Circle shape updates

src/data_morph/bounds/bounding_box.py

@@ -170,25 +170,25 @@ def clone(self) -> BoundingBox:
         )
 
     @property
-    def range(self) -> Iterable[Number]:
+    def range(self) -> tuple[Number, Number]:
         """
         Calculate the range (width) of the bounding box in each direction.
 
         Returns
         -------
-        Iterable[numbers.Number]
+        tuple[Number, Number]
             The range covered by the x and y bounds, respectively.
         """
         return self.x_bounds.range, self.y_bounds.range
 
     @property
-    def center(self) -> Iterable[Number]:
+    def center(self) -> tuple[Number, Number]:
         """
         Calculate the center of the bounding box.
 
         Returns
         -------
-        Iterable[numbers.Number]
+        tuple[Number, Number]
             The center of the x and y bounds, respectively.
         """
         return self.x_bounds.center, self.y_bounds.center

src/data_morph/shapes/circles/__init__.py

@@ -0,0 +1,11 @@
+"""Shapes made up of circles."""
+
+from .bullseye import Bullseye
+from .circle import Circle
+from .rings import Rings
+
+__all__ = [
+    'Bullseye',
+    'Circle',
+    'Rings',
+]

src/data_morph/shapes/circles/bullseye.py

@@ -0,0 +1,50 @@
+"""Bullseye shape."""
+
+from __future__ import annotations
+
+from typing import TYPE_CHECKING
+
+import numpy as np
+
+from .rings import Rings
+
+if TYPE_CHECKING:
+    from ..data.dataset import Dataset
+
+
+class Bullseye(Rings):
+    """
+    Class representing a bullseye shape comprising two concentric circles.
+
+    .. plot::
+       :scale: 75
+       :caption:
+            This shape is generated using the panda dataset.
+
+        from data_morph.data.loader import DataLoader
+        from data_morph.shapes.circles import Bullseye
+
+        _ = Bullseye(DataLoader.load_dataset('panda')).plot()
+
+    See Also
+    --------
+    Circle : The individual rings are represented as circles.
+    """
+
+    @staticmethod
+    def _derive_radii(dataset: Dataset) -> np.ndarray:
+        """
+        Derive the radii for the circles in the bullseye.
+
+        Parameters
+        ----------
+        dataset : Dataset
+            The starting dataset to morph into.
+
+        Returns
+        -------
+        np.ndarray
+            The radii for the circles in the bullseye.
+        """
+        stdev = dataset.data[['x', 'y']].std().mean() * 1.5
+        return np.linspace(stdev, 0, 2, endpoint=False)