skultrafast.lifetimemap
=======================

.. py:module:: skultrafast.lifetimemap


Functions
---------

.. autoapisummary::

   skultrafast.lifetimemap._make_base
   skultrafast.lifetimemap.start_ltm
   skultrafast.lifetimemap.start_ltm_multi


Module Contents
---------------

.. py:function:: _make_base(tup, taus: numpy.ndarray, w=0.1, add_coh: bool = True, add_const: bool = False, norm: bool = False)

.. py:function:: start_ltm(tup, taus, w=0.1, add_coh=False, use_cv=False, add_const=False, verbose=False, **kwargs)

   Calculate the lifetime density map for given data.

   :param tup: tuple with wl, t, data
   :type tup: datatuple
   :param taus: Used to build the basis vectors.
   :type taus: list of floats
   :param w: Used sigma for calculating the , by default 0.1.
   :type w: float, optional
   :param add_coh: If true, coherent contributions are added to the basis.
                   By default False.
   :type add_coh: bool, optional
   :param use_cv: Whether to use cross-validation, by default False
   :type use_cv: bool, optional
   :param add_const: Whether to add an explict constant, by default False
   :type add_const: bool, optional
   :param verbose: Wheater to be verobse, by default False
   :type verbose: bool, optional

   :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.
   :rtype: tuple of (linear_model, coefs, fit, alphas)


.. py:function:: start_ltm_multi(tup, taus, w=0.1, alpha=0.001, **kwargs)