hapsburg.postprocessing
=======================

.. py:module:: hapsburg.postprocessing

.. autoapi-nested-parse::

   Class for calling ROH from Posterior Data. Saves results as a .csv
   created by Pandas.
   Contains Sub-Classes, as well as factory Method.
   Pls always change parameters with set_params method!
   @ Author: Harald Ringbauer, 2019



Attributes
----------

.. autoapisummary::

   hapsburg.postprocessing.folder


Classes
-------

.. autoapisummary::

   hapsburg.postprocessing.PostProcessing
   hapsburg.postprocessing.PostProcessingX
   hapsburg.postprocessing.MMR_PostProcessing


Functions
---------

.. autoapisummary::

   hapsburg.postprocessing.load_Postprocessing


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

.. py:class:: PostProcessing(folder='', load=False, output=True, save=True)

   Bases: :py:obj:`object`


   Class that does PostProcessing of HAPSBURG output.
   Has Methods to save the output as


   .. py:attribute:: folder
      :value: ''



   .. py:attribute:: roh_df
      :value: []



   .. py:attribute:: cutoff_post
      :value: 0.999



   .. py:attribute:: roh_min_l_initial
      :value: 0.02



   .. py:attribute:: roh_min_l_final
      :value: 0.05



   .. py:attribute:: min_len1
      :value: 0.02



   .. py:attribute:: min_len2
      :value: 0.04



   .. py:attribute:: max_gap
      :value: 0.005



   .. py:attribute:: snps_extend
      :value: 0



   .. py:attribute:: merge
      :value: True



   .. py:attribute:: output
      :value: True



   .. py:attribute:: save
      :value: True



   .. py:attribute:: post
      :value: True



   .. py:method:: set_params(**kwargs)

      Set the Parameters.
      Takes keyworded arguments



   .. py:method:: load_data(folder='')

      Load and return genetic Map [l],
      positions [l] and Posterior0 [l]



   .. py:method:: merge_called_blocks(df, max_gap=0)

      Merge Blocks in Dataframe df and return merged Dataframe



   .. py:method:: snp_extend(df, r_map, snps_extend=0)

      Extend Blocks in df by # n_snps.
      Return dataframe of same size but with modified blocks



   .. py:method:: modify_posterior0(posterior0)

      Load and return the posterior.



   .. py:method:: create_df(starts, ends, starts_map, ends_map, l, l_map, iid, ch, roh_min_l, starts_pos=[], ends_pos=[])

      Create and returndthe hapROH dataframe.



   .. py:method:: call_roh(ch=0, iid='')

      Call ROH of Homozygosity from Posterior Data
      bigger than cutoff
      log: Whether Posterior is given in log space



   .. py:method:: clean_up(full=True)

      Removes all additional Data other than the
      ROH Calls and the ROH Ground Truth (To save space)



.. py:class:: PostProcessingX(folder='', load=False, output=True, save=True)

   Bases: :py:obj:`PostProcessing`


   Class to post-process IBD on the X of
   two males. Only difference: Two iids,
   which will get stored seperately.


   .. py:method:: create_df(starts, ends, starts_map, ends_map, l, l_map, iid, ch, roh_min_l, starts_pos=[], ends_pos=[])

      Create and returndthe hapROH dataframe.
      Difference: Here it is a IBD, so two iids are saved.



.. py:class:: MMR_PostProcessing(folder='', load=False, output=True, save=True)

   Bases: :py:obj:`PostProcessing`


   Class that does PostProcessing of HAPSBURG output.
   Same as PostProcessing but load Posterior differently


   .. py:method:: modify_posterior0(posterior0)

      Load and return the posterior. Don't do anything



.. py:function:: load_Postprocessing(folder='', method='Standard', output=True, save=True)

   Factory Method for PostProcessing class


.. py:data:: folder
   :value: './Simulated/1000G_Mosaic/TSI/ch3_10cm/output/iid0/chr3/'