Bug merge detection (#168)

* bug: overcount swcs

* refactor: updated merge/split rates

* refactor: compute rates

---------

Co-authored-by: anna-grim <anna.grim@alleninstitute.org>

Author: anna-grim

src/segmentation_skeleton_metrics/skeleton_metrics.py

@@ -713,15 +713,14 @@ def __call__(self, gt_graphs, results):
         for name, graph in gt_graphs.items():
             # Compute result
             if results["# Splits"][name] > 0:
-                rl = util.compute_segmented_run_length(graph, results)
-                rate = rl / results["# Splits"][name]
+                rl = util.compute_segmented_run_length(graph, results, name)
+                new_results[name] = round(rl / results["# Splits"][name], 2)
             else:
-                rate = np.nan
-            new_results[name] = round(rate, 2)
+                new_results[name] = np.nan
 
-            # Update progress bar
-            if self.verbose:
-                pbar.update(1)
+        # Update progress bar
+        if self.verbose:
+            pbar.update(1)
         return self.reformat(new_results)
 
 
@@ -763,15 +762,14 @@ def __call__(self, gt_graphs, results):
             stored under a column called "self.name".
         """
         new_results = dict()
-        pbar = self.get_pbar(len(results.index))
+        pbar = self.get_pbar(len(gt_graphs))
         for name, graph in gt_graphs.items():
             # Compute result
             if results["# Merges"][name] > 0:
-                rl = util.compute_segmented_run_length(graph, results)
-                rate = rl / results["# Merges"][name]
+                rl = util.compute_segmented_run_length(graph, results, name)
+                new_results[name] = round(rl / results["# Merges"][name], 2)
             else:
-                rate = np.nan
-            new_results[name] = round(rate, 2)
+                new_results[name] = np.nan
 
             # Update progress bar
             if self.verbose:

src/segmentation_skeleton_metrics/utils/util.py

@@ -483,7 +483,7 @@ def compute_weighted_avg(df, column_name):
         return (values * weights).sum() / weights.sum()
 
 
-def compute_segmented_run_length(graph, results):
+def compute_segmented_run_length(graph, results, name):
     """
     Computes the run length of a graph that was segmented.
 
@@ -499,8 +499,8 @@ def compute_segmented_run_length(graph, results):
     float
         Run length of a graph that was segmented.
     """
-    omit_run_length = graph.run_length * results["% Omit"] / 100
-    split_run_length = graph.run_length * results["% Split"] / 100
+    omit_run_length = graph.run_length * results["% Omit Edges"][name] / 100
+    split_run_length = graph.run_length * results["% Split Edges"][name] / 100
     return graph.run_length - omit_run_length - split_run_length