type cleanup

src/stcal/jump/circle.py

@@ -1,5 +1,5 @@
 import random
-from typing import Union, Optional
+from typing import Optional, Union
 
 import numpy
 
@@ -87,7 +87,7 @@ def __repr__(self) -> str:
 def _expand_circle_from_one_point(
  known_boundary_point: tuple[float, float],
  points: list[tuple[float, float]],
-) -> Circle | None:
+) -> Circle:
  """
  iteratively expand a circle from one known boundary point to enclose the given set of points
  from https://www.nayuki.io/page/smallest-enclosing-circle
@@ -107,7 +107,7 @@ def _expand_circle_from_two_points(
  known_boundary_point_a: tuple[float, float],
  known_boundary_point_b: tuple[float, float],
  points: list[tuple[float, float]],
-) -> Circle | None:
+) -> Circle:
  """
  iteratively expand a circle from two known boundary points to enclose the given set of points
  from https://www.nayuki.io/page/smallest-enclosing-circle
@@ -150,7 +150,7 @@ def _expand_circle_from_two_points(
  if left is None and right is None:
  return circle
  elif left is None:
- return right
+ return right if right is not None else Circle(center=(0.0, 0.0), radius=0.0)
  elif right is None:
  return left
  else:

src/stcal/jump/jump.py

@@ -851,9 +851,9 @@ def area_of_polygon(xy: np.ndarray) -> float:
  apply shoelace algorithm on collection of xy vertex pairs
  https://stackoverflow.com/questions/24467972/calculate-area-of-polygon-given-x-y-coordinates
  """
- return 0.5 * np.abs(
+ return float(0.5 * np.abs(
  np.dot(xy[:, 0], np.roll(xy[:, 1], 1)) - np.dot(xy[:, 1], np.roll(xy[:, 0], 1))
- )
+ ))
 
 
 def find_circles(dqplane: np.ndarray, bitmask: np.ndarray, min_area: float) -> list[Circle]: