dcnum.write.event_stash
=======================

.. py:module:: dcnum.write.event_stash


Classes
-------

.. autoapisummary::

   dcnum.write.event_stash.EventStash


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

.. py:class:: EventStash(index_offset: int, feat_nevents: list[int])

   Sort events into predefined arrays for bulk access

   :param index_offset: This is the index offset at which we are working on.
                        Normally, `feat_nevents` is just a slice of a larger
                        array and `index_offset` defines at which position
                        it is taken.
   :param feat_nevents: List that defines how many events there are for each input
                        frame. If summed up, this defines `self.size`.


   .. py:attribute:: events

      Dictionary containing the event arrays


   .. py:attribute:: feat_nevents

      List containing the number of events per input frame


   .. py:attribute:: nev_idx

      Cumulative sum of `feat_nevents` for determining sorting offsets


   .. py:attribute:: size

      Number of events in this stash


   .. py:attribute:: num_frames

      Number of frames in this stash


   .. py:attribute:: index_offset

      Global offset compared to the original data instance.


   .. py:attribute:: indices_for_data

      Array containing the indices in the original data instance.
      These indices correspond to the events in `events`.


   .. py:attribute:: _tracker

      Private array that tracks the progress.


   .. py:method:: is_complete()

      Determine whether the event stash is complete (all events added)



   .. py:method:: add_events(index, events)

      Add events to this stash

      :param index: Global index (from input dataset)
      :type index: int
      :param events: Event dictionary
      :type events: dict



   .. py:method:: require_feature(feat, sample_data)

      Create a new empty feature array in `self.events` and return it

      :param feat: Feature name
      :param sample_data: Sample data for one event of the feature (used to determine
                          shape and dtype of the feature array)