added energy balance

changed how scatter is plotted

pylintrc

@@ -291,7 +291,7 @@ max-args=6
 max-positional-arguments=6
 
 # Maximum number of attributes for a class (see R0902).
-max-attributes=7
+max-attributes=11
 
 # Maximum number of boolean expressions in an if statement (see R0916).
 max-bool-expr=5

pytrnsys_process/plotting/plot_wrappers.py

@@ -41,7 +41,7 @@ def line_plot(
         >>>
         >>> # run the single scenario on a single simulation
         >>> api.process_single_simulation(
-        >>>     _pl.Path("data/results/complete-0-SnkScale0.6000-StoreScale8"),
+        >>>     _pl.Path("path/to/single/simulation"),
         >>>     create_line_plot,
         >>>     )
 
@@ -87,7 +87,7 @@ def bar_chart(
         >>>
         >>> # run the single scenario on a single simulation
         >>> api.process_single_simulation(
-        >>>     _pl.Path("data/results/complete-0-SnkScale0.6000-StoreScale8"),
+        >>>     _pl.Path("path/to/single/simulation"),
         >>>     create_bar_chart,
         >>>     )
 
@@ -133,7 +133,7 @@ def stacked_bar_chart(
         >>>
         >>> # run the single scenario on a single simulation
         >>> api.process_single_simulation(
-        >>>     _pl.Path("data/results/complete-0-SnkScale0.6000-StoreScale8"),
+        >>>     _pl.Path("path/to/single/simulation"),
         >>>     create_stacked_bar_chart,
         >>>     )
 
@@ -179,7 +179,7 @@ def histogram(
         >>>
         >>> # run the single scenario on a single simulation
         >>> api.process_single_simulation(
-        >>>     _pl.Path("data/results/complete-0-SnkScale0.6000-StoreScale8"),
+        >>>     _pl.Path("path/to/single/simulation"),
         >>>     create_histogram,
         >>>     )
 
@@ -195,7 +195,6 @@ def histogram(
 
 def scatter_plot(
         df: _pd.DataFrame,
-        columns: list[str],
         x_column: str,
         y_column: str,
         use_legend: bool = True,
@@ -206,7 +205,6 @@ def scatter_plot(
 
     Args:
         df: DataFrame containing the data to plot
-        columns: List of column names to plot
         x_column: Name of the column to use for x-axis values
         y_column: Name of the column to use for y-axis values
         use_legend: Whether to show the legend
@@ -221,7 +219,6 @@ def scatter_plot(
         >>> def create_scatter_plot(simulation: api.Simulation):
         >>>     fig, ax = api.scatter_plot(
         ...         simulation.hourly,
-        ...         columns=["var1", "var2", "var3"],
         ...         x_column="var1",
         ...         y_column="var2",
         ...     )
@@ -233,21 +230,92 @@ def scatter_plot(
         >>>
         >>> # run the single scenario on a single simulation
         >>> api.process_single_simulation(
-        >>>     _pl.Path("data/results/complete-0-SnkScale0.6000-StoreScale8"),
+        >>>     _pl.Path("path/to/single/simulation"),
         >>>     create_scatter_plot,
         >>>     )
 
     For additional customization options, refer to:
     - Matplotlib documentation: https://matplotlib.org/stable/api/
     - Pandas plotting: https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.plot.scatter.html
     """
-    plotter = pltrs.ScatterPlot()
+    fig, ax = _plt.subplots(figsize=size)
+    columns = [x_column, y_column]
+    df[columns].plot.scatter(
+        legend=use_legend,
+        ax=ax,
+        x=x_column,
+        y=y_column,
+        **kwargs,
+    )
+    ax = pltrs.configure(ax)
+
+    return fig, ax
+
+
+def energy_balance(
+        df: _pd.DataFrame,
+        q_in_columns: list[str],
+        q_out_columns: list[str],
+        q_imb_column: _tp.Optional[str] = None,
+        use_legend: bool = True,
+        size: tuple[float, float] = const.PlotSizes.A4.value,
+        **kwargs: _tp.Any,
+) -> tuple[_plt.Figure, _plt.Axes]:
+    """Create a stacked bar chart showing energy balance with inputs, outputs and imbalance.
+
+    This function creates an energy balance visualization where:
+    - Input energies are shown as positive values
+    - Output energies are shown as negative values
+    - Energy imbalance is either provided or calculated as (sum of inputs + sum of outputs)
+
+    Args:
+        df: DataFrame containing the energy data
+        q_in_columns: List of column names representing energy inputs
+        q_out_columns: List of column names representing energy outputs
+        q_imb_column: Optional column name containing pre-calculated energy imbalance
+        use_legend: Whether to show the legend
+        size: Figure size tuple (width, height)
+        **kwargs: Additional plotting arguments passed to the stacked bar chart
+
+    Returns:
+        Tuple of (matplotlib Figure object, matplotlib Axes object)
+
+    Example:
+        >>> from pytrnsys_process import api
+        >>> def create_energy_balance(simulation: api.Simulation):
+        >>>     fig, ax = api.energy_balance(
+        ...         simulation.monthly,
+        ...         q_in_columns=['solar_gain', 'auxiliary_power'],
+        ...         q_out_columns=['thermal_losses', 'consumption'],
+        ...     )
+        >>>     ax.set_xlabel('Time')
+        >>>     ax.set_ylabel('Energy [kWh]')
+        >>>     ax.set_title('Monthly Energy Balance')
+        >>>     ax.grid(True)
+        >>> # run the single scenario on a single simulation
+        >>> api.process_single_simulation(
+        >>>     _pl.Path("path/to/single/simulation"),
+        >>>     create_energy_balance,
+        >>>     )
+    """
+    df_modified = df.copy()
+
+    for col in q_out_columns:
+        df_modified[col] = -df_modified[col]
+
+    if q_imb_column is None:
+        q_imb_column = "Qimb"
+        df_modified[q_imb_column] = df_modified[
+            q_in_columns + q_out_columns
+            ].sum(axis=1)
+
+    columns_to_plot = q_in_columns + q_out_columns + [q_imb_column]
+
+    plotter = pltrs.StackedBarChart()
     return plotter.plot(
-        df,
-        columns,
+        df_modified,
+        columns_to_plot,
         use_legend=use_legend,
         size=size,
-        x=x_column,
-        y=y_column,
         **kwargs,
     )

pytrnsys_process/plotting/plotters.py

@@ -8,7 +8,7 @@
 
 import pytrnsys_process.constants as const
 import pytrnsys_process.headers as h
-
+from pytrnsys_process import settings as sett
 
 # TODO: provide A4 and half A4 plots to test sizes in latex # pylint: disable=fixme
 # TODO: provide height as input for plot?  # pylint: disable=fixme
@@ -18,23 +18,24 @@
 # TODO: Add colormap support # pylint: disable=fixme
 
 
+# TODO find a better place for this to live in # pylint : disable=fixme
+plot_settings = sett.settings.plot
+
+
+def configure(ax: _plt.Axes) -> _plt.Axes:
+    ax.set_xlabel(
+        plot_settings.x_label, fontsize=plot_settings.label_font_size
+    )
+    ax.set_ylabel(
+        plot_settings.y_label, fontsize=plot_settings.label_font_size
+    )
+    ax.set_title(plot_settings.title, fontsize=plot_settings.title_font_size)
+    _plt.tight_layout()
+    return ax
+
+
 @dataclass
 class ChartBase(h.HeaderValidationMixin):
-    X_LABEL = ""
-    Y_LABEL = ""
-    TITLE = ""
-    COLOR_MAP = "viridis"
-    DATE_FORMAT = "%b %Y"
-    LABEL_FONT_SIZE = 10
-    LEGEND_FONT_SIZE = 8
-    TITLE_FONT_SIZE = 12
-
-    def configure(self, ax: _plt.Axes) -> _plt.Axes:
-        ax.set_xlabel(self.X_LABEL, fontsize=self.LABEL_FONT_SIZE)
-        ax.set_ylabel(self.Y_LABEL, fontsize=self.LABEL_FONT_SIZE)
-        ax.set_title(self.TITLE, fontsize=self.TITLE_FONT_SIZE)
-        _plt.tight_layout()
-        return ax
 
     def plot(
         self,
@@ -101,16 +102,16 @@ def _do_plot(
         fig, ax = _plt.subplots(figsize=size)
         plot_kwargs = {
             "stacked": True,
-            "colormap": self.COLOR_MAP,
+            "colormap": plot_settings.color_map,
             "legend": use_legend,
             "ax": ax,
             **kwargs,
         }
         ax = df[columns].plot.bar(**plot_kwargs)
         ax.set_xticklabels(
-            _pd.to_datetime(df.index).strftime(self.DATE_FORMAT)
+            _pd.to_datetime(df.index).strftime(plot_settings.date_format)
         )
-        ax = self.configure(ax)
+        ax = configure(ax)
 
         return fig, ax
 
@@ -147,10 +148,10 @@ def _do_plot(
 
         ax.set_xticks(x + width * (len(columns) - 1) / 2)
         ax.set_xticklabels(
-            _pd.to_datetime(df.index).strftime(self.DATE_FORMAT)
+            _pd.to_datetime(df.index).strftime(plot_settings.date_format)
         )
         ax.tick_params(axis="x", labelrotation=90)
-        self.configure(ax)
+        configure(ax)
         return fig, ax
 
 
@@ -166,13 +167,13 @@ def _do_plot(
     ) -> tuple[_plt.Figure, _plt.Axes]:
         fig, ax = _plt.subplots(figsize=size)
         plot_kwargs = {
-            "colormap": self.COLOR_MAP,
+            "colormap": plot_settings.color_map,
             "legend": use_legend,
             "ax": ax,
             **kwargs,
         }
         df[columns].plot.line(**plot_kwargs)
-        ax = self.configure(ax)
+        ax = configure(ax)
         return fig, ax
 
 
@@ -190,30 +191,12 @@ def _do_plot(
     ) -> tuple[_plt.Figure, _plt.Axes]:
         fig, ax = _plt.subplots(figsize=size)
         plot_kwargs = {
-            "colormap": self.COLOR_MAP,
+            "colormap": plot_settings.color_map,
             "legend": use_legend,
             "ax": ax,
             "bins": self.bins,
             **kwargs,
         }
         df[columns].plot.hist(**plot_kwargs)
-        ax = self.configure(ax)
-        return fig, ax
-
-
-class ScatterPlot(ChartBase):
-    def _do_plot(
-        self,
-        df: _pd.DataFrame,
-        columns: list[str],
-        use_legend: bool = True,
-            size: tuple[float, float] = const.PlotSizes.A4.value,
-        **kwargs: _tp.Any,
-    ) -> tuple[_plt.Figure, _plt.Axes]:
-        fig, ax = _plt.subplots(figsize=size)
-        # TODO: cleanup the other Plotters to remove the stringy dictionary.
-        df[columns].plot.scatter(
-            colormap=self.COLOR_MAP, legend=use_legend, ax=ax, **kwargs
-        )
-        ax = self.configure(ax)
+        ax = configure(ax)
         return fig, ax

pytrnsys_process/settings.py

@@ -25,6 +25,15 @@ class Plot:
 
     inkscape_path: str = "C://Program Files//Inkscape//bin//inkscape.exe"
 
+    x_label: str = ""
+    y_label: str = ""
+    title: str = ""
+    date_format: str = "%b %Y"
+    color_map: str = "viridis"
+    label_font_size: int = 10
+    legend_font_size: int = 8
+    title_font_size: int = 12
+
 
 @dataclass
 class Reader:

pytrnsys_process/utils.py

@@ -5,7 +5,7 @@
 
 import matplotlib.pyplot as _plt
 
-from pytrnsys_process import settings as _set
+from pytrnsys_process import settings as sett
 from pytrnsys_process.logger import logger
 
 
@@ -19,8 +19,8 @@ def get_sim_folders(path_to_results: _pl.Path) -> _abc.Sequence[_pl.Path]:
 
 def get_files(
         sim_folders: _abc.Sequence[_pl.Path],
-        results_folder_name: str = _set.settings.reader.folder_name_for_printer_files,
-        get_mfr_and_t: bool = _set.settings.reader.read_step_files,
+        results_folder_name: str = sett.settings.reader.folder_name_for_printer_files,
+        get_mfr_and_t: bool = sett.settings.reader.read_step_files,
 ) -> _abc.Sequence[_pl.Path]:
     sim_files: list[_pl.Path] = []
     for sim_folder in sim_folders:
@@ -74,7 +74,7 @@ def export_plots_in_configured_formats(
     >>>     #   etc.
 
     """
-    plot_settings = _set.settings.plot
+    plot_settings = sett.settings.plot
     plots_folder = path_to_directory / "plots"
     plots_folder.mkdir(exist_ok=True)
 
@@ -95,7 +95,7 @@ def export_plots_in_configured_formats(
 
 def convert_svg_to_emf(file_no_suffix: _pl.Path) -> None:
     try:
-        inkscape_path = _set.settings.plot.inkscape_path
+        inkscape_path = sett.settings.plot.inkscape_path
         if not _pl.Path(inkscape_path).exists():
             raise OSError(f"Inkscape executable not found at: {inkscape_path}")
         emf_filepath = file_no_suffix.with_suffix(".emf")