136 lines
4.3 KiB
Python
136 lines
4.3 KiB
Python
import pygame
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import time
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import random
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import pandas as pd
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import joblib
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from area.constants import WIDTH, HEIGHT, TILE_SIZE
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from area.field import drawWindow
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from area.tractor import Tractor, do_actions
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from area.field import tiles, fieldX, fieldY
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from area.field import get_tile_coordinates
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from ground import Dirt
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from plant import Plant
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from bfs import graphsearch, Istate, succ
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from astar import a_star
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WIN = pygame.display.set_mode((WIDTH, HEIGHT))
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pygame.display.set_caption('Intelligent tractor')
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def main():
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run = True
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window = drawWindow(WIN)
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pygame.display.update()
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#getting coordinates of our "goal tile":
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tile_index=127
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tile_x, tile_y = get_tile_coordinates(tile_index)
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if tile_x is not None and tile_y is not None:
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print(f"Coordinates of tile {tile_index} are: ({tile_x}, {tile_y})")
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else: print("Such tile does not exist")
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#mark the goal tile:
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tiles[tile_index].image = "resources/images/sampling_goal.png"
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image = pygame.image.load(tiles[tile_index].image).convert()
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image = pygame.transform.scale(image, (TILE_SIZE, TILE_SIZE))
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WIN.blit(image, (tiles[tile_index].x, tiles[tile_index].y))
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pygame.display.flip()
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#graphsearch activation:
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istate = Istate(170, 100, 2) #initial state
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goaltest = []
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goaltest.append(tile_x) #final state (consists of x and y because direction doesnt matter)
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goaltest.append(tile_y)
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tractor = Tractor(0*TILE_SIZE, 0*TILE_SIZE, 2, None, None)
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tractor.rect.x += fieldX
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tractor.rect.y += fieldY
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tractor.tractor_start = ((istate.get_x(), istate.get_y()))
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#tractor.tractor_start = ((istate.get_x(), istate.get_y(), istate.get_direction))
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tractor.tractor_end = ((goaltest[0], goaltest[1]))
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#moves = (graphsearch(istate, succ, goaltest, tractor))
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moves = (a_star(istate, succ, goaltest, tractor))
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print(moves)
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#main loop:
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while run:
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for event in pygame.event.get():
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if event.type == pygame.QUIT:
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run = False
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#small test of work_on_field method:
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time.sleep(1)
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tile1 = tiles[0]
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p1 = Plant('wheat', 'cereal', random.randint(1,100), random.randint(1,100), random.randint(1,100))
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d1 = Dirt(random.randint(1, 100), random.randint(1,100))
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d1.pests_and_weeds()
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tile1.ground=d1
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if d1.pest:
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pe = 1
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else:
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pe = 0
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if d1.weed:
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we = 1
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else:
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we = 0
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if p1.plant_type == 'cereal':
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t1 = True
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t2 = False
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t3 = False
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t4 = False
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else:
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t1 = False
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if p1.plant_type == 'fruit':
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t2 = True
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t3 = False
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t4 = False
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else:
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t2 = False
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if p1.plant_type == 'vegetable':
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t4 = True
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t3 = False
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else:
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t3 = True
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t4 = False
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dane = {
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'anomalies': [True],
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'temp': [17],
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'water': [d1.water_level],
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'nutri': [d1.nutrients_level],
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'pests': [pe],
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'weeds': [we],
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'ripeness': [p1.growth_level],
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'season_autumn': [True], 'season_spring': [False], 'season_summer': [False], 'season_winter': [False],
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'weather_heavyCloudy': [False], 'weather_partCloudy': [False], 'weather_precipitation': [False],
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'weather_sunny': [True],
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'type_cereal': [t1], 'type_fruit': [t2], 'type_none': [t3], 'type_vegetable': [t4]
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}
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df = pd.DataFrame(dane)
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df.to_csv('model_data.csv', index=False)
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model = joblib.load('model.pkl')
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nowe_dane = pd.read_csv('model_data.csv')
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predykcje = model.predict(nowe_dane)
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# movement based on route-planning (test):
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tractor.draw_tractor(WIN)
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time.sleep(1)
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if moves != False:
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do_actions(tractor, WIN, moves)
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print(predykcje)
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if predykcje == 'work':
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tractor.work_on_field(tile1, d1, p1)
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time.sleep(30)
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print("\n")
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main()
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