Implemented 3D connected components as wrapper class for scipy.ndimage.label

Ticket: https://www.notion.so/qim-dtu/3D-connected-components-ca5c410fef49444eac7c6efd0b56ead4?pvs=4

I have made a simple plot functions that takes the ConnectedComponents object and extracts the connected_components volume.

However I don't know if it is necessary as the user could do this manually.

def plot_connected_components(connected_components: ConnectedComponents, **kwargs):
    """ Plots connected components from the ConnectedComponents class as 2d slices.

    Args:
        connected_components (ConnectedComponents): The connected components class from the qim3d.utils.connected_components module.
        **kwargs: Additional keyword arguments to pass to qim3d.viz.img.slice_viz.

    Returns:
        matplotlib.pyplot: the 3D plot of the connected components.
    """
    fig = slice_viz(connected_components.connected_components, **kwargs)
    return fig

qim3d/utils/cc.py

@@ -2,6 +2,8 @@ import numpy as np
 import torch
 from scipy.ndimage import find_objects, label
 
+from qim3d.io.logger import log
+
 
 class CC:
     def __init__(self, connected_components, num_connected_components):
@@ -12,27 +14,31 @@ class CC:
             connected_components (np.ndarray): The connected components.
             num_connected_components (int): The number of connected components.
         """
-        self.connected_components = connected_components
-        self.num_connected_components = num_connected_components
+        self._connected_components = connected_components
+        self.cc_count = num_connected_components
+    
+    def __len__(self):
+        """
+        Returns the number of connected components in the object.
+        """
+        return self.cc_count
 
     def get_cc(self, index=None, crop=False):
         """
         Get the connected component with the given index, if index is None selects a random component.
 
         Args:
-            index (int): The index of the connected component. If none selects a random component.
+            index (int): The index of the connected component. If none returns all components.
             crop (bool): If True, the volume is cropped to the bounding box of the connected component.
 
         Returns:
             np.ndarray: The connected component as a binary mask.
         """
         if index is None:
-            volume =  self.connected_components == np.random.randint(
-                1, self.num_connected_components + 1
-            )
+            volume = self._connected_components
         else:
-            assert 1 <= index <= self.num_connected_components, "Index out of range."
-            volume = self.connected_components == index
+            assert 1 <= index <= self.cc_count, "Index out of range."
+            volume = self._connected_components == index
             
         if crop:
             # As we index get_bounding_box element 0 will be the bounding box for the connected component at index
@@ -52,10 +58,10 @@ class CC:
         """
 
         if index:
-            assert 1 <= index <= self.num_connected_components, "Index out of range."
-            return find_objects(self.connected_components == index)
+            assert 1 <= index <= self.cc_count, "Index out of range."
+            return find_objects(self._connected_components == index)
         else:
-            return find_objects(self.connected_components)
+            return find_objects(self._connected_components)
 
 
 def get_3d_cc(image: np.ndarray | torch.Tensor):
@@ -69,4 +75,6 @@ def get_3d_cc(image: np.ndarray | torch.Tensor):
         class: Returns class object of the connected components.
     """
     connected_components, num_connected_components = label(image)
+    log.info(f"Total number of connected components found: {num_connected_components}")
+    
     return CC(connected_components, num_connected_components)