def plot_performance_metrics(self): algo_performance = dict() env = Environment(n = 20, p = self.probability_of_obstacles, fire = self.fire) # env.generate_maze() # env.create_graph_from_maze() for n in np.arange(10, 100, 10): print(n) for algo in ["astar"]: for heuristic in ["euclid", "manhattan"]: print(algo, heuristic) if (algo + "_" + heuristic) not in algo_performance: algo_performance[(algo + "_" + heuristic)] = dict() if algo not in algo_performance: algo_performance[algo] = dict() env.algorithm = algo env.create_graph_from_maze() path_finder = PathFinderAlgorithm(environment = env, algorithm = algo, visual = self.visual, heuristic = self.heuristic) path_finder.run_path_finder_algorithm() performances = path_finder.performance_dict if "path_length" not in algo_performance[(algo + "_" + heuristic)]: algo_performance[(algo + "_" + heuristic)]["path_length"] = [] if "maximum_fringe_size" not in algo_performance[(algo + "_" + heuristic)]: algo_performance[(algo + "_" + heuristic)]["maximum_fringe_size"] = [] if "number_of_nodes_expanded" not in algo_performance[(algo + "_" + heuristic)]: algo_performance[(algo + "_" + heuristic)]["number_of_nodes_expanded"] = [] algo_performance[(algo + "_" + heuristic)]['path_length'].append(performances['path_length']) algo_performance[(algo + "_" + heuristic)]['maximum_fringe_size'].append(performances['maximum_fringe_size']) algo_performance[(algo + "_" + heuristic)]['number_of_nodes_expanded'].append(performances['number_of_nodes_expanded']) for algo in ["astar", "thin_astar"]: for heuristic in ["euclid", "manhattan"]: print(algo, heuristic) if (algo + "_" + heuristic) not in algo_performance: algo_performance[(algo + "_" + heuristic)] = dict() env.algorithm = algo path_finder = PathFinderAlgorithm(environment = env, algorithm = algo, q = q, visual = self.visual, heuristic = heuristic) path_finder.run_path_finder_algorithm() performances = path_finder.performance_dict if "path_length" not in algo_performance[(algo + "_" + heuristic)]: algo_performance[(algo + "_" + heuristic)]["path_length"] = [] if "maximum_fringe_size" not in algo_performance[(algo + "_" + heuristic)]: algo_performance[(algo + "_" + heuristic)]["maximum_fringe_size"] = [] if "number_of_nodes_expanded" not in algo_performance[(algo + "_" + heuristic)]: algo_performance[(algo + "_" + heuristic)]["number_of_nodes_expanded"] = [] algo_performance[(algo + "_" + heuristic)]['path_length'].append(performances['path_length']) algo_performance[(algo + "_" + heuristic)]['maximum_fringe_size'].append(performances['maximum_fringe_size']) algo_performance[(algo + "_" + heuristic)]['number_of_nodes_expanded'].append(performances['number_of_nodes_expanded']) return algo_performance
class MazeRunner():
def __init__(self, maze_dimension, probability_of_obstacles, algorithm, visual, heuristic, fire):
self.algorithm = algorithm
self.maze_dimension = maze_dimension
self.probability_of_obstacles = probability_of_obstacles
self.visual = visual
self.heuristic = heuristic
self.fire = fire
def create_environment(self, new_maze = None):
# Create the maze
self.env = Environment(algorithm = self.algorithm, n = self.maze_dimension, p = self.probability_of_obstacles, fire = self.fire)
self.env.generate_maze(new_maze = new_maze)
# Generate graph from the maze
self.env.create_graph_from_maze()
def run(self):
# Run the path finding algorithm on the graph
self.path_finder = PathFinderAlgorithm(environment = self.env,
algorithm = self.algorithm,
visual = self.visual,
heuristic = self.heuristic)
self.path_finder.run_path_finder_algorithm()
def find_solvable_map_size(self):
dim_list = range(10, 250, 10)
runtimes = dict()
for dim in dim_list:
print("Dim = " + str(dim))
self.maze_dimension = dim
self.create_environment()
start = time()
self.run()
end = time() - start
print(end)
runtimes[dim] = end
del self.path_finder
plt.plot(dim_list, runtimes.values(), marker = "o")
plt.figure()
plt.show()
def plot_performance_metrics(self):
algo_performance = dict()
env = Environment(n = 20,
p = self.probability_of_obstacles,
fire = self.fire)
# env.generate_maze()
# env.create_graph_from_maze()
for n in np.arange(10, 100, 10):
print(n)
for algo in ["astar"]:
for heuristic in ["euclid", "manhattan"]:
print(algo, heuristic)
if (algo + "_" + heuristic) not in algo_performance:
algo_performance[(algo + "_" + heuristic)] = dict()
if algo not in algo_performance:
algo_performance[algo] = dict()
env.algorithm = algo
env.create_graph_from_maze()
path_finder = PathFinderAlgorithm(environment = env,
algorithm = algo,
visual = self.visual,
heuristic = self.heuristic)
path_finder.run_path_finder_algorithm()
performances = path_finder.performance_dict
if "path_length" not in algo_performance[(algo + "_" + heuristic)]:
algo_performance[(algo + "_" + heuristic)]["path_length"] = []
if "maximum_fringe_size" not in algo_performance[(algo + "_" + heuristic)]:
algo_performance[(algo + "_" + heuristic)]["maximum_fringe_size"] = []
if "number_of_nodes_expanded" not in algo_performance[(algo + "_" + heuristic)]:
algo_performance[(algo + "_" + heuristic)]["number_of_nodes_expanded"] = []
algo_performance[(algo + "_" + heuristic)]['path_length'].append(performances['path_length'])
algo_performance[(algo + "_" + heuristic)]['maximum_fringe_size'].append(performances['maximum_fringe_size'])
algo_performance[(algo + "_" + heuristic)]['number_of_nodes_expanded'].append(performances['number_of_nodes_expanded'])
for algo in ["astar", "thin_astar"]:
for heuristic in ["euclid", "manhattan"]:
print(algo, heuristic)
if (algo + "_" + heuristic) not in algo_performance:
algo_performance[(algo + "_" + heuristic)] = dict()
env.algorithm = algo
path_finder = PathFinderAlgorithm(environment = env,
algorithm = algo,
q = q,
visual = self.visual,
heuristic = heuristic)
path_finder.run_path_finder_algorithm()
performances = path_finder.performance_dict
if "path_length" not in algo_performance[(algo + "_" + heuristic)]:
algo_performance[(algo + "_" + heuristic)]["path_length"] = []
if "maximum_fringe_size" not in algo_performance[(algo + "_" + heuristic)]:
algo_performance[(algo + "_" + heuristic)]["maximum_fringe_size"] = []
if "number_of_nodes_expanded" not in algo_performance[(algo + "_" + heuristic)]:
algo_performance[(algo + "_" + heuristic)]["number_of_nodes_expanded"] = []
algo_performance[(algo + "_" + heuristic)]['path_length'].append(performances['path_length'])
algo_performance[(algo + "_" + heuristic)]['maximum_fringe_size'].append(performances['maximum_fringe_size'])
algo_performance[(algo + "_" + heuristic)]['number_of_nodes_expanded'].append(performances['number_of_nodes_expanded'])
return algo_performance
