ml-gsd

global-spectral-deconvolution

Global Spectra Deconvolution + Peak optimizer

gsdis using an algorithm that is searching for inflection points to determine the position of peaks and the width of the peaks are between the 2 inflection points. The result of GSD yield to an array of object containing {x, y fwhm and width}. However this width is based on the inflection point and may be different from the 'fwhm' (Full Width Half Maximum).

The second algorithm (optimizePeaks) will optimize the width and FWHM to match the original peak.

API documentation

Parameters

minMaxRatio=0.00025 (0-1)

Threshold to determine if a given peak should be considered as a noise, bases on its relative height compared to the highest peak.

noiseLevel=0 (-inf, inf)

Noise threshold in spectrum units

maxCriteria=true [true||false]

Peaks are local maximum(true) or minimum(false)

smoothY=true [true||false]

Select the peak intensities from a smoothed version of the independent variables?

realTopDetection=false [true||false]

Use a quadratic optimizations with the peak and its 3 closest neighbors to determine the true x,y values of the peak?

sgOptions={windowSize: 5, polynomial: 3}

Savitzky-Golay parameters. windowSize should be odd; polynomial is the degree of the polynomial to use in the approximations. It should be bigger than 2.

heightFactor=0

Factor to multiply the calculated height (usually 2).

derivativeThreshold=0

Filters based on the amplitude of the first derivative

Post methods

GSD.broadenPeaks(peakList, {factor=2, overlap=false})

We enlarge the peaks and add the properties from and to. By default we enlarge of a factor 2 and we don't allow overlap.

GSD.joinBroadPeaks

broadRatio=0.00 (0-1)

If broadRatio is higher than 0, then all the peaks which second derivative smaller than broadRatio * maxAbsSecondDerivative will be marked with the soft mask equal to true.

GSD.optimizePeaks

Example

import { IsotopicDistribution } from 'mf-global';
import { gsd, optimizePeaks } from '../src';

// generate a sample spectrum of the form {x:[], y:[]}
const data = new IsotopicDistribution('C').getGaussian();

let peaks = gsd(data, {
  noiseLevel: 0,
  minMaxRatio: 0.00025, // Threshold to determine if a given peak should be considered as a noise
  realTopDetection: true,
  maxCriteria: true, // inverted:false
  smoothY: false,
  sgOptions: { windowSize: 7, polynomial: 3 },
});
console.log(peaks); // array of peaks {x, y, width, fwhw}, width = distance between inflection points
// GSD

let optimized = optimizePeaks(data, peaks);
console.log(optimized); // array of peaks {x, y, width, fwhm}.

License

MIT