ml-gsd
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    Interface OptimizePeaksOptions

    interface OptimizePeaksOptions {
        factorLimits?: number;
        fromTo?: Partial<FromTo>;
        groupingFactor?: number;
        maxNumberOfPeaks?: number;
        optimization?: OptimizationOptions;
        parameters?: Record<string, InitialParameter>;
        shape?: Shape1D;
    }
    Index

    Properties

    factorLimits? fromTo? groupingFactor? maxNumberOfPeaks? optimization? parameters? shape?

    Properties

    factorLimits?: number

    Width multiplier used to derive the default from / to bounds.

    2
    fromTo?: Partial<FromTo>

    Range over which the optimization is applied. Values default to firstPeak.x - firstPeak.width * factorLimits and lastPeak.x + lastPeak.width * factorLimits when omitted.

    {}
    groupingFactor?: number

    Multiplier applied to peak widths when deciding whether adjacent peaks should be grouped and optimized together.

    1
    maxNumberOfPeaks?: number

    Maximum number of peaks included in a single optimization group. When a group exceeds this size, it is recursively split.

    15
    optimization?: OptimizationOptions

    Kind and options of the algorithm used to optimize parameters.

    { kind: 'lm', options: { timeout: 10 } }
    parameters?: Record<string, InitialParameter>

    Per-parameter optimization options (for example x, y, fwhm, mu), allowing custom init/min/max/gradientDifference values.

    This follows the same structure as ml-spectra-fitting OptimizeOptions.parameters.

    undefined
    shape?: Shape1D

    Shape to use for optimization.

    { kind: 'gaussian' }

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