:py:mod:`km3modules.io`
=======================

.. py:module:: km3modules.io


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

Classes
~~~~~~~

.. autoapisummary::

   km3modules.io.HitsTabulator
   km3modules.io.MCTracksTabulator
   km3modules.io.RecoTracksTabulator
   km3modules.io.EventInfoTabulator
   km3modules.io.OfflineHeaderTabulator




Attributes
~~~~~~~~~~

.. autoapisummary::

   km3modules.io.USR_MC_TRACKS_KEYS


.. py:data:: USR_MC_TRACKS_KEYS
   :value: [b'energy_lost_in_can', b'bx', b'by', b'ichan', b'cc']

   

.. py:class:: HitsTabulator(name=None, **parameters)




   
   Create `kp.Table` from hits provided by `km3io`.


   :Parameters:

       **kind: str**
           The kind of hits to tabulate:
             "offline": the hits in an offline file
             "online": snapshot and triggered hits (will be combined)
             "mc": MC hits

       **split: bool (default: True)**
           Defines whether the hits should be split up into individual arrays
           in a single group (e.g. hits/dom_id, hits/channel_id) or stored
           as a single HDF5Compound array (e.g. hits).














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   .. py:method:: configure()

      
      Configure module, like instance variables etc.
















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   .. py:method:: process(blob)

      
      Knead the blob and return it
















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.. py:class:: MCTracksTabulator(name=None, **parameters)




   
   Create `kp.Table` from MC tracks provided by `km3io`.


   :Parameters:

       **split: bool (default: False)**
           Defines whether the tracks should be split up into individual arrays
           in a single group (e.g. mc_tracks/by, mc_tracks/origin) or stored
           as a single HDF5Compound array (e.g. mc_tracks).

       **read_usr_data: bool (default: False)**
           Parses usr-data which is originally meant for user stored values, but
           was abused by generator software to store properties. This issue will
           be sorted out hopefully soon as it dramatically decreases the processing
           performance and usability.














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   .. py:method:: configure()

      
      Configure module, like instance variables etc.
















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          !! processed by numpydoc !!

   .. py:method:: process(blob)

      
      Knead the blob and return it
















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.. py:class:: RecoTracksTabulator(name=None, **parameters)




   
   Create `kp.Table` from recostruced tracks provided by `km3io`.


   :Parameters:

       **best_tracks: bool (default: False)**
           Additionally determine best track.

       **split: bool (default: False)**
           Defines whether the tracks should be split up into individual arrays
           in a single group (e.g. reco/tracks/dom_id, reco/tracks/channel_id) or stored
           as a single HDF5Compound array (e.g. reco/tracks).














   ..
       !! processed by numpydoc !!
   .. py:method:: configure()

      
      Configure module, like instance variables etc.
















      ..
          !! processed by numpydoc !!

   .. py:method:: process(blob)

      
      Knead the blob and return it
















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          !! processed by numpydoc !!


.. py:class:: EventInfoTabulator(name=None, **parameters)




   
   Create `kp.Table` from event information provided by `km3io`.
















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   .. py:method:: process(blob)

      
      Knead the blob and return it
















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.. py:class:: OfflineHeaderTabulator(name=None, **parameters)




   
   The module which can be attached to the pipeline
















   ..
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   .. py:method:: process(blob)

      
      Knead the blob and return it
















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