fact_anal_exp_conv

TRXASprefitpack.mathfun.fact_anal_exp_conv(t: ndarray, fwhm: float, tau: ndarray, base: bool | None = True, irf: str | None = 'g', eta: float | None = None, intensity: ndarray | None = None, eps: ndarray | None = None) → ndarray[source]

Estimate the best coefficiets when full width at half maximum fwhm and life constant tau are given

When you fits your model to tscan data, you need to have good initial guess for not only life time of each component but also coefficients. To help this it solves linear least square problem to find best coefficients when fwhm and tau are given.

Supported instrumental response functions are

  1. ‘g’: gaussian distribution

  2. ‘c’: cauchy distribution

  3. ‘pv’: pseudo voigt profile

Parameters:

  • t – time

  • fwhm – full width at half maximum of instrumental response function

  • tau – life time for each component

  • base – whether or not include baseline [default: True]

  • irf –

    shape of instrumental response function [default: g]

    • ’g’: normalized gaussian distribution,

    • ’c’: normalized cauchy distribution,

    • ’pv’: pseudo voigt profile \((1-\eta)g(t, {fwhm}) + \eta c(t, {fwhm})\)

  • eta – mixing parameter for pseudo voigt profile (only needed for pseudo voigt profile)

  • intensity – intensity of time scan data to fit

  • eps – standard error of data

Returns:

Best coefficient for given fwhm and tau, if base is set to True then size of coefficient is num_comp + 1, otherwise is num_comp.

Note

the dimension of the intensity must be one.