dacapo.experiments.datasplits.datasets.dataset_config
=====================================================

.. py:module:: dacapo.experiments.datasplits.datasets.dataset_config


Classes
-------

.. autoapisummary::

   dacapo.experiments.datasplits.datasets.dataset_config.DatasetConfig


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

.. py:class:: DatasetConfig

   A class used to define configuration for datasets. This provides the
   framework to create a Dataset instance.

   .. attribute:: name

      str (eg: "sample_dataset").
      A unique identifier to name the dataset.
      It aids in easy identification and reusability of this dataset.
      Advised to keep it short and refrain from using special characters.

   .. attribute:: weight

      int (default=1).
      A numeric value that indicates how frequently this dataset should be
      sampled in comparison to others. Higher the weight, more frequently it
      gets sampled.

   .. method:: verify

      
      Checks and validates the dataset configuration. The specific rules for
      validation need to be defined by the user.

   .. rubric:: Notes

   This class is used to create a configuration object for datasets.


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


   .. py:attribute:: weight
      :type:  int


   .. py:method:: verify() -> Tuple[bool, str]

      Method to verify the dataset configuration.

      Since there is no specific validation logic defined for this DataSet, this
      method will always return True as default reaction and a message stating
      the lack of validation.

      :returns: A tuple of boolean value indicating the check (True or False) and
                message specifying result of validation.
      :rtype: tuple

      :raises NotImplementedError: If the method is not implemented in the derived class.

      .. rubric:: Examples

      >>> dataset_config = DatasetConfig(name="sample_dataset")
      >>> dataset_config.verify()
      (True, "No validation for this DataSet")

      .. rubric:: Notes

      This method is used to validate the configuration of the dataset.