Add table of results

solution.py

@@ -622,7 +622,7 @@ def make_gt_detections(data_shape, gt_tracks, radius):
 
 
 # %%
-def get_metrics(gt_graph, labels, pred_graph, pred_segmentation):
+def get_metrics(gt_graph, labels, run, results_df):
     """Calculate metrics for linked tracks by comparing to ground truth.
 
     Args:
@@ -634,7 +634,6 @@ def get_metrics(gt_graph, labels, pred_graph, pred_segmentation):
     Returns:
         results (dict): Dictionary of metric results.
     """
-
     gt_graph = traccuracy.TrackingGraph(
         graph=gt_graph,
         frame_key="t",
@@ -644,11 +643,11 @@ def get_metrics(gt_graph, labels, pred_graph, pred_segmentation):
     )
 
     pred_graph = traccuracy.TrackingGraph(
-        graph=pred_graph,
+        graph=run.tracks,
         frame_key="t",
         label_key="tracklet_id",
         location_keys=("x", "y"),
-        segmentation=pred_segmentation,
+        segmentation=np.squeeze(run.output_segmentation),
     )
 
     results = run_metrics(
@@ -658,11 +657,24 @@ def get_metrics(gt_graph, labels, pred_graph, pred_segmentation):
         metrics=[CTCMetrics(), DivisionMetrics()],
     )
 
-    return results
+    results_filtered = {}
+    results_filtered.update(results[0]["results"])
+    results_filtered.update(results[1]["results"]["Frame Buffer 0"])
+    results_filtered["name"] = run.run_name
+    current_result = pd.DataFrame(results_filtered, index=[0])[columns]
+
+    if results_df is None:
+        results_df = current_result
+    else:
+        results_df = pd.concat([results_df, current_result])
+
+    return results_df
 
 
 # %%
-get_metrics(gt_tracks, gt_dets, solution_graph, solution_seg.astype(np.uint32))
+results_df = None
+results_df = get_metrics(gt_tracks, gt_dets, basic_run, results_df)
+results_df
 
 # %% [markdown]
 # <div class="alert alert-block alert-warning"><h3>Question 3: Interpret your results based on metrics</h3>
@@ -798,7 +810,8 @@ def solve_drift_optimization(cand_graph):
 widget.view_controller.update_napari_layers(drift_run, time_attr="t", pos_attr=("x", "y"))
 
 # %%
-get_metrics(gt_tracks, gt_dets, solution_graph, solution_seg)
+results_df = get_metrics(gt_tracks, gt_dets, drift_run, results_df)
+results_df
 
 
 # %% [markdown]
@@ -925,7 +938,6 @@ def get_ssvm_solution(cand_graph, solver_weights):
 
 # %%
 solution_seg = relabel_segmentation(solution_graph, segmentation)
-get_metrics(gt_tracks, gt_dets, solution_graph, solution_seg)
 
 # %%
 ssvm_run = MotileRun(
@@ -936,6 +948,11 @@ def get_ssvm_solution(cand_graph, solver_weights):
 
 widget.view_controller.update_napari_layers(ssvm_run, time_attr="t", pos_attr=("x", "y"))
 
+# %%
+
+results_df = get_metrics(gt_tracks, gt_dets, ssvm_run, results_df)
+results_df
+
 # %% [markdown]
 # <div class="alert alert-block alert-warning"><h3>Bonus Question: Interpret SSVM results</h3>
 # <p>