Feature/plotting kwargs and streamline data conversion

CHANGELOG.md

@@ -53,16 +53,22 @@ If upgrading from v2.x, see the [v3.0.0 release notes](https://github.com/flixOp
 If upgrading from v2.x, see the [v3.0.0 release notes](https://github.com/flixOpt/flixOpt/releases/tag/v3.0.0) and [Migration Guide](https://flixopt.github.io/flixopt/latest/user-guide/migration-guide-v3/).
 
 ### ✨ Added
+- Support for plotting kwargs in `results.py`, passed to plotly express and matplotlib.
 
 ### 💥 Breaking Changes
 
 ### ♻️ Changed
+- **Template integration**: Plotly templates now fully control plot styling without hardcoded overrides
+- **Dataset first plotting**: Underlying plotting methods in `plotting.py` now use `xr.Dataset` as the main datatype. DataFrames are automatically converted via `_ensure_dataset()`. Both DataFrames and Datasets can be passed to plotting functions without code changes.
 
 ### 🗑️ Deprecated
 
 ### 🔥 Removed
+- Removed  `plotting.pie_with_plotly()` method as it was not used
 
 ### 🐛 Fixed
+- Improved error messages for `engine='matplotlib'` with multidimensional data
+- Better dimension validation in `results.plot_heatmap()`
 
 ### 🔒 Security
 

examples/02_Complex/complex_example_results.py

@@ -25,8 +25,9 @@
     # --- Detailed Plots ---
     # In depth plot for individual flow rates ('__' is used as the delimiter between Component and Flow
     results.plot_heatmap('Wärmelast(Q_th_Last)|flow_rate')
-    for flow_rate in results['BHKW2'].inputs + results['BHKW2'].outputs:
-        results.plot_heatmap(flow_rate)
+    for bus in results.buses.values():
+        bus.plot_node_balance_pie(show=False, save=f'results/{bus.label}--pie.html')
+        bus.plot_node_balance(show=False, save=f'results/{bus.label}--balance.html')
 
     # --- Plotting internal variables manually ---
     results.plot_heatmap('BHKW2(Q_th)|on')

examples/03_Calculation_types/example_calculation_types.py

@@ -202,35 +202,38 @@ def get_solutions(calcs: list, variable: str) -> xr.Dataset:
 
     # --- Plotting for comparison ---
     fx.plotting.with_plotly(
-        get_solutions(calculations, 'Speicher|charge_state').to_dataframe(),
+        get_solutions(calculations, 'Speicher|charge_state'),
         mode='line',
         title='Charge State Comparison',
         ylabel='Charge state',
+        xlabel='Time in h',
     ).write_html('results/Charge State.html')
 
     fx.plotting.with_plotly(
-        get_solutions(calculations, 'BHKW2(Q_th)|flow_rate').to_dataframe(),
+        get_solutions(calculations, 'BHKW2(Q_th)|flow_rate'),
         mode='line',
         title='BHKW2(Q_th) Flow Rate Comparison',
         ylabel='Flow rate',
+        xlabel='Time in h',
     ).write_html('results/BHKW2 Thermal Power.html')
 
     fx.plotting.with_plotly(
-        get_solutions(calculations, 'costs(temporal)|per_timestep').to_dataframe(),
+        get_solutions(calculations, 'costs(temporal)|per_timestep'),
         mode='line',
         title='Operation Cost Comparison',
         ylabel='Costs [€]',
+        xlabel='Time in h',
     ).write_html('results/Operation Costs.html')
 
     fx.plotting.with_plotly(
-        pd.DataFrame(get_solutions(calculations, 'costs(temporal)|per_timestep').to_dataframe().sum()).T,
+        get_solutions(calculations, 'costs(temporal)|per_timestep').sum('time'),
         mode='stacked_bar',
         title='Total Cost Comparison',
         ylabel='Costs [€]',
     ).update_layout(barmode='group').write_html('results/Total Costs.html')
 
     fx.plotting.with_plotly(
-        pd.DataFrame([calc.durations for calc in calculations], index=[calc.name for calc in calculations]),
+        pd.DataFrame([calc.durations for calc in calculations], index=[calc.name for calc in calculations]).to_xarray(),
         mode='stacked_bar',
     ).update_layout(title='Duration Comparison', xaxis_title='Calculation type', yaxis_title='Time (s)').write_html(
         'results/Speed Comparison.html'

flixopt/aggregation.py

@@ -150,13 +150,17 @@ def plot(self, colormap: str = 'viridis', show: bool = True, save: pathlib.Path
         df_agg = self.aggregated_data.copy().rename(
             columns={col: f'Aggregated - {col}' for col in self.aggregated_data.columns}
         )
-        fig = plotting.with_plotly(df_org, 'line', colors=colormap)
+        fig = plotting.with_plotly(df_org.to_xarray(), 'line', colors=colormap, xlabel='Time in h')
         for trace in fig.data:
             trace.update(dict(line=dict(dash='dash')))
-        fig = plotting.with_plotly(df_agg, 'line', colors=colormap, fig=fig)
+        fig2 = plotting.with_plotly(df_agg.to_xarray(), 'line', colors=colormap, xlabel='Time in h')
+        for trace in fig2.data:
+            fig.add_trace(trace)
 
         fig.update_layout(
-            title='Original vs Aggregated Data (original = ---)', xaxis_title='Index', yaxis_title='Value'
+            title='Original vs Aggregated Data (original = ---)',
+            xaxis_title='Time in h',
+            yaxis_title='Value',
         )
 
         plotting.export_figure(