def run():
label_find_the_result.config(text="Result:")
label_time.config(text="Time:")
label_steps.config(text="Steps:")
btn_run.config(state=tk.DISABLED)
btn_reset.config(state=tk.DISABLED)
radio_dfs.config(state=tk.DISABLED)
radio_bfs.config(state=tk.DISABLED)
radio_bestfs.config(state=tk.DISABLED)
radio_hc.config(state=tk.DISABLED)
algorithm = alg.get()
res = ""
steps = 0
time_start = time.time()
if algorithm == 1:
res = DFS.solve(puzzle_in, window)
print("DFS: ", res)
elif algorithm == 2:
res = BFS.solve(puzzle_in, window)
print("BFS: ", res)
elif algorithm == 3:
res = BestFirstSearch.solve(puzzle_in, window)
print("Best First Search: ", res)
elif algorithm == 4:
res = HillClimbing.solve(puzzle_in, window)
print("Hill Climbing: ", res)
time_end = time.time()
if res is None:
solution = "No!"
else:
solution = "Yes!"
steps = len(res)
output(solution, time_end - time_start, steps)
btn_run.config(state=tk.NORMAL)
btn_reset.config(state=tk.NORMAL)
radio_dfs.config(state=tk.NORMAL)
radio_bfs.config(state=tk.NORMAL)
radio_bestfs.config(state=tk.NORMAL)
radio_hc.config(state=tk.NORMAL)
import sys
sys.path.append('problems')
sys.path.append('algorithms')
from nqueens import NQueens
from bfs import BFS
if __name__ == "__main__":
#added just for easy testing, change to True/False if you want/do not want pruning.
do_prune = True
problem = NQueens(9, do_prune)
bfs = BFS()
#added just for easy testing, change to True/False if you want/do not want all solutions.
find_all_solutions = True
bfs.solve(problem, find_all_solutions)
#added so duplicate solutions will not be printed
if find_all_solutions == False:
bfs.print_solution()
bfs.print_stats()
