adding widget for adding points layer

src/napari_brainbow_diagnose/__init__.py

@@ -10,11 +10,14 @@
 )
 from ._tooltip_pointer import tooltip_pointer_widget
 from ._widget import DiagnoseWidget
+from ._read_csv_widget import read_csv_widget, add_features_widget
 
 __all__ = (
     "tooltip_pointer_widget",
     "make_rgb_cube_data",
     "fetch_chroms_data",
     "load_chroms_data_sample",
     "DiagnoseWidget",
+    "read_csv_widget",
+    "add_features_widget"
 )

src/napari_brainbow_diagnose/_read_csv_widget.py

@@ -0,0 +1,71 @@
+import napari
+from napari.layers import Points
+
+import pandas as pd
+import numpy as np
+
+from magicgui import magicgui
+from magicgui import magic_factory
+from ._utils_channel_space import rgb_to_maxwell_triangle, calculate_brightness
+import pathlib
+
+@magic_factory(call_button="(test) Create a Points layer", auto_call=False)
+def read_csv_widget(filename = pathlib.Path('/path/to/csv/file.csv')):
+    # Getting the current viewer
+    viewer = napari.current_viewer()
+    # Import data
+    df = pd.read_csv(filename, usecols=range(6), names=['axis-0', 'axis-1', 'axis-2', 'red', 'green', 'blue'])
+    # Create points layer
+    coordinates = df[['axis-0', 'axis-1', 'axis-2']].values
+    colors = df[['red', 'green', 'blue']].values
+    points_layer = viewer.add_points(coordinates, name='points', face_color=colors, edge_color=colors, size=20, out_of_slice_display=True)
+
+    # Add Maxwell coordinates
+    df['maxwell_x'], df['maxwell_y'] = rgb_to_maxwell_triangle(df['red'], df['green'], df['blue'])
+    df['brightness'] = calculate_brightness(df['red'], df['green'], df['blue'])
+
+    df = df.sort_values(by='brightness').reset_index(drop=True)
+
+    features_table = {
+        'red': df['red'].values, 'green': df['green'].values, 'blue': df['blue'].values, 
+        'maxwell_x': df['maxwell_x'].values, 'maxwell_y': df['maxwell_y'].values,
+        'brightness_index': df.index, 'brightness': df['brightness']
+        }
+    points_layer.features = features_table
+
+
+# Add color features to an existing points layer which has features 'red', 'green', and 'blue'
+@magic_factory(call_button="Add Features to Points Layer", auto_call=False, points_layer={"label": "Select Points Layer"}, points_selection={"label": "Add selected points feature"})
+def add_features_widget(points_layer: Points, points_selection: bool):
+    # Extract existing features
+    if not all(col in points_layer.features for col in ['red', 'green', 'blue']):
+        raise ValueError("Selected points layer does not have 'red', 'green', and 'blue' features.")
+
+    red = points_layer.features['red']
+    green = points_layer.features['green']
+    blue = points_layer.features['blue']
+
+    # Add Maxwell coordinates
+    maxwell_x, maxwell_y = rgb_to_maxwell_triangle(red, green, blue)
+    brightness = calculate_brightness(red, green, blue)
+
+    features_table = {
+        'red': red.values,
+        'green': green.values,
+        'blue': blue.values,
+        'maxwell_x': maxwell_x.values,
+        'maxwell_y': maxwell_y.values,
+        'brightness': brightness.values,
+        'range': np.arange(len(brightness))
+    }
+
+    for key, value in features_table.items():
+        points_layer.features[key] = value
+
+    if points_selection:
+        selected = points_layer.selected_data
+        clustering = np.zeros(len(points_layer.data))
+        for point_index in selected:
+            clustering[point_index] = 1
+
+        points_layer.features['CLUSTER'] = clustering.astype(int)

src/napari_brainbow_diagnose/_utils_channel_space.py

@@ -26,6 +26,24 @@ def rgb_to_hsv(rgb: np.ndarray, channel_axis: int = -1) -> np.ndarray:
     return skc.rgb2hsv(rgb, channel_axis=channel_axis)
 
 
+def rgb_to_maxwell_triangle(r, g, b):
+    """
+    Given coordinates in rgb color space, returns x and y coordinates of the Maxwell triangle.
+    """
+    s = r+g+b
+    r = r/s
+    g = g/s
+    b = b/s
+    x = (r-b)/np.sqrt(3)
+    y = g
+    return x, y
+
+def calculate_brightness(r, g, b):
+    """
+    Given standardized values (from 0 to 1) of rgb return brightness
+    """
+    return (1 / 2)*(np.maximum(np.maximum(r, g), b) + np.minimum(np.minimum(r, g), b))
+
 # TODO ajouter un paramètre pour choisir l'axe des canaux
 def get_channels_ranges(a: np.ndarray) -> np.ndarray:
     """

src/napari_brainbow_diagnose/napari.yaml

@@ -14,6 +14,12 @@ contributions:
     - id: napari-brainbow-diagnose.DiagnoseWidget
       python_name: napari_brainbow_diagnose._widget:DiagnoseWidget
       title: Diagnose Brainbow Image
+    - id: napari-brainbow-diagnose.read_csv_widget
+      python_name: napari_brainbow_diagnose._read_csv_widget:read_csv_widget
+      title: Load a Points layer
+    - id: napari-brainbow-diagnose.add_features_widget
+      python_name: napari_brainbow_diagnose._read_csv_widget:add_features_widget
+      title: Add color features to existing Points layer
   sample_data:
     - command: napari-brainbow-diagnose.make_rgb_cube_data
       display_name: RGB Cube
@@ -22,7 +28,13 @@ contributions:
       display_name: Chroms Cortex Sample
       key: unique_id.2
   widgets:
+    - command: napari-brainbow-diagnose.read_csv_widget
+      display_name: Load a Points layer
+    - command: napari-brainbow-diagnose.add_features_widget
+      display_name: Add color features to existing Points layer
     - command: napari-brainbow-diagnose.DiagnoseWidget
       display_name: Diagnose Brainbow Image
     - command: napari-brainbow-diagnose.tooltip_pointer_widget
       display_name: Brainbow Tooltip
+
+