Merge pull request #73 from computational-cell-analytics/68-create-a-…

…widget-for-vesicle-pool-assignments

68 create a widget for vesicle pool assignments

synaptic_reconstruction/napari.yaml

@@ -1,5 +1,5 @@
 name: synaptic_reconstruction
-display_name: Synaptic Reconstruction
+display_name: SynapseNet
 # see https://napari.org/stable/plugins/manifest.html for valid categories
 categories: ["Image Processing", "Annotation"]
 contributions:
@@ -16,6 +16,9 @@ contributions:
     - id: synaptic_reconstruction.morphology
       python_name: synaptic_reconstruction.tools.morphology_widget:MorphologyWidget
       title: Morphology Analysis
+    - id: synaptic_reconstruction.vesicle_pooling
+      python_name: synaptic_reconstruction.tools.vesicle_pool_widget:VesiclePoolWidget
+      title: Vesicle Pooling
 
   readers:
     - command: synaptic_reconstruction.file_reader
@@ -32,3 +35,5 @@ contributions:
       display_name: Distance Measurement
     - command: synaptic_reconstruction.morphology
       display_name: Morphology Analysis
+    - command: synaptic_reconstruction.vesicle_pooling
+      display_name: Vesicle Pooling

synaptic_reconstruction/tools/base_widget.py

@@ -1,13 +1,20 @@
+import os
 from pathlib import Path
 
 import napari
 import qtpy.QtWidgets as QtWidgets
 
+from napari.utils.notifications import show_info
 from qtpy.QtWidgets import (
     QWidget, QVBoxLayout, QHBoxLayout, QLabel, QSpinBox, QComboBox, QCheckBox
 )
 from superqt import QCollapsible
 
+try:
+    from napari_skimage_regionprops import add_table
+except ImportError:
+    add_table = None
+
 
 class BaseWidget(QWidget):
     def __init__(self):
@@ -31,12 +38,14 @@ def _create_layer_selector(self, selector_name, layer_type="Image"):
             layer_filter = napari.layers.Image
         elif layer_type == "Labels":
             layer_filter = napari.layers.Labels
+        elif layer_type == "Shapes":
+            layer_filter = napari.layers.Shapes
         else:
             raise ValueError("layer_type must be either 'Image' or 'Labels'.")
 
         selector_widget = QtWidgets.QWidget()
         image_selector = QtWidgets.QComboBox()
-        layer_label = QtWidgets.QLabel(f"{selector_name} Layer:")
+        layer_label = QtWidgets.QLabel(f"{selector_name}:")
 
         # Populate initial options
         self._update_selector(selector=image_selector, layer_filter=layer_filter)
@@ -58,9 +67,23 @@ def _create_layer_selector(self, selector_name, layer_type="Image"):
     def _update_selector(self, selector, layer_filter):
         """Update a single selector with the current image layers in the viewer."""
         selector.clear()
-        image_layers = [layer.name for layer in self.viewer.layers if isinstance(layer, layer_filter)]  # if isinstance(layer, napari.layers.Image)
+        image_layers = [layer.name for layer in self.viewer.layers if isinstance(layer, layer_filter)]
         selector.addItems(image_layers)
 
+    def _get_layer_selector_layer(self, selector_name):
+        """Return the layer currently selected in a given selector."""
+        if selector_name in self.layer_selectors:
+            selector_widget = self.layer_selectors[selector_name]
+
+            # Retrieve the QComboBox from the QWidget's layout
+            image_selector = selector_widget.layout().itemAt(1).widget()
+
+            if isinstance(image_selector, QComboBox):
+                selected_layer_name = image_selector.currentText()
+                if selected_layer_name in self.viewer.layers:
+                    return self.viewer.layers[selected_layer_name]
+        return None  # Return None if layer not found
+
     def _get_layer_selector_data(self, selector_name, return_metadata=False):
         """Return the data for the layer currently selected in a given selector."""
         if selector_name in self.layer_selectors:
@@ -172,7 +195,7 @@ def _add_shape_param(self, names, values, min_val, max_val, step=1, title=None,
             title=title[1] if title is not None else title, tooltip=tooltip
         )
         layout.addLayout(y_layout)
-        
+
         if len(names) == 3:
             z_layout = QVBoxLayout()
             z_param, _ = self._add_int_param(
@@ -262,3 +285,43 @@ def _get_file_path(self, name, textbox, tooltip=None):
         else:
             # Handle the case where the selected path is not a file
             print("Invalid file selected. Please try again.")
+
+    def _handle_resolution(self, metadata, voxel_size_param, ndim):
+        # Get the resolution / voxel size from the layer metadata if available.
+        resolution = metadata.get("voxel_size", None)
+        if resolution is not None:
+            resolution = [resolution[ax] for ax in ("zyx" if ndim == 3 else "yx")]
+
+        # If user input was given then override resolution from metadata.
+        if voxel_size_param.value() != 0.0:  # Changed from default.
+            resolution = ndim * [voxel_size_param.value()]
+
+        assert len(resolution) == ndim
+        return resolution
+
+    def _save_table(self, save_path, data):
+        ext = os.path.splitext(save_path)[1]
+        if ext == "":  # No file extension given, By default we save to CSV.
+            file_path = f"{save_path}.csv"
+            data.to_csv(file_path, index=False)
+        elif ext == ".csv":  # Extension was specified as csv
+            file_path = save_path
+            data.to_csv(file_path, index=False)
+        elif ext == ".xlsx":  # We also support excel.
+            file_path = save_path
+            data.to_excel(file_path, index=False)
+        else:
+            raise ValueError("Invalid extension for table: {ext}. We support .csv or .xlsx.")
+        return file_path
+
+    def _add_properties_and_table(self, layer, table_data, save_path=""):
+        if layer.properties:
+            layer.properties = layer.properties.update(table_data)
+        else:
+            layer.properties = table_data
+        if add_table is not None:
+            add_table(layer, self.viewer)
+        # Save table to file if save path is provided.
+        if save_path != "":
+            file_path = self._save_table(self.save_path.text(), table_data)
+            show_info(f"INFO: Added table and saved file to {file_path}.")

synaptic_reconstruction/tools/distance_measure_widget.py

@@ -1,5 +1,3 @@
-import os
-
 import napari
 import napari.layers
 import numpy as np
@@ -11,27 +9,6 @@
 from .base_widget import BaseWidget
 from .. import distance_measurements
 
-try:
-    from napari_skimage_regionprops import add_table
-except ImportError:
-    add_table = None
-
-
-def _save_distance_table(save_path, data):
-    ext = os.path.splitext(save_path)[1]
-    if ext == "":  # No file extension given, By default we save to CSV.
-        file_path = f"{save_path}.csv"
-        data.to_csv(file_path, index=False)
-    elif ext == ".csv":  # Extension was specified as csv
-        file_path = save_path
-        data.to_csv(file_path, index=False)
-    elif ext == ".xlsx":  # We also support excel.
-        file_path = save_path
-        data.to_excel(file_path, index=False)
-    else:
-        raise ValueError("Invalid extension for table: {ext}. We support .csv or .xlsx.")
-    return file_path
-
 
 class DistanceMeasureWidget(BaseWidget):
     def __init__(self):
@@ -68,47 +45,33 @@ def __init__(self):
     def _to_table_data(self, distances, seg_ids, endpoints1=None, endpoints2=None):
         assert len(distances) == len(seg_ids), f"{distances.shape}, {seg_ids.shape}"
         if seg_ids.ndim == 2:
-            table_data = {"label1": seg_ids[:, 0], "label2": seg_ids[:, 1], "distance": distances}
+            table_data = {"label_id1": seg_ids[:, 0], "label_id2": seg_ids[:, 1], "distance": distances}
         else:
-            table_data = {"label": seg_ids, "distance": distances}
+            table_data = {"label_id": seg_ids, "distance": distances}
         if endpoints1 is not None:
             axis_names = "zyx" if endpoints1.shape[1] == 3 else "yx"
             table_data.update({f"begin-{ax}": endpoints1[:, i] for i, ax in enumerate(axis_names)})
             table_data.update({f"end-{ax}": endpoints2[:, i] for i, ax in enumerate(axis_names)})
         return pd.DataFrame(table_data)
 
-    def _add_lines_and_table(self, lines, properties, table_data, name):
+    def _add_lines_and_table(self, lines, table_data, name):
         line_layer = self.viewer.add_shapes(
             lines,
             name=name,
             shape_type="line",
             edge_width=2,
             edge_color="red",
             blending="additive",
-            properties=properties,
         )
-        if add_table is not None:
-            add_table(line_layer, self.viewer)
-
-        if self.save_path.text() != "":
-            file_path = _save_distance_table(self.save_path.text(), table_data)
-
-        if self.save_path.text() != "":
-            show_info(f"Added distance lines and saved file to {file_path}.")
-        else:
-            show_info("Added distance lines.")
+        self._add_properties_and_table(line_layer, table_data, self.save_path.text())
 
     def on_measure_seg_to_object(self):
         segmentation = self._get_layer_selector_data(self.image_selector_name1)
         object_data = self._get_layer_selector_data(self.image_selector_name2)
-        # get metadata from layer if available
+
+        # Get the resolution / voxel size.
         metadata = self._get_layer_selector_data(self.image_selector_name1, return_metadata=True)
-        resolution = metadata.get("voxel_size", None)
-        if resolution is not None:
-            resolution = [v for v in resolution.values()]
-        # if user input is present override metadata
-        if self.voxel_size_param.value() != 0.0:  # changed from default
-            resolution = segmentation.ndim * [self.voxel_size_param.value()]
+        resolution = self._handle_resolution(metadata, self.voxel_size_param, segmentation.ndim)
 
         (distances,
          endpoints1,
@@ -117,28 +80,23 @@ def on_measure_seg_to_object(self):
             segmentation=segmentation, segmented_object=object_data, distance_type="boundary",
             resolution=resolution
         )
-        lines, properties = distance_measurements.create_object_distance_lines(
+        lines, _ = distance_measurements.create_object_distance_lines(
             distances=distances,
             endpoints1=endpoints1,
             endpoints2=endpoints2,
             seg_ids=seg_ids,
         )
         table_data = self._to_table_data(distances, seg_ids, endpoints1, endpoints2)
-        self._add_lines_and_table(lines, properties, table_data, name="distances")
+        self._add_lines_and_table(lines, table_data, name="distances")
 
     def on_measure_pairwise(self):
         segmentation = self._get_layer_selector_data(self.image_selector_name1)
         if segmentation is None:
             show_info("Please choose a segmentation.")
             return
-        # get metadata from layer if available
+
         metadata = self._get_layer_selector_data(self.image_selector_name1, return_metadata=True)
-        resolution = metadata.get("voxel_size", None)
-        if resolution is not None:
-            resolution = [v for v in resolution.values()]
-        # if user input is present override metadata
-        if self.voxel_size_param.value() != 0.0:  # changed from default
-            resolution = segmentation.ndim * [self.voxel_size_param.value()]
+        resolution = self._handle_resolution(metadata, self.voxel_size_param, segmentation.ndim)
 
         (distances,
          endpoints1,
@@ -153,7 +111,7 @@ def on_measure_pairwise(self):
             distances=properties["distance"],
             seg_ids=np.concatenate([properties["id_a"][:, None], properties["id_b"][:, None]], axis=1)
         )
-        self._add_lines_and_table(lines, properties, table_data, name="pairwise-distances")
+        self._add_lines_and_table(lines, table_data, name="pairwise-distances")
 
     def _create_settings_widget(self):
         setting_values = QWidget()