mirror of
https://github.com/metafy-social/python-scripts.git
synced 2024-11-30 15:31:10 +00:00
84 lines
3.0 KiB
Python
84 lines
3.0 KiB
Python
|
import numpy as np
|
||
|
|
||
|
problem = []
|
||
|
|
||
|
for x in range(9):
|
||
|
i = input()
|
||
|
l = [int(v) for v in i]
|
||
|
problem.append(l)
|
||
|
|
||
|
#print(problem)
|
||
|
|
||
|
np_problem = np.array(problem)
|
||
|
|
||
|
fixed_coordinates = [] # first getting the coordinates where fixed numbers are present
|
||
|
empty_coordinates = []
|
||
|
for i , sub_array in enumerate(problem) :
|
||
|
temp = [[i , c] for c , sub_element in enumerate(sub_array) if sub_element > 0]
|
||
|
temp2 = [[i , j] for j , sub_element2 in enumerate(sub_array) if sub_element2 == 0]
|
||
|
for z in temp : fixed_coordinates.append(z)
|
||
|
for w in temp2 : empty_coordinates.append(w)
|
||
|
|
||
|
l , m , r = [0 , 3 , 6] , [1 , 4 , 7] , [2 , 5 , 8]
|
||
|
|
||
|
avoid_dict = {idx : [] for idx in list(range(0 , len(empty_coordinates)))}
|
||
|
|
||
|
def generate_bounds(r , c) -> list:
|
||
|
|
||
|
lower_bound_c = c if c in l else c - 1 if c in m else c - 2
|
||
|
upper_bound_c = c + 3 if c in l else c + 2 if c in m else c + 1
|
||
|
|
||
|
lower_bound_r = r if r in l else r - 1 if r in m else r - 2
|
||
|
upper_bound_r = r + 3 if r in l else r + 2 if r in m else r + 1
|
||
|
|
||
|
return [lower_bound_c , upper_bound_c , lower_bound_r , upper_bound_r]
|
||
|
|
||
|
|
||
|
def backtrack(return_coordinates) :
|
||
|
|
||
|
n_r , n_c = empty_coordinates[empty_coordinates.index(return_coordinates) - 1] # getting back element coordinates
|
||
|
|
||
|
while [n_r , n_c] != empty_coordinates[empty_coordinates.index(return_coordinates) + 1]:
|
||
|
|
||
|
if np_problem[n_r , n_c] != 0 :
|
||
|
avoid_dict[empty_coordinates.index([n_r , n_c])].append(np_problem[n_r , n_c])
|
||
|
|
||
|
fix_flag = False
|
||
|
r , c = n_r , n_c
|
||
|
for num in range(1 , 10) :
|
||
|
|
||
|
l_b_c , u_b_c , l_b_r , u_b_r = generate_bounds(r , c)
|
||
|
|
||
|
if all([num not in np_problem[l_b_r : u_b_r , l_b_c : u_b_c] , num not in np_problem[r , :] , num not in np_problem[: , c]]) :
|
||
|
if num not in avoid_dict.get(empty_coordinates.index([n_r , n_c])) :
|
||
|
np_problem[n_r , n_c] , fix_flag = num , True
|
||
|
break
|
||
|
|
||
|
if fix_flag : n_r , n_c = empty_coordinates[empty_coordinates.index([n_r , n_c]) + 1]
|
||
|
|
||
|
if not fix_flag :
|
||
|
np_problem[n_r , n_c] = 0
|
||
|
avoid_dict[empty_coordinates.index([n_r , n_c])].clear()
|
||
|
n_r , n_c = empty_coordinates[empty_coordinates.index([n_r , n_c]) - 1]
|
||
|
|
||
|
|
||
|
for r in range(9) :
|
||
|
for c in range(9) :
|
||
|
|
||
|
if [r , c] not in fixed_coordinates :
|
||
|
|
||
|
fix_flag = False
|
||
|
|
||
|
for num in range(1 , 10) :
|
||
|
|
||
|
l_b_c , u_b_c , l_b_r , u_b_r = generate_bounds(r , c)
|
||
|
|
||
|
if all([num not in np_problem[l_b_r : u_b_r , l_b_c : u_b_c] , num not in np_problem[r , :] , num not in np_problem[: , c]]) :
|
||
|
|
||
|
np_problem[r , c] , fix_flag = num , True
|
||
|
break
|
||
|
|
||
|
if not fix_flag : backtrack([r , c])
|
||
|
|
||
|
print(np_problem)
|