Assert leaf_size > 0

changelog.md

@@ -5,7 +5,9 @@ Version 0.3.2
 ------------
 - Fixed issue https://github.com/remydubois/lsnms/issues/12, by masking scores as well as boxes.
 - Added torch and torchvision as proper dev dependencies
-- Fixed Pillow version to 9.3.0 in dev dependencies because 9.4.0 does not compile on my mbp (see https://github.com/python-pillow/Pillow/issues/6862)
+- Fixed Pillow version (dev dep) to 9.3.0 in dev dependencies because 9.4.0 does not compile on my mbp (see https://github.com/python-pillow/Pillow/issues/6862)
+- Removed deprecated arguments: `cutoff_distance` and `tree`. Removed associated tests.
+- Added sanity check to ensure `leaf_size` is strictly positive.
 
 
 Version 0.3.1

lsnms/rtree.py

@@ -57,6 +57,7 @@ def __init__(self, data, leaf_size=16, axis=0, indices=None):
         self.data = data
         self.axis = axis
         # Quick sanity checks
+        assert leaf_size > 0, "Leaf size must be strictly positive"
         assert len(data) > 0, "Empty dataset"
         assert self.data.shape[-1] % 2 == 0, "odd dimensionality"
         assert data.ndim == 2, "Boxes to index should be (n_boxes, 4)"

tests/test_boxtree.py → tests/test_rtree.py

@@ -1,6 +1,7 @@
 import numpy as np
+import pytest
 
-from lsnms.rtree import RTree
+from lsnms.rtree import RNode, RTree
 
 
 def intersection(boxA, boxB):
@@ -35,3 +36,15 @@ def test_intersect_tree():
         out_inter = np.array([inter for i, inter in enumerate(np_intersect) if i not in indices])
         np.testing.assert_allclose(in_inter, intersections)
         np.testing.assert_array_less(out_inter, min_area)
+
+
+def test_build_odd_tree(instances):
+    boxes, _ = instances
+    with pytest.raises(AssertionError):
+        _ = RTree(boxes, leaf_size=0)
+
+
+def test_build_rnode_default_args(instances):
+    boxes, _ = instances
+
+    _ = RNode(boxes)

tests/test_util.py

@@ -5,16 +5,6 @@
 from lsnms.util import box_englobing_boxes, intersection, offset_bboxes
 
 
-def datagen(n=10_000):
-    topleft = np.random.uniform(0.0, high=1_000, size=(n, 2))
-    wh = np.random.uniform(15, 45, size=topleft.shape)
-
-    boxes = np.concatenate([topleft, topleft + wh], axis=1)
-    scores = np.random.uniform(0.1, 1.0, size=len(topleft))
-
-    return boxes, scores
-
-
 @njit
 def intersect_many(tree, boxes):
     intersections = []
@@ -31,8 +21,8 @@ def assert_no_intersect(boxesA, boxesB):
     assert intersection(boxA, boxB) == 0.0
 
 
-def test_offset_bboxes():
-    boxes, _ = datagen()
+def test_offset_bboxes(instances):
+    boxes, _ = instances
     rng = np.random.default_rng(0)
     class_ids = rng.integers(0, 2, size=len(boxes))
 
@@ -50,10 +40,10 @@ def test_offset_bboxes():
 
 
 @pytest.mark.skip(reason="Visual test")
-def test_visual_offset_bboxes():
+def test_visual_offset_bboxes(instances):
     import matplotlib.pyplot as plt
 
-    boxes, _ = datagen()
+    boxes, _ = instances
     # boxes = boxes.reshape(-1, 2, 2).mean(1)
     rng = np.random.default_rng(0)
     class_ids = rng.integers(0, 3, size=len(boxes))