fix bbox planar intersection

e2e/features/image/test_image.py

@@ -3,38 +3,48 @@
 from siibra.features.image.image import Image
 import time
 
+PRERELEASE_FEATURES_W_NO_DATASET = [
+    "The Enriched Connectome - Block face images of full sagittal human brain sections (blockface)",
+    "The Enriched Connectome - 3D polarized light imaging connectivity data of full sagittal human brain sections (HSV fibre orientation map)",
+]
+all_image_features = [f for ft in siibra.features.Feature._SUBCLASSES[siibra.features.image.image.Image] for f in ft._get_instances()]
+
+
+@pytest.mark.parametrize("feature", all_image_features)
+def test_feature_has_datasets(feature: Image):
+    if feature.name in PRERELEASE_FEATURES_W_NO_DATASET:
+        if len(feature.datasets) > 0:
+            pytest.fail(f"Feature '{feature}' was listed as prerelase previosly but now have dataset information. Please update `PRERELEASE_FEATURES_W_NO_DATASET`")
+        pytest.skip(f"Feature '{feature}' has no datasets yet as it is a prerelease data.")
+    assert len(feature.datasets) > 0, f"{feature} has no datasets"
+
+
+def test_images_datasets_names():
+    start = time.time()
+    all_ds_names = {ds.name for f in all_image_features for ds in f.datasets}
+    end = time.time()
+    duration = start - end
+    assert len(all_ds_names) == 10, "expected 10 distinct names"  # this must be updated if new datasets are added
+    assert duration < 1, "Expected getting dataset names to be less than 1s"
+
+
 # Update this as new configs are added
-results = [
+query_and_results = [
     (siibra.features.get(siibra.get_template("big brain"), "CellbodyStainedSection"), 145),
     (siibra.features.get(siibra.get_template("big brain"), "CellBodyStainedVolumeOfInterest"), 2),
     (siibra.features.get(siibra.get_template("mni152"), "image", restrict_space=True), 4),
-    (siibra.features.get(siibra.get_template("mni152"), "image", restrict_space=False), 13),
+    (siibra.features.get(siibra.get_template("mni152"), "image", restrict_space=False), 161),
     (siibra.features.get(siibra.get_region('julich 3.1', 'hoc1 left'), "CellbodyStainedSection"), 45),
     (siibra.features.get(siibra.get_region('julich 2.9', 'hoc1 left'), "CellbodyStainedSection"), 41)
 ]
-features = [f for fts, _ in results for f in fts]
-
-
-@pytest.mark.parametrize("feature", features)
-def test_feature_has_datasets(feature: Image):
-    assert len(feature.datasets) > 0
 
 
-@pytest.mark.parametrize("features, result_len", results)
+@pytest.mark.parametrize("query_results, result_len", query_and_results)
 def test_image_query_results(
-    features: Image,
+    query_results: Image,
     result_len: int
 ):
-    assert len(features) == result_len
-
-
-def test_images_datasets_names():
-    start = time.time()
-    all_ds_names = {ds.name for f in features for ds in f.datasets}
-    end = time.time()
-    duration = start - end
-    assert len(all_ds_names) == 9, "expected 9 distinct names"
-    assert duration < 1, "Expected getting dataset names to be less than 1s"
+    assert len(query_results) == result_len
 
 
 def test_color_channel_fetching():

siibra/locations/boundingbox.py

@@ -188,12 +188,18 @@ def _intersect_bbox(self, other: 'BoundingBox', dims=[0, 1, 2]):
                 result_minpt.append(A[dim])
                 result_maxpt.append(B[dim])
 
+        if result_minpt == result_maxpt:
+            return result_minpt
+
         bbox = BoundingBox(
             point1=point.Point(result_minpt, self.space),
             point2=point.Point(result_maxpt, self.space),
             space=self.space,
         )
-        return bbox if bbox.volume > 0 else None
+
+        if bbox.volume == 0 and sum(cmin == cmax for cmin, cmax in zip(result_minpt, result_maxpt)) == 2:
+            return None
+        return bbox
 
     def _intersect_mask(self, mask: 'Nifti1Image', threshold=0):
         """Intersect this bounding box with an image mask. Returns None if they do not intersect.