lineage.crossval
================

.. py:module:: lineage.crossval

.. autoapi-nested-parse::

   Cross validation.



Attributes
----------

.. autoapisummary::

   lineage.crossval.exe


Functions
---------

.. autoapisummary::

   lineage.crossval.hide_observation
   lineage.crossval.crossval
   lineage.crossval.output_LL


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

.. py:data:: exe

.. py:function:: hide_observation(lineages, percentage, rng=None)

   Taking a list of lineages and the percentage of cells want to be masked, it marks those x% negative.


.. py:function:: crossval(train_populations, num_states, rng=None)

   Perform cross validation for the experimental data which runs in parallel for all states.
   :param train_populations: the populations after applying hide_observation. This includes the list of list of lineages.
   :param hidden_indexes: is a list of list of np.arrays for each lineage,
   filled with zeros and ones. ones refer to the index of those cells that have been hidden.
   :param hidden_obs: list of list of tuples of observations that have been masked in the train_lineage.
   :param num_states: is a range of states we want to run the cross validation for.


.. py:function:: output_LL(complete_population, desired_num_states)

   Given the complete population, it masks 25% of cells and prepares the data for parallel fitting using crossval function.