Package Exports
- ml-gsd
- ml-gsd/src/gsd
- ml-gsd/src/post/broadenPeaks
This package does not declare an exports field, so the exports above have been automatically detected and optimized by JSPM instead. If any package subpath is missing, it is recommended to post an issue to the original package (ml-gsd) to support the "exports" field. If that is not possible, create a JSPM override to customize the exports field for this package.
Readme
global-spectral-deconvolution
Global Spectra Deconvolution + Peak optimizer
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.post.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.post.joinBroadPeaks
GSD.post.optimizePeaks
Example
var CC = require('chemcalc');
var Stat = require('ml-stat');
var peakPicking = require('ml-gsd');
var spectrum = CC.analyseMF('Cl2.Br2', {
isotopomers: 'arrayXXYY',
fwhm: 0.01,
gaussianWidth: 11
});
var xy = spectrum.arrayXXYY;
var x = xy[0];
var y = xy[1];
//Just a fake noiseLevel
var noiseLevel =
Stat.array.median(
y.filter(function(a) {
return a > 0;
})
) * 3;
var options = {
noiseLevel: noiseLevel,
minMaxRatio: 0,
broadRatio: 0,
smoothY: false,
realTopDetection: true
};
var result = peakPicking.gsd(x, y, options);
result = peakPicking.post.optimizePeaks(result, x, y, 1, 'gaussian');