Merge branch 'main' into first-release

synapse_net/tools/base_widget.py

@@ -330,17 +330,8 @@ def _add_properties_and_table(self, layer, table_data, save_path=""):
         layer.properties = table_data
 
         if add_table is not None:
-            table = get_table(layer, self.viewer)
-            if table is None:
-                with _SilencePrint():
-                    add_table(layer, self.viewer)
-            else:
-                # FIXME updating the table does not yet work
-                with _SilencePrint():
-                    table.update_content()
-                # table_dict = table_data.to_dict()
-                # table_dict["index"] = table_dict["label"]
-                # table.set_content(table_dict)
+            with _SilencePrint():
+                add_table(layer, self.viewer)
 
         # Save table to file if save path is provided.
         if save_path != "":

synapse_net/tools/distance_measure_widget.py

@@ -87,7 +87,8 @@ def on_measure_seg_to_object(self):
             seg_ids=seg_ids,
         )
         table_data = self._to_table_data(distances, seg_ids, endpoints1, endpoints2)
-        self._add_lines_and_table(lines, table_data, name="distances")
+        structure_layer_name = self._get_layer_selector_layer(self.image_selector_name2).name
+        self._add_lines_and_table(lines, table_data, name="distances-to-" + structure_layer_name)
 
     def on_measure_pairwise(self):
         segmentation = self._get_layer_selector_data(self.image_selector_name1)

synapse_net/tools/segmentation_widget.py

@@ -189,7 +189,7 @@ def on_predict(self):
             for name, seg in segmentation.items():
                 self.viewer.add_labels(seg, name=name, metadata=metadata)
         else:
-            self.viewer.add_labels(segmentation, name=f"{model_type}-segmentation", metadata=metadata)
+            self.viewer.add_labels(segmentation, name=f"{model_type}", metadata=metadata)
         show_info(f"INFO: Segmentation of {model_type} added to layers.")
 
     def _create_settings_widget(self):

synapse_net/tools/vesicle_pool_widget.py

@@ -30,10 +30,14 @@ def __init__(self):
         # 2. Selector for a distance layer.
         self.dist_selector_name1 = "Distances to Structure"
         self.dist_selector_widget1 = self._create_layer_selector(self.dist_selector_name1, layer_type="Shapes")
+        # 3. Selector for a second distance layer (optional).
+        self.dist_selector_name2 = "Distances to Structure 2"
+        self.dist_selector_widget2 = self._create_layer_selector(self.dist_selector_name2, layer_type="Shapes")
 
         # Add the selector widgets to the layout.
         layout.addWidget(self.vesicle_selector_widget)
         layout.addWidget(self.dist_selector_widget1)
+        layout.addWidget(self.dist_selector_widget2)
 
         # Create the UI elements for defining the vesicle pools:
         # The name of the output name, the name of the vesicle pool, and the criterion for the pool.
@@ -68,6 +72,11 @@ def on_pool_vesicles(self):
 
         distance_layer = self._get_layer_selector_layer(self.dist_selector_name1)
         distances = None if distance_layer is None else distance_layer.properties
+        distance_layer2 = self._get_layer_selector_layer(self.dist_selector_name2)
+        # Check if the second distance is the same as the first.
+        if distance_layer2.name == distance_layer.name:
+            distance_layer2 = None
+        distances2 = None if distance_layer2 is None else distance_layer2.properties
 
         if segmentation is None:
             show_info("INFO: Please choose a segmentation.")
@@ -87,7 +96,9 @@ def on_pool_vesicles(self):
         pool_name = self.pool_name_param.text()
 
         pool_color = self.pool_color_param.text()
-        self._compute_vesicle_pool(segmentation, distances, morphology, pool_layer_name, pool_name, query, pool_color)
+        self._compute_vesicle_pool(
+            segmentation, distances, morphology, pool_layer_name, pool_name, query, pool_color, distances2
+            )
 
     def _update_pool_colors(self, pool_name, pool_color):
         if pool_color == "":
@@ -107,6 +118,7 @@ def _compute_vesicle_pool(
         pool_name: str,
         query: str,
         pool_color: str,
+        distances2: Dict = None
     ):
         """Compute a vesicle pool based on the provided query parameters.
 
@@ -118,6 +130,7 @@ def _compute_vesicle_pool(
             pool_name: Name for the pooled group to be assigned.
             query: Query parameters.
             pool_color: Optional color for the vesicle pool.
+            distances2: Properties from the second distances layer (optional).
         """
         # Check which of the properties are present and construct the combined properties based on this.
         if distances is None and morphology is None:  # No properties were given -> we can't do anything.
@@ -140,7 +153,14 @@ def _compute_vesicle_pool(
             distances = pd.DataFrame(distances).drop(columns=["index"])
             morphology = pd.DataFrame(morphology).drop(columns=["index"])
             merged_df = morphology.merge(distances, left_on="label", right_on="label", suffixes=("_morph", "_dist"))
-
+        # Add distances2 if present.
+        if distances2 is not None:
+            distance_ids = distances2.get("label", [])
+            if set(distance_ids) != set(merged_df.label):
+                show_info("ERROR: The IDs in distances2 and morphology are not identical.")
+                return
+            distances2 = pd.DataFrame(distances2).drop(columns=["index"])
+            merged_df = merged_df.merge(distances2, left_on="label", right_on="label", suffixes=("", "2"))
         # Assign the vesicles to the current pool by filtering the mergeddataframe based on the query.
         filtered_df = self._parse_query(query, merged_df)
         if len(filtered_df) == 0:
@@ -167,6 +187,12 @@ def _compute_vesicle_pool(
             # Combine the vesicle ids corresponding to the previous assignment with the
             # assignment for the new / current pool.
             old_pool_ids = pool_properties.label.values.tolist()
+
+            # Overwrite the intersection of the two pool assignments with the new pool.
+            pool_intersections = np.intersect1d(pool_vesicle_ids, old_pool_ids)
+            old_pool_ids = [item for item in old_pool_ids if item not in pool_intersections]
+            pool_properties = pool_properties[~pool_properties['label'].isin(pool_intersections)]
+
             pool_assignments = sorted(pool_vesicle_ids + old_pool_ids)
 
             # Get a map for each vesicle id to its pool.