Propagate image scale to napari Points layers

cellfinder/napari/detect/detect.py

@@ -148,7 +148,7 @@ def restore_options_defaults(widget: FunctionGui) -> None:
 
 
 def get_results_callback(
-    skip_classification: bool, viewer: napari.Viewer
+    skip_classification: bool, viewer: napari.Viewer, scale
 ) -> Callable:
     """
     Returns the callback that is connected to output of the pipeline.
@@ -162,6 +162,7 @@ def done_func(points):
                 viewer=viewer,
                 name="Cell candidates",
                 cell_type=Cell.UNKNOWN,
+                scale=scale,
             )
 
     else:
@@ -172,6 +173,7 @@ def done_func(points):
                 viewer=viewer,
                 unknown_name="Rejected",
                 cell_name="Detected",
+                scale=scale,
             )
 
     return done_func
@@ -453,7 +455,11 @@ def widget(
         )
 
         worker.returned.connect(
-            get_results_callback(skip_classification, options["viewer"])
+            get_results_callback(
+                skip_classification,
+                options["viewer"],
+                options["signal_image"].scale,
+            )
         )
         # Make sure if the worker emits an error, it is propagated to this
         # thread

cellfinder/napari/utils.py

@@ -1,4 +1,4 @@
-from typing import List, Tuple
+from typing import List, Optional, Tuple
 
 import napari
 import napari.layers
@@ -44,6 +44,7 @@ def add_classified_layers(
     viewer: napari.Viewer,
     unknown_name: str = "Rejected",
     cell_name: str = "Detected",
+    scale: Optional[Tuple[float, float, float]] = None,
 ) -> None:
     """
     Adds cell candidates as two separate point layers - unknowns and cells, to
@@ -60,6 +61,7 @@ def add_classified_layers(
         face_color="lightskyblue",
         visible=False,
         metadata=dict(point_type=Cell.UNKNOWN),
+        scale=scale,
     )
     viewer.add_points(
         cells_to_array(points, Cell.CELL, napari_order=True),
@@ -70,6 +72,7 @@ def add_classified_layers(
         symbol="ring",
         face_color="lightgoldenrodyellow",
         metadata=dict(point_type=Cell.CELL),
+        scale=scale,
     )
 
 
@@ -78,6 +81,7 @@ def add_single_layer(
     viewer: napari.Viewer,
     name: str,
     cell_type: int,
+    scale: Optional[Tuple[float, float, float]] = None,
 ) -> None:
     """
     Adds all cells of cell_type Cell.TYPE to a new point layer in the napari
@@ -93,6 +97,7 @@ def add_single_layer(
         face_color="lightskyblue",
         visible=True,
         metadata=dict(point_type=cell_type),
+        scale=scale,
     )
 
 

tests/napari/test_utils.py

@@ -65,6 +65,32 @@ def test_add_classified_layers(make_napari_viewer):
     assert cells_again == points
 
 
+def test_add_classified_layers_propagates_scale(make_napari_viewer):
+    """Ensure scale is propagated to created Points layers."""
+    scale = (5.0, 1.46, 1.46)
+
+    points = [
+        Cell(pos=[1, 2, 3], cell_type=Cell.CELL),
+        Cell(pos=[4, 5, 6], cell_type=Cell.UNKNOWN),
+    ]
+
+    viewer = make_napari_viewer()
+
+    add_classified_layers(
+        points,
+        viewer,
+        unknown_name="rejected",
+        cell_name="accepted",
+        scale=scale,
+    )
+    # scale is applied to both created Points layers
+    accepted = viewer.layers["accepted"]
+    rejected = viewer.layers["rejected"]
+
+    assert np.allclose(accepted.scale, scale)
+    assert np.allclose(rejected.scale, scale)
+
+
 def test_html_label_widget():
     """Simple unit test for the HTML Label widget"""
     label_widget = html_label_widget("A nice label", tag="h1")