saftig.evaluation.dataset
=========================

.. py:module:: saftig.evaluation.dataset

.. autoapi-nested-parse::

   A representation of a dataset for the evaluation of noise mitigation methods.



Attributes
----------

.. autoapisummary::

   saftig.evaluation.dataset.NDArrayF


Classes
-------

.. autoapisummary::

   saftig.evaluation.dataset.EvaluationDataset


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

.. py:data:: NDArrayF

.. py:class:: EvaluationDataset(sample_rate, witness_conditioning, target_conditioning, witness_evaluation, target_evaluation, signal_conditioning = None, signal_evaluation = None, name = 'Unnamed', target_unit = '1')

   A representation of a dataset for the evaluation of noise mitigation methods.

   Provided sequences will be stored as immutable float64 numpy arrays.

   :param sample_rate: Sample rate in Hz
   :param witness_conditioning: witness channel data for the conditioning
       format: witness_conditioning[sequence_idx][channel_idx][sample_idx]
   :param target_conditioning: target channel data for the conditioning
       format: witness_conditioning[sequence_idx][sample_idx]
   :param witness_evaluation: witness channel data for the evaluation
   :param target_evaluation: target channel data for the evaluation
   :param signal_conditioning: (Optional) A signal that can be subtracted from the target for performance metrics
   :param signal_evaluation: (Optional) A signal that can be subtracted from the target for performance metrics
   :param name: (Optional) a string describing the dataset


   .. py:attribute:: sample_rate
      :type:  float


   .. py:attribute:: witness_conditioning
      :type:  collections.abc.Sequence[collections.abc.Sequence[NDArrayF]]


   .. py:attribute:: target_conditioning
      :type:  collections.abc.Sequence[NDArrayF]


   .. py:attribute:: witness_evaluation
      :type:  collections.abc.Sequence[collections.abc.Sequence[NDArrayF]]


   .. py:attribute:: target_evaluation
      :type:  collections.abc.Sequence[NDArrayF]


   .. py:attribute:: signal_conditioning
      :type:  collections.abc.Sequence[NDArrayF] | None


   .. py:attribute:: signal_evaluation
      :type:  collections.abc.Sequence[NDArrayF] | None


   .. py:attribute:: name
      :type:  str


   .. py:attribute:: target_unit
      :type:  str


   .. py:method:: _prepare_dataset(witness_inp, target_inp, signal_inp = None)
      :staticmethod:


      Convert input to immutable np.float64 arrays and check shape



   .. py:method:: get_min_sequence_len(separate = False)

      Get the length of the shortest sequence in the dataset

      :param separate: If True, returns the minimum separately for conditioning and evaluation data.



   .. py:method:: _hash_wts_data(witness, target, signal = None)
      :staticmethod:


      Calculate a hash value for a set of witness, target, signal data



   .. py:method:: hash_bytes()

      return a hash over the dataset data as a bytes object



   .. py:method:: __hash__()