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 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 as a FWHM to match the original peak. After optimization the width with therefore be always FWHM whichever is the function used.

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.

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.

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

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}, width = distance between inflection points
// GSD

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

License

MIT

customlogic/global-spectral-deconvolution