Added function for calculated weighted average of timesliced dual

src/osemosys2iamc/resultify.py

@@ -163,6 +163,21 @@ def read_file(path: str, osemosys_param: str, region_name_option: str) -> pd.Dat
     return df
 
 
+def calculate_timeslice_dual(
+    input_data: pd.DataFrame, fuels: list[str], yearsplit: pd.DataFrame
+):
+    """Calculate the weighted average dual value"""
+    filtered_data = filter_fuels(input_data, fuels).drop(columns="FUEL")
+
+    index = ["REGION", "TIMESLICE", "YEAR"]
+
+    weighted = filtered_data.set_index(index) * yearsplit.set_index(
+        ["TIMESLICE", "YEAR"]
+    )
+
+    return weighted.groupby(by=["REGION", "YEAR"]).sum().reset_index()
+
+
 def filter_regex(df: pd.DataFrame, patterns: List[str], column: str) -> pd.DataFrame:
     """Generic filtering of rows based on columns that match a list of patterns
 

tests/fixtures/dual/dual_values_EBa11.csv

@@ -0,0 +1,25 @@
+REGION,FUEL,TIMESLICE,YEAR,VALUE
+REGION1,ATE2,S01B1,2015,1
+REGION1,ATE2,S01B1,2016,1
+REGION1,ATE2,S01B1,2017,1
+REGION1,ATE2,S01B1,2018,1
+REGION1,BEE2,S01B1,2015,1
+REGION1,BEE2,S01B1,2016,1
+REGION1,BEE2,S01B1,2017,1
+REGION1,BEE2,S01B1,2018,1
+REGION1,ATE2,S01B2,2015,1
+REGION1,ATE2,S01B2,2016,1
+REGION1,ATE2,S01B2,2017,1
+REGION1,ATE2,S01B2,2018,1
+REGION1,BEE2,S01B2,2015,1
+REGION1,BEE2,S01B2,2016,1
+REGION1,BEE2,S01B2,2017,1
+REGION1,BEE2,S01B2,2018,1
+REGION1,ATE2,S01B3,2015,1
+REGION1,ATE2,S01B3,2016,1
+REGION1,ATE2,S01B3,2017,1
+REGION1,ATE2,S01B3,2018,1
+REGION1,BEE2,S01B3,2015,1
+REGION1,BEE2,S01B3,2016,1
+REGION1,BEE2,S01B3,2017,1
+REGION1,BEE2,S01B3,2018,1

tests/fixtures/dual/yearsplit.csv

@@ -0,0 +1,13 @@
+TIMESLICE,YEAR,VALUE
+S01B1,2015,0.1
+S01B2,2015,0.4
+S01B3,2015,0.5
+S01B1,2016,0.1
+S01B2,2016,0.4
+S01B3,2016,0.5
+S01B1,2017,0.1
+S01B2,2017,0.4
+S01B3,2017,0.5
+S01B1,2018,0.1
+S01B2,2018,0.4
+S01B3,2018,0.5

tests/test_resultify.py

@@ -10,6 +10,7 @@
     calculate_trade,
     read_file,
     iso_to_country,
+    calculate_timeslice_dual,
 )
 
 
@@ -537,6 +538,33 @@ def test_filter_inst_capacity_wi_offshore(self):
         pd.testing.assert_frame_equal(actual, expected)
 
 
+class TestDualPrice:
+    def test_dual_variable_cost(self):
+        folderpath = os.path.join("tests", "fixtures", "dual")
+        input_data = read_file(folderpath, "dual_values_EBa11", "iso2_start")
+        fuels = ["^.{2}(E2)"]
+        yearsplit = read_file(folderpath, "yearsplit", "iso2_start")
+        actual = calculate_timeslice_dual(input_data, fuels, yearsplit)
+
+        data = [
+            ["Austria", 2015, 1.0],
+            ["Austria", 2016, 1.0],
+            ["Austria", 2017, 1.0],
+            ["Austria", 2018, 1.0],
+            ["Belgium", 2015, 1.0],
+            ["Belgium", 2016, 1.0],
+            ["Belgium", 2017, 1.0],
+            ["Belgium", 2018, 1.0],
+        ]
+
+        expected = pd.DataFrame(data=data, columns=["REGION", "YEAR", "VALUE"])
+
+        print(actual)
+        print(expected)
+
+        pd.testing.assert_frame_equal(actual, expected)
+
+
 class TestPrice:
     def test_price_bm(self):
         folderpath = os.path.join("tests", "fixtures")