coverage

from unittest import TestCase

import numpy as np

import deepchem.rl.envs.tictactoe

class TestTicTacToeEnvironment(TestCase):

    def test_constructor(self):

        board = deepchem.rl.envs.tictactoe.TicTacToeEnvironment()

        assert len(board.state) == 1

        assert board.state[0].shape == (3, 3, 2)

        assert np.sum(board.state[0]) == 1 or np.sum(board.state[0]) == 0

    def test_step(self):

        board = deepchem.rl.envs.tictactoe.TicTacToeEnvironment()

        X = deepchem.rl.envs.tictactoe.TicTacToeEnvironment.X

        board._state = [np.zeros(shape=(3, 3, 2), dtype=np.float32)]

        board.step(0)

        assert np.all(board.state[0][0][0] == X)

    def test_winner(self):

        board = deepchem.rl.envs.tictactoe.TicTacToeEnvironment()

        X = deepchem.rl.envs.tictactoe.TicTacToeEnvironment.X

        board.state[0][0][0] = X

        board.state[0][0][1] = X

        assert not board.check_winner(X)

        board.state[0][0][2] = X

        assert board.check_winner(X)

    def test_game_over(self):

        board = deepchem.rl.envs.tictactoe.TicTacToeEnvironment()

        X = deepchem.rl.envs.tictactoe.TicTacToeEnvironment.X

        board.state[0][0][0] = X

        board.state[0][0][1] = X

        assert not board.check_winner(X)

        board.state[0][0][2] = X

        assert board.check_winner(X)

    def test_display(self):

        board = deepchem.rl.envs.tictactoe.TicTacToeEnvironment()

        s = board.display()

        assert s.find("X") == -1

    def test_get_O_move(self):

        board = deepchem.rl.envs.tictactoe.TicTacToeEnvironment()

        empty = deepchem.rl.envs.tictactoe.TicTacToeEnvironment.EMPTY

        move = board.get_O_move()

        assert np.all(board.state[0][move[0]][move[1]] == empty)

    return False

  def game_over(self):

    s = set()

    for i in range(3):

      for j in range(3):

        if np.all(self._state[0][i][j] == TicTacToeEnvironment.EMPTY):