Fixing Issue #84

.github/workflows/test_and_deploy.yml

@@ -19,7 +19,7 @@ jobs:
     runs-on: ${{ matrix.platform }}
     strategy:
       matrix:
-        platform: [ubuntu-latest, windows-latest, macos-latest]
+        platform: [ubuntu-20.04, windows-latest] #, macos-latest]
         python-version: ['3.8', '3.9', '3.10']
 
     steps:

napari_skimage_regionprops/_load_csv.py

@@ -1,5 +1,6 @@
 import numpy as np
 from napari_tools_menu import register_function
+from napari.utils.notifications import show_warning
 
 try:
     import napari
@@ -9,7 +10,7 @@
 
 
 @register_function(menu="Measurement > Load from CSV (nsr)")
-def load_csv(csv_filename:"magicgui.types.PathLike", labels_layer: "napari.layers.Labels", show_table: bool = True, viewer: "napari.Viewer" = None):
+def load_csv(csv_filename:"magicgui.types.PathLike", labels_layer: "napari.layers.Layer", show_table: bool = True, viewer: "napari.Viewer" = None):
     """Save contents of a CSV file into a given layer's properties"""
     import pandas as pd
     # load region properties from csv file
@@ -24,9 +25,25 @@ def load_csv(csv_filename:"magicgui.types.PathLike", labels_layer: "napari.layer
             {"label": np.array(range(1, (len(edited_reg_props) + 1)))}
         )
         edited_reg_props = pd.concat([label_column, edited_reg_props], axis=1)
-
+    # Add 'properties' and 'features' attributes if layer is Surface
+    if isinstance(labels_layer, napari.layers.Surface):
+        # Check if features and properties are already defined
+        if not hasattr(labels_layer, "features"):
+            labels_layer.features = {}
+        if not hasattr(labels_layer, "properties"):
+            labels_layer.properties = {}
+    elif isinstance(labels_layer, napari.layers.Points):
+        # Table shape must match number of points
+        if edited_reg_props.shape[0] < labels_layer.data.shape[0]:
+            # fill in missing rows with NaNs
+            show_warning("Number of rows in CSV file is less than number of points in the layer. Filling in missing rows with NaNs.")
+            edited_reg_props = pd.concat([edited_reg_props, pd.DataFrame(np.nan, index=range(labels_layer.data.shape[0] - edited_reg_props.shape[0]), columns=edited_reg_props.columns)]).reset_index(drop=True)
+        elif edited_reg_props.shape[0] > labels_layer.data.shape[0]:
+            # truncate if necessary
+            show_warning("Number of rows in CSV file is greater than number of points in the layer. Truncating to match number of points.")
+            edited_reg_props = edited_reg_props.iloc[:labels_layer.data.shape[0],:]
     if hasattr(labels_layer, "properties"):
-        labels_layer.properties = edited_reg_props
+        labels_layer.properties = edited_reg_props.to_dict(orient="list")
     if hasattr(labels_layer, "features"):
         labels_layer.features = edited_reg_props
 

napari_skimage_regionprops/_table.py

@@ -29,8 +29,17 @@ def __init__(self, layer: "napari.layers.Layer", viewer: "napari.Viewer" = None)
 
         self._view = QTableWidget()
         self._view.setEditTriggers(QTableWidget.EditTrigger.NoEditTriggers)
+        # Add 'properties' and 'features' attributes if layer is Surface
+        if isinstance(layer, napari.layers.Surface):
+            # Check if features and properties are already defined
+            if not hasattr(layer, "features"):
+                layer.features = {}
+            if not hasattr(layer, "properties"):
+                layer.properties = {}
         if hasattr(layer, "properties"):
             self.set_content(layer.properties)
+        elif hasattr(layer, "features"):
+            self.set_content(layer.features.to_dict(orient="list"))
         else:
             self.set_content({})
 

napari_skimage_regionprops/_tests/test_function.py

@@ -1,4 +1,40 @@
 # from napari_skimage_regionprops import threshold, image_arithmetic
+def generate_sphere_mesh(radius, segments):
+    """
+    Generate vertices and faces for a sphere mesh.
+
+    Parameters:
+    radius (float): Radius of the sphere.
+    segments (int): Number of segments used to generate the sphere, higher means finer mesh.
+
+    Returns:
+    tuple: vertices (N, 3 array), faces (M, 3 array)
+    """
+    import numpy as np
+    theta = np.linspace(0, np.pi, segments)
+    phi = np.linspace(0, 2 * np.pi, segments)
+    theta, phi = np.meshgrid(theta, phi)
+
+    x = radius * np.sin(theta) * np.cos(phi)
+    y = radius * np.sin(theta) * np.sin(phi)
+    z = radius * np.cos(theta)
+
+    vertices = np.column_stack((x.ravel(), y.ravel(), z.ravel()))
+
+    # Generate faces (indices of vertices that make up each triangle)
+    faces = []
+    for i in range(len(theta) - 1):
+        for j in range(len(phi) - 1):
+            v0 = i * len(phi) + j
+            v1 = v0 + 1
+            v2 = v0 + len(phi)
+            v3 = v2 + 1
+            faces.append([v0, v1, v2])
+            faces.append([v1, v3, v2])
+
+    faces = np.array(faces)
+
+    return vertices, faces
 
 # add your tests here...
 def test_regionprops(make_napari_viewer):
@@ -90,6 +126,17 @@ def test_regionprops(make_napari_viewer):
     load_csv("test.csv", labels_layer)
     load_csv("test.csv", labels_layer, viewer)
 
+    points_layer = viewer.add_points(np.array([[2, 1], [2, 5], [5, 3], [6, 6]]))
+    vertices, faces = generate_sphere_mesh(1, 50)
+    surface_layer = viewer.add_surface((vertices, faces))
+
+    # test loading csv to points
+    load_csv("test.csv", points_layer)
+    load_csv("test.csv", points_layer, viewer)
+
+    # test loading csv to surface
+    load_csv("test.csv", surface_layer)
+    load_csv("test.csv", surface_layer, viewer)
 
     # empty table
     table_widget.set_content(None)