import numpy as np
from entity import *
from KM import KM

def dispatch(match_list):
    drivers = list(set([match.driver for match in match_list]))
    orders = list(set([match.order for match in match_list]))

    label = np.zeros(shape=(len(drivers),len(orders)))
    label = label+1000
    for match in match_list:
        driver = match.driver
        order = match.order
        value = match.value
        label[drivers.index(driver),orders.index(order)] = value
        # label[drivers.index(driver),orders.index(order)] = value + 1000
    # print(label)
    max_dispatch = KM(label).max_dispatch
    return [Match(orders[col],drivers[row]) for row,col in max_dispatch]




if __name__ == '__main__':
    d1 = Driver(1,15,20)
    d2 = Driver(2,3,40)
    d3 = Driver(3,33,44)
    d4 = Driver(4,10,19)
    d5 = Driver(5,12,39)
    o1 = Order(1,13,25,15,15,70)
    o2 = Order(2,40,14,30,21,70)
    o3 = Order(3,31,46,20,41,70)
    o4 = Order(4,25,35,11,29,70)
    test_data = [Match(o2,d1,get_value=True),Match(o3,d1,get_value=True),Match(o2,d1,get_value=True),
                 Match(o1,d2,get_value=True),Match(o3,d2,get_value=True),Match(o2,d3,get_value=True),
                 Match(o2,d4,get_value=True),Match(o3,d4,get_value=True),Match(o4,d5,get_value=True)]
    res = dispatch(test_data)
    print(res)
    pass