Fix issue with marginal mix.

Fix issue with losses dictionary.

premise/__init__.py

@@ -1,5 +1,5 @@
 __all__ = ("NewDatabase", "clear_cache", "get_regions_definition")
-__version__ = (2, 0, 0, "dev0")
+__version__ = (2, 0, 0, "dev1")
 
 
 from .new_database import NewDatabase

premise/electricity.py

@@ -141,7 +141,7 @@ def get_production_weighted_losses(
         )
 
         transf_loss += (
-            dict_loss["Transformation loss high voltage"]
+            dict_loss.get("Transformation loss high voltage", 0)
             * dict_loss["Production volume"]
         )
 
@@ -169,12 +169,13 @@ def get_production_weighted_losses(
                 "Production volume": 0,
             },
         )
+
         transf_loss += (
-            dict_loss["Transformation loss medium voltage"]
+            dict_loss.get("Transformation loss medium voltage", 0)
             * dict_loss["Production volume"]
         )
         distr_loss += (
-            dict_loss["Transmission loss to medium voltage"]
+            dict_loss.get("Transmission loss to medium voltage", 0)
             * dict_loss["Production volume"]
         )
         cumul_prod += dict_loss["Production volume"]
@@ -195,11 +196,11 @@ def get_production_weighted_losses(
             },
         )
         transf_loss += (
-            dict_loss["Transformation loss low voltage"]
+            dict_loss.get("Transformation loss low voltage", 0)
             * dict_loss["Production volume"]
         )
         distr_loss += (
-            dict_loss["Transmission loss to low voltage"]
+            dict_loss.get("Transmission loss to low voltage", 0)
             * dict_loss["Production volume"]
         )
         cumul_prod += dict_loss["Production volume"]

premise/marginal_mixes.py

@@ -102,10 +102,11 @@ def fetch_volume_change(data: xr.DataArray, start_year: int, end_year: int) -> n
     """
     Calculate the volume change of a market.
     """
+
     return (
         (
-            data.sel(year=end_year).sum(dim="variables")
-            - data.sel(year=start_year).sum(dim="variables")
+            data.interp(year=end_year).sum(dim="variables")
+            - data.interp(year=start_year).sum(dim="variables")
         )
         / (end_year - start_year)
     ).values

premise/new_database.py

@@ -9,11 +9,8 @@
 import multiprocessing
 import os
 import pickle
-import sys
 from datetime import date
-from functools import partial
 from multiprocessing import Pool as ProcessPool
-from multiprocessing import cpu_count
 from multiprocessing.pool import ThreadPool as Pool
 from pathlib import Path
 from typing import List, Union