Merge branch 'main' of https://github.com/xing-lab-pitt/LiveCellTrack…

…er-dev into main

livecell_tracker/core/napari_visualizer.py

@@ -57,10 +57,13 @@ def gen_trajectories_shapes(
             all_scs.extend(scs)
             all_status.extend([""] * len(traj_shapes))
         properties = {"track_id": track_ids, "sc": all_scs, "status": all_status}
+
+        # Track ID can be UUID, so we need to map it to an integer
+        track_value_indices = [idx for idx, v in enumerate(track_ids)]
         shape_layer = viewer.add_shapes(
             all_shapes,
             properties=properties,
-            face_color=NapariVisualizer.map_colors(properties["track_id"]),
+            face_color=NapariVisualizer.map_colors(track_value_indices),
             face_colormap="viridis",
             shape_type="polygon",
             text=text_parameters,

livecell_tracker/core/sct_operator.py

@@ -761,8 +761,11 @@ def create_scts_operator_viewer(
             )
         new_scts = SingleCellTrajectoryCollection()
         for _, sct in sctc:
-            new_scts.add_trajectory(sct.subsct(time_span[0], time_span[1]))
+            new_scts.add_trajectory(sct.subsct(time_span[0], time_span[1], keep_track_id=True))
         sctc = new_scts
+        main_info(
+            f"A new SCTC object with size {len(sctc)} is created by subsetting the original sctc with time span {time_span}"
+        )
 
     # if the img_dataset is not None, then we can use it to determine the time span
     if img_dataset is not None:
@@ -851,31 +854,31 @@ def _move_span(viewer, offset):
                 all_sc_set = set(single_cells)
                 for sc in sct_operator_scs:
                     if sc not in all_sc_set:
-                        print("<add new sc>:", sc)
+                        main_info("<add new sc>:", sc)
                         single_cells.append(sc)
                 for sc in single_cells:
                     if sc.timeframe < cur_idx or sc.timeframe > cur_idx + span_interval:
                         continue
                     if sc not in sct_operator_scs:
-                        print("<remove sc>:", sc)
+                        main_info("<remove sc>:", sc)
                         single_cells.remove(sc)
             cur_idx += offset
             cur_idx = min(cur_idx, max_time)  # (max_time - span_interval) is acceptable as well here
             cur_idx = max(cur_idx, 0)
             points_layer.metadata["cur_idx"] = cur_idx
             cur_span = (cur_idx, cur_idx + span_interval)
-            print("new span:", cur_span)
+            main_info("new span:", cur_span)
             # if clear_prev_batch:
             #     sct_operator.close()
             # sct_operator = create_scs_edit_viewer(single_cells, img_dataset = dic_dataset, viewer = viewer, time_span=cur_span)
             if clear_prev_batch:
                 # TODO: shapes may be invisible, though select is sc/sct based and should be fine
                 sct_operator.clear_selection()
-            temp_sc_trajs_for_correct = create_sctc_from_scs(single_cells)
-            temp_sc_trajs_for_correct = filter_sctc_by_time_span(temp_sc_trajs_for_correct, cur_span)
-            print("len of temp_sc_trajs_for_correct:", len(temp_sc_trajs_for_correct))
-            if len(temp_sc_trajs_for_correct) != 0:
-                sct_operator.setup_from_sctc(temp_sc_trajs_for_correct)
+            temp_sc_trajs = create_sctc_from_scs(single_cells)
+            temp_sc_trajs = filter_sctc_by_time_span(temp_sc_trajs, cur_span)
+            main_info("len of temp_sc_trajs:", len(temp_sc_trajs))
+            if len(temp_sc_trajs) != 0:
+                sct_operator.setup_from_sctc(temp_sc_trajs)
             else:
                 sct_operator.shape_layer.data = []
             points_layer.metadata["cur_sct_operator"] = sct_operator

livecell_tracker/core/single_cell.py

@@ -16,7 +16,7 @@
 from livecell_tracker.core.datasets import LiveCellImageDataset, SingleImageDataset
 from livecell_tracker.core.io_utils import LiveCellEncoder
 from livecell_tracker.core.sc_key_manager import SingleCellMetaKeyManager as SCKM
-from livecell_tracker.livecell_logger import main_warning
+from livecell_tracker.livecell_logger import main_warning, main_exception
 
 
 # TODO: possibly refactor load_from_json methods into a mixin class
@@ -467,8 +467,8 @@ def write_single_cells_json(single_cells: List["SingleCellStatic"], path: str, d
             try:
                 json.dump(all_sc_jsons, f)
             except TypeError as e:
-                print("sample sc:", all_sc_jsons[0])
-                print("Error writing json file. Check that all attributes are serializable.")
+                main_exception("sample sc:", all_sc_jsons[0])
+                main_exception("Error writing json file. Check that all attributes are serializable.")
                 raise e
 
     def write_json(self, path=None, dataset_json_dir=None):
@@ -1037,7 +1037,7 @@ def copy(self):
 
         return copy.deepcopy(self)
 
-    def subsct(self, min_time, max_time):
+    def subsct(self, min_time, max_time, track_id=None, keep_track_id=False):
         """return a subtrajectory of this trajectory, with timeframes between min_time and max_time. Mother and daugher info will be copied if the min_time and max_time are the start and end of the new trajectory, respectively."""
         require_copy_mothers_info = False
         require_copy_daughters_info = False
@@ -1048,8 +1048,9 @@ def subsct(self, min_time, max_time):
             require_copy_mothers_info = True
         if max_time == self_span[1]:
             require_copy_daughters_info = True
-
-        sub_sct = SingleCellTrajectory(img_dataset=self.img_dataset, mask_dataset=self.mask_dataset)
+        if keep_track_id:
+            track_id = self.track_id
+        sub_sct = SingleCellTrajectory(img_dataset=self.img_dataset, mask_dataset=self.mask_dataset, track_id=track_id)
         for timeframe, sc in self:
             if timeframe >= min_time and timeframe <= max_time:
                 sub_sct.add_single_cell(timeframe, sc)
@@ -1233,18 +1234,24 @@ def _next_track_id(self):
         return max(self.get_track_ids()) + 1
 
 
-def create_sctc_from_scs(scs: List[SingleCellStatic]):
-    temp_sc_trajs_for_correct = SingleCellTrajectoryCollection()
+def create_sctc_from_scs(scs: List[SingleCellStatic]) -> SingleCellTrajectoryCollection:
+    temp_sc_trajs = SingleCellTrajectoryCollection()
     for idx, sc in enumerate(scs):
         sct = SingleCellTrajectory(track_id=idx, timeframe_to_single_cell={sc.timeframe: sc})
-        temp_sc_trajs_for_correct.add_trajectory(sct)
-    return temp_sc_trajs_for_correct
+        temp_sc_trajs.add_trajectory(sct)
+    return temp_sc_trajs
 
 
-def filter_sctc_by_time_span(sctc: SingleCellTrajectoryCollection = None, time_span=(0, np.inf)):
+def filter_sctc_by_time_span(sctc: SingleCellTrajectoryCollection = None, time_span=(0, np.inf), keep_track_id=True):
     new_sctc = SingleCellTrajectoryCollection()
+    track_id_counter = 0
     for _, sct in sctc:
-        subsct = sct.subsct(time_span[0], time_span[1])
+        if keep_track_id:
+            track_id = sct.track_id
+        else:
+            track_id = track_id_counter
+        subsct = sct.subsct(time_span[0], time_span[1], track_id=track_id)
+        track_id_counter += 1
         if subsct.num_scs() > 0:
             new_sctc.add_trajectory(subsct)
     return new_sctc

notebooks/tutorial_mitosis_annotation.ipynb

@@ -139,17 +139,6 @@
     "#                                          dataset_dir=\"./datasets/test_scs_EBSS_starvation/datasets\")\n"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "\n",
-    "\n",
-    "# dic_dataset, mask_dataset = tutorial_three_image_sys()\n"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -174,8 +163,16 @@
     "# scs_path = \"./datasets/test_scs_EBSS_starvation/single_cells.json\"\n",
     "# scs_path = \"./datasets/test_scs_EBSS_starvation/XY16/tmp_corrected_scs.json\"\n",
     "# scs_path = \"./datasets/test_scs_EBSS_starvation/XY1/single_cells.json\"\n",
-    "scs_path = \"./datasets/test_scs_EBSS_starvation/XY1/corrected_scs.json\"\n",
-    "single_cells = SingleCellStatic.load_single_cells_json(path=scs_path)"
+    "# scs_path = \"./datasets/test_scs_EBSS_starvation/XY1/corrected_scs.json\"\n",
+    "# single_cells = SingleCellStatic.load_single_cells_json(path=scs_path)\n",
+    "# dic_dataset = single_cells[0].img_dataset\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "load sample tutorial 3-image data"
    ]
   },
   {
@@ -184,7 +181,9 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "dic_dataset = single_cells[0].img_dataset"
+    "from livecell_tracker.segment.utils import prep_scs_from_mask_dataset\n",
+    "dic_dataset, mask_dataset = tutorial_three_image_sys()\n",
+    "single_cells = prep_scs_from_mask_dataset(mask_dataset, dic_dataset)"
    ]
   },
   {
@@ -228,7 +227,19 @@
    "outputs": [],
    "source": [
     "from livecell_tracker.core.sct_operator import create_scs_edit_viewer, SctOperator, create_scs_edit_viewer_by_interval, _get_viewer_sct_operator\n",
-    "from livecell_tracker.core.single_cell import create_sctc_from_scs, filter_sctc_by_time_span\n"
+    "from livecell_tracker.core.single_cell import create_sctc_from_scs, filter_sctc_by_time_span"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# points_layer = viewer.layers[\"_lcx_sct_cur_idx\"]\n",
+    "# sct_operator: SctOperator = points_layer.metadata[\"cur_sct_operator\"]\n",
+    "# # sct_operator.traj_collection._next_track_id()\n",
+    "# sct_operator.traj_collection.get_all_trajectories()[0]"
    ]
   },
   {
@@ -238,6 +249,7 @@
    "outputs": [],
    "source": [
     "# sct_operator = create_scs_edit_viewer(single_cells, img_dataset = dic_dataset)\n",
+    "span_interval = 10\n",
     "viewer = create_scs_edit_viewer_by_interval(single_cells, img_dataset=dic_dataset, span_interval = 10, viewer = None)\n",
     "# for i in range(0, len(single_cells), span_interval):\n",
     "#     sct_operator = create_scs_edit_viewer(single_cells, img_dataset = dic_dataset, viewer = viewer, time_span=(i, i+span_interval))\n",