274 lines
14 KiB
Python
274 lines
14 KiB
Python
import algorithms.dijkstra as dijkstra
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import algorithms.a_star as a_star
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import algorithms.bidirectional as bidirectional
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import dataset.generate_graph as gen_graph
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import dataset.generate_grid as gen_grid
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import time
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import tracemalloc
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import os
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import random as rand
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def do_experiments():
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graph_groups1 = ["5n"]
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graph_groups2 = ["200", "500", "1000", "2000", "5000", "10000", "20000", "50000"]
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grid_groups = ["20x20", "50x50", "100x100", "150x150", "250x250", "500x500"]
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print("Starting graph testing")
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for group1 in graph_groups1:
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dijkstra_mean_times, dijkstra_mean_memory, dijkstra_mean_errors = [], [], []
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a_star_mean_times, a_star_mean_memory, a_star_mean_errors = [], [], []
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bidirectional_mean_times, bidirectional_mean_memory, bidirectional_mean_errors = [], [], []
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print(group1)
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for group2 in graph_groups2:
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print(group2, end=", ")
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di_mean_time, di_mean_memory, di_mean_error, a_mean_time, a_mean_memory, a_mean_error, bi_mean_time, bi_mean_memory, bi_mean_error = get_measurements_graphs(group1, group2)
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dijkstra_mean_times.append(di_mean_time)
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dijkstra_mean_memory.append(di_mean_memory)
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dijkstra_mean_errors.append(di_mean_error)
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a_star_mean_times.append(a_mean_time)
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a_star_mean_memory.append(a_mean_memory)
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a_star_mean_errors.append(a_mean_error)
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bidirectional_mean_times.append(bi_mean_time)
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bidirectional_mean_memory.append(bi_mean_memory)
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bidirectional_mean_errors.append(bi_mean_error)
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print()
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write_output_table_graph(group1, graph_groups2, dijkstra_mean_times, dijkstra_mean_memory, dijkstra_mean_errors,
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a_star_mean_times, a_star_mean_memory, a_star_mean_errors, bidirectional_mean_times,
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bidirectional_mean_memory, bidirectional_mean_errors)
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# print("Starting grid testing")
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# dijkstra_mean_times, dijkstra_mean_memory, dijkstra_mean_errors = [], [], []
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# a_star_mean_times, a_star_mean_memory, a_star_mean_errors = [], [], []
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# bidirectional_mean_times, bidirectional_mean_memory, bidirectional_mean_errors = [], [], []
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# for group in grid_groups:
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# print(group, end=", ")
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# di_mean_time, di_mean_memory, di_mean_error, a_mean_time, a_mean_memory, a_mean_error, bi_mean_time, bi_mean_memory, bi_mean_error = get_measurements_grids(group)
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# dijkstra_mean_times.append(di_mean_time)
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# dijkstra_mean_memory.append(di_mean_memory)
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# dijkstra_mean_errors.append(di_mean_error)
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# a_star_mean_times.append(a_mean_time)
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# a_star_mean_memory.append(a_mean_memory)
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# a_star_mean_errors.append(a_mean_error)
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# bidirectional_mean_times.append(bi_mean_time)
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# bidirectional_mean_memory.append(bi_mean_memory)
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# bidirectional_mean_errors.append(bi_mean_error)
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# write_output_table_grid(grid_groups, dijkstra_mean_times, dijkstra_mean_memory, dijkstra_mean_errors,
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# a_star_mean_times, a_star_mean_memory, a_star_mean_errors, bidirectional_mean_times,
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# bidirectional_mean_memory, bidirectional_mean_errors)
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def get_measurements_graphs(group1, group2):
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dijkstra_time, dijkstra_memory, dijkstra_weight = [], [], []
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a_star_time, a_star_memory, a_star_weight = [], [], []
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bidirectional_time, bidirectional_memory, bidirectional_weight = [], [], []
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error_a_star, error_bi = [], []
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for i in range(1, len(os.listdir("dataset/graphs/" + group1 + "/" + group2)) + 1):
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filename = "graph" + str(i)
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N, A, A_b, w = gen_graph.read_graph_from_file(filename, path="dataset/graphs/" + group1 + "/" + group2 + "/")
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for j in range(3):
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start_node_index = rand.randint(0, len(N) - 1)
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goal_node_index = rand.randint(0, len(N) - 1)
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while goal_node_index == start_node_index:
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goal_node_index = rand.randint(0, len(N) - 1)
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start_node = None
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goal_node = None
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for index, node in enumerate(N):
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if index == goal_node_index:
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goal_node = node
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if index == start_node_index:
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start_node = node
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if start_node is not None and goal_node is not None:
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break
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startTime = time.time()
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tracemalloc.start()
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weight = dijkstra.dijkstra_algorithm(start_node, goal_node, N, A, w)[1]
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dijkstra_memory.append(tracemalloc.get_traced_memory()[1])
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dijkstra_time.append((time.time() - startTime))
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dijkstra_weight.append(weight)
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tracemalloc.stop()
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startTime = time.time()
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tracemalloc.start()
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weight = a_star.a_star_algorithm(start_node, goal_node, N, A, w, a_star.heuristic_cost)[1]
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a_star_memory.append(tracemalloc.get_traced_memory()[1])
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a_star_time.append((time.time() - startTime))
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a_star_weight.append(weight)
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tracemalloc.stop()
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startTime = time.time()
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tracemalloc.start()
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weight = bidirectional.bidirectional_algorithm(start_node, goal_node, N, A, A_b, w, a_star.heuristic_cost)[
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1]
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bidirectional_memory.append(tracemalloc.get_traced_memory()[1])
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bidirectional_time.append((time.time() - startTime))
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bidirectional_weight.append(weight)
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tracemalloc.stop()
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for i in range(len(dijkstra_weight)):
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error_a_star.append((a_star_weight[i] - dijkstra_weight[i]) / dijkstra_weight[i])
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error_bi.append((bidirectional_weight[i] - dijkstra_weight[i]) / dijkstra_weight[i])
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return sum(dijkstra_time) / len(dijkstra_time), sum(dijkstra_memory) / len(dijkstra_memory), 0.0, \
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sum(a_star_time) / len(a_star_time), sum(a_star_memory) / len(a_star_memory), sum(error_a_star) / len(error_a_star),\
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sum(bidirectional_time) / len(bidirectional_time), sum(bidirectional_memory) / len(bidirectional_memory), sum(error_bi) / len(error_bi)
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def get_measurements_grids(group):
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dijkstra_time, dijkstra_memory, dijkstra_weight = [], [], []
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a_star_time, a_star_memory, a_star_weight = [], [], []
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bidirectional_time, bidirectional_memory, bidirectional_weight = [], [], []
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error_a_star, error_bi = [], []
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for i in range(1, len(os.listdir('dataset/grids/' + group + "/")) + 1):
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filename = "grid" + str(i)
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N, A, A_b, w = gen_grid.read_grid_graph_from_file(filename, path="dataset/grids/" + group + "/")
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for j in range(3):
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start_node_index = rand.randint(0, len(N) - 1)
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goal_node_index = rand.randint(0, len(N) - 1)
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while goal_node_index == start_node_index:
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goal_node_index = rand.randint(0, len(N) - 1)
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start_node = None
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goal_node = None
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for index, node in enumerate(N):
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if index == goal_node_index:
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goal_node = node
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if index == start_node_index:
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start_node = node
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if start_node is not None and goal_node is not None:
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break
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startTime = time.time()
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tracemalloc.start()
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weight = dijkstra.dijkstra_algorithm(start_node, goal_node, N, A, w)[1]
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dijkstra_memory.append(tracemalloc.get_traced_memory()[1])
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dijkstra_time.append((time.time() - startTime))
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dijkstra_weight.append(weight)
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tracemalloc.stop()
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startTime = time.time()
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tracemalloc.start()
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weight = a_star.a_star_algorithm(start_node, goal_node, N, A, w, a_star.heuristic_cost_manhattan)[1]
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a_star_memory.append(tracemalloc.get_traced_memory()[1])
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a_star_time.append((time.time() - startTime))
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a_star_weight.append(weight)
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tracemalloc.stop()
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startTime = time.time()
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tracemalloc.start()
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weight = bidirectional.bidirectional_algorithm(start_node, goal_node, N, A, A_b, w,
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a_star.heuristic_cost_manhattan)[1]
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bidirectional_memory.append(tracemalloc.get_traced_memory()[1])
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bidirectional_time.append((time.time() - startTime))
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bidirectional_weight.append(weight)
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tracemalloc.stop()
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for i in range(len(dijkstra_weight)):
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error_a_star.append((a_star_weight[i] - dijkstra_weight[i]) / dijkstra_weight[i])
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error_bi.append((bidirectional_weight[i] - dijkstra_weight[i]) / dijkstra_weight[i])
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return sum(dijkstra_time) / len(dijkstra_time), sum(dijkstra_memory) / len(dijkstra_memory), 0.0, \
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sum(a_star_time) / len(a_star_time), sum(a_star_memory) / len(a_star_memory), sum(error_a_star) / len(error_a_star),\
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sum(bidirectional_time) / len(bidirectional_time), sum(bidirectional_memory) / len(bidirectional_memory), sum(error_bi) / len(error_bi)
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def write_output_table_graph(edges_number, nodes_number_list, dijkstra_time, dijkstra_memory, dijkstra_weight,
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a_star_time, a_star_memory, a_star_weight, bidirectional_time, bidirectional_memory,
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bidirectional_weight):
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with open("output/graphs_times_" + edges_number + ".out", "w", encoding="utf-8") as file:
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file.write("\\begin{table}[]\n")
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file.write("\\begin{tabular}{|l|l|l|l|}\n")
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file.write("\\hline\n")
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file.write("grupa & Dijkstra & A* & Bi A* \\\\ \\hline\n")
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with open("output/graphs_memory_" + edges_number + ".out", "w", encoding="utf-8") as file:
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file.write("\\begin{table}[]\n")
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file.write("\\begin{tabular}{|l|l|l|l|}\n")
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file.write("\\hline\n")
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file.write("grupa & Dijkstra & A* & Bi A* \\\\ \\hline\n")
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with open("output/graphs_errors_" + edges_number + ".out", "w", encoding="utf-8") as file:
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file.write("\\begin{table}[]\n")
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file.write("\\begin{tabular}{|l|l|l|l|}\n")
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file.write("\\hline\n")
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file.write("grupa & Dijkstra & A* & Bi A* \\\\ \\hline\n")
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with open("output/graphs_times_" + edges_number + ".out", "a", encoding="utf-8") as file:
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for j in range(len(dijkstra_time)):
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file.write(" " + nodes_number_list[j] + " & " + str(round(dijkstra_time[j], 5))
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+ " & " + str(round(a_star_time[j], 5)) + " & " + str(round(bidirectional_time[j], 5)) +
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" \\\\ \\hline\n")
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file.write("\\end{tabular}\n")
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file.write("\\end{table}\n")
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with open("output/graphs_memory_" + edges_number + ".out", "a", encoding="utf-8") as file:
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for j in range(len(dijkstra_time)):
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file.write(" " + nodes_number_list[j] + " & " + str(round(dijkstra_memory[j], 5))
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+ " & " + str(round(a_star_memory[j], 5)) + " & " + str(round(bidirectional_memory[j], 5))
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+ " \\\\ \\hline\n")
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file.write("\\end{tabular}\n")
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file.write("\\end{table}\n")
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with open("output/graphs_errors_" + edges_number + ".out", "a", encoding="utf-8") as file:
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for j in range(len(dijkstra_time)):
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file.write(" " + nodes_number_list[j] + " & " +
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str(round(dijkstra_weight[j], 5)) + " & " + str(round(a_star_weight[j], 5)) + " & " +
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str(round(bidirectional_weight[j], 5)) + " \\\\ \\hline\n")
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file.write("\\end{tabular}\n")
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file.write("\\end{table}\n")
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def write_output_table_grid(group, dijkstra_time, dijkstra_memory, dijkstra_weight, a_star_time, a_star_memory,
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a_star_weight, bidirectional_time, bidirectional_memory, bidirectional_weight):
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with open("output/grids_times.out", "w", encoding="utf-8") as file:
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file.write("\\begin{table}[]\n")
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file.write("\\begin{tabular}{|l|l|l|l|}\n")
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file.write("\\hline\n")
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file.write("grupa & Dijkstra & A* & Bi A* \\\\ \\hline\n")
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with open("output/grids_memory.out", "w", encoding="utf-8") as file:
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file.write("\\begin{table}[]\n")
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file.write("\\begin{tabular}{|l|l|l|l|}\n")
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file.write("\\hline\n")
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file.write("grupa & Dijkstra & A* & Bi A* \\\\ \\hline\n")
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with open("output/grids_weights.out", "w", encoding="utf-8") as file:
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file.write("\\begin{table}[]\n")
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file.write("\\begin{tabular}{|l|l|l|l|}\n")
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file.write("\\hline\n")
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file.write("grupa & Dijkstra & A* & Bi A* \\\\ \\hline\n")
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with open("output/grids_times.out", "a", encoding="utf-8") as file:
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for j in range(len(dijkstra_time)):
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file.write(
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" " + group[j] + " & "
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+ str(round(dijkstra_time[j], 5))
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+ " & " + str(round(a_star_time[j], 5)) + " & " + str(round(bidirectional_time[j], 5)) +
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" \\\\ \\hline\n")
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file.write("\\end{tabular}\n")
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file.write("\\end{table}\n")
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with open("output/grids_memory.out", "a", encoding="utf-8") as file:
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for j in range(len(dijkstra_time)):
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file.write(" " + group[j] + " & " + str(round(dijkstra_memory[j], 5))
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+ " & " + str(round(a_star_memory[j], 5)) + " & " + str(round(bidirectional_memory[j], 5))
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+" \\\\ \\hline\n")
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file.write("\\end{tabular}\n")
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file.write("\\end{table}\n")
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with open("output/grids_weights.out", "a", encoding="utf-8") as file:
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for j in range(len(dijkstra_time)):
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file.write(" " + group[j] + " & " +
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str(round(dijkstra_weight[j], 5)) + " & " + str(round(a_star_weight[j], 5)) + " & " +
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str(round(bidirectional_weight[j], 5)) + " \\\\ \\hline\n")
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file.write("\\end{tabular}\n")
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file.write("\\end{table}\n")
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if __name__ == '__main__':
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do_experiments()
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