Q: How do we use constraint propagation to solve the naked twins problem?
A: The idea of Constraint propagation is repeated application of the constraint as many times as possible until a solution is obtained, or the constraint can no longer be used to improve the solution.
Naked Twins is one of the best ways to improve the solvability of the sudoku. This identifies a pair of boxes corresponding to the same set of peers with same two numbers as possibilities and eliminate these values from all boxes that have these two boxes under consideration as peers. Naked twins is used together with eliminate and only-choice mentioned in the course to reduce the total number of probabilities.
Q: How do we use constraint propagation to solve the diagonal sudoku problem?
A: The best way to solve diagonal sudoku I set the diagonal constraint as a part of normal sudoku solver. Because of this, all the diagonal entries will have the corresponding diagonal entries as their peers. This will solve the diagonal constraint by not accepting the values that doesn’t solve the criteria.
This project requires Python 3.
We recommend students install Anaconda, a pre-packaged Python distribution that contains all of the necessary libraries and software for this project. Please try using the environment we provided in the Anaconda lesson of the Nanodegree.
Optionally, you can also install pygame if you want to see your visualization. If you've followed our instructions for setting up our conda environment, you should be all set.
If not, please see how to download pygame here.
solution.py- You'll fill this in as part of your solution.solution_test.py- Do not modify this. You can test your solution by runningpython solution_test.py.PySudoku.py- Do not modify this. This is code for visualizing your solution.visualize.py- Do not modify this. This is code for visualizing your solution.
To visualize your solution, please only assign values to the values_dict using the assign_value function provided in solution.py
Before submitting your solution to a reviewer, you are required to submit your project to Udacity's Project Assistant, which will provide some initial feedback.
The setup is simple. If you have not installed the client tool already, then you may do so with the command pip install udacity-pa.
To submit your code to the project assistant, run udacity submit from within the top-level directory of this project. You will be prompted for a username and password. If you login using google or facebook, visit this link for alternate login instructions.
This process will create a zipfile in your top-level directory named sudoku-.zip. This is the file that you should submit to the Udacity reviews system.