def test_a_star_search(self):
ss = SliderSearch(3)
res = ss.search_a_star()
exp = [[0,1,2,3,4,5,6,7,8]]
assert res == exp
ss = SliderSearch(3, [1,0,2,3,4,5,6,7,8])
res = ss.search_a_star()
exp = [[1,0,2,3,4,5,6,7,8],[0,1,2,3,4,5,6,7,8]]
def main():
hard = [4, 1, 2, 3, 0, 5, 6, 7, 8]
wat = [4, 1, 2, 0, 3, 5, 6, 7, 8]
wat2 = [0, 1, 2, 4, 3, 5, 6, 8, 7]
moder = [0, 1, 2, 5, 4, 3, 6, 8, 7]
hmm = [4, 8, 5, 7, 6, 1, 0, 2, 3]
#ss = SliderSearch(3, moder)
ss = SliderSearch(3, wat2)
path = ss.search_a_star()
print_path(path)
def test_heuristics(self):
ss = SliderSearch(3)
assert ss.heuristic_misplaced(ss.puzzle.puzzle) == 0
assert ss.heuristic_manhatten_distance(ss.puzzle.puzzle) == 0
ss = SliderSearch(3, [3, 1, 2, 0, 4, 5, 6, 7, 8])
assert ss.heuristic_misplaced(ss.puzzle.puzzle) == 2
assert ss.heuristic_manhatten_distance(ss.puzzle.puzzle) == 2
ss = SliderSearch(3, [8, 1, 2, 3, 4, 5, 6, 7, 0])
assert ss.heuristic_misplaced(ss.puzzle.puzzle) == 2
assert ss.heuristic_manhatten_distance(ss.puzzle.puzzle) == 8
ss = SliderSearch(3, [4, 8, 5, 7, 6, 1, 0, 2, 3])
assert ss.heuristic_misplaced(ss.puzzle.puzzle) == 9
assert ss.heuristic_manhatten_distance(ss.puzzle.puzzle) == 20
def test_goal_state(self):
ss = SliderSearch(4)
expected_goal_state = [x for x in xrange(16)]
assert ss.goal_state() == expected_goal_state
