gnome.outputters.binary
=======================

.. py:module:: gnome.outputters.binary

.. autoapi-nested-parse::

   Binary Outputter
   For use in Gnome Analyst



Attributes
----------

.. autoapisummary::

   gnome.outputters.binary.le_dtype
   gnome.outputters.binary.header_dtype


Classes
-------

.. autoapisummary::

   gnome.outputters.binary.BinaryOutput


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

.. py:data:: le_dtype

.. py:data:: header_dtype

.. py:class:: BinaryOutput(filename, zip_output=True, **kwargs)

   Bases: :py:obj:`gnome.outputters.outputter.OutputterFilenameMixin`, :py:obj:`gnome.outputters.outputter.Outputter`


   class that outputs GNOME trajectory results on a time step by time step basis
   this is the format output by desktop GNOME for use in Gnome Analyst

   :param str filename: full path and basename of the zip file

   :param zip_output=True: whether to zip up the output binary files

   other arguments as defined in the Outputter class


   .. py:attribute:: name

      define as property in base class so all objects will have a name
      by default


   .. py:attribute:: output_dir


   .. py:attribute:: zip_output
      :value: True



   .. py:attribute:: filedir


   .. py:attribute:: file_num
      :value: 0



   .. py:attribute:: cleaned_up
      :value: False



   .. py:method:: prepare_for_model_run(model_start_time, spills, uncertain=False, **kwargs)

      .. function:: prepare_for_model_run(model_start_time,
                                          cache=None,
                                          uncertain=False,
                                          spills=None,
                                          **kwargs)

      Reset file_num and uncertainty

      This must be done in prepare_for_model_run because if model _state
      changes, it is rewound and re-run from the beginning.

      If there are existing output files, they are deleted here.

      This takes more than standard 'cache' argument. Some of these are
      required arguments - they contain None for defaults because non-default
      argument cannot follow default argument. Since cache is already 2nd
      positional argument for Renderer object, the required non-default
      arguments must be defined following 'cache'.

      If uncertainty is on, then SpillContainerPair object contains
      identical _data_arrays in both certain and uncertain SpillContainer's,
      the data itself is different, but they contain the same type of data
      arrays. If uncertain, then data arrays for uncertain spill container
      are written to separate files.

      .. note::
          Does not take any other input arguments; however, to keep the
          interface the same for all outputters, define kwargs in case
          future outputters require different arguments.



   .. py:method:: write_output(step_num, islast_step=False)

      Write data from time step to binary file



   .. py:method:: output_to_file(filename, sc)

      dump a timestep's data into binary files for Gnome Analyst



   .. py:method:: clean_output_files()

      deletes output files that may be around

      called by prepare_for_model_run

      here in case it needs to be called from elsewhere



   .. py:method:: post_model_run()

      This is where to clean up -- close files, etc.