Put max parameter back to output_parameters

sedos-project · Dec 10, 2024 · 813babd · 813babd
1 parent b303bff
commit 813babd
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Showing 3 changed files with 13 additions and 12 deletions.
diff --git a/data_adapter_oemof/adapters.py b/data_adapter_oemof/adapters.py
@@ -79,8 +79,6 @@ def get_default_parameters(self) -> dict:
             )
 
         defaults = self.default_post_mapping_calculations(defaults)
-        if "max_profile" in defaults:
-            defaults["profile"] = defaults["max_profile"].columns[0]
         if not defaults["input_parameters"]:
             defaults.pop("input_parameters")
         if not defaults["output_parameters"]:
@@ -356,12 +354,18 @@ def default_post_mapping_calculations(self, mapped_defaults):
         -------
 
         """
+        if len(self.structure["outputs"]) == 0:
+            change_parameter = "input_parameters"
+        else:
+            change_parameter = "output_parameters"
+
         # I:
         if self.process_name[-1] == "0":
             mapped_defaults = calculations.decommission(
                 process_name=self.process_name,
                 adapter_dict=mapped_defaults,
                 column="capacity",
+                input_output_parameters=change_parameter,
             )
         elif self.process_name[-1] == "1" or self.process_name[-1] == "2":
             mapped_defaults["expandable"] = True
@@ -389,6 +393,7 @@ def default_post_mapping_calculations(self, mapped_defaults):
                     process_name=self.process_name,
                     adapter_dict=mapped_defaults,
                     column="amount",
+                    input_output_parameters=change_parameter,
                 )
 
         # III:

diff --git a/data_adapter_oemof/build_datapackage.py b/data_adapter_oemof/build_datapackage.py
@@ -560,12 +560,6 @@ def _reduce_lists(x):
                 constraint_parameters = pd.DataFrame(components)
             else:
                 parametrized_elements[process_name] = pd.DataFrame(components)
-
-                # if 'max_profile' exists the time series is added in `timeseries` and removed from `parametrized_elements`
-                # todo un-hard-code --> max_profile is set in calculations.decommission() which is called by Adapter.default_post_mapping_calculations()
-                if "max_profile" in parametrized_elements[process_name]:
-                    timeseries = parametrized_elements[process_name]["max_profile"][0]
-                    parametrized_elements[process_name].drop(columns=["max_profile"], inplace=True)
                 if not timeseries.empty:
                     parametrized_sequences.update({process_name: timeseries})
         # Create Bus Element from all unique `busses` found in elements

diff --git a/data_adapter_oemof/calculations.py b/data_adapter_oemof/calculations.py
@@ -46,7 +46,7 @@ def get_capacity_cost(overnight_cost, fixed_cost, lifetime, wacc):
 
 
 def decommission(
-    process_name, adapter_dict: dict, column: str = "capacity", max_column: str = "max",
+    process_name, adapter_dict: dict, column: str = "capacity", max_column: str = "max", input_output_parameters: str = "output_parameters",
 ) -> dict:
     """
 
@@ -93,18 +93,18 @@ def decommission(
         return adapter_dict
 
     # I:
-    if max_column not in adapter_dict["output_parameters"].keys():
+    if max_column not in adapter_dict[input_output_parameters].keys():
         max = list(adapter_dict[column] / np.nanmax(adapter_dict[column]))
 
     # II:
     else:
         max = list(multiply_two_lists(
-                adapter_dict["output_parameters"][max_column],
+                adapter_dict[input_output_parameters][max_column],
                 adapter_dict[column]
             ) / np.nanmax(adapter_dict[column]))
 
     # max must be extended to time series over all time steps of each period
-    column_name = ["max_timeseries"]
+    column_name = [f"max_timeseries_{process_name}"]
     timeseries = pd.DataFrame(columns=column_name)
     for y in adapter_dict["year"]:
         ts = pd.DataFrame(data=[1 for i in range(8760)], columns=column_name,
@@ -114,6 +114,8 @@ def decommission(
     max_time_series = adapt_profile_with_yearly_value(profile=timeseries, value=max)
 
     adapter_dict["max_profile"] = max_time_series
+    adapter_dict[input_output_parameters][max_column] = list(max_time_series[column_name[0]].values)
+    adapter_dict[input_output_parameters] = json.dumps(adapter_dict[input_output_parameters])
 
     # set `column` value to maximum value
     adapter_dict[column] = np.nanmax(adapter_dict[column])