4 ms·

I must be missing something. malib does not have solve_cover, and this specific function is used without definition in the Sudoku example. The shown solution se

I must be missing something. malib does not have solve_cover, and this specific function is used without definition in the Sudoku example. The shown solution seems to be the order in which the digits are solved and not the actual digits in their correct location, because the solution matrix has repeat digits everywhere, and the first 21 digits are the provided solution digits in order.

PennRobotics 4y ago
This just needed a few corrections to get running: * solve_cover should simply be solve * The solution is a list with elements in the form (digit, x location, y location), zero-indexed. So I changed the ending some: out = [['0','0','0','0','0','0','0','0','0','\n'], ['0','0','0','0','0','0','0','0','0','\n'], ['0','0','0','0','0','0','0','0','0','\n'], ['0','0','0','0','0','0','0','0','0','\n'], ['0','0','0','0','0','0','0','0','0','\n'], ['0','0','0','0','0','0','0','0','0','\n'], ['0','0','0','0','0','0','0','0','0','\n'], ['0','0','0','0','0','0','0','0','0','\n'], ['0','0','0','0','0','0','0','0','0']] for d, x, y in solution: out[x][y] = str(d) print(''.join([a for b in out for a in b])) # Flatten 2d array There's probably a more elegant/pythonic way to do each code block, but this will get you a valid solution matrix: (Format lines were added during posting.) 842|713|695 913|652|847 675|498|213 ---+---+--- 354|267|189 189|345|726 267|189|534 ---+---+--- 521|974|368 438|526|971 796|831|452 It is a bit interesting seeing the similarities and differences between the posted article and Norvig's Sudoku solver[1]. I've always appreciated how Norvig is concise and still has intermediate representations for debugging (e.g. shows all of the possible digits for a cell that hasn't yet been solved). The article's solver is MUCH faster in non-exact cases: The "multiple solution" example from Norvig (which Norvig states takes 3 minutes to solve) is done in 10 ms using this solver (plus, it finds a different valid solution), and the "impossible solution" (which fails after 24 minutes) gives a StopIteration after 90 ms. [1] https://norvig.com/sudoku.html https://norvig.com/sudoku.html

PennRobotics 4y ago

This just needed a few corrections to get running: * solve_cover should simply be solve * The solution is a list with elements in the form (digit, x location, y location), zero-indexed. So I changed the ending some: out = [['0','0','0','0','0','0','0','0','0','\n'], ['0','0','0','0','0','0','0','0','0','\n'], ['0','0','0','0','0','0','0','0','0','\n'], ['0','0','0','0','0','0','0','0','0','\n'], ['0','0','0','0','0','0','0','0','0','\n'], ['0','0','0','0','0','0','0','0','0','\n'], ['0','0','0','0','0','0','0','0','0','\n'], ['0','0','0','0','0','0','0','0','0','\n'], ['0','0','0','0','0','0','0','0','0']] for d, x, y in solution: out[x][y] = str(d) print(''.join([a for b in out for a in b])) # Flatten 2d array There's probably a more elegant/pythonic way to do each code block, but this will get you a valid solution matrix: (Format lines were added during posting.) 842|713|695 913|652|847 675|498|213 ---+---+--- 354|267|189 189|345|726 267|189|534 ---+---+--- 521|974|368 438|526|971 796|831|452 It is a bit interesting seeing the similarities and differences between the posted article and Norvig's Sudoku solver[1]. I've always appreciated how Norvig is concise and still has intermediate representations for debugging (e.g. shows all of the possible digits for a cell that hasn't yet been solved). The article's solver is MUCH faster in non-exact cases: The "multiple solution" example from Norvig (which Norvig states takes 3 minutes to solve) is done in 10 ms using this solver (plus, it finds a different valid solution), and the "impossible solution" (which fails after 24 minutes) gives a StopIteration after 90 ms. [1] https://norvig.com/sudoku.html https://norvig.com/sudoku.html