Carbon price

README.md

@@ -7,8 +7,8 @@ Convert OSeMOSYS results to IAMC format
 It is currently necessary to install the OpenEntrance dependency as an editable installation.
 See [issue](https://github.com/openENTRANCE/openentrance/issues/202)
 
-    pip install git+https://github.com/osemosys/osemosys2iamc@main#egg=osemosys2iamc
     pip install -e git+https://github.com/openENTRANCE/openentrance.git@main#egg=openentrance
+    pip install git+https://github.com/osemosys/osemosys2iamc@main#egg=osemosys2iamc
 
 ## Run the package
 

src/osemosys2iamc/resultify.py

@@ -13,8 +13,6 @@
 
 """
 import functools
-from multiprocessing.sharedctypes import Value
-from sqlite3 import DatabaseError
 import pandas as pd
 import pyam
 from openentrance import iso_mapping
@@ -32,6 +30,7 @@ def read_file(filename) -> pd.DataFrame:
 
     return df
 
+
 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
 
@@ -41,6 +40,7 @@ def filter_regex(df: pd.DataFrame, patterns: List[str], column: str) -> pd.DataF
     masks = [df[column].str.match(p) for p in patterns]
     return pd.concat([df[mask] for mask in masks])
 
+
 def filter_fuels(df: pd.DataFrame, fuels: List[str]) -> pd.DataFrame:
     """Returns rows which match list of regex patterns in ``technologies``
 
@@ -53,6 +53,7 @@ def filter_fuels(df: pd.DataFrame, fuels: List[str]) -> pd.DataFrame:
     """
     return filter_regex(df, fuels, 'FUEL')
 
+
 def filter_technologies(df: pd.DataFrame, technologies: List[str]) -> pd.DataFrame:
     """Returns rows which match list of regex patterns in ``technologies``
 
@@ -65,16 +66,19 @@ def filter_technologies(df: pd.DataFrame, technologies: List[str]) -> pd.DataFra
     """
     return filter_regex(df, technologies, 'TECHNOLOGY')
 
+
 def filter_technology_fuel(df: pd.DataFrame, technologies: List, fuels: List) -> pd.DataFrame:
     """Return rows which match ``technologies`` and ``fuels``
     """
     df = filter_technologies(df, technologies)
     df = filter_fuels(df, fuels)
 
-    df = df.groupby(by=['REGION','YEAR'], as_index=False)["VALUE"].sum()
+    df = df.groupby(by=['REGION', 'YEAR'], as_index=False)["VALUE"].sum()
     return df[df.VALUE != 0]
 
-def filter_emission_tech(df: pd.DataFrame, emission: List[str], technologies: Optional[List[str]]=None) -> pd.DataFrame:
+
+def filter_emission_tech(df: pd.DataFrame, emission: List[str],
+                         technologies: Optional[List[str]] = None) -> pd.DataFrame:
     """Return annual emissions or captured emissions by one or several technologies.
 
     Parameters
@@ -90,14 +94,19 @@ def filter_emission_tech(df: pd.DataFrame, emission: List[str], technologies: Op
     pandas.DataFrame
     """
 
-    df['REGION'] = df['TECHNOLOGY'].str[:2]
+    # Try to extract region from technology
+    try:
+        df['REGION'] = df['TECHNOLOGY'].str[:2]
+    except KeyError:
+        # No Technology column
+        pass
     df = filter_regex(df, emission, 'EMISSION')
 
     if technologies:
-    # Create a list of masks, one for each row that matches the pattern listed in ``tech``
+        # Create a list of masks, one for each row that matches the pattern listed in ``tech``
         df = filter_technologies(df, technologies)
 
-    df = df.groupby(by=['REGION','YEAR'], as_index=False)["VALUE"].sum()
+    df = df.groupby(by=['REGION', 'YEAR'], as_index=False)["VALUE"].sum()
     return df[df.VALUE != 0]
 
 def filter_capacity(df: pd.DataFrame, technologies: List[str]) -> pd.DataFrame:

tests/fixtures/carbonprice.csv

@@ -0,0 +1,6 @@
+VALUE,constraint,REGION,EMISSION,YEAR
+-0.011043939576413982,Constr E8_AnnualEmissionsLimit,REGION1,CO2,2036
+-0.013899709405226217,Constr E8_AnnualEmissionsLimit,REGION1,CO2,2037
+-0.014572746545426708,Constr E8_AnnualEmissionsLimit,REGION1,CO2,2038
+-0.011609757344217923,Constr E8_AnnualEmissionsLimit,REGION1,CO2,2039
+0.0,Constr E8_AnnualEmissionsLimit,REGION1,UKWO,2060

tests/test_resultify.py

@@ -553,3 +553,34 @@ def test_price_bm(self):
         print(expected)
 
         pd.testing.assert_frame_equal(actual, expected)
+
+class TestCarbonPrice:
+
+    def test_carbon_price(self):
+        """
+        VALUE,constraint,REGION,EMISSION,YEAR
+        -0.011043939576413982,Constr E8_AnnualEmissionsLimit,REGION1,CO2,2036
+        -0.013899709405226217,Constr E8_AnnualEmissionsLimit,REGION1,CO2,2037
+        -0.014572746545426708,Constr E8_AnnualEmissionsLimit,REGION1,CO2,2038
+        -0.011609757344217923,Constr E8_AnnualEmissionsLimit,REGION1,CO2,2039
+        0.0,Constr E8_AnnualEmissionsLimit,REGION1,UKWO,2060
+        """
+
+        filepath = os.path.join("tests","fixtures","carbonprice.csv")
+        input_data = pd.read_csv(filepath)
+        emission = ['CO2']
+        actual = filter_emission_tech(input_data, emission)
+
+        data = [
+            ['REGION1',2036,-0.011043939576413982],
+            ['REGION1',2037,-0.013899709405226217],
+            ['REGION1',2038,-0.014572746545426708],
+            ['REGION1',2039,-0.011609757344217923],
+        ]
+
+        expected = pd.DataFrame(data=data, columns=["REGION", "YEAR", "VALUE"])
+
+        print(actual)
+        print(expected)
+
+        pd.testing.assert_frame_equal(actual, expected)