all tracks for label docs

nellie/tracking/all_tracks_for_label.py

@@ -5,7 +5,42 @@
 
 
 class LabelTracks:
+    """
+    A class to track labeled objects over multiple timepoints in a microscopy image using flow interpolation.
+
+    Attributes
+    ----------
+    im_info : ImInfo
+        An object containing image metadata and memory-mapped image data.
+    num_t : int
+        Number of timepoints in the image.
+    label_im_path : str
+        Path to the labeled instance image.
+    im_memmap : np.ndarray or None
+        Memory-mapped original image data.
+    label_memmap : np.ndarray or None
+        Memory-mapped labeled instance image data.
+
+    Methods
+    -------
+    initialize()
+        Initializes memory-mapped data for both the raw image and the labeled instance image.
+    run(label_num=None, start_frame=0, end_frame=None, min_track_num=0, skip_coords=1, max_distance_um=0.5)
+        Runs the tracking process for labeled objects across timepoints, both forward and backward.
+    """
     def __init__(self, im_info: ImInfo, num_t: int = None, label_im_path: str = None):
+        """
+        Initializes the LabelTracks class with image metadata, timepoints, and label image path.
+
+        Parameters
+        ----------
+        im_info : ImInfo
+            An instance of the ImInfo class containing image metadata and paths.
+        num_t : int, optional
+            Number of timepoints in the image (default is None, in which case it is inferred from the image metadata).
+        label_im_path : str, optional
+            Path to the labeled instance image. If not provided, defaults to the 'im_instance_label' path in `im_info`.
+        """
         self.im_info = im_info
         self.num_t = num_t
         if label_im_path is None:
@@ -19,10 +54,41 @@ def __init__(self, im_info: ImInfo, num_t: int = None, label_im_path: str = None
         self.label_memmap = None
 
     def initialize(self):
+        """
+        Initializes memory-mapped data for both the raw image and the labeled instance image.
+
+        This method prepares the image data and the labeled data for processing, mapping them into memory.
+        """
         self.label_memmap = self.im_info.get_memmap(self.label_im_path)
         self.im_memmap = self.im_info.get_memmap(self.im_info.im_path)
 
     def run(self, label_num=None, start_frame=0, end_frame=None, min_track_num=0, skip_coords=1, max_distance_um=0.5):
+        """
+        Runs the tracking process for labeled objects across timepoints, using flow interpolation.
+
+        This method uses forward and backward interpolation to track objects across multiple frames, starting from a given
+        frame. It can also track specific labels or all labels in the image.
+
+        Parameters
+        ----------
+        label_num : int, optional
+            Label number to track. If None, all labels are tracked (default is None).
+        start_frame : int, optional
+            The starting frame from which to begin tracking (default is 0).
+        end_frame : int, optional
+            The ending frame for the tracking. If None, tracks until the last frame (default is None).
+        min_track_num : int, optional
+            Minimum track number to assign to the coordinates (default is 0).
+        skip_coords : int, optional
+            The interval at which coordinates are sampled (default is 1).
+        max_distance_um : float, optional
+            Maximum distance allowed for interpolation (in micrometers, default is 0.5).
+
+        Returns
+        -------
+        tuple
+            A list of tracks and a dictionary of track properties.
+        """
         if end_frame is None:
             end_frame = self.num_t
         num_frames = self.label_memmap.shape[0] - 1