Add additional checks and optional debug print mode to avoid passing …

…empty skeletons to FilFinder2D

fil_finder/filfinder2D.py

@@ -575,7 +575,8 @@ def analyze_skeletons(self,
                           max_prune_iter=10,
                           verbose=False,
                           save_png=False,
-                          save_name=None):
+                          save_name=None,
+                          debug=False,):
         '''
 
         Prune skeleton structure and calculate the branch and longest-path
@@ -614,6 +615,8 @@ def analyze_skeletons(self,
             Saves the plot made in verbose mode. Disabled by default.
         save_name : str, optional
             Prefix for the saved plots.
+        debug : bool, optional
+            Enables debug mode with extra printing
         '''
 
         if relintens_thresh > 1.0 or relintens_thresh <= 0.0:
@@ -636,7 +639,9 @@ def analyze_skeletons(self,
         else:
             skel_thresh = self.converter.to_pixel(skel_thresh)
 
-        self.skel_thresh = np.ceil(skel_thresh)
+        # Ensure the minimum is always >1 pixel.
+
+        self.skel_thresh = min(np.ceil(skel_thresh), 1 * u.pix)
 
         # Set the minimum branch length to be the beam size.
         if branch_thresh is None:
@@ -649,21 +654,32 @@ def analyze_skeletons(self,
         # Label individual filaments and define the set of filament objects
         labels, num = nd.label(self.skeleton, eight_con())
 
+        if debug:
+            print(f"Found {num} filaments before removing short skeletons")
+
         # Find the objects that don't satisfy skel_thresh
-        if self.skel_thresh > 0.:
-            obj_sums = nd.sum(self.skeleton, labels, range(1, num + 1))
-            remove_fils = np.where(obj_sums <= self.skel_thresh.value)[0]
+        obj_sums = nd.sum(self.skeleton, labels, range(1, num + 1))
+        remove_fils = np.where(obj_sums <= self.skel_thresh.value)[0]
+
+        for lab in remove_fils:
+            if debug:
+                print(f"Removing {lab} with {obj_sums[lab]} pixels")
+            self.skeleton[np.where(labels == lab + 1)] = 0
+
+        # Relabel after deleting short skeletons.
+        labels, num = nd.label(self.skeleton, eight_con())
 
-            for lab in remove_fils:
-                self.skeleton[np.where(labels == lab + 1)] = 0
+        if debug:
+            print(f"Found {num} filaments after removing short skeletons")
 
-            # Relabel after deleting short skeletons.
-            labels, num = nd.label(self.skeleton, eight_con())
+        self.filaments = []
 
+        for lab in range(1, num + 1):
+            if debug:
+                print(f"Filament {lab} has {np.sum(labels == lab)} pixels")
 
-        self.filaments = [Filament2D(np.where(labels == lab),
-                                     converter=self.converter) for lab in
-                          range(1, num + 1)]
+            self.filaments.append(Filament2D(np.where(labels == lab),
+                                             converter=self.converter))
 
         # Now loop over the skeleton analysis for each filament object
         with concurrent.futures.ProcessPoolExecutor(nthreads) as executor: