chore!: remove default export and update dependencies

package.json

@@ -37,16 +37,16 @@
   },
   "homepage": "https://github.com/mljs/regression-base#readme",
   "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/BaseRegression.ts

@@ -0,0 +1,99 @@
+import { type NumberArray } from 'cheminfo-types';
+import { isAnyArray } from 'is-any-array';
+
+import { checkArrayLength } from './checkArrayLength';
+
+export interface RegressionScore {
+  r: number;
+  r2: number;
+  chi2: number;
+  rmsd: number;
+}
+export 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: number[] = 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),
+    };
+  }
+}

src/__tests__/test.test.ts → src/__tests__/BaseRegression.test.ts

@@ -1,6 +1,6 @@
 import { expect, it, describe } from 'vitest';
 
-import BaseRegression from '..';
+import { BaseRegression } from '..';
 
 class NoPredict extends BaseRegression {}
 class Basic extends BaseRegression {
@@ -17,6 +17,7 @@ class Basic extends BaseRegression {
 describe('base regression', () => {
   it('should not be directly constructable', () => {
     expect(() => {
+      // eslint-disable-next-line no-new
       new BaseRegression();
     }).toThrow(/BaseRegression must be subclassed/);
   });

src/__tests__/checkArrayLength.test.ts

@@ -1,6 +1,6 @@
 import { expect, it, describe } from 'vitest';
 
-import checkArrayLength from '../checkArrayLength';
+import { checkArrayLength } from '..';
 
 describe('checkArrayLength', () => {
   it('throws on different Length', () => {

src/__tests__/maybeToPrecision.test.ts

@@ -1,6 +1,6 @@
 import { expect, it, describe } from 'vitest';
 
-import maybeToPrecision from '../maybeToPrecision';
+import { maybeToPrecision } from '..';
 
 describe('maybeToPrecision', () => {
   it('positive number - no digit', () => {

src/checkArrayLength.ts

@@ -6,7 +6,7 @@ import { isAnyArray } from 'is-any-array';
  * @param y - second array
  * @throws if x or y are not the same length, or if they are not arrays
  */
-export default function checkArrayLength(x: NumberArray, y: NumberArray) {
+export function checkArrayLength(x: NumberArray, y: NumberArray) {
   if (!isAnyArray(x) || !isAnyArray(y)) {
     throw new TypeError('x and y must be arrays');
   }

src/index.ts

@@ -1,103 +1,3 @@
-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

@@ -4,7 +4,7 @@
  * @param figures
  * @returns - A string representation of `number`.
  */
-export default function maybeToPrecision(number: number, figures?: number) {
+export function maybeToPrecision(number: number, figures?: number) {
   if (number < 0) {
     number = 0 - number;
     if (typeof figures === 'number') {

tsconfig.json

@@ -5,10 +5,9 @@
     "moduleResolution": "node",
     "outDir": "lib",
     "sourceMap": true,
+    "skipLibCheck": true,
     "strict": true,
     "target": "es2020"
   },
-  "include": [
-    "./src/**/*"
-  ]
+  "include": ["./src/**/*"]
 }