ml

src/main/ml.ts

@@ -1,5 +1,6 @@
 import { setDecimalPlaces } from './format';
 import { getArithmeticMean, getStandardDeviation } from './statistics';
+import { IMlStandardizeResult } from '../types';
 
 /**
  * Returns a copy of array, where each value will be in the range [0, 1].
@@ -21,11 +22,28 @@ export const mlNormalize = (data: number[], decimalPlaces = Infinity): number[]
 };
 
 /**
- * Returns a copy of array, where each value will be in the range [-1, 1]
+ * Changes value to be in the range [-1, 1].
  */
-export const mlStandardize = (data: number[], decimalPlaces = Infinity): number[] => {
-    const copy = [...data];
-    const mean = getArithmeticMean(copy) ?? 0;
-    const stdDev = getStandardDeviation(copy, decimalPlaces);
-    return copy.map(val => (val - mean) / stdDev);
+export const mlStandardizeValue = (value: number, mean: number, stdDev: number, decimalPlaces = Infinity) : number => {
+    if(stdDev === 0) return 0;
+    return setDecimalPlaces((value - mean) / stdDev, decimalPlaces);
+};
+
+/**
+ * Returns a copy of array, where each value will be in the range [-1, 1].
+ */
+export const mlStandardizeArray = (data: number[], mean: number, stdDev: number, decimalPlaces = Infinity) : number[] => {
+    return [...data].map(value => mlStandardizeValue(value, mean, stdDev, decimalPlaces));
+};
+
+export const mlStandardizeTestData = (data: number[], decimalPlaces = Infinity): IMlStandardizeResult => {
+    const mean = getArithmeticMean(data) ?? 0;
+    const stdDev = getStandardDeviation(data);
+    const _data = mlStandardizeArray(data, mean, stdDev, decimalPlaces);
+
+    return {
+        mean: setDecimalPlaces(mean, decimalPlaces),
+        stdDev: setDecimalPlaces(stdDev, decimalPlaces),
+        data: _data,
+    };
 };

src/types.ts

@@ -34,4 +34,10 @@ export interface ICircle {
     r: number;
 }
 
-export type IPolygon = Vector2[];
+export type IPolygon = Vector2[];
+
+export interface IMlStandardizeResult {
+    mean: number;
+    stdDev: number;
+    data: number[];
+}

test/ml.test.ts

@@ -1,4 +1,4 @@
-import { mlNormalize } from '../src/main/ml';
+import { mlNormalize, mlStandardizeTestData } from '../src/main/ml';
 
 describe('ML', () => {
 
@@ -24,4 +24,45 @@ describe('ML', () => {
             expect(mlNormalize([1, 1, 2, 3, 4], 2)).toStrictEqual([0, 0, 0.33, 0.67, 1]);
         });
     });
+
+    describe('Standardize', () => {
+        it('returns an object with mean and standard deviation of 0 when data is empty', () => {
+            const result = mlStandardizeTestData([]);
+            expect(result.mean).toBe(0);
+            expect(result.stdDev).toBe(0);
+            expect(result.data).toStrictEqual([]);
+        });
+
+        it('returns an object with mean and standard deviation when data contains only one element', () => {
+            const result = mlStandardizeTestData([5]);
+            expect(result.mean).toBe(5);
+            expect(result.stdDev).toBe(0);
+            expect(result.data).toStrictEqual([0]);
+        });
+
+        it('returns the correct mean, standard deviation, and standardized data', () => {
+            const data = [2, 4, 4, 4, 5, 5, 7, 9];
+
+            // Expected mean and standard deviation (calculated manually)
+            const expectedMean = 5;
+            const expectedStdDev = 2;
+
+            // Expected standardized data (calculated manually)
+            const expectedData = [-1.5, -0.5, -0.5, -0.5, 0, 0, 1, 2];
+
+            // Call the function
+            const result = mlStandardizeTestData(data);
+
+            // Assert the mean, standard deviation, and standardized data
+            expect(result.mean).toBe(expectedMean);
+            expect(result.stdDev).toBe(expectedStdDev);
+            expect(result.data).toEqual(expectedData);
+        });
+
+        it('returns the mean and standard deviation with specified decimal places', () => {
+            const result = mlStandardizeTestData([1, 2, 3, 4, 5], 2);
+            expect(result.mean).toStrictEqual(3);
+            expect(result.stdDev).toStrictEqual(1.41);
+        });
+    });
 });