Source code for ml4co_kit.wrapper.routing.tsp.pctsp

r"""
PCTSP Wrapper.
"""

# Copyright (c) 2024 Thinklab@SJTU
# ML4CO-Kit is licensed under Mulan PSL v2.
# You can use this software according to the terms and conditions of the Mulan PSL v2.
# You may obtain a copy of Mulan PSL v2 at:
# http://license.coscl.org.cn/MulanPSL2
#
# THIS SOFTWARE IS PROVIDED ON AN "AS IS" BASIS, WITHOUT WARRANTIES OF ANY KIND,
# EITHER EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO NON-INFRINGEMENT,
# MERCHANTABILITY OR FIT FOR A PARTICULAR PURPOSE.
# See the Mulan PSL v2 for more details.


import pathlib
import numpy as np
from typing import Union, List
from ml4co_kit.task.base import TASK_TYPE
from ml4co_kit.wrapper.base import WrapperBase
from ml4co_kit.utils.time_utils import tqdm_by_time
from ml4co_kit.utils.file_utils import check_file_path
from ml4co_kit.task.routing.tsp.pctsp import PCTSPTask
from ml4co_kit.task.routing.base import DISTANCE_TYPE, ROUND_TYPE


[docs]class PCTSPWrapper(WrapperBase): def __init__( self, precision: Union[np.float32, np.float64] = np.float32 ): super(PCTSPWrapper, self).__init__( task_type=TASK_TYPE.PCTSP, precision=precision ) self.task_list: List[PCTSPTask] = list()
[docs] def from_txt( self, file_path: pathlib.Path, distance_type: DISTANCE_TYPE = DISTANCE_TYPE.EUC_2D, round_type: ROUND_TYPE = ROUND_TYPE.NO, ref: bool = False, overwrite: bool = True, normalize: bool = False, show_time: bool = False ): """Read task data from ``.txt`` file""" # Overwrite task list if overwrite is True if overwrite: self.task_list: List[PCTSPTask] = list() # Read task data from ``.txt`` file with open(file_path, "r") as file: load_msg = f"Loading data from {file_path}" for idx, line in tqdm_by_time(enumerate(file), load_msg, show_time): # Load data line = line.strip() split_line_0 = line.split("depots ")[1] split_line_1 = split_line_0.split(" points ") depots = split_line_1[0] split_line_2 = split_line_1[1].split(" penalties ") points = split_line_2[0] split_line_3 = split_line_2[1].split(" prizes ") penalties = split_line_3[0] split_line_4 = split_line_3[1].split(" required_prize ") prizes = split_line_4[0] split_line_5 = split_line_4[1].split(" output ") required_prize = split_line_5[0] tour = split_line_5[1] # Parse depot coordinates depots = depots.split(" ") depots = np.array([float(depots[0]), float(depots[1])], dtype=self.precision) # Parse points coordinates points = points.split(" ") points = np.array( [ [float(points[i]), float(points[i + 1])] for i in range(0, len(points), 2) ], dtype=self.precision ) # Parse penalties penalties = penalties.split(" ") penalties = np.array([ float(penalties[i]) for i in range(len(penalties)) ], dtype=self.precision) # Parse prizes prizes = prizes.split(" ") prizes = np.array( [float(prizes[i]) for i in range(len(prizes))], dtype=self.precision ) # Parse required_prize required_prize = float(required_prize) # Parse tour tour = tour.split(" ") tour = np.array( [int(tour[i]) for i in range(len(tour))] ) tour -= 1 # Create a new task and add it to ``self.task_list`` if overwrite: pctsp_task = PCTSPTask( distance_type=distance_type, round_type=round_type, precision=self.precision ) else: pctsp_task = self.task_list[idx] pctsp_task.from_data( depots=depots, points=points, penalties=penalties, prizes=prizes, required_prize=required_prize, sol=tour, ref=ref, normalize=normalize ) if overwrite: self.task_list.append(pctsp_task)
[docs] def to_txt( self, file_path: pathlib.Path, show_time: bool = False, mode: str = "w" ): """Write task data to ``.txt`` file""" # Check file path check_file_path(file_path) # Save task data to ``.txt`` file with open(file_path, mode) as f: write_msg = f"Writing data to {file_path}" for task in tqdm_by_time(self.task_list, write_msg, show_time): # Check data and get variables task._check_depots_not_none() task._check_points_not_none() task._check_penalties_not_none() task._check_prizes_not_none() task._check_required_prize_not_none() task._check_sol_not_none() depots = task.depots points = task.points prizes = task.prizes penalties = task.penalties required_prize = task.required_prize sol = task.sol # Write data to ``.txt`` file f.write("depots " + str(depots[0]) + str(" ") + str(depots[1])) f.write(" points" + str(" ")) f.write( " ".join( str(x) + str(" ") + str(y) for x, y in points ) ) f.write(" penalties " + str(" ").join(str(penalty) for penalty in penalties)) f.write(" prizes " + str(" ").join(str(prize) for prize in prizes)) f.write(" required_prize " + str(required_prize)) f.write(str(" output ")) f.write(str(" ").join(str(node_idx + 1) for node_idx in sol)) f.write("\n") f.close()