ml-regression-polynomial - npm Package Compare versions

Comparing version 3.0.0 to 3.0.1

lib-esm/index.d.ts

 import { type NumberArray } from 'cheminfo-types';
-import BaseRegression from 'ml-regression-base';
+import { BaseRegression } from 'ml-regression-base';
 interface PolynomialRegressionOptions {
@@ -4,0 +4,0 @@ interceptAtZero?: boolean;

lib-esm/index.js

 import { Matrix, MatrixTransposeView, solve } from 'ml-matrix';
-import BaseRegression, { checkArrayLength, maybeToPrecision, } from 'ml-regression-base';
+import { BaseRegression, checkArrayLength, maybeToPrecision, } from 'ml-regression-base';
 export class PolynomialRegression extends BaseRegression {
@@ -37,3 +37,3 @@ /**
         for (let k = 0; k < this.powers.length; k++) {
-            y += this.coefficients[k] * Math.pow(x, this.powers[k]);
+            y += this.coefficients[k] * x ** this.powers[k];
         }
@@ -140,3 +140,3 @@ return y;
             else {
-                F.set(i, k, Math.pow(x[i], powers[k]));
+                F.set(i, k, x[i] ** powers[k]);
             }
@@ -143,0 +143,0 @@ }

lib/index.d.ts

 import { type NumberArray } from 'cheminfo-types';
-import BaseRegression from 'ml-regression-base';
+import { BaseRegression } from 'ml-regression-base';
 interface PolynomialRegressionOptions {
@@ -4,0 +4,0 @@ interceptAtZero?: boolean;

lib/index.js

 "use strict";
-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 __setModuleDefault = (this && this.__setModuleDefault) || (Object.create ? (function(o, v) {
-    Object.defineProperty(o, "default", { enumerable: true, value: v });
-}) : function(o, v) {
-    o["default"] = v;
-});
-var __importStar = (this && this.__importStar) || function (mod) {
-    if (mod && mod.__esModule) return mod;
-    var result = {};
-    if (mod != null) for (var k in mod) if (k !== "default" && Object.prototype.hasOwnProperty.call(mod, k)) __createBinding(result, mod, k);
-    __setModuleDefault(result, mod);
-    return result;
-};
 Object.defineProperty(exports, "__esModule", { value: true });
 exports.PolynomialRegression = void 0;
 const ml_matrix_1 = require("ml-matrix");
-const ml_regression_base_1 = __importStar(require("ml-regression-base"));
-class PolynomialRegression extends ml_regression_base_1.default {
+const ml_regression_base_1 = require("ml-regression-base");
+class PolynomialRegression extends ml_regression_base_1.BaseRegression {
     /**
@@ -63,3 +40,3 @@ * @param x - independent or explanatory variable
         for (let k = 0; k < this.powers.length; k++) {
-            y += this.coefficients[k] * Math.pow(x, this.powers[k]);
+            y += this.coefficients[k] * x ** this.powers[k];
         }
@@ -167,3 +144,3 @@ return y;
             else {
-                F.set(i, k, Math.pow(x[i], powers[k]));
+                F.set(i, k, x[i] ** powers[k]);
             }
@@ -170,0 +147,0 @@ }

package.json

 {
   "name": "ml-regression-polynomial",
-  "version": "3.0.0",
+  "version": "3.0.1",
   "description": "Polynomial Regression",
@@ -39,15 +39,16 @@ "types": "./lib/index.d.ts",
   "devDependencies": {
-    "@vitest/coverage-v8": "^0.34.5",
-    "eslint": "^8.50.0",
-    "eslint-config-cheminfo-typescript": "^12.0.4",
-    "prettier": "^3.0.3",
-    "rimraf": "^5.0.5",
-    "typescript": "^5.2.2",
-    "vitest": "^0.34.5"
+    "@vitest/coverage-v8": "^1.6.0",
+    "eslint": "^8.56.0",
+    "eslint-config-cheminfo-typescript": "^12.4.0",
+    "ml-spectra-processing": "^14.5.0",
+    "prettier": "^3.2.5",
+    "rimraf": "^5.0.7",
+    "typescript": "^5.4.5",
+    "vitest": "^1.6.0"
   },
   "dependencies": {
-    "cheminfo-types": "^1.7.2",
-    "ml-matrix": "^6.10.5",
-    "ml-regression-base": "^3.0.0"
+    "cheminfo-types": "^1.7.3",
+    "ml-matrix": "^6.11.0",
+    "ml-regression-base": "^4.0.0"
   }
-}
+}

src/__tests__/test.test.ts

 import { NumberArray } from 'cheminfo-types';
+import { createRandomArray, xSum } from 'ml-spectra-processing';
 import { expect, it, describe } from 'vitest';
@@ -19,2 +20,15 @@
 describe('Polynomial regression', () => {
+  it('basic linear test', () => {
+    const size = 1000;
+    const x = new Array(size).fill(0).map((_, i) => i);
+    const y = new Array(size).fill(1);
+    const regression = new PolynomialRegression(x, y, 1, {
+      interceptAtZero: false,
+    });
+    let difference = 0;
+    for (let i = 0; i < size; i++) {
+      difference += Math.abs(regression.predict(x[i]) - y[i]);
+    }
+    expect(difference).closeTo(0, 1e-6);
+  });
   it('degree 2', () => {
@@ -120,2 +134,24 @@ const x = [-3, 0, 2, 4];
   });
+
+  it('white noise regression', () => {
+    const size = 1000000;
+    const x = new Array(size).fill(0).map((_, i) => i);
+    const y = Array.from(
+      createRandomArray({
+        seed: 0,
+        mean: 0,
+        distribution: 'normal',
+        length: size,
+      }),
+    );
+    const regression = new PolynomialRegression(x, y, 1, {
+      interceptAtZero: false,
+    });
+    const newY = [];
+    for (let i = 0; i < size; i++) {
+      newY.push(y[i] - regression.predict(x[i]));
+    }
+    const newSumY = xSum(newY);
+    expect(newSumY).toBeCloseTo(0, 1e-6);
+  });
 });

src/index.ts

 import { type NumberArray } from 'cheminfo-types';
 import { Matrix, MatrixTransposeView, solve } from 'ml-matrix';
-import BaseRegression, {
+import {
+  BaseRegression,
   checkArrayLength,
@@ -53,3 +54,3 @@ maybeToPrecision,
     for (let k = 0; k < this.powers.length; k++) {
-      y += this.coefficients[k] * Math.pow(x, this.powers[k]);
+      y += this.coefficients[k] * x ** this.powers[k];
     }
@@ -166,3 +167,3 @@ return y;
       } else {
-        F.set(i, k, Math.pow(x[i], powers[k]));
+        F.set(i, k, x[i] ** powers[k]);
       }
@@ -169,0 +170,0 @@ }

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Improved metrics

Total package byte prevSize

40918

increased by0.96%

Lines of code

681

increased by1.95%

Number of medium supply chain risk alerts

0

decreased by-100%

Worsened metrics

Dev dependency count

8

increased by14.29%

Dependency changes

• + Addedml-regression-base@4.0.0(transitive)

• - Removedml-regression-base@3.0.0(transitive)

• Updatedcheminfo-types@^1.7.3

• Updatedml-matrix@^6.11.0

• Updatedml-regression-base@^4.0.0