[Algorithm Design and Techniques]

Author: loiane

src/ts/algorithms/dynamic-programing/knapsack.ts

@@ -13,12 +13,12 @@ export function knapSack(capacity: number, weights: number[], values: number[],
         const a = values[i - 1] + kS[i - 1][w - weights[i - 1]];
         const b = kS[i - 1][w];
         kS[i][w] = a > b ? a : b; // max(a,b)
-        console.log(a + ' can be part of the solution');
+        // console.log(a + ' can be part of the solution');
       } else {
         kS[i][w] = kS[i - 1][w];
       }
     }
-    console.log(kS[i].join());
+    // console.log(kS[i].join());
   }
 
   // extra algorithm to find the items that are part of the solution
@@ -37,13 +37,13 @@ function findValues(
   let i = n;
   let k = capacity;
 
-  console.log('Items that are part of the solution:');
+  // console.log('Items that are part of the solution:');
 
   while (i > 0 && k > 0) {
     if (kS[i][k] !== kS[i - 1][k]) {
-      console.log(
+      /* console.log(
         'item ' + i + ' can be part of solution w,v: ' + weights[i - 1] + ',' + values[i - 1]
-      );
+      ); */
       i--;
       k = k - kS[i][k];
     } else {

src/ts/algorithms/dynamic-programing/longest-common-subsequence-print.ts

@@ -27,8 +27,8 @@ export function lcs(wordX: string, wordY: string) {
         solution[i][j] = l[i][j] === l[i - 1][j] ? 'top' : 'left';
       }
     }
-    console.log(l[i].join());
-    console.log(solution[i].join());
+    // console.log(l[i].join());
+    // console.log(solution[i].join());
   }
 
   printSolution(solution, wordX, m, n);
@@ -55,5 +55,5 @@ function printSolution(solution: Array<Array<string>>, wordX: string, m: number,
     x = solution[a][b];
   }
 
-  console.log('lcs: ' + answer);
+  // console.log('lcs: ' + answer);
 }

src/ts/algorithms/dynamic-programing/longest-common-subsequence.ts

@@ -22,7 +22,7 @@ export function lcs(wordX: string, wordY: string) {
         l[i][j] = a > b ? a : b; // max(a,b)
       }
     }
-    console.log(l[i].join());
+    // console.log(l[i].join());
   }
 
   return l[m][n];

src/ts/algorithms/dynamic-programing/matrix-chain-multiplication.ts

@@ -32,8 +32,8 @@ export function matrixChainOrder(p: number[]): number {
     }
   }
 
-  console.log(m);
-  console.log(s);
+  // console.log(m);
+  // console.log(s);
 
   printOptimalParenthesis(s, 1, n - 1);
 
@@ -42,11 +42,11 @@ export function matrixChainOrder(p: number[]): number {
 
 function printOptimalParenthesis(s: Array<Array<number>>, i: number, j: number) {
   if (i === j) {
-    console.log('A[' + i + ']');
+    // console.log('A[' + i + ']');
   } else {
-    console.log('(');
+    // console.log('(');
     printOptimalParenthesis(s, i, s[i][j]);
     printOptimalParenthesis(s, s[i][j] + 1, j);
-    console.log(')');
+    // console.log(')');
   }
 }

src/ts/algorithms/greedy/knapsack.ts

@@ -7,12 +7,12 @@ function knapSack(capacity: number, weights: number[], values: number[]) {
     if (weights[i] <= capacity - load) {
       val += values[i];
       load += weights[i];
-      console.log('using item ' + (i + 1) + ' for the solution');
+      // console.log('using item ' + (i + 1) + ' for the solution');
     } else {
       const r = (capacity - load) / weights[i];
       val += r * values[i];
       load += weights[i];
-      console.log('using ratio of ' + r + ' for item ' + (i + 1) + ' for the solution');
+      // console.log('using ratio of ' + r + ' for item ' + (i + 1) + ' for the solution');
     }
   }
   return val;