feat: dark mode for plots

src/safeds/data/tabular/plotting/_column_plotter.py

@@ -1,6 +1,6 @@
 from __future__ import annotations
 
-from typing import TYPE_CHECKING
+from typing import TYPE_CHECKING, Literal
 
 from safeds._utils import _figure_to_image
 from safeds._validation._check_columns_are_numeric import _check_column_is_numeric
@@ -29,10 +29,15 @@ class ColumnPlotter:
     def __init__(self, column: Column):
         self._column: Column = column
 
-    def box_plot(self) -> Image:
+    def box_plot(self, *, theme: Literal["dark", "light"] = "light") -> Image:
         """
         Create a box plot for the values in the column. This is only possible for numeric columns.
 
+        Parameters
+        ----------
+        theme:
+            The color theme of the plot. Default is "light".
+
         Returns
         -------
         plot:
@@ -54,27 +59,84 @@ def box_plot(self) -> Image:
 
         import matplotlib.pyplot as plt
 
-        fig, ax = plt.subplots()
-        ax.boxplot(
-            self._column._series.drop_nulls(),
-            patch_artist=True,
-        )
-
-        ax.set(title=self._column.name)
-        ax.set_xticks([])
-        ax.yaxis.grid(visible=True)
-        fig.tight_layout()
-
-        return _figure_to_image(fig)
-
-    def histogram(self, *, max_bin_count: int = 10) -> Image:
+        def _set_boxplot_colors(box: dict, theme: str) -> None:
+            if theme == "dark":
+                for median in box["medians"]:
+                    median.set(color="orange", linewidth=1.5)
+
+                for box_part in box["boxes"]:
+                    box_part.set(color="white", linewidth=1.5, facecolor="cyan")
+
+                for whisker in box["whiskers"]:
+                    whisker.set(color="white", linewidth=1.5)
+
+                for cap in box["caps"]:
+                    cap.set(color="white", linewidth=1.5)
+
+                for flier in box["fliers"]:
+                    flier.set(marker="o", color="white", alpha=0.5)
+            else:
+                for median in box["medians"]:
+                    median.set(color="orange", linewidth=1.5)
+
+                for box_part in box["boxes"]:
+                    box_part.set(color="black", linewidth=1.5, facecolor="blue")
+
+                for whisker in box["whiskers"]:
+                    whisker.set(color="black", linewidth=1.5)
+
+                for cap in box["caps"]:
+                    cap.set(color="black", linewidth=1.5)
+
+                for flier in box["fliers"]:
+                    flier.set(marker="o", color="black", alpha=0.5)
+
+        style = "dark_background" if theme == "dark" else "default"
+        with plt.style.context(style):
+            if theme == "dark":
+                plt.rcParams.update(
+                    {
+                        "text.color": "white",
+                        "axes.labelcolor": "white",
+                        "axes.edgecolor": "white",
+                        "xtick.color": "white",
+                        "ytick.color": "white",
+                        "grid.color": "gray",
+                        "grid.linewidth": 0.5,
+                    },
+                )
+            else:
+                plt.rcParams.update(
+                    {
+                        "grid.linewidth": 0.5,
+                    },
+                )
+
+            fig, ax = plt.subplots()
+            box = ax.boxplot(
+                self._column._series.drop_nulls(),
+                patch_artist=True,
+            )
+
+            _set_boxplot_colors(box, theme)
+
+            ax.set(title=self._column.name)
+            ax.set_xticks([])
+            ax.yaxis.grid(visible=True)
+            fig.tight_layout()
+
+            return _figure_to_image(fig)
+
+    def histogram(self, *, max_bin_count: int = 10, theme: Literal["dark", "light"] = "light") -> Image:
         """
         Create a histogram for the values in the column.
 
         Parameters
         ----------
         max_bin_count:
             The maximum number of bins to use in the histogram. Default is 10.
+        theme:
+            The color theme of the plot. Default is "light".
 
         Returns
         -------
@@ -87,16 +149,33 @@ def histogram(self, *, max_bin_count: int = 10) -> Image:
         >>> column = Column("test", [1, 2, 3])
         >>> histogram = column.plot.histogram()
         """
-        return self._column.to_table().plot.histograms(max_bin_count=max_bin_count)
+        import matplotlib.pyplot as plt
 
-    def lag_plot(self, lag: int) -> Image:
+        style = "dark_background" if theme == "dark" else "default"
+        with plt.style.context(style):
+            if theme == "dark":
+                plt.rcParams.update(
+                    {
+                        "text.color": "white",
+                        "axes.labelcolor": "white",
+                        "axes.edgecolor": "white",
+                        "xtick.color": "white",
+                        "ytick.color": "white",
+                    },
+                )
+
+            return self._column.to_table().plot.histograms(max_bin_count=max_bin_count)
+
+    def lag_plot(self, lag: int, *, theme: Literal["dark", "light"] = "light") -> Image:
         """
         Create a lag plot for the values in the column.
 
         Parameters
         ----------
         lag:
             The amount of lag.
+        theme:
+            The color theme of the plot. Default is "light".
 
         Returns
         -------
@@ -114,21 +193,34 @@ def lag_plot(self, lag: int) -> Image:
         >>> column = Column("values", [1, 2, 3, 4])
         >>> image = column.plot.lag_plot(2)
         """
-        if self._column.row_count > 0:
-            _check_column_is_numeric(self._column, operation="create a lag plot")
-
         import matplotlib.pyplot as plt
 
-        fig, ax = plt.subplots()
-        series = self._column._series
-        ax.scatter(
-            x=series.slice(0, max(len(self._column) - lag, 0)),
-            y=series.slice(lag),
-        )
-        ax.set(
-            xlabel="y(t)",
-            ylabel=f"y(t + {lag})",
-        )
-        fig.tight_layout()
-
-        return _figure_to_image(fig)
+        style = "dark_background" if theme == "dark" else "default"
+        with plt.style.context(style):
+            if theme == "dark":
+                plt.rcParams.update(
+                    {
+                        "text.color": "white",
+                        "axes.labelcolor": "white",
+                        "axes.edgecolor": "white",
+                        "xtick.color": "white",
+                        "ytick.color": "white",
+                    },
+                )
+
+            if self._column.row_count > 0:
+                _check_column_is_numeric(self._column, operation="create a lag plot")
+
+            fig, ax = plt.subplots()
+            series = self._column._series
+            ax.scatter(
+                x=series.slice(0, max(len(self._column) - lag, 0)),
+                y=series.slice(lag),
+            )
+            ax.set(
+                xlabel="y(t)",
+                ylabel=f"y(t + {lag})",
+            )
+            fig.tight_layout()
+
+            return _figure_to_image(fig)