Interface OptimizeOptions

Links parameters from multiple peaks into a shared optimization variable. The actual peak value is reconstructed as sharedVariable * factor + offset.

The kind and options of the algorithm use to optimize parameters.

Options of each parameter to be optimized. For example, for a pseudoVoigt shape this can include x, y, fwhm and mu values.

Each parameter can define init, min, max and gradientDifference to set the initial guess, bounds and finite-difference step. These options can be numbers or callbacks. Callback options receive the original peak values provided by the user. Each shape has defaults, so this can be undefined.

Kind of shape used for fitting.