chore: fix prettier

package.json

@@ -15,7 +15,7 @@
     "prepack": "npm run compile",
     "prettier": "prettier --check src",
     "prettier-write": "prettier --write src",
-    "test": "npm run test-coverage && npm run eslint",
+    "test": "npm run test-coverage && npm run eslint && npm run prettier",
     "test-only": "jest",
     "test-coverage": "jest --coverage"
   },
@@ -39,6 +39,7 @@
     "eslint": "^8.57.0",
     "eslint-config-cheminfo": "^9.2.0",
     "jest": "^29.7.0",
+    "prettier": "^3.2.5",
     "rollup": "^4.17.2"
   },
   "dependencies": {

src/__tests__/index.test.js

@@ -4,23 +4,14 @@ describe('Power regression', () => {
   it('basic test', () => {
     const x = [17.6, 26, 31.9, 38.9, 45.8, 51.2, 58.1, 64.7, 66.7, 80.8, 82.9];
     const y = [
-      159.9,
-      206.9,
-      236.8,
-      269.9,
-      300.6,
-      323.6,
-      351.7,
-      377.6,
-      384.1,
-      437.2,
-      444.7
+      159.9, 206.9, 236.8, 269.9, 300.6, 323.6, 351.7, 377.6, 384.1, 437.2,
+      444.7,
     ];
     const result = new PowerRegression(x, y);
 
     const expected = {
       A: 24.12989312,
-      B: 0.65949782
+      B: 0.65949782,
     };
     expect(result.A).toBeCloseTo(expected.A, 10e-4);
     expect(result.B).toBeCloseTo(expected.B, 10e-4);
@@ -43,7 +34,7 @@ describe('Power regression', () => {
     const regression = PowerRegression.load({
       name: 'powerRegression',
       A: 1,
-      B: -1
+      B: -1,
     });
 
     expect(regression.predict(4)).toStrictEqual(0.25);
@@ -52,19 +43,19 @@ describe('Power regression', () => {
     expect(model).toStrictEqual({
       name: 'powerRegression',
       A: 1,
-      B: -1
+      B: -1,
     });
   });
 
   it('test latex formatting of big / small numbers', () => {
     const regression = PowerRegression.load({
       name: 'powerRegression',
       A: 1000000000,
-      B: -0.000000001
+      B: -0.000000001,
     });
 
     expect(regression.toLaTeX(4)).toStrictEqual(
-      'f(x) = \\frac{1.000e^{+9}}{x^{1.000e^{-9}}}'
+      'f(x) = \\frac{1.000e^{+9}}{x^{1.000e^{-9}}}',
     );
   });
 });

src/index.js

@@ -1,7 +1,7 @@
 import {
   BaseRegression,
   checkArrayLength,
-  maybeToPrecision
+  maybeToPrecision,
 } from 'ml-regression-base';
 import { SimpleLinearRegression } from 'ml-regression-simple-linear';
 
@@ -26,14 +26,14 @@ export class PowerRegression extends BaseRegression {
     return {
       name: 'powerRegression',
       A: this.A,
-      B: this.B
+      B: this.B,
     };
   }
 
   toString(precision) {
     return `f(x) = ${maybeToPrecision(
       this.A,
-      precision
+      precision,
     )} * x^${maybeToPrecision(this.B, precision)}`;
   }
 
@@ -42,12 +42,12 @@ export class PowerRegression extends BaseRegression {
     if (this.B >= 0) {
       latex = `f(x) = ${maybeToPrecision(
         this.A,
-        precision
+        precision,
       )}x^{${maybeToPrecision(this.B, precision)}}`;
     } else {
       latex = `f(x) = \\frac{${maybeToPrecision(
         this.A,
-        precision
+        precision,
       )}}{x^{${maybeToPrecision(-this.B, precision)}}}`;
     }
     latex = latex.replace(/e([+-]?[0-9]+)/g, 'e^{$1}');