caikit.interfaces.ts.data_model.timeseries_evaluation
=====================================================

.. py:module:: caikit.interfaces.ts.data_model.timeseries_evaluation

.. autoapi-nested-parse::

   The core data model object for a TimeSeries Evaluator.



Attributes
----------

.. autoapisummary::

   caikit.interfaces.ts.data_model.timeseries_evaluation.log
   caikit.interfaces.ts.data_model.timeseries_evaluation.error


Classes
-------

.. autoapisummary::

   caikit.interfaces.ts.data_model.timeseries_evaluation.Id
   caikit.interfaces.ts.data_model.timeseries_evaluation.EvaluationRecord
   caikit.interfaces.ts.data_model.timeseries_evaluation.EvaluationResult


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

.. py:data:: log

.. py:data:: error

.. py:class:: Id

   Bases: :py:obj:`caikit.core.DataObjectBase`


   A single instance of Id
   Representation of ids that can be either text or index. Customized
   this way to be able to work with repeated


   .. py:attribute:: value
      :type:  Union[py_to_proto.dataclass_to_proto.Annotated[str, OneofField('text'), FieldNumber(1)], py_to_proto.dataclass_to_proto.Annotated[int, OneofField('index'), FieldNumber(2)]]


.. py:class:: EvaluationRecord(id_values=None, metric_values=None, offset=None)

   Bases: :py:obj:`caikit.core.DataObjectBase`


   A single EvaluationRecord for EvaluationResult
   Representation of EvaluationRecord for each row in the dataframe
   EvaluationRecord{id_values=["A", "B"], metric_values=[0.234, 0.568, 0.417], offset="overall"}


   .. py:attribute:: id_values
      :type:  py_to_proto.dataclass_to_proto.Annotated[List[Id], FieldNumber(1)]


   .. py:attribute:: metric_values
      :type:  py_to_proto.dataclass_to_proto.Annotated[List[float], FieldNumber(2)]


   .. py:attribute:: offset
      :type:  py_to_proto.dataclass_to_proto.Annotated[Id, FieldNumber(3)]


.. py:class:: EvaluationResult(records=None, id_cols=None, metric_cols=None, offset_col=None, df=None, producer_id=None)

   Bases: :py:obj:`caikit.core.DataObjectBase`


   EvaluationResult containing the evaluation results
   Representation of EvaluationResult stores rows of the dataframe as list of records string lists
   to keep track of id and metric columns


   .. py:attribute:: records
      :type:  py_to_proto.dataclass_to_proto.Annotated[List[EvaluationRecord], FieldNumber(1)]


   .. py:attribute:: id_cols
      :type:  py_to_proto.dataclass_to_proto.Annotated[List[str], FieldNumber(2)]


   .. py:attribute:: metric_cols
      :type:  py_to_proto.dataclass_to_proto.Annotated[List[str], FieldNumber(3)]


   .. py:attribute:: offset_col
      :type:  py_to_proto.dataclass_to_proto.Annotated[str, FieldNumber(4)]


   .. py:attribute:: producer_id
      :type:  py_to_proto.dataclass_to_proto.Annotated[caikit.core.data_model.ProducerId, FieldNumber(5)]


   .. py:method:: as_pandas() -> pandas.DataFrame

      Generate and return a pandas DataFrame