initial.py

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

from global_parameters import *
import pickle
import pandas as pd
from util import *
from floyd_path import *
def initialize():
    '''
    initialize fare, distance, travel_time model
                requests, vehicles
    '''
    with open('models/fare_model/fare_model.csv', 'rb') as fare_file:
        fare = np.loadtxt(fname=fare_file,
                          delimiter=",",
                      skiprows=0,)
        set_value('fare', fare)
    with open('models/distance_model/distance_model.csv', 'rb') as distance_file:
        distance = np.loadtxt(fname=distance_file,
                              delimiter=",",
                              skiprows=0)
        shortest_dis, predecessors = floyd_warshall(distance)
        set_value('shortest_dis', shortest_dis)
        set_value('predecessors', predecessors)
    with open('models/travel_time_model/driving_time_model.csv') as travel_time_file:
        travel_time = np.loadtxt(fname=travel_time_file,
                                 delimiter=",",
                                 skiprows=0)
        travel_time = travel_time.reshape([24, GRID_NUMS + 1, GRID_NUMS + 1])
        set_value('travel_time', travel_time)
    with open('request_dict/request_dict_2018-06.pkl', 'rb') as request_file:
        request = pickle.load(request_file)
        set_value('request_all', request)
        # max_ = 0
        # for key1 in request.keys():
        #     for key2 in request[key1].keys():
        #         len_ = 0
        #         for key3 in request[key1][key2].keys():
        #             len_ += len(request[key1][key2][key3])
        #         if max_ < len_:
        #             max_ = len_
        #         print('%i day '%key1,'%i time:' % key2, ':', len_)
        # print('max:', max_)

    with open('vehicles_df/vehicles_df.csv', 'rb') as vehicle_file:
        vehicle = pd.read_csv(vehicle_file,
                              na_filter=False,
                              usecols=['vehicle_ID',
                                       'start_loc',
                                       'start_time',
                                       'stop_time',
                                       ],
                              dtype={'vehicle_ID':np.int,
                                     'start_loc':np.int,
                                     'start_time':np.int,
                                     'stop_time':np.int,
                                     },
                              nrows=TOTAL_VEHICLES_NUMS,
                              )
        VEHICLES = []
        for i in range(len(vehicle)):
            vehicle_ins = Vehicle(v_id=vehicle.loc[i,'vehicle_ID'],
                                  location=vehicle.loc[i, 'start_loc'],
                                  start_time=0,
                                  stop_time=vehicle.loc[i, 'stop_time'])
            VEHICLES.append(vehicle_ins)
        set_value('VEHICLES', VEHICLES)
        # print(len(VEHICLES))
    with open('vehicle_dict/vehicle_dict.pkl', 'rb') as vehicle_dict_file:
        vehicle_dict = pickle.load(vehicle_dict_file)
        set_value('vehicle_serve', vehicle_dict)


# def test():
#     with open('models/fare_model/fare_model.csv', 'rb') as fare_file:
#         fare = np.loadtxt(fname=fare_file,
#                           delimiter=",",
#                       skiprows=0,)
#         set_value('fare', fare)
#         max = 0
#         for i in range(1,266):
#             for j in range(1,266):
#                 max = fare[i][j] if fare[i][j] > max else max
#         print(max)
# test()
# initialize()