Find Anagram Mappings

class Solution {
public:
    const int shiftBits = 7;
    const int maskLastBits = (1 << shiftBits) - 1;
    
    vector<int> findAnagramMappings(vector<int>& A, vector<int>& B) {
        for (int idx = 0; idx < A.size(); idx++) {
            A[idx] = (A[idx] << shiftBits) + idx;
            B[idx] = (B[idx] << shiftBits) + idx;
        }
        
        sort(A.begin(), A.end());
        sort(B.begin(), B.end());
        
        vector<int> result(A.size());
        for (int idx = 0; idx < A.size(); idx++) {
            result[A[idx] & maskLastBits] = (B[idx] & maskLastBits);
        }

        return result;
    }
};

The code provides a solution for finding anagram mappings between two vectors, A and B, where each vector contains integer elements. The mapping is determined by the position of elements from A in B. Each element in the result vector corresponds to the index of the element in B that is an anagram of the element in A at the same index.

• The code defines two constants, shiftBits and maskLastBits, to manipulate indices and values during sorting for correlation.
• Each element in both A and B is re-encoded by shifting the element's value left by seven bits and then adding the original index. This encoding allows the sorting of vectors based on the original values while preserving the index information.
• After re-encoding, both vectors A and B are sorted.
• A result vector of the same size as A and B is prepared. The code then decodes the sorted lists using bitwise AND with maskLastBits to extract the original indices. The index from B (decoded) is placed at the index from A (decoded) in the result vector.

This method efficiently maps the indices of vector A to the corresponding indices in vector B where similar elements exist, leveraging bit manipulation and sorting.

class Solution {
  final int shiftAmount = 7;
  final int mask = (1 << shiftAmount) - 1;

  public int[] getAnagramMappings(int[] array1, int[] array2) {
    // Embed the index with the element
    for (int i = 0; i < array1.length; i++) {
      array1[i] = (array1[i] << shiftAmount) + i;
      array2[i] = (array2[i] << shiftAmount) + i;
    }

    // Sort arrays to align the original elements
    Arrays.sort(array1);
    Arrays.sort(array2);

    // Result array for storing mappings
    int[] resultMappings = new int[array1.length];
    for (int i = 0; i < array1.length; i++) {
      // Extract original indices and map them
      resultMappings[array1[i] & mask] = (array2[i] & mask);
    }

    return resultMappings;
  }
}

This solution in Java outlines a method to find anagram mappings between two integer arrays. The goal is to identify the indices of elements in array1 that correspond to the elements in array2 where both arrays are anagrams of each other. To achieve this, the logic involves manipulating and sorting data to align the arrays based on the values of the elements while also tracking their original positions. Follow these steps to understand the implementation:

1. The method getAnagramMappings takes two integer arrays array1 and array2 as parameters.

2. First, the code combines each element in the arrays with its respective index. This combination makes sorting the arrays based on the elements' values easier without losing the index information. Here, bitwise left shift and addition are used to embed the index with the element.

3. Next, both arrays are sorted. This sorting is based on the newly computed values from the previous step, which ensures that the actual values of the elements dictate the order post-sort.

4. A result array resultMappings is initialized to store the final mappings of indices. It is of the same length as input arrays.

5. Finally, the code iterates through the sorted arrays. Using bitwise AND operation with a mask, it extracts the original indices from the encoded values and maps them accordingly to reconstruct the index mapping between the two arrays.

This method effectively finds and records index mappings between two arrays that are anagrams of each other, relying on encoding indices and elements together, sorting, and then decoding them to achieve the correct mapping.