mescal.utils
============

.. py:module:: mescal.utils


Functions
---------

.. autoapisummary::

   mescal.utils._short_name_ds_type
   mescal.utils.change_mapping_year
   mescal.utils.change_year_in_name
   mescal.utils.ecoinvent_unit_convention
   mescal.utils.expand_impact_category_levels
   mescal.utils.premise_changing_names
   mescal.utils.random_code


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

.. py:function:: _short_name_ds_type(ds_type: str) -> str

   Returns the short name of the LCI dataset type

   :param ds_type: type of LCI dataset
   :return: short name of the LCI dataset type


.. py:function:: change_mapping_year(mapping: pandas.DataFrame, year_from: int, year_to: int) -> pandas.DataFrame

   Change the year in the name of the activities and databases in the mapping file

   :param mapping: mapping file between the LCI database and the ESM database
   :param year_from: year of the original mapping file
   :param year_to: year of the new mapping file
   :return: updated mapping file


.. py:function:: change_year_in_name(row: pandas.Series, year_from: int, year_to: int) -> pandas.Series

   Change the year in the name of the activity and database

   :param row: row of the mapping file
   :param year_from: year of the original mapping file
   :param year_to: year of the new mapping file
   :return: updated mapping row


.. py:function:: ecoinvent_unit_convention(unit: str) -> str

   Reformat unit to the ecoinvent convention

   :param unit: unit to reformat
   :return: ecoinvent unit


.. py:function:: expand_impact_category_levels(df: pandas.DataFrame, impact_category_col: str = 'Impact_category') -> pandas.DataFrame

   Expand the impact category levels into separate columns

   :param df: dataframe with impact category column
   :param impact_category_col: name of the impact category column
   :return: the dataframe with expanded impact category levels


.. py:function:: premise_changing_names(activity_name: str, activity_prod: str, activity_loc: str, name_premise_db, premise_db_dict_name: dict, premise_changes: pandas.DataFrame = None) -> tuple[str, str, str]

   Returns the updated name, product and location in case some changes have occurred in premise

   :param activity_name: name of the LCI dataset
   :param activity_prod: product of the LCI dataset
   :param activity_loc: location of the LCI dataset
   :param name_premise_db: name of the premise database
   :param premise_db_dict_name: dictionary of the database with (name, product, location, database) as key
   :param premise_changes: file of the premise name changes impacting the mapping
   :return: the updated name, product and location of the LCI dataset


.. py:function:: random_code() -> str

   Create a random code

   :return: code