Update Jacobi method parameter types

Author: nikoscham

src/methods/jacobiMethodScript.js

@@ -10,9 +10,9 @@
 
 /**
  * Solves a system of linear equations using the Jacobi iterative method
- * @param {Array<Array<number>>} A - The coefficient matrix (must be square)
- * @param {Array<number>} b - The right-hand side vector
- * @param {Array<number>} x0 - Initial guess for solution vector
+ * @param {array} A - The coefficient matrix (must be square)
+ * @param {array} b - The right-hand side vector
+ * @param {array} x0 - Initial guess for solution vector
  * @param {number} [maxIterations=100] - Maximum number of iterations
  * @param {number} [tolerance=1e-7] - Convergence tolerance
  * @returns {object} An object containing:
@@ -21,47 +21,47 @@
  *  - converged: Boolean indicating whether the method converged
  */
 export function jacobiMethod(A, b, x0, maxIterations = 100, tolerance = 1e-7) {
-    const n = A.length; // Size of the square matrix
-    let x = [...x0];    // Current solution (starts with initial guess)
-    let xNew = new Array(n); // Next iteration's solution
-    
-    for (let iteration = 0; iteration < maxIterations; iteration++) {
-        // Perform one iteration
-        for (let i = 0; i < n; i++) {
-            let sum = 0;
-            // Calculate sum of A[i][j] * x[j] for j ≠ i
-            for (let j = 0; j < n; j++) {
-                if (j !== i) {
-                    sum += A[i][j] * x[j];
-                }
-            }
-            // Update xNew[i] using the Jacobi formula
-            xNew[i] = (b[i] - sum) / A[i][i];
-        }
-        
-        // Check convergence
-        let maxDiff = 0;
-        for (let i = 0; i < n; i++) {
-            maxDiff = Math.max(maxDiff, Math.abs(xNew[i] - x[i]));
-        }
-        
-        // Update x for next iteration
-        x = [...xNew];
-        
-        // If difference is small enough, we've converged
-        if (maxDiff < tolerance) {
-            return {
-                solution: x,
-                iterations: iteration + 1,
-                converged: true
-            };
+  const n = A.length; // Size of the square matrix
+  let x = [...x0];    // Current solution (starts with initial guess)
+  let xNew = new Array(n); // Next iteration's solution
+  
+  for (let iteration = 0; iteration < maxIterations; iteration++) {
+    // Perform one iteration
+    for (let i = 0; i < n; i++) {
+      let sum = 0;
+      // Calculate sum of A[i][j] * x[j] for j ≠ i
+      for (let j = 0; j < n; j++) {
+        if (j !== i) {
+          sum += A[i][j] * x[j];
         }
+      }
+      // Update xNew[i] using the Jacobi formula
+      xNew[i] = (b[i] - sum) / A[i][i];
     }
 
-    // If we reach here, we didn't converge within maxIterations
-    return {
+    // Check convergence
+    let maxDiff = 0;
+    for (let i = 0; i < n; i++) {
+      maxDiff = Math.max(maxDiff, Math.abs(xNew[i] - x[i]));
+    }
+    
+    // Update x for next iteration
+    x = [...xNew];
+    
+    // If difference is small enough, we've converged
+    if (maxDiff < tolerance) {
+      return {
         solution: x,
-        iterations: maxIterations,
-        converged: false
-    };
+        iterations: iteration + 1,
+        converged: true
+      };
+    }
+  }
+  
+  // If we reach here, we didn't converge within maxIterations
+  return {
+    solution: x,
+    iterations: maxIterations,
+    converged: false
+  };
 }