Traktor/tractor.py

import pygame
from constant import size, rows, cols
from decisiontree import predict
from neuralnetwork import predict_image


class Tractor:
    def __init__(self, row, col, model, feature_columns, neuralnetwork):
        self.row = row
        self.col = col
        self.images = {
            "up": pygame.image.load("tractor/up.png"),
            "down": pygame.image.load("tractor/down.png"),
            "left": pygame.image.load("tractor/left.png"),
            "right": pygame.image.load("tractor/right.png")
        }
        self.direction = "down"
        self.model = model
        self.feature_columns = feature_columns
        self.neuralnetwork = neuralnetwork

    def draw(self, win):
        tractor_image = self.images[self.direction]
        win.blit(tractor_image, (self.col * size, self.row * size))

    def turn_left(self):
        if self.direction == "up":
            self.direction = "left"
        elif self.direction == "left":
            self.direction = "down"
        elif self.direction == "down":
            self.direction = "right"
        elif self.direction == "right":
            self.direction = "up"

    def turn_right(self):
        if self.direction == "up":
            self.direction = "right"
        elif self.direction == "right":
            self.direction = "down"
        elif self.direction == "down":
            self.direction = "left"
        elif self.direction == "left":
            self.direction = "up"
    

    def move_forward(self, board):
        if self.direction == "up" and self.row > 0:
            next_row, next_col = self.row - 1, self.col
        elif self.direction == "left" and self.col > 0:
            next_row, next_col = self.row, self.col - 1
        elif self.direction == "down" and self.row < rows - 1:
            next_row, next_col = self.row + 1, self.col
        elif self.direction == "right" and self.col < cols - 1:
            next_row, next_col = self.row, self.col + 1
        else:
            return  # Nie możemy się ruszyć poza planszę

        image_path = board.vegetables[next_row][next_col]  # Ścieżka do obrazu warzywa

            # Predykcja warzywa po obrazie
        if image_path is not None:
            print(image_path, "mialo byc")
            vegetable_name = predict_image(image_path, self.neuralnetwork)
            print(vegetable_name, "jest")
        
        if board.is_dirt(next_row, next_col) and board.board[next_row][next_col] != 10:
            soil_features = board.soil_features
            sample = {
                "wilgotnosc_gleby": soil_features["wilgotnosc_gleby"],
                "temperatura_gleby": soil_features["temperatura_gleby"],
                "opady_deszczu": soil_features["opady_deszczu"],
                "wiek_rosliny": soil_features["wiek_rosliny"],
                "proc_ekspo_na_swiatlo": soil_features["proc_ekspo_na_swiatlo"],
                "pora_dnia": soil_features["pora_dnia"],
                "pora_roku": soil_features["pora_roku"],
                "roslina": "warzywa/" + str(vegetable_name)  + ".png"
            }

            should_water = predict(self.model, self.feature_columns, sample)
            print(f"Predykcja dla pola ({next_row}, {next_col}) z cechami {sample}: {should_water}")
            if should_water[0].strip() == 'tak':
                board.set_soil(next_row, next_col)
            else:
                board.set_fakedirt(next_row, next_col)
        self.row, self.col = next_row, next_col  # Przemieszczamy traktor niezależnie od predykcji