feat: add norm method (#57)

Add norm computation with frobenius and max norms.

Author: jajoe

__tests__/matrix/utility.js

@@ -110,6 +110,21 @@ describe('utility methods', () => {
         expect(() => m2.det()).toThrow(/square/);
     });
 
+    it('norm Frobenius', () => {
+        var m1 = new Matrix([[1, 1, 1], [3, 3, 3], [1, 1, 1]]);
+        expect(m1.norm()).toBeCloseTo(5.7445626465380286, 2);
+    });
+
+    it('norm Frobenius 2', () => {
+        var m1 = new Matrix([[1, 1, 1], [3, 3, 3], [1, 1, 1]]);
+        expect(m1.norm('frobenius')).toBeCloseTo(5.7445626465380286, 2);
+    });
+
+    it('norm max', () => {
+        var m1 = new Matrix([[1, 1, 1], [3, 3, 3], [1, 1, 1]]);
+        expect(m1.norm('max')).toBe(3);
+    });
+
     it('transpose rectangular', () => {
         var matrix = new Matrix([[0, 1, 2], [3, 4, 5]]);
         var transpose = matrix.transpose();

src/abstractMatrix.js

@@ -923,6 +923,27 @@ export default function AbstractMatrix(superCtor) {
             return prod;
         }
 
+        /**
+         * Returns the norm of a matrix.
+         * @param {string} type - "frobenius" (default) or "max" return resp. the Frobenius norm and the max norm.
+         * @return {number}
+         */
+        norm(type = 'frobenius') {
+            var result = 0;
+            if (type === 'max') {
+                return this.max();
+            } else if (type === 'frobenius') {
+                for (var i = 0; i < this.rows; i++) {
+                    for (var j = 0; j < this.columns; j++) {
+                        result = result + this.get(i, j) * this.get(i, j);
+                    }
+                }
+                return Math.sqrt(result);
+            } else {
+                throw new RangeError(`unknown norm type: ${type}`);
+            }
+        }
+
         /**
          * Computes the cumulative sum of the matrix elements (in place, row by row)
          * @return {Matrix} this