ml-regression-base - npm Package Compare versions

Comparing version 2.1.6 to 3.0.0

lib/index.js

@@ -1,121 +0,90 @@
-'use strict';
-
-Object.defineProperty(exports, '__esModule', { value: true });
-
-var isAnyArray = require('is-any-array');
-
-function maybeToPrecision(value, digits) {
-  if (value < 0) {
-    value = 0 - value;
-    if (typeof digits === 'number') {
-      return `- ${value.toPrecision(digits)}`;
-    } else {
-      return `- ${value.toString()}`;
+"use strict";
+var __importDefault = (this && this.__importDefault) || function (mod) {
+    return (mod && mod.__esModule) ? mod : { "default": mod };
+};
+Object.defineProperty(exports, "__esModule", { value: true });
+exports.checkArrayLength = exports.maybeToPrecision = void 0;
+const is_any_array_1 = require("is-any-array");
+const checkArrayLength_1 = __importDefault(require("./checkArrayLength"));
+exports.checkArrayLength = checkArrayLength_1.default;
+var maybeToPrecision_1 = require("./maybeToPrecision");
+Object.defineProperty(exports, "maybeToPrecision", { enumerable: true, get: function () { return __importDefault(maybeToPrecision_1).default; } });
+class BaseRegression {
+    constructor() {
+        if (new.target === BaseRegression) {
+            throw new Error('BaseRegression must be subclassed');
+        }
     }
-  } else {
-    if (typeof digits === 'number') {
-      return value.toPrecision(digits);
-    } else {
-      return value.toString();
+    predict(x) {
+        if (typeof x === 'number') {
+            return this._predict(x);
+        }
+        else if ((0, is_any_array_1.isAnyArray)(x)) {
+            const y = [];
+            for (const xVal of x) {
+                y.push(this._predict(xVal));
+            }
+            return y;
+        }
+        else {
+            throw new TypeError('x must be a number or array');
+        }
     }
-  }
-}
-
-function checkArraySize(x, y) {
-  if (!isAnyArray.isAnyArray(x) || !isAnyArray.isAnyArray(y)) {
-    throw new TypeError('x and y must be arrays');
-  }
-  if (x.length !== y.length) {
-    throw new RangeError('x and y arrays must have the same length');
-  }
-}
-
-class BaseRegression {
-  constructor() {
-    if (new.target === BaseRegression) {
-      throw new Error('BaseRegression must be subclassed');
+    // eslint-disable-next-line @typescript-eslint/no-unused-vars
+    _predict(x) {
+        throw new Error('_predict must be implemented');
     }
-  }
-
-  predict(x) {
-    if (typeof x === 'number') {
-      return this._predict(x);
-    } else if (isAnyArray.isAnyArray(x)) {
-      const y = [];
-      for (let i = 0; i < x.length; i++) {
-        y.push(this._predict(x[i]));
-      }
-      return y;
-    } else {
-      throw new TypeError('x must be a number or array');
+    train() {
+        // Do nothing for this package
     }
-  }
-
-  _predict() {
-    throw new Error('_predict must be implemented');
-  }
-
-  train() {
-    // Do nothing for this package
-  }
-
-  toString() {
-    return '';
-  }
-
-  toLaTeX() {
-    return '';
-  }
-
-  /**
-   * Return the correlation coefficient of determination (r) and chi-square.
-   * @param {Array<number>} x
-   * @param {Array<number>} y
-   * @return {object}
-   */
-  score(x, y) {
-    if (!isAnyArray.isAnyArray(x) || !isAnyArray.isAnyArray(y) || x.length !== y.length) {
-      throw new Error('x and y must be arrays of the same length');
+    // eslint-disable-next-line @typescript-eslint/no-unused-vars
+    toString(precision) {
+        return '';
     }
-
-    const n = x.length;
-    const y2 = new Array(n);
-    for (let i = 0; i < n; i++) {
-      y2[i] = this._predict(x[i]);
+    // eslint-disable-next-line @typescript-eslint/no-unused-vars
+    toLaTeX(precision) {
+        return '';
     }
-
-    let xSum = 0;
-    let ySum = 0;
-    let chi2 = 0;
-    let rmsd = 0;
-    let xSquared = 0;
-    let ySquared = 0;
-    let xY = 0;
-    for (let i = 0; i < n; i++) {
-      xSum += y2[i];
-      ySum += y[i];
-      xSquared += y2[i] * y2[i];
-      ySquared += y[i] * y[i];
-      xY += y2[i] * y[i];
-      if (y[i] !== 0) {
-        chi2 += ((y[i] - y2[i]) * (y[i] - y2[i])) / y[i];
-      }
-      rmsd += (y[i] - y2[i]) * (y[i] - y2[i]);
+    /**
+     * Return the correlation coefficient of determination (r) and chi-square.
+     * @param x - explanatory variable
+     * @param y - response variable
+     * @return - Object with further statistics.
+     */
+    score(x, y) {
+        (0, checkArrayLength_1.default)(x, y);
+        const n = x.length;
+        const y2 = new Array(n);
+        for (let i = 0; i < n; i++) {
+            y2[i] = this._predict(x[i]);
+        }
+        let xSum = 0;
+        let ySum = 0;
+        let chi2 = 0;
+        let rmsd = 0;
+        let xSquared = 0;
+        let ySquared = 0;
+        let xY = 0;
+        for (let i = 0; i < n; i++) {
+            xSum += y2[i];
+            ySum += y[i];
+            xSquared += y2[i] * y2[i];
+            ySquared += y[i] * y[i];
+            xY += y2[i] * y[i];
+            if (y[i] !== 0) {
+                chi2 += ((y[i] - y2[i]) * (y[i] - y2[i])) / y[i];
+            }
+            rmsd += (y[i] - y2[i]) * (y[i] - y2[i]);
+        }
+        const r = (n * xY - xSum * ySum) /
+            Math.sqrt((n * xSquared - xSum * xSum) * (n * ySquared - ySum * ySum));
+        return {
+            r,
+            r2: r * r,
+            chi2,
+            rmsd: Math.sqrt(rmsd / n),
+        };
     }
-
-    const r =
-      (n * xY - xSum * ySum) /
-      Math.sqrt((n * xSquared - xSum * xSum) * (n * ySquared - ySum * ySum));
-
-    return {
-      r: r,
-      r2: r * r,
-      chi2: chi2,
-      rmsd: Math.sqrt(rmsd / n),
-    };
-  }
 }
-
-exports.checkArrayLength = checkArraySize;
-exports["default"] = BaseRegression;
-exports.maybeToPrecision = maybeToPrecision;
+exports.default = BaseRegression;
+//# sourceMappingURL=index.js.map

package.json

 {
   "name": "ml-regression-base",
-  "version": "2.1.6",
+  "version": "3.0.0",
   "description": "Base class for regression modules",
-  "main": "lib/index.js",
-  "module": "src/index.js",
-  "types": "regression-base.d.ts",
+  "main": "./lib/index.js",
+  "module": "./lib-esm/index.js",
+  "types": "./lib/index.d.ts",
   "sideEffects": false,
   "files": [
-    "regression-base.d.ts",
+    "src",
     "lib",
-    "src"
+    "lib-esm"
   ],
   "scripts": {
-    "compile": "rollup -c",
+    "check-types": "tsc --noEmit",
+    "clean": "rimraf lib lib-esm",
     "eslint": "eslint src",
     "eslint-fix": "npm run eslint -- --fix",
-    "prepublishOnly": "npm run compile",
-    "test": "npm run test-coverage && npm run eslint",
-    "test-coverage": "jest --coverage",
-    "test-only": "jest"
+    "prepack": "npm run tsc",
+    "prettier": "prettier --check src",
+    "prettier-write": "prettier --write src",
+    "test": "npm run test-only && npm run eslint && npm run prettier && npm run check-types",
+    "test-only": "vitest run --coverage",
+    "tsc": "npm run clean && npm run tsc-cjs && npm run tsc-esm",
+    "tsc-cjs": "tsc --project tsconfig.cjs.json",
+    "tsc-esm": "tsc --project tsconfig.esm.json"
   },
@@ -34,16 +39,15 @@ "repository": {
   "homepage": "https://github.com/mljs/regression-base#readme",
-  "jest": {
-    "testEnvironment": "node"
-  },
   "dependencies": {
-    "is-any-array": "^2.0.0"
+    "cheminfo-types": "^1.7.2",
+    "is-any-array": "^2.0.1"
   },
   "devDependencies": {
-    "@babel/plugin-transform-modules-commonjs": "^7.16.8",
-    "eslint": "^8.7.0",
-    "eslint-config-cheminfo": "^7.2.1",
-    "jest": "^27.4.7",
-    "prettier": "^2.5.1",
-    "rollup": "^2.65.0"
+    "@vitest/coverage-v8": "^0.34.1",
+    "eslint": "^8.46.0",
+    "eslint-config-cheminfo-typescript": "^12.0.4",
+    "prettier": "^3.0.1",
+    "rimraf": "^5.0.1",
+    "typescript": "^5.1.6",
+    "vitest": "^0.34.1"
   }
 }

README.md

@@ -57,5 +57,5 @@ # regression-base
 [codecov-url]: https://codecov.io/gh/mljs/regression-base
-[ci-image]: https://github.com/mljs/regression-base/workflows/Node.js%20CI/badge.svg?branch=master
+[ci-image]: https://github.com/mljs/regression-base/workflows/Node.js%20CI/badge.svg?branch=main
 [ci-url]: https://github.com/mljs/regression-base/actions?query=workflow%3A%22Node.js+CI%22
 [download-image]: https://img.shields.io/npm/dm/ml-regression-base.svg
 [download-url]: https://npmjs.org/package/ml-regression-base

New alerts

Major refactor

Supply chain risk

Package has recently undergone a major refactor. It may be unstable or indicate significant internal changes. Use caution when updating to versions that include significant changes.

Found 1 instance in 1 package

Improved metrics

Total package byte prevSize

33585

93.43%

Number of package files

33

175%

Lines of code

596

69.8%

Worsened metrics

Dependency count

2

100%

Dev dependency count

7

16.67%

Number of medium supply chain risk alerts

1

Infinity%

Dependency changes

• + Added

  cheminfo-types@^1.7.2

• + Added

  cheminfo-types@1.8.1
  (transitive)

• Updated

  is-any-array@^2.0.1