bw2data.weighting_normalization
===============================

.. py:module:: bw2data.weighting_normalization


Classes
-------

.. autoapisummary::

   bw2data.weighting_normalization.Normalization
   bw2data.weighting_normalization.Weighting


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

.. py:class:: Normalization(name)

   Bases: :py:obj:`bw2data.ia_data_store.ImpactAssessmentDataStore`


   LCIA normalization data - used to transform meaningful units, like mass or damage, into "person-equivalents" or some such thing.

   The data schema for IA normalization is:

   .. code-block:: python

           Schema([
               [valid_tuple, maybe_uncertainty]
           ])

   where:
       * ``valid_tuple`` is a dataset identifier, like ``("biosphere", "CO2")``
       * ``maybe_uncertainty`` is either a number or an uncertainty dictionary



   .. py:method:: process_row(row)

      Given ``(flow key, amount)``, return a dictionary for array insertion.



   .. py:attribute:: _metadata


   .. py:attribute:: matrix
      :value: 'normalization_matrix'



   .. py:attribute:: validator


.. py:class:: Weighting(name)

   Bases: :py:obj:`bw2data.ia_data_store.ImpactAssessmentDataStore`


   LCIA weighting data - used to combine or compare different impact categories.

   The data schema for weighting is a one-element list:

   .. code-block:: python

           Schema(All(
               [uncertainty_dict],
               Length(min=1, max=1)
           ))



   .. py:method:: process_row(row)

      Return an empty tuple (as ``dtype_fields`` is empty), and the weighting uncertainty dictionary.



   .. py:method:: write(data)

      Because of DataStore assumptions, need a one-element list



   .. py:attribute:: _metadata


   .. py:attribute:: matrix
      :value: 'weighting_matrix'



   .. py:attribute:: validator