add statistics-function for variable Final Energy [by Sector]|Agriculture

pypsa_validation_processing/configs/mapping.default.yaml

@@ -7,3 +7,4 @@
 
 Final Energy [by Carrier]|Electricity: Final_Energy_by_Carrier__Electricity
 Final Energy [by Sector]|Transportation: Final_Energy_by_Sector__Transportation
+Final Energy [by Sector]|Agriculture: Final_Energy_by_Sector__Agriculture

pypsa_validation_processing/statistics_functions.py

@@ -109,3 +109,45 @@ def Final_Energy_by_Sector__Transportation(
         .sum()
     )
     return res
+
+
+def Final_Energy_by_Sector__Agriculture(n: pypsa.Network) -> pd.Series:
+    """Extract agriculture-sector final energy from a PyPSA Network.
+
+    Returns the total energy consumed by the transportation sector (excluding
+    transmission / distribution losses) across the pypsa-network.
+
+    Parameters
+    ----------
+    n : pypsa.Network
+        PyPSA network to process.
+
+    Returns
+    -------
+    pd.Series
+        Pandas Series with Multiindex of ``country`` and ``unit``
+
+    Notes
+    -----
+    Includes carriers ['agriculture electricity','agriculture heat','agriculture machinery electric',
+    'agriculture machinery oil'] executed on Load-Components. Agriculture machinery oil is also carrier
+    of Links and Buses, as Demand is assumed fixed. _Time series of Agriculture demand are assumed
+    to be constant in PyPSA-EUR._
+    """
+    carriers = [
+        "agriculture electricity",
+        "agriculture heat",
+        "agriculture machinery electric",
+        "agriculture machinery oil",
+    ]
+    res = (
+        n.statistics.energy_balance(
+            carrier=carriers,
+            groupby=["carrier", "unit", "country"],
+            components="Load",
+            direction="withdrawal",  # for positive values
+        )
+        .groupby(["country", "unit"])
+        .sum()
+    )
+    return res

tests/test_statistics_functions.py

@@ -7,6 +7,7 @@
 
 from pypsa_validation_processing.statistics_functions import (
     Final_Energy_by_Carrier__Electricity,
+    Final_Energy_by_Sector__Agriculture,
     Final_Energy_by_Sector__Transportation,
 )
 
@@ -103,3 +104,49 @@ def test_multiple_networks(self, mock_network_collection: MockNetworkCollection)
             assert isinstance(result.index, pd.MultiIndex)
             assert result.index.names == ["country", "unit"]
             assert len(result) > 0
+
+
+# ---------------------------------------------------------------------------
+# Tests for Final_Energy_by_Sector__Agriculture
+# ---------------------------------------------------------------------------
+
+
+class TestFinalEnergyBySectorAgriculture:
+    """Test suite for Final_Energy_by_Sector__Agriculture function."""
+
+    def test_returns_series(self, mock_network: MockPyPSANetwork):
+        """Test that the function returns a pandas Series."""
+        result = Final_Energy_by_Sector__Agriculture(mock_network)
+        assert isinstance(result, pd.Series)
+
+    def test_has_country_and_unit_multiindex(self, mock_network: MockPyPSANetwork):
+        """Test that result has MultiIndex with country and unit levels."""
+        result = Final_Energy_by_Sector__Agriculture(mock_network)
+        assert isinstance(result.index, pd.MultiIndex)
+        assert result.index.names == ["country", "unit"]
+
+    def test_not_empty(self, mock_network: MockPyPSANetwork):
+        """Test that result is not empty."""
+        result = Final_Energy_by_Sector__Agriculture(mock_network)
+        assert len(result) > 0
+
+    def test_numeric_values(self, mock_network: MockPyPSANetwork):
+        """Test that result values are numeric."""
+        result = Final_Energy_by_Sector__Agriculture(mock_network)
+        assert result.dtype in [float, int] or pd.api.types.is_numeric_dtype(
+            result.dtype
+        )
+
+    def test_contains_austria(self, mock_network: MockPyPSANetwork):
+        """Test that result contains Austria (AT) data."""
+        result = Final_Energy_by_Sector__Agriculture(mock_network)
+        assert "AT" in result.index.get_level_values("country")
+
+    def test_multiple_networks(self, mock_network_collection: MockNetworkCollection):
+        """Test processing multiple networks from collection."""
+        for network in mock_network_collection:
+            result = Final_Energy_by_Sector__Agriculture(network)
+            assert isinstance(result, pd.Series)
+            assert isinstance(result.index, pd.MultiIndex)
+            assert result.index.names == ["country", "unit"]
+            assert len(result) > 0