Projekt_Sztuczna_Inteligencja/algorithms/learn/genetic_algorithm/helpers.py

from minefield import Minefield
import project_constants as const

from project_constants import Direction
from algorithms.search.a_star import State, graphsearch
from objects.mine_models.chained_mine import ChainedMine
from objects.mine_models.time_mine import TimeMine


def possible_states(row, column):
    possible_states = []

    if Minefield.is_valid_move(row + 1, column):
        possible_states.append(State(row + 1, column, Direction.UP))

    if Minefield.is_valid_move(row - 1, column):
        possible_states.append(State(row + 1, column, Direction.DOWN))

    if Minefield.is_valid_move(row, column + 1):
        possible_states.append(State(row, column + 1, Direction.LEFT))

    if Minefield.is_valid_move(row, column - 1):
        possible_states.append(State(row, column - 1, Direction.RIGHT))

    return possible_states


def create_scores_table(minefield):
    mines = get_mines_coords(minefield)
    dict_table = {
        mine1: {
            mine2: {
                direction: 0

                for direction in Direction}
            for mine2 in mines}
        for mine1 in mines}

    dict_table[(0, 0)] = {mine: {Direction.RIGHT: 0} for mine in mines}

    for mine in mines:
        _, end_state, cost = \
            graphsearch(State(0, 0, Direction.RIGHT),
                        minefield,
                        target_type="mine",
                        tox=mine[0],
                        toy=mine[1],
                        with_data=True)

        dict_table[(0, 0)][mine][Direction.RIGHT] = (end_state, cost)

    for mine1 in mines:
        for mine2 in mines:
            for initial_state in possible_states(mine1[0], mine1[1]):
                _, end_state, cost = \
                    graphsearch(initial_state,
                                minefield,
                                target_type="mine",
                                tox=mine2[0],
                                toy=mine2[1],
                                with_data=True)

                dict_table[mine1][mine2][initial_state.direction] = (end_state, cost)

    return dict_table


def get_score(minefield, speciment, table=None):
    score = 0
    initial_state = State(0, 0, Direction.RIGHT)

    if table is not None:
        for el_index in range(len(speciment) - 1):

            if table[(initial_state.row, initial_state.column)] \
                    [(speciment[el_index][0], speciment[el_index][1])] \
                    [initial_state.direction]:

                end_state, cost = table[(initial_state.row, initial_state.column)] \
                    [(speciment[el_index][0], speciment[el_index][1])] \
                    [initial_state.direction]

                initial_state = State(speciment[el_index][0], speciment[el_index][1], end_state.direction)

            else:
                action_sequence, _, cost = \
                    graphsearch(initial_state,
                                minefield,
                                target_type="mine",
                                tox=speciment[el_index][0],
                                toy=speciment[el_index][1],
                                with_data=True)

            mine = minefield.matrix[speciment[el_index][0]][speciment[el_index][1]].mine

            if isinstance(mine, ChainedMine) and mine.predecessor is not None and mine.predecessor.active:
                cost += 200

            mine.active = False

            for _ in range(cost):
                minefield.next_turn()

            score += cost

        score += 200 * minefield.explosions

        return score

    # IF THERE IS NO TABLE
    else:
        for el_index in range(len(speciment) - 1):
            action_sequence, initial_state, cost = \
                graphsearch(initial_state,
                            minefield,
                            target_type="mine",
                            tox=speciment[el_index][0],
                            toy=speciment[el_index][1],
                            with_data=True)

            mine = minefield.matrix[speciment[el_index][0]][speciment[el_index][1]].mine

            if isinstance(mine, ChainedMine) and mine.predecessor is not None and mine.predecessor.active:
                cost += 200

            mine.active = False

            for _ in range(cost):
                minefield.next_turn()

            score += cost

        score += 200 * minefield.explosions
        return score


def get_mines_coords(minefield: Minefield):
    mines = list()

    for row in range(const.V_GRID_VER_TILES):
        for column in range(const.V_GRID_VER_TILES):
            mine = minefield.matrix[row][column].mine

            if mine is not None:
                mines.append((row, column))

    return mines