrix.matrix[currentNode.X + 1][currentNode.Y - 1].walk_through == 1:
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children.append(self.matrix.matrix[currentNode.X + 1][currentNode.Y - 1])
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if currentNode.Y >= 0:
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if self.matrix.matrix[currentNode.X + 1][currentNode.Y].walk_through == 1:
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children.append(self.matrix.matrix[currentNode.X + 1][currentNode.Y])
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if currentNode.position[0] >= 0:
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if currentNode.position[1] + 1 < len(self.matrix.matrix[0]):
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if self.matrix.matrix[currentNode.position[0]][currentNode.position[1] + 1].walk_through == 1:
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children.append(
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self.matrix.matrix[currentNode.position[0]][currentNode.position[1] + 1])
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if currentNode.position[1] - 1 >= 0:
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if self.matrix.matrix[currentNode.position[0]][currentNode.position[1] - 1].walk_through == 1:
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children.append(
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self.matrix.matrix[currentNode.position[0]][currentNode.position[1] - 1])
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if currentNode.X - 1 >= 0:
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if currentNode.Y + 1 < len(self.matrix.matrix[0]):
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if self.matrix.matrix[currentNode.X - 1][currentNode.Y + 1].walk_through == 1:
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children.append(self.matrix.matrix[currentNode.X - 1][currentNode.Y + 1])
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if currentNode.Y - 1 >= 0:
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if self.matrix.matrix[currentNode.X - 1][currentNode.Y - 1].walk_through == 1:
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children.append(self.matrix.matrix[currentNode.X - 1][currentNode.Y - 1])
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if currentNode.Y >= 0:
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if self.matrix.matrix[currentNode.X - 1][currentNode.Y].walk_through == 1:
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children.append(self.matrix.matrix[currentNode.X - 1][currentNode.Y])
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if currentNode.position[0] + 1 < len(self.matrix.matrix):
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if currentNode.position[1] + 1 < len(self.matrix.matrix[0]):
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if self.matrix.matrix[currentNode.position[0] + 1][currentNode.position[1] + 1].walk_through == 1:
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children.append(
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self.matrix.matrix[currentNode.position[0] + 1][currentNode.position[1] + 1])
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if currentNode.position[1] - 1 >= 0:
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if self.matrix.matrix[currentNode.position[0] + 1][currentNode.position[1] - 1].walk_through == 1:
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children.append(
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self.matrix.matrix[currentNode.position[0] + 1][currentNode.position[1] - 1])
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if currentNode.position[1] >= 0:
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if self.matrix.matrix[currentNode.position[0] + 1][currentNode.position[1]].walk_through == 1:
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children.append(
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self.matrix.matrix[currentNode.position[0] + 1][currentNode.position[1]])
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if currentNode.position[0] - 1 >= 0:
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if currentNode.position[1] + 1 < len(self.matrix.matrix[0]):
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if self.matrix.matrix[currentNode.position[0] - 1][currentNode.position[1] + 1].walk_through == 1:
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children.append(
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self.matrix.matrix[currentNode.position[0] - 1][currentNode.position[1] + 1])
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if currentNode.position[1] - 1 >= 0:
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if self.matrix.matrix[currentNode.position[0] - 1][currentNode.position[1] - 1].walk_through == 1:
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children.append(
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self.matrix.matrix[currentNode.position[0] - 1][currentNode.position[1] - 1])
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if currentNode.position[1] >= 0:
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if self.matrix.matrix[currentNode.position[0] - 1][currentNode.position[1]].walk_through == 1:
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children.append(
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self.matrix.matrix[currentNode.position[0] - 1][currentNode.position[1]])
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perm = 0
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for child in children:
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for closedChild in closedList:
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if child == closedChild:
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perm = 1
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continue
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if perm == 1:
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perm = 0
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continue
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child.startCost = currentNode.startCost + 1
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child.heuristic = ((child.position[0] - goalNode.position[0]) ** 2) + ((child.position[1] - goalNode.position[1]) ** 2)
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child.heuristic = ((child.position[0] - goalNode.position[0]) ** 2) + (
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(child.position[1] - goalNode.position[1]) ** 2)
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child.totalCost = child.startCost + child.heuristic
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for openNode in openList:
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if child == openNode and child.startCost > openNode.startCost:
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if child == openNode and child.startCost >= openNode.startCost:
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perm = 1
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continue
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if perm == 1:
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perm = 0
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continue
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openList.append(child)
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def getTotalCost(tile):
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return tile.totalCost
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