RIAssigner.compute.Kovats
=========================

.. py:module:: RIAssigner.compute.Kovats


Classes
-------

.. autoapisummary::

   RIAssigner.compute.Kovats.Kovats


Functions
---------

.. autoapisummary::

   RIAssigner.compute.Kovats._update_index
   RIAssigner.compute.Kovats._compute_kovats


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

.. py:class:: Kovats

   Bases: :py:obj:`RIAssigner.compute.ComputationMethod.ComputationMethod`


   Class to compute the Kovats retention index.


   .. py:method:: compute(query: RIAssigner.data.Data.Data, reference: RIAssigner.data.Data.Data) -> List[RIAssigner.data.Data.Data.RetentionIndexType]

      Compute non-isothermal Kovats retention index.
      For details see https://webbook.nist.gov/chemistry/gc-ri/.

      :param query: Dataset for which to compute retention indices.
      :param reference: Reference dataset with retention times and retention indices

      :returns: **retention_indices** -- List of computed retention indices
      :rtype: List[Data.RetentionIndexType]



   .. py:method:: _compute_ri(target_rt: RIAssigner.data.Data.Data.RetentionTimeType, reference_rts: Iterable[RIAssigner.data.Data.Data.RetentionTimeType], reference_ris: Iterable[RIAssigner.data.Data.Data.RetentionTimeType], index: int) -> RIAssigner.data.Data.Data.RetentionIndexType

      Compute retention index for target retention time.

      :param target_rt: Retention time for which to compute the index
      :type target_rt: Data.RetentionTimeType
      :param reference_rts: Reference retention times
      :type reference_rts: Iterable[Data.RetentionTimeType]
      :param reference_ris: Reference retention indices
      :type reference_ris: Iterable[Data.RetentionTimeType]
      :param index: Current reference index
      :type index: int

      :returns: Computed retention index
      :rtype: Data.RetentionIndexType



.. py:function:: _update_index(target_rt: float, reference_rts: Iterable[RIAssigner.data.Data.Data.RetentionTimeType], index: int)

   Get the indices of previosly eluting and next eluting reference compounds.
   Retention times in 'Data' objects are sorted in ascending order, so this method assumes
   that 'reference_rt' is sorted in ascending order.

   :param reference_rts: Retention times of reference compounds.


.. py:function:: _compute_kovats(target_rt: float, reference_rts: Iterable[RIAssigner.data.Data.Data.RetentionTimeType], reference_ris: Iterable[RIAssigner.data.Data.Data.RetentionIndexType], index: int) -> float

   Compute retention index according to Van den Dool (see https://webbook.nist.gov/chemistry/gc-ri/)

   :param target_rt: Retention time for which to compute the RI
   :type target_rt: float
   :param reference_rts: Reference data retention times
   :type reference_rts: Iterable[Data.RetentionTimeType]
   :param reference_ris: Reference data retention indices
   :type reference_ris: Iterable[Data.RetentionIndexType]
   :param index: Higher index of reference compound (n+1)
   :type index: int

   :returns: Computed retention index
   :rtype: Data.RetentionIndexType