Merge pull request #31 from rl-institut/fixes/labels-and-colors

Rework labels and colors

oemoflex/tools/colors.csv

@@ -11,9 +11,9 @@ H2 GT,magenta
 CH4 GT,#d62728
 Nuclear ST,pink
 
-Liion Battery,#9467bd
-BAT discharge,#9467bd
-BAT charge,#9467bd
+Battery,#9467bd
+Battery out,#9467bd
+Battery in,#9467bd
 
 El. H2 cavern,orchid
 BEV,gold

oemoflex/tools/labels.yaml

@@ -1,39 +1,18 @@
-!!python/tuple ['-biomass-gt', '-electricity', 'flow']: Biomass GT
-!!python/tuple ['-biomass-st', '-electricity', 'flow']: Biomass ST
-!!python/tuple ['-ch4-gt', '-electricity', 'flow']: CH4 GT
-!!python/tuple ['-electricity', '-electricity-demand', 'flow']: El. demand
-!!python/tuple ['-electricity', '-electricity-curtailment', 'flow']: Curtailment
-!!python/tuple ['-electricity-shortage', '-electricity', 'flow']: Shortage
-!!python/tuple ['-electricity', '-electricity-liion-battery', 'flow']: BAT charge
-!!python/tuple ['-electricity-liion-battery', '-electricity', 'flow']: BAT discharge
-!!python/tuple ['-solar-pv', '-electricity', 'flow']: PV
-!!python/tuple ['-wind-onshore', '-electricity', 'flow']: Wind on
-!!python/tuple ['-electricity-transmission', '-electricity', 'flow']: Import
-!!python/tuple ['-electricity', '-electricity-transmission', 'flow']: Export
-!!python/tuple ['-heat', '-heat-demand', 'flow']: Heat demand
-!!python/tuple ['-ch4-boiler', '-heat', 'flow']: CH4 Boiler
-
-biomass : Biomass
-ch4: CH4
-hard coal: Hard coal
-oil: Oil
-lignite: Lignite
-other: Other
-
-BE-biomass-st: Biomass ST
-BB-biomass-st: Biomass ST
-BE-electricity-curtailment: El. curtailment
-BB-electricity-curtailment: Curtailment
-BE-electricity-demand: El demand
-BB-electricity-demand: El. Demand
-BE-electricity-liion-battery: Liion Battery
-BB-electricity-liion-battery: Liion Battery
-BE-electricity-shortage: El. shortage
-BB-electricity-shortage: Shortage
-BE-BB-electricity-transmission: Transmission
-BE-ch4-gt: CH4
-BB-ch4-gt: CH4
-BE-solar-pv: PV
-BB-solar-pv: PV
-BE-wind-onshore: Wind on
-BB-wind-onshore: Wind
+biomass-gt: Biomass GT
+biomass-st: Biomass ST
+ch4-boiler: CH4 Boiler
+ch4-bpchp: CH4 Backpressure CHP
+ch4-extchp: CH4 Extraction CHP
+ch4-gt: CH4 GT
+electricity-curtailment: Curtailment
+electricity-demand: El. demand
+electricity-electrolyzer: Electrolyzer
+electricity-liion_battery: Battery
+electricity-pth: res. PtH
+electricity-shortage: Shortage
+electricity-transmission: Import/Export
+h2-gt: H2 GT
+heat-demand: Heat demand
+hydro-ror: Hydro ROR
+solar-pv: PV
+wind-onshore: Wind on

oemoflex/tools/plots.py

@@ -21,6 +21,13 @@
     colors_odict[i] = colors_csv.loc["Color", i]
 
 
+def check_undefined_colors(labels, color_labels):
+    undefined_colors = list(set(labels).difference(color_labels))
+
+    if undefined_colors:
+        raise KeyError(f"Undefined colors {undefined_colors}.")
+
+
 def map_labels(df, labels_dict=general_labels_dict):
     r"""
     Renames columns according to the specifications in the label_dict. The data has multilevel
@@ -67,7 +74,7 @@ def rename_by_string_matching(columns, labels_dict):
         List with new column names.
     """
 
-    def map_tuple(tuple, dictionary):
+    def map_tuple(tupl, dictionary):
         r"""
         The corresponding value of the tuple which is supposed to be a key in the dictionary is
         retrieved.
@@ -85,56 +92,47 @@ def map_tuple(tuple, dictionary):
         mapped : string
             String with new column name.
         """
-        mapped = None
-
-        for key, value in dictionary.items():
-
-            if concrete_in_generic(tuple, key):
-                mapped = value
+        mapped = [
+            value for key, value in dictionary.items() if any([key in y for y in tupl])
+        ]
 
-            else:
-                continue
-
-        if not mapped:
-            raise KeyError(f"No mapping defined for {col}.")
+        if len(mapped) > 1:
+            raise ValueError("Multiple labels are matching.")
+        elif not mapped:
+            raise KeyError(f"No label matches for {tupl}.")
+        else:
+            mapped = mapped[0]
 
         return mapped
 
-    def concrete_in_generic(concrete_tuple, generic_tuple):
+    def rename_duplicated(columns_tuple, columns_mapped, dictionary):
         r"""
-        It is checked if the concrete_tuple is contained in the generic_tuple which is a key of
-        the labels_dict. Thus, it is checked if a multilevel column name is contained in the
-        labels_dict.
-
-        Parameters
-        ---------------
-        concrete_tuple : tuple
-            Column names which need to be adapted to a concise name.
-        generic_tuple : tuple
-            Contains old and new column names. The new column names are used for the labels in the
-            plot.
-
-        Returns
-        ----------
-        True or False : Boolean
-            Boolean whether concrete_tuple is contained in generic_tuple.
+        Appends a suffix to those columns that are not unique. This happens in
+        oemof because a component can appear as the first or second entry in a tuple, which
+        signifies the output or input of the component, respectively.
         """
-        for concrete, generic in zip(concrete_tuple, generic_tuple):
-            if generic in concrete:
-                continue
+        columns_duplicated = columns_mapped.duplicated(keep=False)
+
+        mapped_where = [
+            j
+            for tupl in columns_tuple
+            for j, x in enumerate(tupl)
+            if any([key in x for key in dictionary.keys()])
+        ]
 
-            else:
-                return False
+        mapped_where = pd.Series(mapped_where)
 
-        return True
+        columns_mapped.loc[columns_duplicated & (mapped_where == 0)] += " out"
 
-    renamed_columns = list()
+        columns_mapped.loc[columns_duplicated & mapped_where == 1] += " in"
 
-    for col in columns:
+        return columns_mapped
 
-        renamed_col = map_tuple(col, labels_dict)
+    # Map column names
+    renamed_columns = pd.Series(map(lambda x: map_tuple(x, labels_dict), columns))
 
-        renamed_columns.append(renamed_col)
+    # If there are duplicates, append in/out
+    renamed_columns = rename_duplicated(columns, renamed_columns, labels_dict)
 
     return renamed_columns
 
@@ -314,6 +312,8 @@ def plot_dispatch_plotly(
     fig : plotly.graph_objs._figure.Figure
         Interactive plotly dispatch plot
     """
+    check_undefined_colors(df.columns, colors_odict.keys())
+
     # make sure to obey order as definded in colors_odict
     generic_order = list(colors_odict)
     concrete_order = generic_order.copy()
@@ -395,6 +395,8 @@ def stackplot(ax, df, colors_odict):
     colors_odict : collections.OrderedDictionary
         Ordered dictionary with labels as keys and colourcodes as values.
     """
+    check_undefined_colors(df.columns, colors_odict.keys())
+
     # y is a list which gets the correct stack order from colors file
     colors = []
     labels = []
@@ -426,6 +428,8 @@ def lineplot(ax, df, colors_odict):
     colors_odict : collections.OrderedDictionary
         Ordered dictionary with labels as keys and colourcodes as values.
     """
+    check_undefined_colors(df.columns, colors_odict.keys())
+
     for i in df.columns:
         ax.plot(df.index, df[i], color=colors_odict[i], label=i)
 
@@ -449,6 +453,8 @@ def plot_dispatch(ax, df, df_demand, unit, colors_odict=colors_odict):
     colors_odict : collections.OrderedDictionary
         Ordered dictionary with labels as keys and colourcodes as values.
     """
+    check_undefined_colors(df.columns, colors_odict.keys())
+
     # apply EngFormatter on axis
     ax = eng_format(ax, unit=unit)