skultrafast.lifetimemap

Module Contents

Functions

_make_base(tup, taus[, w, add_coh, add_const, norm])

start_ltm(tup, taus[, w, add_coh, use_cv, add_const, ...])

Calculate the lifetime density map for given data.

start_ltm_multi(tup, taus[, w, alpha])

skultrafast.lifetimemap._make_base(tup, taus: numpy.ndarray, w=0.1, add_coh: bool = True, add_const: bool = False, norm: bool = False)[source]
skultrafast.lifetimemap.start_ltm(tup, taus, w=0.1, add_coh=False, use_cv=False, add_const=False, verbose=False, **kwargs)[source]

Calculate the lifetime density map for given data.

Parameters:

  • tup (datatuple) – tuple with wl, t, data

  • taus (list of floats) – Used to build the basis vectors.

  • w (float, optional) – Used sigma for calculating the , by default 0.1.

  • add_coh (bool, optional) – If true, coherent contributions are added to the basis. By default False.

  • use_cv (bool, optional) – Whether to use cross-validation, by default False

  • add_const (bool, optional) – Whether to add an explict constant, by default False

  • verbose (bool, optional) – Wheater to be verobse, by default False

Returns:

The linear model is the used sklearn model. Coefs is the arrary of the coefficents, fit contains the resulting fit and alphas is an array of the applied alpha value when using cv.

Return type:

tuple of (linear_model, coefs, fit, alphas)

skultrafast.lifetimemap.start_ltm_multi(tup, taus, w=0.1, alpha=0.001, **kwargs)[source]