import pygame
from treelearn import treelearn
import loadmodel
from astar import astar
from state import State
import time
from garbage_truck import GarbageTruck
from heuristicfn import heuristicfn
from map import randomize_map
from heuristicfn import heuristicfn
import pygame as pg
import random
from request import Request

def apply_tree(request_list):

    print("Przed zastosowaniem drzewa na liście jest śmieci: ", len(request_list))

    for address in request_list:
        r = [
                    0, 
                    0,
                    address.volume,
                    address.last_collection,
                    address.is_paid,
                    address.odour_intensity,
                    address.weight,
                    address.type
                ]
        clf = treelearn()
        if clf.predict([r]) == False:
            request_list.pop(request_list.index(address))

    print("Po zastosowaniu drzewa na liście jest śmieci: ", len(request_list))
    return request_list