feat!: update dependencies (#186)

It is always advisable to import individual packages, as it is much easier to track the breaking changes. 
Because we updated all the dependencies, numerous bug fixes, features, and breaking changes have been incorporated.

eslint.config.mjs

@@ -0,0 +1,16 @@
+import cheminfo from 'eslint-config-cheminfo';
+import globals from 'globals';
+
+export default [
+  ...cheminfo,
+  {
+    languageOptions: {
+      globals: {
+        ...globals.node,
+      },
+    },
+    rules: {
+      //      "camelcase": "off",
+    }
+  }
+]

package.json

@@ -4,15 +4,15 @@
   "description": "Machine learning tools",
   "main": "src/index.js",
   "scripts": {
-    "compile": "rollup -c",
     "build": "cheminfo-build --root ML",
+    "compile": "rollup -c",
     "eslint": "eslint src --cache",
     "eslint-fix": "npm run eslint -- --fix",
     "prepack": "npm run compile",
     "prettier": "prettier --check src",
     "prettier-write": "prettier --write src",
     "test": "npm run test-only && npm run eslint && npm run prettier",
-    "test-only": "jest --coverage"
+    "test-only": "vitest run --coverage"
   },
   "files": [
     "src",
@@ -71,38 +71,38 @@
     "ml-distance-matrix": "^2.0.1",
     "ml-fcnnls": "^3.0.0",
     "ml-fnn": "^5.0.0",
-    "ml-gsd": "^12.1.3",
+    "ml-gsd": "^12.1.8",
     "ml-hash-table": "^1.0.0",
     "ml-hclust": "^3.1.0",
     "ml-kernel": "^3.0.0",
     "ml-kmeans": "^6.0.0",
     "ml-knn": "^3.0.0",
     "ml-levenberg-marquardt": "^4.1.3",
-    "ml-matrix": "^6.11.0",
+    "ml-matrix": "^6.12.0",
     "ml-naivebayes": "^4.0.0",
     "ml-ngmca": "^1.0.0",
     "ml-pad-array": "^2.0.0",
     "ml-pca": "^4.1.1",
     "ml-performance": "^0.2.0",
     "ml-pls": "^4.3.2",
-    "ml-random": "^1.0.1",
+    "ml-random": "^2.0.0",
     "ml-random-forest": "^2.1.0",
-    "ml-regression": "^5.0.0",
+    "ml-regression": "^6.2.0",
     "ml-savitzky-golay": "^5.0.0",
     "ml-som": "^0.0.6",
     "ml-sparse-matrix": "^2.1.0",
-    "ml-xsadd": "^2.0.0",
+    "ml-xsadd": "^3.0.1",
     "num-sort": "^3.0.0"
   },
   "devDependencies": {
-    "@babel/plugin-transform-modules-commonjs": "^7.23.3",
-    "@types/jest": "^29.5.12",
+    "@babel/plugin-transform-modules-commonjs": "^7.25.7",
+    "@vitest/coverage-v8": "^2.1.3",
     "cheminfo-build": "^1.2.0",
-    "eslint": "^8.56.0",
-    "eslint-config-cheminfo": "^9.1.1",
+    "eslint": "^9.12.0",
+    "eslint-config-cheminfo": "^12.0.1",
     "esm": "^3.2.25",
-    "jest": "^29.7.0",
-    "prettier": "^3.2.4",
-    "rollup": "^4.9.6"
+    "prettier": "^3.3.3",
+    "rollup": "^4.24.0",
+    "vitest": "^2.1.3"
   }
 }

src/__tests__/index.test.js

@@ -1,8 +1,39 @@
-/* eslint-disable import/namespace */
+import { it, describe, expect } from 'vitest';
+
 import * as ML from '..';
 
 describe('Check all properties are defined', () => {
+  const objectsAndNbKeys = {
+    Distance: 42,
+    Similarity: 11,
+    Array: 11,
+    ArrayXY: 10,
+    BitArray: 12,
+    KMeans: 2,
+    HClust: 2,
+    NaiveBayes: 2,
+    CrossValidation: 6,
+    FCNNLS: 2,
+    MatrixLib: 36,
+    GSD: 7,
+  };
+
   it.each(Object.keys(ML))('Check %s', (key) => {
+    // if a function it should key should start with lowercase
+    // if a class it should key should start with uppercase
     expect(ML[key]).toBeDefined();
+
+    if (objectsAndNbKeys[key]) {
+      expect(typeof ML[key]).toBe('object');
+      expect(Object.keys(ML[key]).length).toBe(objectsAndNbKeys[key]);
+    } else if (key[0] === key[0].toUpperCase()) {
+      // should be a class
+      expect(typeof ML[key]).toBe('function');
+      expect(typeof ML[key].prototype).toBe('object');
+      expect(ML[key].prototype?.constructor).toBe(ML[key]);
+    } else {
+      // should be function
+      expect(typeof ML[key]).toBe('function');
+    }
   });
 });

src/index.js

@@ -2,31 +2,17 @@
 /* eslint-disable import/order */
 /* eslint-disable import/first */
 
-import { DecisionTreeClassifier, DecisionTreeRegression } from 'ml-cart';
-import {
-  RandomForestClassifier,
-  RandomForestRegression,
-} from 'ml-random-forest';
-
 // Try to keep this list in the same structure as the README.
 
 // Unsupervised learning
 export { PCA } from 'ml-pca';
-import * as HClust from 'ml-hclust';
-export { HClust };
-import * as KMeans from 'ml-kmeans';
-export { KMeans };
 
 // Supervised learning
-import * as NaiveBayes from 'ml-naivebayes';
-export { NaiveBayes };
+
 export { default as KNN } from 'ml-knn';
 export { PLS, KOPLS, OPLS, oplsNipals } from 'ml-pls';
-import * as CrossValidation from 'ml-cross-validation';
-export { CrossValidation };
+
 export { ConfusionMatrix } from 'ml-confusion-matrix';
-export { DecisionTreeClassifier };
-export { RandomForestClassifier };
 
 // Artificial neural networks
 export { default as FNN } from 'ml-fnn';
@@ -42,13 +28,9 @@ export {
   TheilSenRegression,
   RobustPolynomialRegression,
 } from 'ml-regression';
-export { DecisionTreeRegression };
-export { RandomForestRegression };
 
 // Optimization
 export { levenbergMarquardt } from 'ml-levenberg-marquardt';
-import * as FCNNLS from 'ml-fcnnls';
-export { FCNNLS };
 
 // Math
 import * as MatrixLib from 'ml-matrix';
@@ -61,7 +43,6 @@ const {
   QrDecomposition,
 } = MatrixLib;
 export {
-  MatrixLib,
   Matrix,
   SVD,
   EVD,
@@ -72,10 +53,9 @@ export {
 
 export { SparseMatrix } from 'ml-sparse-matrix';
 export { default as Kernel } from 'ml-kernel';
-import { distance, similarity } from 'ml-distance';
-export { distance as Distance, similarity as Similarity };
+export { distance as Distance, similarity as Similarity } from 'ml-distance';
 export { default as distanceMatrix } from 'ml-distance-matrix';
-export { default as XSadd } from 'ml-xsadd';
+export { XSadd } from 'ml-xsadd';
 export { nGMCA } from 'ml-ngmca';
 
 // Statistics
@@ -89,9 +69,7 @@ export { default as BitArray } from 'ml-bit-array';
 export { default as HashTable } from 'ml-hash-table';
 export { default as padArray } from 'ml-pad-array';
 export { default as binarySearch } from 'binary-search';
-export { default as Random } from 'ml-random';
-import * as GSD from 'ml-gsd';
-export { GSD };
+export { Random } from 'ml-random';
 
 import min from 'ml-array-min';
 import max from 'ml-array-max';
@@ -140,3 +118,15 @@ export const ArrayXY = {
   equallySpaced,
   filterX,
 };
+export { DecisionTreeClassifier, DecisionTreeRegression } from 'ml-cart';
+export {
+  RandomForestClassifier,
+  RandomForestRegression,
+} from 'ml-random-forest';
+export * as HClust from 'ml-hclust';
+export * as KMeans from 'ml-kmeans';
+export * as NaiveBayes from 'ml-naivebayes';
+export * as CrossValidation from 'ml-cross-validation';
+export * as FCNNLS from 'ml-fcnnls';
+export * as MatrixLib from 'ml-matrix';
+export * as GSD from 'ml-gsd';