Try to debug CLI tests

Author: constantinpape

flamingo_tools/measurements.py

@@ -53,12 +53,12 @@ def intensity_measures(seg_id):
 
         bb_min = np.array([
             row.bb_min_z.item(), row.bb_min_y.item(), row.bb_min_x.item()
-        ]) / resolution
+        ]).astype("float32") / resolution
         bb_min = np.round(bb_min, 0).astype("uint32")
 
         bb_max = np.array([
             row.bb_max_z.item(), row.bb_max_y.item(), row.bb_max_x.item()
-        ]) / resolution
+        ]).astype("float32") / resolution
         bb_max = np.round(bb_max, 0).astype("uint32")
 
         bb = tuple(
@@ -68,15 +68,16 @@ def intensity_measures(seg_id):
 
         local_image = image[bb]
         mask = segmentation[bb] == seg_id
+        assert mask.sum() > 0, f"Segmentation ID {seg_id} is empty."
         masked_intensity = local_image[mask]
 
         # Do the base intensity measurements.
         measures = {
             "label_id": seg_id,
             "mean": np.mean(masked_intensity),
             "stdev": np.std(masked_intensity),
-            "min": np.nanmin(masked_intensity),
-            "max": np.nanmax(masked_intensity),
+            "min": np.min(masked_intensity),
+            "max": np.max(masked_intensity),
             "median": np.median(masked_intensity),
         }
         for percentile in (5, 10, 25, 75, 90, 95):

flamingo_tools/segmentation/postprocessing.py

@@ -118,11 +118,11 @@ def neighbors_in_radius(table: pd.DataFrame, radius: float = 15) -> np.ndarray:
 def _compute_table(segmentation, resolution):
     props = measure.regionprops(segmentation)
     label_ids = np.array([prop.label for prop in props])
-    coordinates = np.array([prop.centroid for prop in props])
+    coordinates = np.array([prop.centroid for prop in props]).astype("float32")
     # transform pixel distance to physical units
     coordinates = coordinates * resolution
-    bb_min = np.array([prop.bbox[:3] for prop in props]) * resolution
-    bb_max = np.array([prop.bbox[3:] for prop in props]) * resolution
+    bb_min = np.array([prop.bbox[:3] for prop in props]).astype("float32") * resolution
+    bb_max = np.array([prop.bbox[3:] for prop in props]).astype("float32") * resolution
     sizes = np.array([prop.area for prop in props])
     table = pd.DataFrame({
         "label_id": label_ids,