def test_get_number_of_queens_on_board(self): size = 5 queens = (XYLocation(1, 1), XYLocation(2, 4), XYLocation(3, 3)) nqb = NQueensBoard(size) nqb.set_board(queens) self.assertEqual(3, nqb.get_number_of_queens_on_board())
def test_get_number_of_attacking_pairs_v(self): size = 5 queens = (XYLocation(1, 3), XYLocation(1, 4), XYLocation(1, 0)) nqb = NQueensBoard(size) nqb.set_board(queens) self.assertEqual(3, nqb.get_number_of_attacking_pairs())
def test_create_board(self): size = 5 nqb = NQueensBoard(size) for r in range(size): for c in range(size): self.assertFalse(nqb.queen_exists_at_square(r, c))
def create_random_board(): board = NQueensBoard(SIZE) for c in range(SIZE): r = randint(0, SIZE - 1) board.add_queen_at(XYLocation(c, r)) return board
def test_remove_queen_action(self): queens = (XYLocation(1, 3), XYLocation(1, 4), XYLocation(1, 0)) nqb = NQueensBoard(5) nqb.set_board(queens) nqrf = NQResultFunction() new_board = nqrf.result(nqb, QueenAction(QueenAction.REMOVE_QUEEN, XYLocation(1, 4))) self.assertEquals(2, new_board.get_number_of_queens_on_board())
def test_actions(self): nqb = NQueensBoard(3) nqb.add_queen_at(XYLocation(0, 0)) nqiaf = NQIActionsFunctions() actions = nqiaf.actions(nqb) expected_actions = [QueenAction(QueenAction.PLACE_QUEEN, XYLocation(1, 2)), QueenAction(QueenAction.PLACE_QUEEN, XYLocation(2, 1))] self.assertSameElements(expected_actions, actions)
def test_move_queen(self): nqb = NQueensBoard(5) nqb.add_queen_at(XYLocation(3, 4)) nqrf = NQResultFunction() new_board = nqrf.result(nqb, QueenAction(QueenAction.MOVE_QUEEN, XYLocation(3, 1))) self.assertFalse(new_board.queen_exists_at_square(4, 3)) self.assertTrue(new_board.queen_exists_at_square(1, 3))
def test_move_queen(self): nqb = NQueensBoard(5) nqb.add_queen_at(XYLocation(3, 4)) nqrf = NQResultFunction() new_board = nqrf.result( nqb, QueenAction(QueenAction.MOVE_QUEEN, XYLocation(3, 1))) self.assertFalse(new_board.queen_exists_at_square(4, 3)) self.assertTrue(new_board.queen_exists_at_square(1, 3))
def test_remove_queen_action(self): queens = (XYLocation(1, 3), XYLocation(1, 4), XYLocation(1, 0)) nqb = NQueensBoard(5) nqb.set_board(queens) nqrf = NQResultFunction() new_board = nqrf.result( nqb, QueenAction(QueenAction.REMOVE_QUEEN, XYLocation(1, 4))) self.assertEquals(2, new_board.get_number_of_queens_on_board())
def test_actions(self): nqb = NQueensBoard(3) nqb.add_queen_at(XYLocation(0, 0)) nqiaf = NQIActionsFunctions() actions = nqiaf.actions(nqb) expected_actions = [ QueenAction(QueenAction.PLACE_QUEEN, XYLocation(1, 2)), QueenAction(QueenAction.PLACE_QUEEN, XYLocation(2, 1)) ] self.assertSameElements(expected_actions, actions)
def test_place_queen(self): nqb = NQueensBoard(5) nqrf = NQResultFunction() new_board = nqrf.result( nqb, QueenAction(QueenAction.PLACE_QUEEN, XYLocation(1, 2))) self.assertTrue(new_board.queen_exists_at_square(2, 1))
def test_get_state(self): string = "23041" conv = NQueensConverter(5) expected_board = NQueensBoard(5) expected_board.add_queen_at(XYLocation(0, 2)) expected_board.add_queen_at(XYLocation(1, 3)) expected_board.add_queen_at(XYLocation(2, 0)) expected_board.add_queen_at(XYLocation(3, 4)) expected_board.add_queen_at(XYLocation(4, 1)) self.assertEqual(expected_board, conv.get_state(string))
def test_add_queen_at(self): nqb = NQueensBoard(5) nqb.add_queen_at(XYLocation(3, 4)) self.assertTrue(nqb.queen_exists_at_square(4, 3))
def test_remove_queen_from(self): nqb = NQueensBoard(5) nqb.add_queen_at(XYLocation(3, 4)) nqb.remove_queen_from(XYLocation(3, 4)) self.assertEqual(0, len(nqb.get_queen_positions()))
from aima.core.search.framework import TreeSearch, Problem from aima.core.search.uninformed import DepthFirstSearch __author__ = 'Ivan Mushketik' ## # Example of solving N-queens problem with help of DFS # Size of the chess board SIZE = 5 # Using tree DFS ts = TreeSearch() dfs = DepthFirstSearch(ts) # Create empty board empty_board = NQueensBoard(SIZE) # Define N-queen board p = Problem(empty_board, NQIActionsFunctions(), NQResultFunction(), NQueensGoalTest()) # Get list of actions to solve a problem actions = dfs.search(p) board_to_show = NQueensBoard(SIZE) rf = NQResultFunction() # Print each action and perform each action (putting new queen on a board) for action in actions: print(action) board_to_show = rf.result(board_to_show, action) # Print result board print(board_to_show)