export class MSComparator {
    /**
     * Create a class that will be able to get the similarity between 2 spectra
     * The similarity is based on 'cosine' similarity. The goal is 2 prepare 2 vectors
     * on which the similarity is calculated.
     * The vectors are created by taking the mass and the intensity of the peaks.
     * @param {object} [options={}]
     * @param {number} [options.nbPeaks] - Before comparing spectra how many peaks should be kept
     * @param {number} [options.minNbCommonPeaks] - Minimum number of peaks in common to consider any similarity
     * @param {number} [options.minIntensity] - What is the minimal relative intensity to keep a peak
     * @param {number} [options.massPower=3] - High power will give more weight to the mass. If you would prefer to observe fragments you should use a number less than 1
     * @param {number} [options.intensityPower=0.6] - How important is the intensity. By default we don't give to much importance to it
     * @param {number[]} [options.selectedMasses] - List of allowed masses.
     * @param {number|Function} [options.delta=0.1] - Tolerance in Da (u) to consider 2 peaks as aligned. If a function is provided it will be called with the mass of the peak
     */
    constructor(options?: {
        nbPeaks?: number | undefined;
        minNbCommonPeaks?: number | undefined;
        minIntensity?: number | undefined;
        massPower?: number | undefined;
        intensityPower?: number | undefined;
        selectedMasses?: number[] | undefined;
        delta?: number | Function | undefined;
    });
    options: {
        nbPeaks?: number | undefined;
        minNbCommonPeaks?: number | undefined;
        minIntensity?: number | undefined;
        massPower: number;
        intensityPower: number;
        selectedMasses?: number[] | undefined;
        delta: number | Function;
    };
    cache: WeakMap<WeakKey, any>;
    /**
     * Get the similarity between a spectrum and a list of masses.
     * The main issue is that we don't have the intensity of the peaks.
     * So we will use the intensity of the closest peak.
     * @param {import('cheminfo-types').DataXY} dataXY
     * @param {number[]} masses
     */
    getSimilarityToMasses(dataXY: import("cheminfo-types").DataXY, masses: number[]): {
        nbCommonPeaks: number;
        nbPeaks1: number;
        nbPeaks2: number;
        tanimoto: number;
        cosine: number;
    };
    /**
     *
     * @param {import('cheminfo-types').DataXY} dataXY1
     * @param {import('cheminfo-types').DataXY} dataXY2
     */
    getSimilarity(dataXY1: import("cheminfo-types").DataXY, dataXY2: import("cheminfo-types").DataXY): {
        nbCommonPeaks: number;
        nbPeaks1: number;
        nbPeaks2: number;
        tanimoto: number;
        cosine: number;
    };
}
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