Lennart Schürmann <[email protected]>
 
 `MIT license <https://github.com/oemof/oemof-solph/blob/dev/LICENSE>`_
 
 """
-
 
 from oemof.solph import EnergySystem
 from oemof.solph import Model
 from oemof.solph import buses
 from oemof.solph import components as cmp

         \times P_{\mathrm{out},n}(p, t)
             \quad \forall t \in T, \forall n in {1,2} \\
         &
 
     """
+
     CONSTRAINT_GROUP = True
 
     def __init__(self, *args, **kwargs):
         super().__init__(*args, **kwargs)
 

                 msg.format(len(inputs)),
                 debugging.SuspiciousUsageWarning,
             )
 
         super().__init__(
-            label=label,
-            inputs=inputs,
-            custom_properties=custom_attributes
+            label=label, inputs=inputs, custom_properties=custom_attributes
         )
 
     def constraint_group(self):
         pass

     +--------------------+------------------------+------+--------------------------------------------+
 
     Note that :math:`P_{max}(t) \cdot Y(t)` is merged into one variable,
     called `status_nominal[n, o, p, t]`.
     """  # noqa: E501
+
     CONSTRAINT_GROUP = True
 
     def __init__(self, *args, **kwargs):
         super().__init__(*args, **kwargs)
 

                 msg.format(len(outputs)),
                 debugging.SuspiciousUsageWarning,
             )
 
         super().__init__(
-            label=label,
-            outputs=outputs,
-            custom_properties=custom_attributes
+            label=label, outputs=outputs, custom_properties=custom_attributes
         )
 
     def constraint_group(self):
         pass

     :class:`~oemof.solph.components.experimental._piecewise_linear_converter.PiecewiseLinearConverter`
 
     **The following constraints are created:**
 
     """
+
     CONSTRAINT_GROUP = True
 
     def __init__(self, *args, **kwargs):
         super().__init__(*args, **kwargs)
 

     :math:`\eta_{el,min,woDH}`      `Eta_el_min_woDH[n,t]`  P    el. eff. at min. fuel flow w/o distr. heating
     :math:`\eta_{el,max,woDH}`      `Eta_el_max_woDH[n,t]`  P    el. eff. at max. fuel flow w/o distr. heating
     =============================== ======================= ==== =============================================
 
     """  # noqa: E501
+
     CONSTRAINT_GROUP = True
 
     def __init__(self, *args, **kwargs):
         super().__init__(*args, **kwargs)
 

 
     for lb in labels:
         subset = (
             df.T.groupby(
                 lambda x1: (
-                    lambda fr, to, ty: "output"
-                    if (fr == lb and ty == "flow")
-                    else "input"
-                    if (to == lb and ty == "flow")
-                    else "level"
-                    if (fr == lb and ty != "flow")
-                    else None
+                    lambda fr, to, ty: (
+                        "output"
+                        if (fr == lb and ty == "flow")
+                        else (
+                            "input"
+                            if (to == lb and ty == "flow")
+                            else (
+                                "level"
+                                if (fr == lb and ty != "flow")
+                                else None
+                            )
+                        )
+                    )
                 )(*x1)
             )
             .sum()
             .T
         )

     # Extraction steps that are the same for both model types
     df = create_dataframe(model)
 
     # create a dict of dataframes keyed by oemof tuples
     df_dict = {
-        k
-        if len(k) > 1
-        else (k[0], None): v[["timestep", "variable_name", "value"]]
+        k if len(k) > 1 else (k[0], None): v[
+            ["timestep", "variable_name", "value"]
+        ]
         for k, v in df.groupby("oemof_tuple")
     }
 
     # Define index
     if model.es.timeindex is None:

     converted into strings that represent the object labels
     e.g. results[('pp1','bus1')].
     """
     if keep_none_type:
         converted = {
-            tuple([str(e) if e is not None else None for e in k])
-            if isinstance(k, tuple)
-            else str(k)
-            if k is not None
-            else None: v
+            (
+                tuple([str(e) if e is not None else None for e in k])
+                if isinstance(k, tuple)
+                else str(k) if k is not None else None
+            ): v
             for k, v in result.items()
         }
     else:
         converted = {
             tuple(map(str, k)) if isinstance(k, tuple) else str(k): v

 by the contributors recorded in the version control history of the file,
 available from its original location oemof/tests/test_components.py
 
 SPDX-License-Identifier: MIT
 """
+
 import pytest
 
 from oemof import solph
 
 

         :math:`\omega_{t}`                                         P    Objective weighting of the model for timestep t
         :math:`year_{max}`                                         P    Last year of the optimization horizon
         ================================= ======================== ==== =======================================
 
     """  # noqa: E501
+
     CONSTRAINT_GROUP = True
 
     def __init__(self, *args, **kwargs):
         super().__init__(*args, **kwargs)
 

         :math:`\mathbb{P}`                                         S    Periods of the model
         :math:`\textrm{TIMEINDEX}`                                 S    Timeindex set of the model (periods, timesteps)
         ================================= ======================== ==== =======================================
 
     """  # noqa: E501
+
     CONSTRAINT_GROUP = True
 
     def __init__(self, *args, **kwargs):
         super().__init__(*args, **kwargs)
 

         :math:`\omega_{t}`                                         P    Objective weighting of the model for timestep t
         :math:`year_{max}`                                         P    Last year of the optimization horizon
         ================================= ======================== ==== =======================================
 
     """  # noqa E:501
+
     CONSTRAINT_GROUP = True
 
     def __init__(self, *args, **kwargs):
         super().__init__(*args, **kwargs)
 

         :math:`\mathbb{P}`                                         S    Periods of the model
         :math:`\textrm{TIMEINDEX}`                                 S    Timeindex set of the model (periods, timesteps)
         ================================= ======================== ==== =======================================
 
     """  # noqa: E501
+
     CONSTRAINT_GROUP = True
 
     def __init__(self, *args, **kwargs):
         super().__init__(*args, **kwargs)
 

                                                                                                | resp. in the last hours before the current"
             :math:`year_{max}`                                                            P    Last year of the optimization horizon
             =========================================== ================================= ==== =======================================
 
     """  # noqa: E501
+
     CONSTRAINT_GROUP = True
 
     def __init__(self, *args, **kwargs):
         super().__init__(*args, **kwargs)
 

         :math:`\mathbb{P}`                                         S    Periods of the model
         :math:`\textrm{TIMEINDEX}`                                 S    Timeindex set of the model (periods, timesteps)
         ================================= ======================== ==== =======================================
 
     """  # noqa: E501
+
     CONSTRAINT_GROUP = True
 
     def __init__(self, *args, **kwargs):
         super().__init__(*args, **kwargs)