piel.experimental.analysis.operating_point
==========================================

.. py:module:: piel.experimental.analysis.operating_point


Functions
---------

.. autoapisummary::

   piel.experimental.analysis.operating_point.create_experiment_data_collection_from_unique_parameters


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

.. py:function:: create_experiment_data_collection_from_unique_parameters(experiment_data: piel.types.experimental.ExperimentData) -> piel.types.experimental.ExperimentDataCollection

   Each individual raw ``ExperimentData`` can contain multiple operating points or unique parameters which are being
   tested. It can be handy to create subsets of ``ExperimentData`` -> multiple ``ExperimentData``s
   that correspond to relevant operating points stored with the relevant parameters both internally and in an
   ``ExperimentDataCollection``. As such, it is easier to understand the collection of data
   measurements based on this and perform plotting accordingly in a more relevant implementation. Likewise,
   the corresponding operating point metadata is encoded in the generated ``ExperimentData`` sets.

   First, we will need to extract the operating points from the ``ExperimentData.experiment.parameters``.
   This can be done by identifying the unique elements from the pandas DataFrame.
   Then, we will need to create a new ``ExperimentData`` for each of the operating points.
   Finally, we will need to create a new ``ExperimentDataCollection`` with the new ``ExperimentData``.