Add spade shape

src/data_morph/shapes/factory.py

@@ -53,6 +53,7 @@ class ShapeFactory:
         'rectangle': polygons.Rectangle,
         'rings': circles.Rings,
         'star': polygons.Star,
+        'spade': points.Spade,
     }
 
     AVAILABLE_SHAPES: list[str] = sorted(_SHAPE_MAPPING.keys())

src/data_morph/shapes/points.py

@@ -304,3 +304,66 @@ def distance(self, x: Number, y: Number) -> int:
             Always returns 0 to allow for scattering of the points.
         """
         return 0
+
+
+class Spade(PointCollection):
+    """
+    Class for the spade shape.
+
+    .. plot::
+       :scale: 75
+       :caption:
+            This shape is generated using the panda dataset.
+
+        from data_morph.data.loader import DataLoader
+        from data_morph.shapes.points import Spade
+
+        _ = Spade(DataLoader.load_dataset('panda')).plot()
+
+    Parameters
+    ----------
+    dataset : Dataset
+        The starting dataset to morph into other shapes.
+    """
+
+    def __init__(self, dataset: Dataset) -> None:
+        x_bounds = dataset.data_bounds.x_bounds
+        y_bounds = dataset.data_bounds.y_bounds
+
+        # make heart points using Heart
+        heart_stack = Heart(dataset).points
+
+        # Graph heart curve
+        x_shift = sum(x_bounds) / 2
+        y_shift = sum(y_bounds) / 2
+
+        # vertical flip for heart
+        heart_y = -1.0 * (heart_stack[:, 1] - y_shift) + y_shift
+
+        # Here, I reference kevinr1299 codes
+        # Graph line base
+        line_x = np.linspace(-6, 6, num=12)
+        line_y = np.repeat(-16, 12)
+
+        # Graph left wing
+        left_x = np.linspace(-6, 0, num=12)
+        left_y = 0.278 * np.power(left_x + 6.0, 2) - 16.0
+
+        # Graph right wing
+        right_x = np.linspace(0, 6, num=12)
+        right_y = 0.278 * np.power(right_x - 6.0, 2) - 16.0
+
+        # shift and scale the base and wing
+        x = np.concatenate((line_x, left_x, right_x), axis=0)
+        y = np.concatenate((line_y, left_y, right_y), axis=0)
+
+        # scale by the half the widest width of the spade
+        scale_factor = (x_bounds[1] - x_shift) / 16
+
+        x = x * scale_factor + x_shift
+        y = y * scale_factor + y_shift
+
+        x = np.concatenate((heart_stack[:, 0], x), axis=0)
+        y = np.concatenate((heart_y, y), axis=0)
+
+        super().__init__(*np.stack([x, y], axis=1))