#!/usr/bin/env python3
# -*- coding: utf-8 -*-

"""
@author: 徐胜虎
@contact:1813366784@qq.com
@version: 1.0.0
@license: Apache Licence
@file: x.py
@time: 2024/1/28 19:13
"""
import itertools
import sys
from typing import Iterable

import pandas as pd


def cal_distance(elem: str, refer_data: dict = None):
    route_list = elem.split('-')
    route_num = len(route_list)
    route_distance = 0
    for i in range(route_num - 1):
        start = route_list[i]
        end = route_list[i + 1]
        elem_key = frozenset([start, end])
        if elem_key in refer_data:
            route_distance += refer_data.get(elem_key)
        else:
            raise KeyError(f'字典同时没有键{elem_key}键')
    return route_distance


# 武汉-黄冈黄州-浠水-蕲春-武穴-黄梅县
# 以最小距离为最优
def cal_min_path_distance(start: str = None, must_pass: Iterable[str] = None, refer_data: dict = None):
    min_route_path = None
    min_re = sys.maxsize
    for route in itertools.permutations(must_pass):

        route_str = start + '-' + '-'.join(route)
        res = cal_distance(route_str, refer_data)
        if res < min_re:
            min_route_path = route_str
            min_re = res
    return min_route_path, min_re


def cal_min_cost_distance(start: str = '武汉', must_pass: Iterable[str] = None, refer_data: dict = None,
                          refer_cost: dict = None):
    min_route_path = None
    min_re = sys.maxsize
    for route in itertools.permutations(must_pass):
        route_str = start + '-' + '-'.join(route)
        total_distance = cal_distance(route_str, refer_data)
        rest = total_distance - refer_cost[route[-1]][0]
        if rest < 0:
            continue
        res = rest * 2.5 + refer_cost[route[-1]][1]
        # print(total_distance - refer_cost[route[-1]][0])
        # total_distance - refer_cost[route[-1]][1]

        if res < min_re:
            min_route_path = route_str
            min_re = res
    return min_route_path, min_re


received_data = pd.read_excel('resources/template/1月份账单.xlsx', header=0, keep_default_na=False, sheet_name='Sheet4',
                              engine='openpyxl')
# noinspection PyTypeChecker
refer_distance_data = pd.read_excel('resources/template/信息录入表.xlsx', header=0, keep_default_na=False,
                                    sheet_name='鄂东数据字典', usecols=('序号', '线路', '公里数', '起点', '终点'))
# noinspection PyTypeChecker
refer_cost_data = pd.read_excel('resources/template/信息录入表.xlsx', header=0, keep_default_na=False,
                                sheet_name='鄂东数据字典', usecols=('最终站点', '站点公里数', '单价'))

refer_distance_data.drop(columns='序号', inplace=True)

refer_distance_data['路线'] = refer_distance_data[['起点', '终点']].apply(lambda row: '-'.join(row), axis=1)

refer_data_dict = dict(
    zip(refer_distance_data[['起点', '终点']].apply(lambda row_: frozenset([row_['起点'], row_['终点']]), axis=1),
        refer_distance_data['公里数']))

refer_cost_dict = dict(
    zip(refer_cost_data['最终站点'], tuple(zip(refer_cost_data['站点公里数'], refer_cost_data['单价']))))

re = cal_min_path_distance(start='武汉', must_pass=['鄂州五环', '黄冈黄州', '蕲春', '团风'],
                           refer_data=refer_data_dict)

re = cal_min_cost_distance(start='武汉', must_pass=['黄冈黄州', '浠水', '蕲春', '武穴','黄梅县'],
                           refer_data=refer_data_dict, refer_cost=refer_cost_dict)

re = cal_min_cost_distance(start='武汉', must_pass=['鄂州五环','黄冈黄州', '团风','浠水', '蕲春', '武穴','黄梅县'],
                           refer_data=refer_data_dict, refer_cost=refer_cost_dict)

total_temp = []
for i in range(2, 8):
    for elem in itertools.combinations(['鄂州五环', '黄冈黄州', '黄梅县', '蕲春', '团风', '武穴', '浠水'], i):
        re = cal_min_cost_distance(start='武汉', must_pass=elem,
                                   refer_data=refer_data_dict, refer_cost=refer_cost_dict)
        total_temp.append(re)

df = pd.DataFrame(total_temp,columns=['路线','实际运费'])
df.to_excel('resources/temp/result.xlsx')

print(re)