praca_magisterska/main.py

import algorithms.dijkstra as dijkstra
import algorithms.a_star as a_star
import algorithms.bidirectional as bidirectional
import dataset.generate_graph as gen_graph
import dataset.generate_grid as gen_grid
import time
import tracemalloc
import os
import random as rand


def do_experiments():

    graph_groups1 = ["2n", "5n"]
    graph_groups2 = ["200", "500", "1000", "2000", "5000", "10000"]
    grid_groups = ["20x20", "50x50", "100x100", "150x150", "250x250", "500x500"]

    print("Starting graph testing")
    for group1 in graph_groups1:
        dijkstra_mean_times, dijkstra_mean_memory, dijkstra_mean_errors = [], [], []
        a_star_mean_times, a_star_mean_memory, a_star_mean_errors = [], [], []
        bidirectional_mean_times, bidirectional_mean_memory, bidirectional_mean_errors = [], [], []
        print(group1)

        for group2 in graph_groups2:
            print(group2,)
            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)
            dijkstra_mean_times.append(di_mean_time)
            dijkstra_mean_memory.append(di_mean_memory)
            dijkstra_mean_errors.append(di_mean_error)
            a_star_mean_times.append(a_mean_time)
            a_star_mean_memory.append(a_mean_memory)
            a_star_mean_errors.append(a_mean_error)
            bidirectional_mean_times.append(bi_mean_time)
            bidirectional_mean_memory.append(bi_mean_memory)
            bidirectional_mean_errors.append(bi_mean_error)
        print()
        write_output_table_graph(group1, graph_groups2, dijkstra_mean_times, dijkstra_mean_memory, dijkstra_mean_errors,
                                 a_star_mean_times, a_star_mean_memory, a_star_mean_errors, bidirectional_mean_times,
                                 bidirectional_mean_memory, bidirectional_mean_errors)

    print("Starting grid testing")
    dijkstra_mean_times, dijkstra_mean_memory, dijkstra_mean_errors = [], [], []
    a_star_mean_times, a_star_mean_memory, a_star_mean_errors = [], [], []
    bidirectional_mean_times, bidirectional_mean_memory, bidirectional_mean_errors = [], [], []
    for group in grid_groups:
        print(group, end=", ")
        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)
        dijkstra_mean_times.append(di_mean_time)
        dijkstra_mean_memory.append(di_mean_memory)
        dijkstra_mean_errors.append(di_mean_error)
        a_star_mean_times.append(a_mean_time)
        a_star_mean_memory.append(a_mean_memory)
        a_star_mean_errors.append(a_mean_error)
        bidirectional_mean_times.append(bi_mean_time)
        bidirectional_mean_memory.append(bi_mean_memory)
        bidirectional_mean_errors.append(bi_mean_error)
    write_output_table_grid(grid_groups, dijkstra_mean_times, dijkstra_mean_memory, dijkstra_mean_errors,
                             a_star_mean_times, a_star_mean_memory, a_star_mean_errors, bidirectional_mean_times,
                             bidirectional_mean_memory, bidirectional_mean_errors)


def get_measurements_graphs(group1, group2):
    dijkstra_time, dijkstra_memory, dijkstra_weight = [], [], []
    a_star_time, a_star_memory, a_star_weight = [], [], []
    bidirectional_time, bidirectional_memory, bidirectional_weight = [], [], []
    error_a_star, error_bi = [], []

    for i in range(1, len(os.listdir("dataset/graphs/" + group1 + "/" + group2)) + 1):
        filename = "graph" + str(i)
        print(filename)
        N, A, A_b, w = gen_graph.read_graph_from_file(filename, path="dataset/graphs/" + group1 + "/" + group2 + "/")
        for j in range(3):
            start_node_index = rand.randint(0, len(N) - 1)
            goal_node_index = rand.randint(0, len(N) - 1)
            while goal_node_index == start_node_index:
                goal_node_index = rand.randint(0, len(N) - 1)
            start_node = None
            goal_node = None
            for index, node in enumerate(N):
                if index == goal_node_index:
                    goal_node = node
                if index == start_node_index:
                    start_node = node
                if start_node is not None and goal_node is not None:
                    break

            startTime = time.time()
            tracemalloc.start()
            weight = dijkstra.dijkstra_algorithm(start_node, goal_node, N, A, w)[1]
            dijkstra_memory.append(tracemalloc.get_traced_memory()[1])
            dijkstra_time.append((time.time() - startTime))
            dijkstra_weight.append(weight)
            tracemalloc.stop()

            startTime = time.time()
            tracemalloc.start()
            weight = a_star.a_star_algorithm(start_node, goal_node, N, A, w, a_star.heuristic_cost)[1]
            a_star_memory.append(tracemalloc.get_traced_memory()[1])
            a_star_time.append((time.time() - startTime))
            a_star_weight.append(weight)
            tracemalloc.stop()

            startTime = time.time()
            tracemalloc.start()
            weight = bidirectional.bidirectional_algorithm(start_node, goal_node, N, A, A_b, w, a_star.heuristic_cost)[
                1]
            bidirectional_memory.append(tracemalloc.get_traced_memory()[1])
            bidirectional_time.append((time.time() - startTime))
            bidirectional_weight.append(weight)
            tracemalloc.stop()

    for i in range(len(dijkstra_weight)):
        error_a_star.append((a_star_weight[i] - dijkstra_weight[i]) / dijkstra_weight[i])
        error_bi.append((bidirectional_weight[i] - dijkstra_weight[i]) / dijkstra_weight[i])

    return sum(dijkstra_time) / len(dijkstra_time), sum(dijkstra_memory) / len(dijkstra_memory), 0.0, \
           sum(a_star_time) / len(a_star_time), sum(a_star_memory) / len(a_star_memory), sum(error_a_star) / len(error_a_star),\
           sum(bidirectional_time) / len(bidirectional_time), sum(bidirectional_memory) / len(bidirectional_memory), sum(error_bi) / len(error_bi)


def get_measurements_grids(group):
    dijkstra_time, dijkstra_memory, dijkstra_weight = [], [], []
    a_star_time, a_star_memory, a_star_weight = [], [], []
    bidirectional_time, bidirectional_memory, bidirectional_weight = [], [], []
    error_a_star, error_bi = [], []

    for i in range(1, len(os.listdir('dataset/grids/' + group + "/")) + 1):
        filename = "grid" + str(i)
        N, A, A_b, w = gen_grid.read_grid_graph_from_file(filename, path="dataset/grids/" + group + "/")
        for j in range(3):
            start_node_index = rand.randint(0, len(N) - 1)
            goal_node_index = rand.randint(0, len(N) - 1)
            while goal_node_index == start_node_index:
                goal_node_index = rand.randint(0, len(N) - 1)
            start_node = None
            goal_node = None
            for index, node in enumerate(N):
                if index == goal_node_index:
                    goal_node = node
                if index == start_node_index:
                    start_node = node
                if start_node is not None and goal_node is not None:
                    break
            startTime = time.time()
            tracemalloc.start()
            weight = dijkstra.dijkstra_algorithm(start_node, goal_node, N, A, w)[1]
            dijkstra_memory.append(tracemalloc.get_traced_memory()[1])
            dijkstra_time.append((time.time() - startTime))
            dijkstra_weight.append(weight)
            tracemalloc.stop()

            startTime = time.time()
            tracemalloc.start()
            weight = a_star.a_star_algorithm(start_node, goal_node, N, A, w, a_star.heuristic_cost_manhattan)[1]
            a_star_memory.append(tracemalloc.get_traced_memory()[1])
            a_star_time.append((time.time() - startTime))
            a_star_weight.append(weight)
            tracemalloc.stop()

            startTime = time.time()
            tracemalloc.start()
            weight = bidirectional.bidirectional_algorithm(start_node, goal_node, N, A, A_b, w,
                                                           a_star.heuristic_cost_manhattan)[1]
            bidirectional_memory.append(tracemalloc.get_traced_memory()[1])
            bidirectional_time.append((time.time() - startTime))
            bidirectional_weight.append(weight)
            tracemalloc.stop()

    for i in range(len(dijkstra_weight)):
        error_a_star.append((a_star_weight[i] - dijkstra_weight[i]) / dijkstra_weight[i])
        error_bi.append((bidirectional_weight[i] - dijkstra_weight[i]) / dijkstra_weight[i])

    return sum(dijkstra_time) / len(dijkstra_time), sum(dijkstra_memory) / len(dijkstra_memory), 0.0, \
           sum(a_star_time) / len(a_star_time), sum(a_star_memory) / len(a_star_memory), sum(error_a_star) / len(error_a_star),\
           sum(bidirectional_time) / len(bidirectional_time), sum(bidirectional_memory) / len(bidirectional_memory), sum(error_bi) / len(error_bi)


def write_output_table_graph(edges_number, nodes_number_list, dijkstra_time, dijkstra_memory, dijkstra_weight,
                             a_star_time, a_star_memory, a_star_weight, bidirectional_time, bidirectional_memory,
                             bidirectional_weight):
    with open("output/graphs_times_" + edges_number + ".out", "w", encoding="utf-8") as file:
        file.write("\\begin{table}[]\n")
        file.write("\\begin{tabular}{|l|l|l|l|}\n")
        file.write("\\hline\n")
        file.write("grupa & Dijkstra & A* & Bi A* \\\\ \\hline\n")

    with open("output/graphs_memory_" + edges_number + ".out", "w", encoding="utf-8") as file:
        file.write("\\begin{table}[]\n")
        file.write("\\begin{tabular}{|l|l|l|l|}\n")
        file.write("\\hline\n")
        file.write("grupa & Dijkstra & A* & Bi A* \\\\ \\hline\n")

    with open("output/graphs_errors_" + edges_number + ".out", "w", encoding="utf-8") as file:
        file.write("\\begin{table}[]\n")
        file.write("\\begin{tabular}{|l|l|l|l|}\n")
        file.write("\\hline\n")
        file.write("grupa & Dijkstra & A* & Bi A* \\\\ \\hline\n")

    with open("output/graphs_times_" + edges_number + ".out", "a", encoding="utf-8") as file:
        for j in range(len(dijkstra_time)):
            file.write(" " + nodes_number_list[j] + " & " + str(round(dijkstra_time[j], 5))
                       + " & " + str(round(a_star_time[j], 5)) + " & " + str(round(bidirectional_time[j], 5)) +
                       " \\\\ \\hline\n")
        file.write("\\end{tabular}\n")
        file.write("\\end{table}\n")

    with open("output/graphs_memory_" + edges_number + ".out", "a", encoding="utf-8") as file:
        for j in range(len(dijkstra_time)):
            file.write(" " + nodes_number_list[j] + " & " + str(round(dijkstra_memory[j], 5))
                       + " & " + str(round(a_star_memory[j], 5)) + " & " + str(round(bidirectional_memory[j], 5))
                       + " \\\\ \\hline\n")
        file.write("\\end{tabular}\n")
        file.write("\\end{table}\n")

    with open("output/graphs_errors_" + edges_number + ".out", "a", encoding="utf-8") as file:
        for j in range(len(dijkstra_time)):
            file.write(" " + nodes_number_list[j] + " & " +
                       str(round(dijkstra_weight[j], 5)) + " & " + str(round(a_star_weight[j], 5)) + " & " +
                       str(round(bidirectional_weight[j], 5)) + " \\\\ \\hline\n")
        file.write("\\end{tabular}\n")
        file.write("\\end{table}\n")


def write_output_table_grid(group, dijkstra_time, dijkstra_memory, dijkstra_weight, a_star_time, a_star_memory,
                            a_star_weight, bidirectional_time, bidirectional_memory, bidirectional_weight):
    with open("output/grids_times.out", "w", encoding="utf-8") as file:
        file.write("\\begin{table}[]\n")
        file.write("\\begin{tabular}{|l|l|l|l|}\n")
        file.write("\\hline\n")
        file.write("grupa & Dijkstra & A* & Bi A* \\\\ \\hline\n")

    with open("output/grids_memory.out", "w", encoding="utf-8") as file:
        file.write("\\begin{table}[]\n")
        file.write("\\begin{tabular}{|l|l|l|l|}\n")
        file.write("\\hline\n")
        file.write("grupa & Dijkstra & A* & Bi A* \\\\ \\hline\n")

    with open("output/grids_weights.out", "w", encoding="utf-8") as file:
        file.write("\\begin{table}[]\n")
        file.write("\\begin{tabular}{|l|l|l|l|}\n")
        file.write("\\hline\n")
        file.write("grupa & Dijkstra & A* & Bi A* \\\\ \\hline\n")

    with open("output/grids_times.out", "a", encoding="utf-8") as file:
        for j in range(len(dijkstra_time)):
            file.write(
                " " + group[j] + " & "
                + str(round(dijkstra_time[j], 5))
                + " & " + str(round(a_star_time[j], 5)) + " & " + str(round(bidirectional_time[j], 5)) +
                " \\\\ \\hline\n")
        file.write("\\end{tabular}\n")
        file.write("\\end{table}\n")

    with open("output/grids_memory.out", "a", encoding="utf-8") as file:
        for j in range(len(dijkstra_time)):
            file.write(" " + group[j] + " & " + str(round(dijkstra_memory[j], 5))
                       + " & " + str(round(a_star_memory[j], 5)) + " & " + str(round(bidirectional_memory[j], 5))
                       +" \\\\ \\hline\n")

        file.write("\\end{tabular}\n")
        file.write("\\end{table}\n")

    with open("output/grids_weights.out", "a", encoding="utf-8") as file:
        for j in range(len(dijkstra_time)):
            file.write(" " + group[j] + " & " +
                       str(round(dijkstra_weight[j], 5)) + " & " + str(round(a_star_weight[j], 5)) + " & " +
                       str(round(bidirectional_weight[j], 5)) + " \\\\ \\hline\n")
        file.write("\\end{tabular}\n")
        file.write("\\end{table}\n")


if __name__ == '__main__':
    do_experiments()