ml-regression-base - npm Package Compare versions

Comparing version 3.0.0 to 4.0.0

lib-esm/checkArrayLength.d.ts

@@ -8,3 +8,3 @@ import { NumberArray } from 'cheminfo-types';
  */
-export default function checkArrayLength(x: NumberArray, y: NumberArray): void;
+export declare function checkArrayLength(x: NumberArray, y: NumberArray): void;
 //# sourceMappingURL=checkArrayLength.d.ts.map

lib-esm/checkArrayLength.js

@@ -8,3 +8,3 @@ import { isAnyArray } from 'is-any-array';
  */
-export default function checkArrayLength(x, y) {
+export function checkArrayLength(x, y) {
     if (!isAnyArray(x) || !isAnyArray(y)) {
@@ -11,0 +11,0 @@ throw new TypeError('x and y must be arrays');

lib-esm/index.d.ts

@@ -1,27 +0,4 @@
-import { type NumberArray } from 'cheminfo-types';
-import checkArrayLength from './checkArrayLength';
-export { default as maybeToPrecision } from './maybeToPrecision';
-export interface RegressionScore {
-    r: number;
-    r2: number;
-    chi2: number;
-    rmsd: number;
-}
-export default class BaseRegression {
-    constructor();
-    predict(x: number): number;
-    predict(x: NumberArray): number[];
-    _predict(x: number): number;
-    train(): void;
-    toString(precision?: number): string;
-    toLaTeX(precision?: number): string;
-    /**
-     * 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: NumberArray, y: NumberArray): RegressionScore;
-}
-export { checkArrayLength, type NumberArray };
+export * from './BaseRegression';
+export * from './checkArrayLength';
+export * from './maybeToPrecision';
 //# sourceMappingURL=index.d.ts.map

lib-esm/index.js

@@ -1,82 +0,4 @@
-import { isAnyArray } from 'is-any-array';
-import checkArrayLength from './checkArrayLength';
-export { default as maybeToPrecision } from './maybeToPrecision';
-export default class BaseRegression {
-    constructor() {
-        if (new.target === BaseRegression) {
-            throw new Error('BaseRegression must be subclassed');
-        }
-    }
-    predict(x) {
-        if (typeof x === 'number') {
-            return this._predict(x);
-        }
-        else if (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');
-        }
-    }
-    // eslint-disable-next-line @typescript-eslint/no-unused-vars
-    _predict(x) {
-        throw new Error('_predict must be implemented');
-    }
-    train() {
-        // Do nothing for this package
-    }
-    // eslint-disable-next-line @typescript-eslint/no-unused-vars
-    toString(precision) {
-        return '';
-    }
-    // eslint-disable-next-line @typescript-eslint/no-unused-vars
-    toLaTeX(precision) {
-        return '';
-    }
-    /**
-     * 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) {
-        checkArrayLength(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),
-        };
-    }
-}
-export { checkArrayLength };
+export * from './BaseRegression';
+export * from './checkArrayLength';
+export * from './maybeToPrecision';
 //# sourceMappingURL=index.js.map

lib-esm/maybeToPrecision.d.ts

@@ -7,3 +7,3 @@ /**
  */
-export default function maybeToPrecision(number: number, figures?: number): string;
+export declare function maybeToPrecision(number: number, figures?: number): string;
 //# sourceMappingURL=maybeToPrecision.d.ts.map

lib-esm/maybeToPrecision.js

@@ -7,3 +7,3 @@ /**
  */
-export default function maybeToPrecision(number, figures) {
+export function maybeToPrecision(number, figures) {
     if (number < 0) {
@@ -10,0 +10,0 @@ number = 0 - number;

lib/checkArrayLength.d.ts

@@ -8,3 +8,3 @@ import { NumberArray } from 'cheminfo-types';
  */
-export default function checkArrayLength(x: NumberArray, y: NumberArray): void;
+export declare function checkArrayLength(x: NumberArray, y: NumberArray): void;
 //# sourceMappingURL=checkArrayLength.d.ts.map

lib/checkArrayLength.js

 "use strict";
 Object.defineProperty(exports, "__esModule", { value: true });
+exports.checkArrayLength = void 0;
 const is_any_array_1 = require("is-any-array");
@@ -18,3 +19,3 @@ /**
 }
-exports.default = checkArrayLength;
+exports.checkArrayLength = checkArrayLength;
 //# sourceMappingURL=checkArrayLength.js.map

lib/index.d.ts

@@ -1,27 +0,4 @@
-import { type NumberArray } from 'cheminfo-types';
-import checkArrayLength from './checkArrayLength';
-export { default as maybeToPrecision } from './maybeToPrecision';
-export interface RegressionScore {
-    r: number;
-    r2: number;
-    chi2: number;
-    rmsd: number;
-}
-export default class BaseRegression {
-    constructor();
-    predict(x: number): number;
-    predict(x: NumberArray): number[];
-    _predict(x: number): number;
-    train(): void;
-    toString(precision?: number): string;
-    toLaTeX(precision?: number): string;
-    /**
-     * 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: NumberArray, y: NumberArray): RegressionScore;
-}
-export { checkArrayLength, type NumberArray };
+export * from './BaseRegression';
+export * from './checkArrayLength';
+export * from './maybeToPrecision';
 //# sourceMappingURL=index.d.ts.map

lib/index.js

 "use strict";
-var __importDefault = (this && this.__importDefault) || function (mod) {
-    return (mod && mod.__esModule) ? mod : { "default": mod };
+var __createBinding = (this && this.__createBinding) || (Object.create ? (function(o, m, k, k2) {
+    if (k2 === undefined) k2 = k;
+    var desc = Object.getOwnPropertyDescriptor(m, k);
+    if (!desc || ("get" in desc ? !m.__esModule : desc.writable || desc.configurable)) {
+      desc = { enumerable: true, get: function() { return m[k]; } };
+    }
+    Object.defineProperty(o, k2, desc);
+}) : (function(o, m, k, k2) {
+    if (k2 === undefined) k2 = k;
+    o[k2] = m[k];
+}));
+var __exportStar = (this && this.__exportStar) || function(m, exports) {
+    for (var p in m) if (p !== "default" && !Object.prototype.hasOwnProperty.call(exports, p)) __createBinding(exports, m, p);
 };
 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');
-        }
-    }
-    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');
-        }
-    }
-    // eslint-disable-next-line @typescript-eslint/no-unused-vars
-    _predict(x) {
-        throw new Error('_predict must be implemented');
-    }
-    train() {
-        // Do nothing for this package
-    }
-    // eslint-disable-next-line @typescript-eslint/no-unused-vars
-    toString(precision) {
-        return '';
-    }
-    // eslint-disable-next-line @typescript-eslint/no-unused-vars
-    toLaTeX(precision) {
-        return '';
-    }
-    /**
-     * 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),
-        };
-    }
-}
-exports.default = BaseRegression;
+__exportStar(require("./BaseRegression"), exports);
+__exportStar(require("./checkArrayLength"), exports);
+__exportStar(require("./maybeToPrecision"), exports);
 //# sourceMappingURL=index.js.map

lib/maybeToPrecision.d.ts

@@ -7,3 +7,3 @@ /**
  */
-export default function maybeToPrecision(number: number, figures?: number): string;
+export declare function maybeToPrecision(number: number, figures?: number): string;
 //# sourceMappingURL=maybeToPrecision.d.ts.map

lib/maybeToPrecision.js

 "use strict";
 Object.defineProperty(exports, "__esModule", { value: true });
+exports.maybeToPrecision = void 0;
 /**
@@ -26,3 +27,3 @@ * Cast `number` to string. Optionally `digits` specifies significant figures.
 }
-exports.default = maybeToPrecision;
+exports.maybeToPrecision = maybeToPrecision;
 //# sourceMappingURL=maybeToPrecision.js.map

package.json

 {
   "name": "ml-regression-base",
-  "version": "3.0.0",
+  "version": "4.0.0",
   "description": "Base class for regression modules",
@@ -40,14 +40,14 @@ "main": "./lib/index.js",
   "dependencies": {
-    "cheminfo-types": "^1.7.2",
+    "cheminfo-types": "^1.7.3",
     "is-any-array": "^2.0.1"
   },
   "devDependencies": {
-    "@vitest/coverage-v8": "^0.34.1",
+    "@vitest/coverage-v8": "^1.6.0",
     "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"
+    "eslint-config-cheminfo-typescript": "^12.4.0",
+    "prettier": "^3.2.5",
+    "rimraf": "^5.0.7",
+    "typescript": "^5.4.5",
+    "vitest": "^1.6.0"
   }
 }

src/__tests__/checkArrayLength.test.ts

 import { expect, it, describe } from 'vitest';
 
-import checkArrayLength from '../checkArrayLength';
+import { checkArrayLength } from '..';
 
@@ -5,0 +5,0 @@ describe('checkArrayLength', () => {

src/__tests__/maybeToPrecision.test.ts

 import { expect, it, describe } from 'vitest';
 
-import maybeToPrecision from '../maybeToPrecision';
+import { maybeToPrecision } from '..';
 
@@ -5,0 +5,0 @@ describe('maybeToPrecision', () => {

src/checkArrayLength.ts

@@ -9,3 +9,3 @@ import { NumberArray } from 'cheminfo-types';
  */
-export default function checkArrayLength(x: NumberArray, y: NumberArray) {
+export function checkArrayLength(x: NumberArray, y: NumberArray) {
   if (!isAnyArray(x) || !isAnyArray(y)) {
@@ -12,0 +12,0 @@ throw new TypeError('x and y must be arrays');

src/index.ts

@@ -1,103 +0,3 @@
-import { type NumberArray } from 'cheminfo-types';
-import { isAnyArray } from 'is-any-array';
-
-import checkArrayLength from './checkArrayLength';
-
-export { default as maybeToPrecision } from './maybeToPrecision';
-
-export interface RegressionScore {
-  r: number;
-  r2: number;
-  chi2: number;
-  rmsd: number;
-}
-export default class BaseRegression {
-  constructor() {
-    if (new.target === BaseRegression) {
-      throw new Error('BaseRegression must be subclassed');
-    }
-  }
-
-  predict(x: number): number;
-  predict(x: NumberArray): number[];
-  predict(x: number | NumberArray) {
-    if (typeof x === 'number') {
-      return this._predict(x);
-    } else if (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');
-    }
-  }
-
-  // eslint-disable-next-line @typescript-eslint/no-unused-vars
-  _predict(x: number): number {
-    throw new Error('_predict must be implemented');
-  }
-
-  train() {
-    // Do nothing for this package
-  }
-
-  // eslint-disable-next-line @typescript-eslint/no-unused-vars
-  toString(precision?: number) {
-    return '';
-  }
-
-  // eslint-disable-next-line @typescript-eslint/no-unused-vars
-  toLaTeX(precision?: number) {
-    return '';
-  }
-
-  /**
-   * 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: NumberArray, y: NumberArray): RegressionScore {
-    checkArrayLength(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),
-    };
-  }
-}
-
-export { checkArrayLength, type NumberArray };
+export * from './BaseRegression';
+export * from './checkArrayLength';
+export * from './maybeToPrecision';

src/maybeToPrecision.ts

@@ -7,3 +7,3 @@ /**
  */
-export default function maybeToPrecision(number: number, figures?: number) {
+export function maybeToPrecision(number: number, figures?: number) {
   if (number < 0) {
@@ -10,0 +10,0 @@ number = 0 - number;

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

Fixed 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

34717

3.37%

Number of package files

42

27.27%

Lines of code

614

3.02%

Dependency changes

• Updated

  cheminfo-types@^1.7.3