ml-gsd/lib/post/optimizePeaks.d.ts

Global Spectral Deconvolution

import type { DataXY, FromTo } from 'cheminfo-types';
import type { Shape1D } from 'ml-peak-shape-generator';
import type { OptimizationOptions } from 'ml-spectra-fitting';
import type { Peak } from './optimizePeaksWithLogs.ts';
export interface OptimizePeaksOptions {
    /**
     * baseline
     */
    baseline?: number;
    /**
     * range to apply the optimization
     */
    fromTo?: Partial<FromTo>;
    /**
     * Shape to use for optimization
     * @default {kind:'gaussian'}
     */
    shape?: Shape1D;
    /**
     * Number of times we should multiply the width determining if the peaks have to be grouped and therefore optimized together
     * @default 1
     */
    groupingFactor?: number;
    /**
     * Define the min / max values
     * @default 2
     */
    factorLimits?: number;
    /**
     * it's specify the kind and options of the algorithm use to optimize parameters.
     */
    optimization?: OptimizationOptions;
}
/**
 * Optimize the position (x), max intensity (y), full width at half maximum (fwhm)
 * and the ratio of gaussian contribution (mu) if it's required. It currently supports three kind of shapes: gaussian, lorentzian and pseudovoigt
 * @param data - An object containing the x and y data to be fitted.
 * @param peakList - A list of initial parameters to be optimized. e.g. coming from a peak picking [{x, y, width}].
 */
export declare function optimizePeaks<T extends Peak>(data: DataXY, peakList: T[], options?: OptimizePeaksOptions): (T extends {
    id: string;
} ? import("./optimizePeaksWithLogs.ts").GSDPeakOptimizedID : import("../GSDPeakOptimized.ts").GSDPeakOptimized)[];
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