saved_chats/#35325

USER: https://codeforces.com/contest/1980/problem/E

BOT: Thanks! Now could you provide a link to the editorial.



USER: https://codeforces.com/blog/entry/130135

BOT: Would you like hints to help you solve the problem or an interactive explanation of the editorial (hint/editorial)? 



USER: interactive  explanation

BOT: Would you like hints to help you solve the problem or an interactive explanation of the editorial (hint/editorial)? 



USER: explanation

BOT: Would you like hints to help you solve the problem or an interactive explanation of the editorial (hint/editorial)? 



USER: editorial

BOT: Idea: senjougaharin Prepared by: senjougaharin
**Tutorial**
For each element, you can calculate its positions in both matrices. You can see that the rearrangement of rows does not affect the column positions of the elements being rearranged. Similarly, column rearrangement does not affect row positions. Since the permutation of rows affects the entire rows, for all elements that have the same position row in the original matrix, the position row in the resulting matrix must also match. Similarly, the columns must match.
In order to check the coincidence of rows and columns, let's count 4 arrays — the positions of rows and columns in the original and received matrices. Then you need to check that for all $$$x$$$ with the same row value in the original matrix, the row values in the resulting matrix are the same. Similarly, the values of the columns should be the same.
**Solution**
Let me know if you have any questions.



USER: How will i write an algo for this ? 

BOT: To determine if matrix `a` can be transformed into matrix `b` using the allowed operations, you need to compare the positions of elements in both matrices. First, create two mappings: one for the positions of elements in matrix `a` and another for the positions in matrix `b`. Each mapping will store the row and column indices of each element. Next, group elements by their row and column indices in both matrices. For each group of elements that share the same row in matrix `a`, ensure that their corresponding positions in matrix `b` also share the same row. Similarly, for each group of elements that share the same column in matrix `a`, ensure their corresponding positions in matrix `b` share the same column.

To implement this, iterate through each element in the matrices and populate the mappings with their respective positions. Then, for each unique row in matrix `a`, collect all elements that appear in that row and verify that these elements appear in the same row in matrix `b`. Repeat this process for columns. If all checks pass, it is possible to transform matrix `a` into matrix `b` using the allowed operations; otherwise, it is not.



USER: Let's try question A

BOT: To determine if matrix `a` can be transformed into matrix `b` using the allowed operations (swapping rows or columns), you need to compare the positions of elements in both matrices. Start by creating two dictionaries: one for the positions of elements in matrix `a` and another for the positions in matrix `b`. Each dictionary will map each element to its row and column indices. For example, if element `x` is at position (i, j) in matrix `a`, store this information in the dictionary for matrix `a`.

Next, verify that the relative positions of elements in both matrices are consistent. For each row in matrix `a`, collect all elements that appear in that row and check if these elements appear in the same row in matrix `b`. Similarly, for each column in matrix `a`, collect all elements that appear in that column and check if these elements appear in the same column in matrix `b`. If all elements in each row and column of matrix `a` can be matched to the same row and column in matrix `b`, then it is possible to transform matrix `a` into matrix `b` using the allowed operations. If any mismatch is found, the transformation is not possible.



USER: https://codeforces.com/contest/1980

BOT: To determine if matrix `a` can be transformed into matrix `b` using the allowed operations (swapping rows or columns), you need to compare the positions of elements in both matrices. Start by creating two mappings: one for the positions of elements in matrix `a` and another for the positions in matrix `b`. Each mapping will store the row and column indices of each element. For example, if element `x` is at position (i, j) in matrix `a`, store this information in the dictionary for matrix `a`. Do the same for matrix `b`.

Next, verify that the relative positions of elements in both matrices are consistent. For each unique row in matrix `a`, collect all elements that appear in that row and check if these elements appear in the same row in matrix `b`. Similarly, for each unique column in matrix `a`, collect all elements that appear in that column and check if these elements appear in the same column in matrix `b`. If all elements in each row and column of matrix `a` can be matched to the same row and column in matrix `b`, then it is possible to transform matrix `a` into matrix `b` using the allowed operations. If any mismatch is found, the transformation is not possible.



USER: Hint

BOT: To determine if matrix `a` can be transformed into matrix `b` using the allowed operations (swapping rows or columns), you need to ensure that the relative positions of elements in both matrices are consistent. Start by creating two dictionaries: one for the positions of elements in matrix `a` and another for the positions in matrix `b`. Each dictionary will map each element to its row and column indices. For example, if element `x` is at position (i, j) in matrix `a`, store this information in the dictionary for matrix `a`. Do the same for matrix `b`. This allows you to track where each element is located in both matrices.

Next, verify that the relative positions of elements in both matrices are consistent by comparing the rows and columns. For each unique row in matrix `a`, collect all elements that appear in that row and check if these elements appear in the same row in matrix `b`. Similarly, for each unique column in matrix `a`, collect all elements that appear in that column and check if these elements appear in the same column in matrix `b`. If all elements in each row and column of matrix `a` can be matched to the same row and column in matrix `b`, then it is possible to transform matrix `a` into matrix `b` using the allowed operations. If any mismatch is found, the transformation is not possible. This approach ensures that the structure of the permutation is preserved during the transformation.



USER: Hey

BOT: To determine if matrix `a` can be transformed into matrix `b` using the allowed operations (swapping rows or columns), you need to ensure that the relative positions of elements in both matrices are consistent. Start by creating two mappings: one for the positions of elements in matrix `a` and another for the positions in matrix `b`. Each mapping will store the row and column indices of each element. For instance, if element `x` is at position (i, j) in matrix `a`, store this information in the dictionary for matrix `a`. Do the same for matrix `b`. This allows you to track where each element is located in both matrices.

Next, verify that the relative positions of elements in both matrices are consistent by comparing the rows and columns. For each unique row in matrix `a`, collect all elements that appear in that row and check if these elements appear in the same row in matrix `b`. Similarly, for each unique column in matrix `a`, collect all elements that appear in that column and check if these elements appear in the same column in matrix `b`. If all elements in each row and column of matrix `a` can be matched to the same row and column in matrix `b`, then it is possible to transform matrix `a` into matrix `b` using the allowed operations. If any mismatch is found, the transformation is not possible. This approach ensures that the structure of the permutation is preserved during the transformation.