mlNormalize

src/index-esm.ts

@@ -17,4 +17,5 @@ export * from './main/collision-detection';
 export * from './main/animation';
 export * from './main/circle-ellipse';
 export * from './main/sequence';
-export * from './main/statistics';
+export * from './main/statistics';
+export * from './main/ml';

src/index.ts

@@ -18,6 +18,7 @@ import * as animation from './main/animation';
 import * as circleEllipse from './main/circle-ellipse';
 import * as sequence from './main/sequence';
 import * as statistics from './main/statistics';
+import * as ml from './main/ml';
 
 const api = {
     ...vector,
@@ -40,6 +41,7 @@ const api = {
     ...circleEllipse,
     ...sequence,
     ...statistics,
+    ...ml,
 };
 
 declare global {
@@ -69,4 +71,5 @@ export * from './main/collision-detection';
 export * from './main/animation';
 export * from './main/circle-ellipse';
 export * from './main/sequence';
-export * from './main/statistics';
+export * from './main/statistics';
+export * from './main/ml';

src/main/ml.ts

@@ -0,0 +1,21 @@
+import { setDecimalPlaces } from './format';
+
+/**
+ * Returns a copy of array, where each value will be in the range [0, 1].
+ * const newValue = (value - array_min) / (array_max - array_min)
+ */
+export const mlNormalize = (data: number[], decimalPlaces = Infinity): number[] => {
+    const copy = [...data];
+
+    const min = Math.min(...copy);
+    const max = Math.max(...copy);
+
+    const diff = max - min;
+    if(diff === 0) return [0];
+
+    for(let i=0; i<copy.length; i++) {
+        copy[i] = setDecimalPlaces((copy[i] - min) / diff, decimalPlaces);
+    }
+
+    return copy;
+};

src/main/statistics.ts

@@ -1,8 +1,7 @@
+import { setDecimalPlaces } from './format';
 
 // -------------------- CENTRAL TENDENCY ----------------------------
 
-import { setDecimalPlaces } from './format';
-
 /**
  * Central tendency: Calculate the Average (mean)
  * Sum of all numbers divided by the array length.

test/ml.test.ts

@@ -0,0 +1,27 @@
+import { mlNormalize } from '../src/main/ml';
+
+describe('ML', () => {
+
+    describe('mlNormalize()', () => {
+
+        test('[]', () => {
+            expect(mlNormalize([])).toStrictEqual([]);
+        });
+
+        test('[2]', () => {
+            expect(mlNormalize([2])).toStrictEqual([0]);
+        });
+
+        test('[1, 2, 3]', () => {
+            expect(mlNormalize([1, 2, 3])).toStrictEqual([0, 0.5, 1]);
+        });
+
+        test('[-1, -2]', () => {
+            expect(mlNormalize([-1, -2])).toStrictEqual([1, 0]);
+        });
+
+        test('[1, 1, 2, 3, 4]', () => {
+            expect(mlNormalize([1, 1, 2, 3, 4], 2)).toStrictEqual([0, 0, 0.33, 0.67, 1]);
+        });
+    });
+});