Merge branch 'main' into pypsa-de-merge

Author: pworschischek-aggmag

.pre-commit-config.yaml

@@ -51,10 +51,3 @@ repos:
   rev: v0.11.0
   hooks:
   - id: snakefmt
-
-
-- repo: https://github.com/sourcery-ai/sourcery
-  rev: v1.37.0
-  hooks:
-  - id: sourcery
-    args: [--diff=git diff HEAD, --no-summary]

config/config.at.yaml

@@ -6,8 +6,8 @@ run:
   prefix: v2025.03
   name:
 #  - ExPol
-#  - AT10_KN2040
-  - KN2045_Mix
+  - AT10_KN2040
+#  - KN2045_Mix
 #  - KN2045_Elek
 #  - KN2045_H2
 #  - KN2045_NFniedrig

config/test/config.at10.yaml

@@ -5,7 +5,7 @@
 run:
   prefix: "test-sector-myopic-at10"
   name:
-  - KN2045_Mix
+  - AT10_KN2040
 
 # need to include additional neighbor countries, because the
 # administrative clustering will not filter lines to connected

evals/plots/sankey.py

@@ -15,39 +15,15 @@
 pd.set_option("display.max_columns", 20)
 
 
-def read_iamc_data_frame():
+def read_iamc_data_frame(filepath):
     xls = pd.read_excel(
-        "/IdeaProjects/pypsa-at/results/v2025.02/KN2045_Mix/evaluation/exported_iamc_variables.xlsx",
+        filepath,
         index_col=[0, 1, 2, 3, 4],
     )
     xls.columns.name = "Year"
     return xls.stack()
 
 
-def main():
-    year = "2050"
-    region = "GB0"
-
-    df = read_iamc_data_frame()
-    df = rename_aggregate(df, "TWh", level="Unit").div(1e6)
-    df = filter_by(df, Year=year, Region=region)
-
-    raw_mapping = get_mapping(df)
-    variables = df.index.unique("Variable")
-    for k, v in raw_mapping.items():
-        if k in variables:
-            clean_mapping[k] = v
-        else:
-            print(f"Skipping '{k}' because it does not exist in {region} {year}.")
-
-    iamc = pyam.IamDataFrame(df)
-    fig = iamc.plot.sankey(mapping=clean_mapping)
-
-    fig.update_layout(height=600)
-
-    plotly.io.show(fig)
-
-
 def get_mapping(df) -> (dict, set):
     mapping = {}
     nodes = set()
@@ -147,14 +123,15 @@ def get_xmap(nodes) -> dict:
 
 
 if __name__ == "__main__":
-    FILEPATH = "/IdeaProjects/pypsa-at/results/v2025.02/KN2045_Mix/evaluation/exported_iamc_variables.xlsx"
-    df = read_iamc_data_frame()
+    df = read_iamc_data_frame(
+        filepath="/IdeaProjects/pypsa-at/results/v2025.03/AT10_KN2040/evaluation/exported_iamc_variables.xlsx"
+    )
     mapping, nodes = get_mapping(df)
     mapping_sorted = {k: mapping[k] for k in sorted(mapping, key=sort_mapping)}
     xmap = get_xmap(nodes)
     df = rename_aggregate(df, "TWh", level="Unit").div(1e6)
     year = "2050"
-    region = "GB0"
+    region = "FR0"
     df = filter_by(df, Year=year, Region=region)
 
     clean_mapping = {}
@@ -173,8 +150,6 @@ def get_xmap(nodes) -> dict:
 
     node["x"] = [xmap.get(label, 0.2) for label in node["label"]]
     node["y"] = [xmap.get(label, 0.4) for label in node["label"]]
-    # node["y"] = [ymap[label] for label in node["label"]]
-    # node["color"] = [colormap[label] for label in node["label"]]
 
     new_sankey = Sankey(
         node=node,
@@ -184,6 +159,6 @@ def get_xmap(nodes) -> dict:
 
     fig = Figure(data=[new_sankey])
 
-    fig.update_layout(height=600)
+    fig.update_layout(height=800)
 
     plotly.io.show(fig)

scripts/pypsa-at/export_iamc_variables.py

@@ -382,7 +382,9 @@ def collect_regional_nh3_loads():
     )
 
     # check that imbalances are equal to imbalances in the network
-    pd.testing.assert_series_equal(imbalances_iamc, imbalances_bus, check_names=False)
+    pd.testing.assert_series_equal(
+        imbalances_iamc, imbalances_bus, check_names=False, atol=1e-3
+    )
     if not imbalances_bus.abs().le(1e-3).all():
         logger.warning(f"Imbalances detected for bus carrier {bc}:\n{imbalances_bus}.")
     var[f"{FINAL}|{BC_ALIAS[bc]}|Agriculture"] = nh3_regional_supply.groupby(IDX).sum()
@@ -1190,9 +1192,9 @@ def calculate_sankey_totals():
     if "snakemake" not in globals():
         snakemake = mock_snakemake(
             "export_iamc_variables",
-            run="KN2045_Mix",
-            prefix="test-sector-myopic-at10",
-            config="config/test/config.at10.yaml",
+            run="AT10_KN2040",
+            # prefix="test-sector-myopic-at10",
+            # config="config/test/config.at10.yaml",
         )
     configure_logging(snakemake)
 
@@ -1204,8 +1206,8 @@ def calculate_sankey_totals():
         "drop_zeros": False,
         "drop_unit": False,
     }
-    # calculate all statistics and process them to IAMC data model. The idea is to
-    # calculate everything once and remove rows from the global statistic. This way
+    # Calculate all statistics and process them to IAMC datamodel. The idea is to
+    # calculate everything just once and remove rows from the global statistic. This way
     # we make sure that nothing is counted twice or forgotten.
     SUPPLY = collect_myopic_statistics(
         networks, "supply", groupby=groupby, **kwargs

scripts/pypsa-de/build_scenarios.py

@@ -178,7 +178,7 @@ def write_to_scenario_yaml(input, output, scenarios, df):
     for scenario in scenarios:
         if config.get(scenario) is None:
             logger.warning(
-                f"Found an empty scenario config for {scenario}. Using default config `pypsa.de.yaml`."
+                f"Found an empty scenario config for {scenario}. Using default config `pypsa.at.yaml`."
             )
             config[scenario] = {}
         if config[scenario].get("weather_year", False):
@@ -199,7 +199,7 @@ def write_to_scenario_yaml(input, output, scenarios, df):
             .get(
                 "reference_scenario",
                 snakemake.config["iiasa_database"]["reference_scenario"],
-            )  # Using the default reference scenario from pypsa.de.yaml
+            )  # Using the default reference scenario from pypsa.at.yaml
         )
 
         planning_horizons = [