def __init__(self, src, dst, city, dimension, adjacency_list, heuristic_matrices):
self.__src = src
self.__dst = dst
self.__city = city
self.__open_list = []
self.__closed_list = []
self.__dimension = self.__dimension_index(dimension)
self.__org_node = LoadData.load_org_node(city)
self.__org_path = LoadData.load_org_path(city, 6)
self.__link_table = adjacency_list
self.__heuristic = heuristic_matrices
# self.__heuristic = self.__calculate_heuristic()
self.__dimension_cost, self.__heuristic_cost, self.__total_cost = ({} for _ in range(3))
self.__dimension_cost = {node: float("inf") for node in self.__org_node.keys()}
self.__dimension_cost[self.__src] = 0
self.__heuristic_cost[self.__src] = self.__heuristic.loc[self.__src, self.__dst]
self.__total_cost[self.__src] = \
self.__heuristic_cost[self.__src] + self.__heuristic_cost[self.__src]
self.__previous_node = {self.__src: None}
heapq.heappush(self.__open_list, (self.__total_cost[self.__src], self.__src))
def calculate_heuristic(city):
"""
計算 heuristic matrices
:param city:
:return:
"""
org_node = LoadData.load_org_node(city)
data = np.array(list(org_node.values()))
result = euclidean_distances(data, data)
header = [x for x in list(org_node.keys())]
pd_data = pd.DataFrame(result, columns=header)
# print(pd_data.shape)
return pd_data
def __init__(self, src, dst, dtype, location, dimension):
self.src = int(src)
self.dst = int(dst)
self.org_node = LoadData.load_org_node(location)
self.org_path = LoadData.load_org_path(location, dimension)
self.link_table = LoadData.load_linking_table(location)
# print('org_node', self.org_node)
# print('org_path', self.org_path)
# print('self.link_table', self.link_table)
self.heap = Heap(dtype)
self.quadrant = self.__get_quadrant(self.src, self.dst)
if __name__ == '__main__':
# 基本設定
"""
# 基本設定
# Dimension: 目前執行的實驗有多少維度
# city: 城市名稱(Oldenburg, California, North America)
1. 要改地點(city)和維度名稱(dimension)
2. 資料數量的分配情況
"""
# 載入路網節點
city = 'Oldenburg'
node = list(LoadData.load_org_node(city).keys())
heuristic_matrices = calculate_heuristic(city)
print('終點數量', len(node))
# 要重新收集的最段路徑維度資料(要修改)
# file_name = ['NotFoundNode(Distance)', 'NotFoundNode(Time)',
# 'NotFoundNode(Dimension3)', 'NotFoundNode(Dimension4)',
# 'NotFoundNode(Dimension5)', 'NotFoundNode(Dimension6)']
"""
# 基本設定
dimension = [Distance, TIme, Dimension3, Dimension4, Dimension5, Dimension6]
dimension 需要改
"""
dimension = "Time"
file_name = 'data/Oldenburg/NotFoundNode/NotFoundNode(' + dimension + ').txt'
