docs: add futures annotations import for older py versions

dclab/features/bright.py

@@ -2,6 +2,8 @@
 Computation of mean and standard deviation of grayscale values inside the
 RT-DC event image mask.
 """
+from __future__ import annotations
+
 import numpy as np
 import numpy.typing as npt
 

dclab/features/bright_bc.py

@@ -2,10 +2,17 @@
 Computation of mean and standard deviation of grayscale values inside the
 RT-DC event image mask with background-correction taken into account.
 """
+from __future__ import annotations
+
 import numpy as np
+import numpy.typing as npt
 
 
-def get_bright_bc(mask, image, image_bg, bg_off=None, ret_data="avg,sd"):
+def get_bright_bc(mask: npt.NDArray[bool] | list[npt.NDArray[bool]],
+                  image: npt.NDArray | list[npt.NDArray],
+                  image_bg: npt.NDArray | list[npt.NDArray],
+                  bg_off: float | npt.NDArray = None,
+                  ret_data: str = "avg,sd"):
     """Compute avg and/or std of the background-corrected event brightness
 
     The background-corrected event brightness is defined by the

dclab/features/bright_perc.py

@@ -2,6 +2,8 @@
 Computation of the 10th and 90th percentile of grayscale values inside the
 RT-DC event image mask with background-correction taken into account.
 """
+from __future__ import annotations
+
 import numpy as np
 import numpy.typing as npt
 

dclab/features/contour.py

@@ -1,8 +1,11 @@
 """Computation of event contour from event mask"""
+from __future__ import annotations
+
 from collections import deque
 import numbers
 
 import numpy as np
+import numpy.typing as npt
 
 # equivalent to
 # from skimage.measure import find_contours
@@ -14,15 +17,15 @@ class NoValidContourFoundError(BaseException):
 
 
 class LazyContourList(object):
-    def __init__(self, masks, max_events=1000):
+    def __init__(self, masks: npt.ArrayLike, max_events: int = 1000):
         """A list-like object that computes contours upon indexing
 
         Parameters
         ----------
-        masks: array-like
+        masks
             3D array of masks, may be an HDF5 dataset or any other
             structure that supports indexing
-        max_events: int
+        max_events
             maximum number of contours to keep in the contour list;
             set to 0/False/None to cache all contours