solver.py

import os
import sys
sys.path.append('..')
sys.path.append('../..')
import argparse
import utils
import networkx as nx
from solvers.mst import mst_dfs_solve
from solvers.flp import flp_solve
from solvers.local_search import local_search_solve
from solvers.greedy import greedy_shortest_path_solve

from student_utils import *
"""
======================================================================
  Complete the following function.
======================================================================
"""

def solve(list_of_locations,
          list_of_homes,
          starting_car_location,
          adjacency_matrix,
          params=[]):
    """
    Write your algorithm here.
    Input:
        list_of_locations: A list of locations such that node i of the graph corresponds to name at index i of the list
        list_of_homes: A list of homes
        starting_car_location: The name of the starting location for the car
        adjacency_matrix: The adjacency matrix from the input file
    Output:
        A list of locations representing the car path
        A dictionary mapping drop-off location to a list of homes of TAs that got off at that particular location
        NOTE: both outputs should be in terms of indices not the names of the locations themselves
    """
    G, _ = adjacency_matrix_to_graph(adjacency_matrix)
    mst_t, mst_d = mst_dfs_solve(list_of_locations, list_of_homes, starting_car_location, adjacency_matrix)
    greedy_t, greedy_d = greedy_shortest_path_solve(list_of_locations, list_of_homes, starting_car_location, adjacency_matrix)

    flp_t_0, flp_d_0 = flp_solve(list_of_locations,
                                 list_of_homes,
                                 starting_car_location,
                                 adjacency_matrix, 0)
    flp_t_1, flp_d_1 = flp_solve(list_of_locations,
                                 list_of_homes,
                                 starting_car_location,
                                 adjacency_matrix, 1)
    flp_t_2, flp_d_2 = flp_solve(list_of_locations,
                                 list_of_homes,
                                 starting_car_location,
                                 adjacency_matrix, 2)
    options = [
        ('FLP0', flp_t_0, flp_d_0),
        ('FLP1', flp_t_1, flp_d_1),
        ('FLP2', flp_t_2, flp_d_2),
        ('MST_DFS', mst_t, mst_d),
        ('GREEDY_SP', greedy_t, greedy_d),
    ]
    solver_name, solution, dropoffs = min(options, key=lambda x: cost_of_solution(G, x[1], x[2])[0])
    print(f'\nUsed {solver_name}\n')
    local_t, local_d = local_search_solve(list_of_locations,
                                          list_of_homes,
                                          starting_car_location,
                                          adjacency_matrix,
                                          initial_solution=solution)
    return local_t, local_d

"""
======================================================================
   No need to change any code below this line
======================================================================
"""

"""
Convert solution with path and dropoff_mapping in terms of indices
and write solution output in terms of names to path_to_file + file_number + '.out'
"""
def convertToFile(path, dropoff_mapping, path_to_file, list_locs):
    string = ''
    for node in path:
        string += list_locs[node] + ' '
    string = string.strip()
    string += '\n'

    dropoffNumber = len(dropoff_mapping.keys())
    string += str(dropoffNumber) + '\n'
    for dropoff in dropoff_mapping.keys():
        strDrop = list_locs[dropoff] + ' '
        for node in dropoff_mapping[dropoff]:
            strDrop += list_locs[node] + ' '
        strDrop = strDrop.strip()
        strDrop += '\n'
        string += strDrop
    utils.write_to_file(path_to_file, string)

def solve_from_file(input_file, output_directory, params=[]):
    print('Processing', input_file)

    input_data = utils.read_file(input_file)
    num_of_locations, num_houses, list_locations, list_houses, starting_car_location, adjacency_matrix = data_parser(input_data)
    car_path, drop_offs = solve(list_locations, list_houses, starting_car_location, adjacency_matrix, params=params)

    basename, filename = os.path.split(input_file)
    if not os.path.exists(output_directory):
        os.makedirs(output_directory)
    output_file = utils.input_to_output(input_file, output_directory)

    convertToFile(car_path, drop_offs, output_file, list_locations)


def solve_all(input_directory, output_directory, params=[]):
    input_files = utils.get_files_with_extension(input_directory, 'in')

    for input_file in input_files:
        try:
            solve_from_file(input_file, output_directory, params=params)
        except:
            with open('./err.txt', 'a') as f:
                f.write(input_file + '\n')


if __name__=="__main__":
    parser = argparse.ArgumentParser(description='Parsing arguments')
    parser.add_argument('--all', action='store_true', help='If specified, the solver is run on all files in the input directory. Else, it is run on just the given input file')
    parser.add_argument('input', type=str, help='The path to the input file or directory')
    parser.add_argument('output_directory', type=str, nargs='?', default='.', help='The path to the directory where the output should be written')
    parser.add_argument('params', nargs=argparse.REMAINDER, help='Extra arguments passed in')
    args = parser.parse_args()
    output_directory = args.output_directory
    if args.all:
        input_directory = args.input
        solve_all(input_directory, output_directory, params=args.params)
    else:
        input_file = args.input
        solve_from_file(input_file, output_directory, params=args.params)