diff --git a/src/deep_neurographs/doubles_removal.py b/src/deep_neurographs/doubles_removal.py
index 440c82d..4a90002 100644
--- a/src/deep_neurographs/doubles_removal.py
+++ b/src/deep_neurographs/doubles_removal.py
@@ -12,7 +12,7 @@
 import networkx as nx
 
 
-def run(neurograph, max_size, node_spacing):
+def run(neurograph, min_size, max_size, node_spacing, output_dir=None):
     """
     Removes connected components from "neurgraph" that are likely to be a
     double.
@@ -25,6 +25,8 @@ def run(neurograph, max_size, node_spacing):
         Maximum size of connected components to be searched.
     node_spacing : int
         Expected distance in microns between nodes in "neurograph".
+    output_dir : str or None, optional
+        Directory that doubles will be written to. The default is None.
 
     Returns
     -------
@@ -41,16 +43,20 @@ def run(neurograph, max_size, node_spacing):
         swc_id = get_swc_id(neurograph, nodes)
         if swc_id not in not_doubles:
             xyz_arr = inspect_component(neurograph, nodes)
-            if len(xyz_arr) > 0 and len(xyz_arr) * node_spacing < max_size:
+            upper_bound = len(xyz_arr) * node_spacing < max_size
+            lower_bound = len(xyz_arr) * node_spacing > min_size
+            if upper_bound and lower_bound:
                 not_double_id = is_double(neurograph, xyz_arr, swc_id)
                 if not_double_id:
                     doubles_cnt += 1
+                    if output_dir:
+                        neurograph.to_swc(output_dir, nodes, color="1.0 0.0 0.0")
                     neurograph = remove_component(neurograph, nodes, swc_id)
                     not_doubles.add(not_double_id)
     print("# Doubles detected:", doubles_cnt)
 
 
-def is_double(neurograph, xyz_arr, swc_id_i):
+def is_double(neurograph, fragment, swc_id_i):
     """
     Determines whether the connected component corresponding to "root" is a
     double of another connected component.
@@ -59,7 +65,7 @@ def is_double(neurograph, xyz_arr, swc_id_i):
     ---------
     neurograph : NeuroGraph
         Graph to be searched for doubles.
-    xyz_arr : numpy.ndarray
+    fragment : numpy.ndarray
         Array containing xyz coordinates corresponding to some fragment (i.e.
         connected component in neurograph).
     swc_id_i : str
@@ -76,8 +82,8 @@ def is_double(neurograph, xyz_arr, swc_id_i):
     """
     # Compute projections
     hits = dict()
-    for xyz_i in xyz_arr:
-        for xyz_j in neurograph.query_kdtree(xyz_i, 6):
+    for xyz_i in fragment:
+        for xyz_j in neurograph.query_kdtree(xyz_i, 5):
             try:
                 swc_id_j = neurograph.xyz_to_swc(xyz_j)
                 if swc_id_i != swc_id_j:
@@ -88,7 +94,7 @@ def is_double(neurograph, xyz_arr, swc_id_i):
     # Check criteria
     if len(hits) > 0:
         swc_id_j = utils.find_best(hits)
-        percent_hit = len(hits[swc_id_j]) / len(xyz_arr)
+        percent_hit = len(hits[swc_id_j]) / len(fragment)
     else:
         percent_hit = 0
     return swc_id_j if swc_id_j is not None and percent_hit > 0.5 else None
diff --git a/src/deep_neurographs/neurograph.py b/src/deep_neurographs/neurograph.py
index 1c8a37e..a7e2994 100644
--- a/src/deep_neurographs/neurograph.py
+++ b/src/deep_neurographs/neurograph.py
@@ -666,18 +666,23 @@ def component_cardinality(self, root):
                     queue.append((j, k))
         return cardinality
 
-    def to_zipped_swcs(self, zip_path):
+    def to_zipped_swcs(self, zip_path, color=None):
         n_components = gutils.count_components(self)
         print(f"Writing {n_components} swcs to local machine!")
         with zipfile.ZipFile(zip_path, "w") as zipf:
             for nodes in nx.connected_components(self):
-                self.to_zipped_swc(zipf, nodes)
+                self.to_zipped_swc(zipf, nodes, color)
 
-    def to_zipped_swc(self, zipf, nodes):
+    def to_zipped_swc(self, zipf, nodes, color):
         with StringIO() as text_buffer:
+            # Preamble
             n_entries = 0
             node_to_idx = dict()
+            if color:
+                text_buffer.write("# COLOR " + color)
             text_buffer.write("# id, type, z, y, x, r, pid")
+
+            # Write entries
             for i, j in nx.dfs_edges(self.subgraph(nodes)):
                 # Initialize
                 if n_entries == 0:
@@ -718,16 +723,18 @@ def to_swcs(self, swc_dir):
             for i, nodes in enumerate(nx.connected_components(self)):
                 threads.append(executor.submit(self.to_swc, swc_dir, nodes))
 
-    def to_swc(self, swc_dir, nodes):
+    def to_swc(self, swc_dir, nodes, color=None):
         """
         Generates list of swc entries for a given connected component.
 
         Parameters
         ----------
-        path : str
-            Path that swc for component will be written to.
-        Component : list[int]
-            List of nodes contained in "component".
+        swc_dir : str
+            Directory that swc will be written to.
+        nodes : list[int]
+            Nodes to be written to an swc file.
+        color : None or str
+            Color that swc files should be given.
 
         Returns
         -------
@@ -753,7 +760,7 @@ def to_swc(self, swc_dir, nodes):
             node_to_idx[j] = len(entry_list)
 
         # Write
-        swc_utils.write(path, entry_list)
+        swc_utils.write(path, entry_list, color=color)
 
     def branch_to_entries(self, entry_list, i, j, parent):
         # Orient branch
diff --git a/src/deep_neurographs/swc_utils.py b/src/deep_neurographs/swc_utils.py
index c7b0146..5af7c2d 100644
--- a/src/deep_neurographs/swc_utils.py
+++ b/src/deep_neurographs/swc_utils.py
@@ -235,7 +235,7 @@ def write_list(path, entry_list, color=None):
     with open(path, "w") as f:
         # Preamble
         if color is not None:
-            f.write("# COLOR" + color)
+            f.write("# COLOR " + color)
         else:
             f.write("# id, type, z, y, x, r, pid")