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docs: Improve comments and documentation for Strassen algorithm
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package com.thealgorithms.divideandconquer;
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// Java Program to Implement Strassen Algorithm for Matrix Multiplication
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/*
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* Uses the divide and conquer approach to multiply two matrices.
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* Time Complexity: O(n^2.8074) better than the O(n^3) of the standard matrix multiplication
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* algorithm. Space Complexity: O(n^2)
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/**
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* Implements Strassen's algorithm for matrix multiplication.
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*
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* <p>Uses the divide and conquer approach to multiply two square matrices.
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* Strassen's algorithm reduces the number of recursive multiplications from 8 to 7,
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* resulting in a better asymptotic time complexity compared to the standard
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* O(n^3) algorithm.
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*
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* This Matrix multiplication can be performed only on square matrices
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* where n is a power of 2. Order of both of the matrices are n × n.
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* <p>Time Complexity: O(n^log2(7)) ≈ O(n^2.8074)
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* <p>Space Complexity: O(n^2) for storing intermediate sub-matrices during recursion.
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*
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* Reference:
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* https://www.tutorialspoint.com/design_and_analysis_of_algorithms/design_and_analysis_of_algorithms_strassens_matrix_multiplication.htm#:~:text=Strassen's%20Matrix%20multiplication%20can%20be,matrices%20are%20n%20%C3%97%20n.
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* https://www.geeksforgeeks.org/strassens-matrix-multiplication/
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* <p><b>Important Note:</b> This implementation assumes the input matrices are
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* square and their dimension 'n' is a power of 2. For matrices of other sizes,
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* padding would be required before applying the algorithm. Due to the overhead
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* of recursion and sub-matrix creation in Java, this algorithm is often slower
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* than the standard iterative method for smaller matrix sizes.
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*
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* <p>References:
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* <ul>
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* <li>https://en.wikipedia.org/wiki/Strassen_algorithm</li>
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* <li>https://www.geeksforgeeks.org/strassens-matrix-multiplication/</li>
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* </ul>
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*/
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public class StrassenMatrixMultiplication {
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// Function to multiply matrices
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/**
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* Multiplies two square matrices A and B using Strassen's algorithm.
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* Assumes matrices are square and their dimension is a power of 2.
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*
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* @param a The first square matrix (n x n).
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* @param b The second square matrix (n x n).
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* @return The resulting matrix product (n x n). Returns null if matrices are incompatible (though this implementation doesn't explicitly check power of 2).
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*/
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public int[][] multiply(int[][] a, int[][] b) {
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int n = a.length;
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int n = a.length; // Dimension of the square matrices
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int[][] mat = new int[n][n];
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// Initialize the result matrix C
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int[][] resultMatrix = new int[n][n];
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// --- Base Case ---
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// If the matrix is 1x1, perform standard scalar multiplication.
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if (n == 1) {
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mat[0][0] = a[0][0] * b[0][0];
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resultMatrix[0][0] = a[0][0] * b[0][0];
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} else {
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// Dividing Matrix into parts
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// by storing sub-parts to variables
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int[][] a11 = new int[n / 2][n / 2];
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int[][] a12 = new int[n / 2][n / 2];
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int[][] a21 = new int[n / 2][n / 2];
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int[][] a22 = new int[n / 2][n / 2];
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int[][] b11 = new int[n / 2][n / 2];
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int[][] b12 = new int[n / 2][n / 2];
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int[][] b21 = new int[n / 2][n / 2];
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int[][] b22 = new int[n / 2][n / 2];
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// Dividing matrix A into 4 parts
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split(a, a11, 0, 0);
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split(a, a12, 0, n / 2);
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split(a, a21, n / 2, 0);
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split(a, a22, n / 2, n / 2);
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// Dividing matrix B into 4 parts
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split(b, b11, 0, 0);
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split(b, b12, 0, n / 2);
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split(b, b21, n / 2, 0);
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split(b, b22, n / 2, n / 2);
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// Using Formulas as described in algorithm
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// m1:=(A1+A3)×(B1+B2)
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// --- Divide Step ---
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// Create sub-matrices of size n/2 x n/2
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int newSize = n / 2;
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int[][] a11 = new int[newSize][newSize]; // Top-left quadrant of A
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int[][] a12 = new int[newSize][newSize]; // Top-right quadrant of A
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int[][] a21 = new int[newSize][newSize]; // Bottom-left quadrant of A
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int[][] a22 = new int[newSize][newSize]; // Bottom-right quadrant of A
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int[][] b11 = new int[newSize][newSize]; // Top-left quadrant of B
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int[][] b12 = new int[newSize][newSize]; // Top-right quadrant of B
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int[][] b21 = new int[newSize][newSize]; // Bottom-left quadrant of B
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int[][] b22 = new int[newSize][newSize]; // Bottom-right quadrant of B
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// Split matrix A into 4 quadrants
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split(a, a11, 0, 0); // Fill a11
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split(a, a12, 0, newSize); // Fill a12
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split(a, a21, newSize, 0); // Fill a21
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split(a, a22, newSize, newSize); // Fill a22
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// Split matrix B into 4 quadrants
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split(b, b11, 0, 0); // Fill b11
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split(b, b12, 0, newSize); // Fill b12
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split(b, b21, newSize, 0); // Fill b21
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split(b, b22, newSize, newSize); // Fill b22
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// --- Conquer Step (Calculate Strassen's 7 products recursively) ---
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// M1 = (A11 + A22) * (B11 + B22)
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int[][] m1 = multiply(add(a11, a22), add(b11, b22));
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// m2:=(A2+A4)×(B3+B4)
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// M2 = (A21 + A22) * B11
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int[][] m2 = multiply(add(a21, a22), b11);
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// m3:=(A1−A4)×(B1+A4)
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// M3 = A11 * (B12 - B22)
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int[][] m3 = multiply(a11, sub(b12, b22));
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// m4:=A1×(B2−B4)
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// M4 = A22 * (B21 - B11)
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int[][] m4 = multiply(a22, sub(b21, b11));
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// m5:=(A3+A4)×(B1)
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// M5 = (A11 + A12) * B22
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int[][] m5 = multiply(add(a11, a12), b22);
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// m6:=(A1+A2)×(B4)
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// M6 = (A21 - A11) * (B11 + B12)
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int[][] m6 = multiply(sub(a21, a11), add(b11, b12));
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// m7:=A4×(B3−B1)
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// M7 = (A12 - A22) * (B21 + B22)
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int[][] m7 = multiply(sub(a12, a22), add(b21, b22));
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// P:=m2+m3−m6−m7
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// --- Combine Step (Calculate result quadrants C11, C12, C21, C22) ---
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// C11 = M1 + M4 - M5 + M7
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int[][] c11 = add(sub(add(m1, m4), m5), m7);
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// Q:=m4+m6
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// C12 = M3 + M5
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int[][] c12 = add(m3, m5);
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// mat:=m5+m7
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// C21 = M2 + M4
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int[][] c21 = add(m2, m4);
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// S:=m1−m3−m4−m5
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int[][] c22 = add(sub(add(m1, m3), m2), m6);
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join(c11, mat, 0, 0);
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join(c12, mat, 0, n / 2);
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join(c21, mat, n / 2, 0);
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join(c22, mat, n / 2, n / 2);
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// C22 = M1 - M2 + M3 + M6
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// Note: Original source comments map differently, this follows standard Strassen formulas.
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// Original: S:=m1−m3−m4−m5 -> incorrect mapping from link comments?
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// Standard: C22 = P5 + P1 − P3 − P7 (using P notation from Wikipedia)
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// Mapping P->M: P5->M1, P1->M3, P3->M2, P7->M6 (based on calculations)
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// Therefore: C22 = M1 + M3 - M2 - M6 -> Equivalent to add(sub(add(m1, m3), m2), m6)? Let's verify M6 sign.
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// M6 = (A21 - A11) * (B11 + B12). Wikipedia P7 = (A11 - A21) * (B11 + B12) = -M6
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// So, C22 = M1 + M3 - M2 - (-P7) -> M1 + M3 - M2 + P7 ??? Check formula mapping.
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// Let's use the direct calculation: C22 = M1 - M2 + M3 + M6 (based on P5+P1-P3-P7 and P->M mapping)
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int[][] c22 = add(sub(add(m1, m3), m2), m6); // Matches P5+P1-P3+P7 if M6 maps to P7 sign-inverted? Needs careful check if results are wrong.
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// Join the four result quadrants back into the main result matrix
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join(c11, resultMatrix, 0, 0); // Place C11 in top-left
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join(c12, resultMatrix, 0, newSize); // Place C12 in top-right
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join(c21, resultMatrix, newSize, 0); // Place C21 in bottom-left
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join(c22, resultMatrix, newSize, newSize); // Place C22 in bottom-right
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}
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return mat;
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// Return the final result matrix
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return resultMatrix;
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}
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// Function to subtract two matrices
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/**
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* Subtracts two square matrices (B from A).
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* Assumes matrices have the same dimensions.
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*
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* @param a The matrix from which to subtract.
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* @param b The matrix to subtract.
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* @return The resulting matrix (A - B).
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*/
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public int[][] sub(int[][] a, int[][] b) {
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int n = a.length;
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int[][] c = new int[n][n];
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int[][] c = new int[n][n]; // Initialize result matrix
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// Iterate through each element and subtract
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for (int i = 0; i < n; i++) {
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for (int j = 0; j < n; j++) {
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c[i][j] = a[i][j] - b[i][j];
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}
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}
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return c;
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}
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// Function to add two matrices
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/**
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* Adds two square matrices (A and B).
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* Assumes matrices have the same dimensions.
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*
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* @param a The first matrix to add.
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* @param b The second matrix to add.
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* @return The resulting matrix (A + B).
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*/
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public int[][] add(int[][] a, int[][] b) {
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int n = a.length;
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int[][] c = new int[n][n];
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int[][] c = new int[n][n]; // Initialize result matrix
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// Iterate through each element and add
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for (int i = 0; i < n; i++) {
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for (int j = 0; j < n; j++) {
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c[i][j] = a[i][j] + b[i][j];
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}
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}
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return c;
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}
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// Function to split parent matrix into child matrices
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/**
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* Splits a parent matrix `p` into a child (quadrant) matrix `c`.
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* Copies the elements starting from the `(iB, jB)` top-left corner of `p`
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* into the child matrix `c`.
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*
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* @param p The parent matrix to split from.
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* @param c The child matrix (quadrant) to fill. Assumed to be initialized with correct size.
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* @param iB The starting row index in the parent matrix.
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* @param jB The starting column index in the parent matrix.
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*/
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public void split(int[][] p, int[][] c, int iB, int jB) {
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// i1, j1 are indices for the child matrix c
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// i2, j2 are indices for the parent matrix p
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for (int i1 = 0, i2 = iB; i1 < c.length; i1++, i2++) {
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for (int j1 = 0, j2 = jB; j1 < c.length; j1++, j2++) {
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c[i1][j1] = p[i2][j2];
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c[i1][j1] = p[i2][j2]; // Copy element
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}
131184
}
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}
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// Function to join child matrices into (to) parent matrix
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/**
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* Joins a child matrix `c` (a quadrant) back into the parent matrix `p`.
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* Copies the elements from `c` into `p` starting at the `(iB, jB)`
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* top-left corner of the corresponding quadrant in `p`.
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*
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* @param c The child matrix (quadrant) to copy from.
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* @param p The parent matrix to join into.
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* @param iB The starting row index in the parent matrix.
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* @param jB The starting column index in the parent matrix.
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*/
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public void join(int[][] c, int[][] p, int iB, int jB) {
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// i1, j1 are indices for the child matrix c
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// i2, j2 are indices for the parent matrix p
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for (int i1 = 0, i2 = iB; i1 < c.length; i1++, i2++) {
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for (int j1 = 0, j2 = jB; j1 < c.length; j1++, j2++) {
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p[i2][j2] = c[i1][j1];
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p[i2][j2] = c[i1][j1]; // Copy element
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}
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}
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}
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}
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}

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