xyObjectNormedY

.github/workflows/lactame-head.yml

@@ -7,7 +7,7 @@ on:
       - main
 
 env:
-  NODE_VERSION: 20.x
+  NODE_VERSION: 24.x
 
 jobs:
   deploy:

.github/workflows/lactame.yml

@@ -5,7 +5,7 @@ on:
     types: [published]
 
 env:
-  NODE_VERSION: 20.x
+  NODE_VERSION: 24.x
 
 jobs:
   deploy:

.github/workflows/typedoc.yml

@@ -6,7 +6,7 @@ on:
     types: [published]
 
 env:
-  NODE_VERSION: 20.x
+  NODE_VERSION: 24.x
   ENTRY_FILE: 'src/index.ts'
 
 jobs:

CHANGELOG.md

@@ -1,5 +1,33 @@
 # Changelog
 
+## [14.14.1](https://github.com/mljs/spectra-processing/compare/v14.14.0...v14.14.1) (2025-08-06)
+
+
+### Bug Fixes
+
+* support TypeScript 5.9 TypedArray changes ([18ac5a6](https://github.com/mljs/spectra-processing/commit/18ac5a6a003506ee47d20d9b8cb8f3c4fd215e7a))
+* **xWhittakerSmoother:** ensure baseline is initialized as Float64Array ([18ac5a6](https://github.com/mljs/spectra-processing/commit/18ac5a6a003506ee47d20d9b8cb8f3c4fd215e7a))
+* **xWhittakerSmoother:** use correct name to whittaker smoother ([#311](https://github.com/mljs/spectra-processing/issues/311)) ([18ac5a6](https://github.com/mljs/spectra-processing/commit/18ac5a6a003506ee47d20d9b8cb8f3c4fd215e7a))
+
+## [14.14.0](https://github.com/mljs/spectra-processing/compare/v14.13.0...v14.14.0) (2025-07-23)
+
+
+### Features
+
+* add matrixTranspose function ([#309](https://github.com/mljs/spectra-processing/issues/309)) ([0b00126](https://github.com/mljs/spectra-processing/commit/0b001263d25ca966a676360f7e54807232b6cc02))
+
+## [14.13.0](https://github.com/mljs/spectra-processing/compare/v14.12.0...v14.13.0) (2025-07-09)
+
+
+### Features
+
+* implement reimZeroFilling function ([#306](https://github.com/mljs/spectra-processing/issues/306)) ([9f02d91](https://github.com/mljs/spectra-processing/commit/9f02d9130e243e4948c718931e26771df7d1105e))
+
+
+### Bug Fixes
+
+* remove non-existent "zone" export ([#308](https://github.com/mljs/spectra-processing/issues/308)) ([d1d5777](https://github.com/mljs/spectra-processing/commit/d1d57776170777bcb5c79f924efff523f16720a7))
+
 ## [14.12.0](https://github.com/mljs/spectra-processing/compare/v14.11.0...v14.12.0) (2025-04-27)
 
 

eslint.config.mjs

@@ -1,5 +1,5 @@
-import cheminfo from 'eslint-config-cheminfo-typescript';
 import { defineConfig } from 'eslint/config';
+import cheminfo from 'eslint-config-cheminfo-typescript';
 
 export default defineConfig([
   ...cheminfo,
@@ -9,6 +9,7 @@ export default defineConfig([
       'jsdoc/lines-before-block': 'off',
       'no-loss-of-precision': 'off',
       '@typescript-eslint/prefer-for-of': 'off',
+      'unicorn/no-array-reverse': 'off',
       'unicorn/import-style': [
         'error',
         {

package.json

@@ -1,6 +1,6 @@
 {
   "name": "ml-spectra-processing",
-  "version": "14.12.0",
+  "version": "14.14.1",
   "description": "Various method to process spectra",
   "main": "./lib/index.js",
   "module": "./lib-esm/index.js",
@@ -46,10 +46,6 @@
       "node": "./lib/xyObject/index.js",
       "default": "./lib-esm/xyObject/index.js"
     },
-    "./zone": {
-      "node": "./lib/zone/index.js",
-      "default": "./lib-esm/zone/index.js"
-    },
     "./zones": {
       "node": "./lib/zones/index.js",
       "default": "./lib-esm/zones/index.js"
@@ -88,19 +84,19 @@
   },
   "homepage": "https://github.com/mljs/spectra-processing#readme",
   "devDependencies": {
-    "@types/node": "^22.15.2",
-    "@vitest/coverage-v8": "^3.1.2",
+    "@types/node": "^24.2.0",
+    "@vitest/coverage-v8": "^3.2.4",
     "cheminfo-build": "^1.2.1",
-    "eslint": "^9.25.1",
-    "eslint-config-cheminfo-typescript": "^18.0.0",
+    "eslint": "^9.32.0",
+    "eslint-config-cheminfo-typescript": "^19.0.0",
     "jest-matcher-deep-close-to": "^3.0.2",
     "jscpd": "^4.0.5",
     "ml-spectra-fitting": "^4.2.4",
-    "prettier": "^3.5.3",
+    "prettier": "^3.6.2",
     "rimraf": "^6.0.1",
     "spectrum-generator": "^8.1.0",
-    "typescript": "^5.8.3",
-    "vitest": "^3.1.2"
+    "typescript": "^5.9.2",
+    "vitest": "^3.2.4"
   },
   "dependencies": {
     "binary-search": "^1.3.6",

src/__tests__/__snapshots__/index.test.ts.snap

@@ -6,6 +6,7 @@ exports[`test existence of exported functions 1`] = `
   "reimAutoPhaseCorrection",
   "reimFFT",
   "reimPhaseCorrection",
+  "reimZeroFilling",
   "getOutputArray",
   "xAbsolute",
   "xAbsoluteMedian",
@@ -73,6 +74,7 @@ exports[`test existence of exported functions 1`] = `
   "xSum",
   "xUniqueSorted",
   "xVariance",
+  "xWhittakerSmoother",
   "xWhitakerSmoother",
   "xyReduce",
   "xyAlign",
@@ -132,6 +134,7 @@ exports[`test existence of exported functions 1`] = `
   "xyObjectMinMaxValues",
   "xyObjectMinXPoint",
   "xyObjectMinYPoint",
+  "xyObjectNormedY",
   "xyObjectSlotX",
   "xyObjectSortX",
   "xyObjectSumY",
@@ -164,6 +167,7 @@ exports[`test existence of exported functions 1`] = `
   "matrixZPivotRescale",
   "matrixZRescale",
   "matrixZRescalePerColumn",
+  "matrixTranspose",
   "createNumberArray",
   "createDoubleArray",
   "createFromToArray",

src/__tests__/index.test.ts

@@ -1,8 +1,9 @@
-import { expect, it } from 'vitest';
+import { expect, test } from 'vitest';
 
 import * as SpectraProcessing from '../index';
 
-it('test existence of exported functions', () => {
+test('test existence of exported functions', () => {
   const exports = Object.keys(SpectraProcessing);
+
   expect(exports).toMatchSnapshot();
 });

src/matrix/__tests__/matrixAbsoluteMedian.test.ts

@@ -8,5 +8,6 @@ test('matrixAbsoluteMedian', () => {
     [1, 2, 3],
   ];
   const absoluteMedian = matrixAbsoluteMedian(matrix);
+
   expect(absoluteMedian).toBe(2);
 });

src/matrix/__tests__/matrixApplyNumericalDecoding.test.ts

@@ -26,5 +26,6 @@ test('should return an array of numbers', () => {
   );
 
   const nonNumbers = matrix.flat().filter((value) => typeof value !== 'number');
+
   expect(nonNumbers).toHaveLength(0);
 });

src/matrix/__tests__/matrixAutoCorrelation.test.ts

@@ -9,12 +9,14 @@ test('simple', () => {
     [3, 1],
   ];
   const result = matrixAutoCorrelation(matrix);
+
   expect(result[0]).toBeCloseTo(1, 10);
   expect(result[1]).toBeCloseTo(-1, 10);
 });
 
 test('test matrixAutoCorrelation too small', () => {
   const matrix = [[0]];
+
   expect(() => matrixAutoCorrelation(matrix)).toThrow(
     'can not calculate info if matrix contains less than 2 rows',
   );

src/matrix/__tests__/matrixBoxPlot.test.ts

@@ -17,6 +17,7 @@ test('test matrixBoxPlot even', () => {
     [10, 100],
     [11, 110],
   ];
+
   expect(matrixBoxPlot(matrix)).toStrictEqual({
     q1: Float64Array.from([2.5, 25]),
     median: Float64Array.from([5.5, 55]),
@@ -28,6 +29,7 @@ test('test matrixBoxPlot even', () => {
 
 test('test matrixBoxPlot even small', () => {
   const matrix = [[0], [1], [2], [3], [4], [5]];
+
   expect(matrixBoxPlot(matrix)).toStrictEqual({
     q1: Float64Array.from([1]),
     median: Float64Array.from([2.5]),
@@ -39,6 +41,7 @@ test('test matrixBoxPlot even small', () => {
 
 test('test matrixBoxPlot odd', () => {
   const matrix = [[0], [1], [2], [3], [4], [5], [6], [7], [8], [9], [10]];
+
   expect(matrixBoxPlot(matrix)).toStrictEqual({
     q1: Float64Array.from([2]),
     median: Float64Array.from([5]),
@@ -50,6 +53,7 @@ test('test matrixBoxPlot odd', () => {
 
 test('test matrixBoxPlot odd small', () => {
   const matrix = [[0], [1], [2], [3], [4]];
+
   expect(matrixBoxPlot(matrix)).toStrictEqual({
     q1: Float64Array.from([0.5]),
     median: Float64Array.from([2]),
@@ -61,6 +65,7 @@ test('test matrixBoxPlot odd small', () => {
 
 test('test matrixBoxPlot too small', () => {
   const matrix = [[0], [1], [2], [4]];
+
   expect(() => matrixBoxPlot(matrix)).toThrow(
     'can not calculate info if matrix contains less than 5 rows',
   );

src/matrix/__tests__/matrixCenterZMean.test.ts

@@ -9,6 +9,7 @@ test('matrixCenterZMean', () => {
     [3, 1, 3, 1],
   ];
   const result = matrixCenterZMean(data);
+
   expect(result).toStrictEqual([
     Float64Array.from([-1, 1, 0, 0]),
     Float64Array.from([0, 0, -1, 1]),

src/matrix/__tests__/matrixCholeskySolver.test.ts

@@ -8,6 +8,7 @@ import { matrixCholeskySolver } from '../matrixCholeskySolver';
 import { matrixCuthillMckee } from '../matrixCuthillMckee';
 
 type Func = (b: NumberArray) => NumberArray;
+
 test('solve a least square system', () => {
   const x = xSequentialFillFromTo({ from: 0, to: Math.PI, size: 101 });
   const noise = x.map(() => Math.random() * 0.1 - 0.05);
@@ -22,17 +23,23 @@ test('solve a least square system', () => {
   const weighted = addWeights(upperTriangularNonZeros, y, weights);
 
   const cho = matrixCholeskySolver(weighted.leftHandSide, dimension) as Func;
+
   expect(cho).not.toBeNull();
+
   const smoothed = cho(weighted.rightHandSide);
+
   expect(smoothed[50]).toBeLessThan(0.2);
   expect(smoothed[50]).toBeGreaterThan(-0.2);
 
   //ignore the outlier, it implicates the smooth should pass closer to zero.
   weights[50] = 0;
   const weighted2 = addWeights(upperTriangularNonZeros, y, weights);
   const cho2 = matrixCholeskySolver(weighted.leftHandSide, dimension) as Func;
+
   expect(cho2).not.toBeNull();
+
   const smoothed2 = cho2(weighted2.rightHandSide);
+
   expect(smoothed2[50]).toBeLessThan(smoothed[50]);
 
   const permutationEncodedArray = matrixCuthillMckee(
@@ -46,6 +53,8 @@ test('solve a least square system', () => {
   ) as Func;
 
   expect(cho3).not.toBeNull();
+
   const smoothed3 = cho2(weighted2.rightHandSide);
-  expect(smoothed3[50]).toEqual(smoothed3[50]);
+
+  expect(smoothed3[50]).toStrictEqual(smoothed3[50]);
 });

src/matrix/__tests__/matrixClone.test.ts

@@ -6,6 +6,7 @@ import { datasetForEncoding } from './fixtures/encoding';
 
 test('should return an array of numbers', () => {
   const matrix = matrixClone(datasetForEncoding);
+
   expect(matrix).toStrictEqual(datasetForEncoding);
   expect(matrix).not.toBe(datasetForEncoding);
 });

src/matrix/__tests__/matrixColumnsCorrelation.test.ts

@@ -9,6 +9,7 @@ test('matrixColumnsCorrelation', () => {
     [3, 1, 3, 1],
   ];
   const result = matrixColumnsCorrelation(data);
+
   expect(result).toMatchCloseTo([
     Float64Array.from([1, -1, 1, -1]),
     Float64Array.from([-1, 1, -1, 1]),

src/matrix/__tests__/matrixCreateEmpty.test.ts

@@ -7,6 +7,7 @@ test('matrixCreateEmpty with default constructor', () => {
     nbColumns: 2,
     nbRows: 3,
   });
+
   expect(matrix).toHaveLength(3);
   expect(matrix[0]).toHaveLength(2);
   expect(matrix[0]).toBeInstanceOf(Float64Array);
@@ -24,11 +25,12 @@ test('matrixCreateEmpty with Array constructor', () => {
     nbRows: 3,
     ArrayConstructor: Array,
   });
+
   expect(matrix).toHaveLength(3);
   expect(matrix[0]).toHaveLength(2);
   expect(matrix[0]).toBeInstanceOf(Array);
 
-  expect(matrix).toEqual([
+  expect(matrix).toStrictEqual([
     [0, 0],
     [0, 0],
     [0, 0],
@@ -41,6 +43,7 @@ test('matrixCreateEmpty with Int16Array constructor', () => {
     nbRows: 3,
     ArrayConstructor: Int16Array,
   });
+
   expect(matrix).toHaveLength(3);
   expect(matrix[0]).toHaveLength(2);
   expect(matrix[0]).toBeInstanceOf(Int16Array);

src/matrix/__tests__/matrixCuthillMckee.test.ts

@@ -34,6 +34,7 @@ test('permutation to reduce bandwidth', () => {
     permutationEncodedArray,
     dimension,
   );
+
   expect(bandwidth(reducedBandwidthMatrix)).toBeLessThan(bandwidth(matrix));
 });
 

src/matrix/__tests__/matrixGetSubMatrix.test.ts

@@ -18,9 +18,11 @@ test('should extract submatrix correctly without duplication', () => {
 
   const subMatrix = matrixGetSubMatrix(matrix, options);
   const expectedResult = [new Float64Array([2, 3]), new Float64Array([5, 6])];
-  expect(subMatrix).toEqual(expectedResult);
+
+  expect(subMatrix).toStrictEqual(expectedResult);
 
   subMatrix[0][0] = 10;
+
   expect(matrix[0][1]).toBe(10);
 });
 
@@ -40,9 +42,11 @@ test('should extract submatrix correctly with duplication', () => {
 
   const subMatrix = matrixGetSubMatrix(matrix, options);
   const expectedResult = [new Float64Array([2, 3]), new Float64Array([5, 6])];
-  expect(subMatrix).toEqual(expectedResult);
+
+  expect(subMatrix).toStrictEqual(expectedResult);
 
   subMatrix[0][0] = 10;
+
   expect(matrix[0][1]).toBe(2);
 });
 

src/matrix/__tests__/matrixHistogram.test.ts

@@ -11,6 +11,7 @@ test('simple case', () => {
   ];
   const histogram = matrixHistogram(matrix, { nbSlots: 10, centerX: false });
   histogram.y = Array.from(histogram.y);
+
   expect(histogram.x).toStrictEqual([0, 1, 2, 3, 4, 5, 6, 7, 8, 9]);
   expect(histogram.y).toStrictEqual([1, 1, 2, 3, 3, 3, 3, 2, 1, 1]);
 });
@@ -26,6 +27,7 @@ test('absolute values', () => {
     absolute: true,
   });
   histogram.y = Array.from(histogram.y);
+
   expect(histogram.x).toStrictEqual([0, 1, 2, 3, 4]);
   expect(histogram.y).toStrictEqual([2, 2, 2, 2, 2]);
 });
@@ -42,6 +44,7 @@ test('logBaseX', () => {
     absolute: true,
   });
   histogram.y = Array.from(histogram.y);
+
   expect(histogram.x).toStrictEqual([1, 2, 3, 4, 5]);
   expect(histogram.y).toStrictEqual([2, 2, 2, 2, 2]);
 });
@@ -58,6 +61,7 @@ test('simple y log case', () => {
     centerX: false,
   });
   histogram.y = Array.from(histogram.y);
+
   expect(histogram.x).toStrictEqual([1, 2, 3, 4, 5, 6]);
   expect(histogram.y).toMatchCloseTo([
     1, 0.3010299956639812, 0.3010299956639812, 0.3010299956639812, 0,