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ml-gsd - npm Package Compare versions

Comparing version 6.6.2 to 6.6.3

src/__tests__/simpleShifted.js

7

CHANGELOG.md
# Changelog
### [6.6.3](https://www.github.com/mljs/global-spectral-deconvolution/compare/v6.6.2...v6.6.3) (2021-06-18)
### Bug Fixes
* maxCriteria=false gives more consistent results ([2652ec2](https://www.github.com/mljs/global-spectral-deconvolution/commit/2652ec265193207ff128348c8d0207d74e1b0c0c))
### [6.6.2](https://www.github.com/mljs/global-spectral-deconvolution/compare/v6.6.1...v6.6.2) (2021-05-11)

@@ -4,0 +11,0 @@

21

lib/index.js

@@ -60,17 +60,14 @@ 'use strict';

if (maxCriteria === false) {
for (let i = 0; i < y.length; i++) {
y[i] *= -1;
}
}
if (noiseLevel === undefined) {
noiseLevel = equalSpaced ? getNoiseLevel(y) : 0;
}
const yCorrection = { m: 1, b: noiseLevel };
if (!maxCriteria) {
yCorrection.m = -1;
yCorrection.b *= -1;
}
for (let i = 0; i < y.length; i++) {
y[i] = yCorrection.m * y[i] - yCorrection.b;
y[i] -= noiseLevel;
}
for (let i = 0; i < y.length; i++) {

@@ -224,3 +221,5 @@ if (y[i] < 0) {

x: frequency,
y: (yData[minddY[j]] + yCorrection.b) / yCorrection.m,
y: maxCriteria
? yData[minddY[j]] + noiseLevel
: -yData[minddY[j]] - noiseLevel,
width: widthProcessor(width),

@@ -227,0 +226,0 @@ soft: broadMask[j],

{
"name": "ml-gsd",
"version": "6.6.2",
"version": "6.6.3",
"description": "Global Spectra Deconvolution",

@@ -61,6 +61,6 @@ "main": "lib/index.js",

"cheminfo-build": "^1.1.10",
"eslint": "^7.26.0",
"eslint": "^7.27.0",
"eslint-config-cheminfo": "^5.2.4",
"esm": "^3.2.25",
"jest": "^26.6.3",
"jest": "^27.0.1",
"jest-matcher-deep-close-to": "^2.0.1",

@@ -71,3 +71,3 @@ "mf-global": "^1.3.6",

"prettier": "^2.3.0",
"rollup": "^2.47.0",
"rollup": "^2.50.1",
"spectrum-generator": "^4.7.1",

@@ -80,4 +80,4 @@ "xy-parser": "^3.1.1"

"ml-spectra-fitting": "^1.0.0",
"ml-spectra-processing": "^6.5.0"
"ml-spectra-processing": "^6.6.0"
}
}

@@ -10,9 +10,13 @@ import { toMatchCloseTo } from 'jest-matcher-deep-close-to';

let y = [];
let negY = [];
for (let i = 0; i < 10; i++) {
x.push(x.length);
y.push(0);
negY.push(0);
}
for (let i = 0; i <= 10; i++) {
x.push(x.length);
y.push(i > 5 ? 10 - i : i);
let newY = i > 5 ? 10 - i : i;
y.push(newY);
negY.push(-newY);
}

@@ -22,2 +26,3 @@ for (let i = 0; i < 10; i++) {

y.push(0);
negY.push(0);
}

@@ -43,2 +48,20 @@

it('gsd negative peak', () => {
let peaks = gsd(
{ x, y: negY },
{
realTopDetection: false,
maxCriteria: false,
smoothY: true,
sgOptions: {
windowSize: 5,
polynomial: 3,
},
},
);
expect(peaks[0].y).toBeCloseTo(-4.657, 3);
expect(peaks[0].base).toBeCloseTo(1.1956, 3);
expect(peaks[0].x).toStrictEqual(15);
});
it('gsd not realtop asymetric', () => {

@@ -45,0 +68,0 @@ let Y2 = y.slice(0);

@@ -50,17 +50,14 @@ import { getShapeGenerator } from 'ml-peak-shape-generator';

if (maxCriteria === false) {
for (let i = 0; i < y.length; i++) {
y[i] *= -1;
}
}
if (noiseLevel === undefined) {
noiseLevel = equalSpaced ? getNoiseLevel(y) : 0;
}
const yCorrection = { m: 1, b: noiseLevel };
if (!maxCriteria) {
yCorrection.m = -1;
yCorrection.b *= -1;
}
for (let i = 0; i < y.length; i++) {
y[i] = yCorrection.m * y[i] - yCorrection.b;
y[i] -= noiseLevel;
}
for (let i = 0; i < y.length; i++) {

@@ -214,3 +211,5 @@ if (y[i] < 0) {

x: frequency,
y: (yData[minddY[j]] + yCorrection.b) / yCorrection.m,
y: maxCriteria
? yData[minddY[j]] + noiseLevel
: -yData[minddY[j]] - noiseLevel,
width: widthProcessor(width),

@@ -217,0 +216,0 @@ soft: broadMask[j],

@@ -0,1 +1,2 @@

import { toMatchCloseTo } from 'jest-matcher-deep-close-to';
import { generateSpectrum } from 'spectrum-generator';

@@ -5,2 +6,4 @@

expect.extend({ toMatchCloseTo });
describe('optimizePeaks', () => {

@@ -19,2 +22,12 @@ it('Should throw because execution time is over timeout', () => {

let result = optimizePeaks(data, [{ x: 0.01, y: 0.9, width: 0.11 }]);
expect(result).toMatchCloseTo([
{
x: -3.419674049814014e-8,
y: 0.999994064595118,
width: 0.12000070163648587,
group: 0,
},
]);
const options = {

@@ -21,0 +34,0 @@ optimization: {

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