Package Exports

ml-peak-shape-generator

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Readme

ml-peak-shape-generator

Peak shape generator, the current kind of shapes supported are:

Name	Equation
Gaussian	$y\cdot exp\left[-\frac{1}{2}\frac{\delta}{\sigma^2}\right]$
Lorentzian	$y\cdot\frac{\omega^2}{4\delta + \omega^2}$
Pseudo Voigt	$y \cdot\left[x_g\cdot exp\left[-\frac{1}{2}\frac{\delta}{\sigma^2}\right] + x_l\cdot\frac{\omega^2}{4\delta + \omega^2}\right]$

where

$\delta = \left(t - x\right)^2$	$\sigma = \frac{width}{2\sqrt{2 \cdot ln(2)}}$	$\omega = width$

Installation

$ npm i ml-peak-shape-generator

Usage

import { gaussian, lorentzian, pseudoVoigt} from 'ml-peak-shape-generator';

// It's possible to specify the windows size with factor option
let {data, fwhm} = gaussian({factor: 3.5, sd: 500});
// or fix the number of points as Full Width at Half Maximum
let {data, fwhm} = gaussian({factor: 3.5, fwhm: 500});

// It's possible to specify the windows size with factor option
let {data, fwhm} = loretzian({factor: 5, fwhm: 500});

// It's possible to specify the windows size with factor option
let {data, fwhm} = pseudoVoigt({{factor: 5, fwhm: 500}});

import { getShape, GAUSSIAN, LORENTZIAN, PSEUDO_VOIGT} from 'ml-peak-shape-generator';

// If you want to dynamically select a shape you can use the `getShape` method.
let {data, fwhm} = getShape(LORENTZIAN, {factor: 3.5, sd: 500});

It is also possible to get a function that allows to calculate y for any x

import { gaussianFct} from 'ml-peak-shape-generator';
const func = gaussianFct({ x: 0, y: 2, width: 0.2 });

You can create a class as well and add many peaks

const peakShapeGenerator = new PeakShapeGenerator({cacheSize:20});

let shape = peakShapeGenerator.getShape(GAUSSIAN, { fwhm: 500 });
let shape2 = peakShapeGenerator.getShape(GAUSSIAN, { fwhm: 500 });
// shape===shape2 true

let shape3 = peakShapeGenerator.getShape(GAUSSIAN, { fwhm: 100 });
// shape===shape3 false
let shape4 = peakShapeGenerator.getShape(GAUSSIAN, { fwhm: 100 });
// shape3===shape4 true

API Documentation

License

MIT