diff --git a/cell2mol/new_c2m_driver.py b/cell2mol/new_c2m_driver.py
index 1ad1c7e0..1f75df98 100644
--- a/cell2mol/new_c2m_driver.py
+++ b/cell2mol/new_c2m_driver.py
@@ -111,9 +111,9 @@
 
         # Reconstruction of the unit cell
         reference = Atoms(symbols=refcell.labels, scaled_positions=refcell.frac_coord, cell=cell_vector, pbc=True)
-        all_molecules, reconstructed_molecules, final_remaining_fragments = reconstuct(reference, newcell, cell_pos, cell_fracs, cell_vector, sym_ops, debug=debug)    
-        # all_molecules.extend(reconstructed_molecules)
-        exit()
+        all_molecules, reconstructed_molecules = reconstuct(reference, newcell, sym_ops, debug=debug)    
+        all_molecules.extend(reconstructed_molecules)
+
         if not newcell.error_reconstruction :
             # Get moleclist for the unit cell
             newcell = get_moleclist(newcell, refcell, all_molecules, debug=debug)
@@ -152,6 +152,7 @@
                 refcell.assign_spin(debug=debug)
                 refcell.create_bonds(debug=debug)
         # Save cell object
+        
         newcell.save(cell_fname)
     
     # Save reference cell object
diff --git a/cell2mol/new_cell_reconstruction.py b/cell2mol/new_cell_reconstruction.py
index 2f879c8f..f1b793b0 100644
--- a/cell2mol/new_cell_reconstruction.py
+++ b/cell2mol/new_cell_reconstruction.py
@@ -305,8 +305,8 @@ def merge_elements(fragments, target_ref, cell_vector, debug: int=0):
                 if newmolec is None: 
                     print(f"\tNOT MERGED {[k.formula for k in comb]}")
                 else :
-                    print(comb[0].ref_indices)
-                    print(comb[1].ref_indices)
+                    # print(comb[0].ref_indices)
+                    # print(comb[1].ref_indices)
                     print(f"\tMERGED {newmolec.formula} from {[k.formula for k in comb]} at indices {idx_comb}")
                     small_set = set(newmolec.ref_indices)
                     print(f"{newmolec.formula} {newmolec.natoms=} {len(small_set)=} {small_set=}")
@@ -338,20 +338,15 @@ def fragments_reconstruct (subset_remaining_fragments, target_ref, cell_vector,
 
     for newmolec in fragments:
         small_set = set(newmolec.ref_indices)
-        # print(f"{small_set=}")
         if small_set.issubset(target_ref): 
             if sorted(small_set) == target_ref:
-                newmolec.subtype = "Rec. Molecule"
-                print("Molecule found", newmolec.formula)
                 list_of_found_molecules.append(newmolec)
             elif newmolec.natoms == 1 and (newmolec.set_element_count()[4] + newmolec.set_element_count()[3] == 1):
                 newmolec.subtype = "fragment"
                 print("Hydrogen found", newmolec.formula)
                 list_of_bigger_fragments.append(newmolec)
             else :
-                newmolec.subtype = "Rec. Fragment"
-                print("Bigger fragment found", newmolec.formula)
-                list_of_bigger_fragments.append(newmolec)               
+                list_of_bigger_fragments.append(newmolec)            
 
     print(f"{len(list_of_found_molecules)=}")
     print(f"{len(list_of_bigger_fragments)=}")
@@ -430,9 +425,32 @@ def fragments_reconstruct_old (subset_remaining_fragments, target_ref, cell_vect
             
     return list_of_found_molecules, remaining_frag
 
+######################################################
+
+def get_updated_indices(sp_idx, new, cell_labels, cell_pos, cell_fracs, debug: int=0):
+    """
+    sp_idx : index of the symmetry operation
+    new : ase atoms object by applying symmetry operations to the reference structure
+    cell_labels : list of chemical symbols of the atoms in the unit cell
+    cell_pos : list of cartesian coordinates of the atoms in the unit cell
+    cell_fracs : list of fractional coordinates of the atoms in the unit cell
+    """
+    indices_lists = []
+    new_labels =  new.get_chemical_symbols()
+    new_pos = new.get_positions()    
+    new_fracs = new.get_scaled_positions()
+
+    for jdx, (n_l, n_p, n_f) in enumerate(zip(new_labels, new_pos, new_fracs)):
+        for kdx, (l, p, f) in enumerate(zip(cell_labels, cell_pos, cell_fracs)):
+            if n_l == l and np.allclose(n_p, p, atol=1e-5, rtol=1e-3) and np.allclose(n_f, f, atol=1e-5, rtol=1e-3):
+                if debug > 2: 
+                    print(f"symmtry operation {sp_idx}:", f"atom of new (index: {jdx})", n_l, n_p, n_f, \
+                          f"is the same as the atom of the unit cell (index: {kdx})", l, p, f)
+                indices_lists.append((jdx, kdx))
+    return indices_lists
 
 ######################################################
-def get_updated_indices (new, cell_pos, cell_fracs, all_found, debug: int=0):
+def get_updated_indices_old (new, cell_labels, cell_pos, cell_fracs, all_found, debug: int=0):
 
     # new structure : ase atoms object by applying symmetry operations to the reference structure
     # Find the indices of the atoms in the unit cell that have the same cartisian coordinates as the atoms in the new structure
@@ -457,9 +475,9 @@ def get_updated_indices (new, cell_pos, cell_fracs, all_found, debug: int=0):
         for j, i in enumerate(indices_in_ref):
             if i == -1:
                     print(f"Cannot find the {j}th atom of the new structure based on fractional coordinates from the unit cell.")
-                    print(f"{new_labels[j]=} {new.positions[j]=} {new_fracs[j]=}")
+                    print(f"{j} {new_labels[j]=} {new.positions[j]=} {new_fracs[j]=}")
                     print(f"Its fractional coord disagrees with the fractional coord of the {updated[j]}th atom of the unit cell.")
-                    print(f"{cell_pos[updated[j]]=} {cell_fracs[updated[j]]=}")
+                    print(f"{updated[j]} {cell_labels[updated[j]]=} {cell_pos[updated[j]]=} {cell_fracs[updated[j]]=}")
             # else :
                 # print(new_labels[i], np.allclose(new.positions[i], cell_pos[updated[j]]), np.allclose(new_fracs[i], cell_fracs[updated[j]]))
 
@@ -500,7 +518,12 @@ def sort_remaining_fragments_list (original_remaining_fragments):
     return remaining_fragments
 
 ######################################################
-def reconstuct (reference, newcell, cell_pos, cell_fracs, cell_vector, sym_ops, debug: int=0):
+def reconstuct (reference, newcell, sym_ops, debug: int=0):
+    
+    cell_labels = newcell.labels
+    cell_pos = newcell.coord
+    cell_fracs = newcell.frac_coord
+    cell_vector = newcell.cell_vector
 
     new_structures = apply_symmetry_operations_reference(reference, cell_vector, sym_ops)
     print(f"Number of symmetry operations: {len(new_structures)}")
@@ -508,20 +531,25 @@ def reconstuct (reference, newcell, cell_pos, cell_fracs, cell_vector, sym_ops,
     all_found = []
     all_molecules = []
     reconstructed_molecules = []
-
     remaining_fragments = [[] for _ in range(len(newcell.refmoleclist))]
 
     for idx, new in enumerate(new_structures):
         print(f"Applying symmetry operations to reference {idx}")
+        indices_lists = get_updated_indices(idx, new, cell_labels, cell_pos, cell_fracs, debug=debug)
 
-        updated, indices_in_ref = get_updated_indices(new, cell_pos, cell_fracs, all_found, debug=debug)
-        all_found.extend(updated)
+        updated_lists = [i for i in indices_lists if i[1] not in all_found]   
+        updated_ref_indices = [i[0] for i in updated_lists]
+        updated_cell = [i[1] for i in updated_lists]
+        print(f"{len(updated_cell)=} {updated_cell=}")
+        print(f"{len(updated_ref_indices)=} {updated_ref_indices=}")
+
+        all_found.extend(updated_cell)
         print(len(all_found))
         print(len(all_found) == len(cell_pos))
 
-        if len(updated) > 0 :
+        if len(updated_cell) > 0 :
             # #### make blocks and get fragments ####
-            initial_fragments = get_fragments (newcell, updated, indices_in_ref, debug=0)    
+            initial_fragments = get_fragments (newcell, updated_cell, updated_ref_indices, debug=0)    
             molecules, fragments = classify_fragments(initial_fragments, newcell, debug=0)
             all_molecules.extend(molecules)
             
@@ -560,60 +588,61 @@ def reconstuct (reference, newcell, cell_pos, cell_fracs, cell_vector, sym_ops,
                     print("only one fragment", frag_list[0].formula, "is found")
                     remaining_fragments[i].extend(frag_list)
                     print(f"symmetry operations: {idx} with ref{i} {[frag.formula for frag in remaining_fragments[i]]=}")
-    print("all_molecules", len(all_molecules), [mol.formula for mol in all_molecules])
-    print("reconstructed_molecules", len(reconstructed_molecules), [mol.formula for mol in reconstructed_molecules])
-    for i, rem in enumerate(all_molecules + reconstructed_molecules):
-        print(rem.formula)
-        writexyz("/Users/ycho/cell2mol/cell2mol/test/ACEYOW",\
-                    f"reconstructed_molecules_{rem.formula}_{i}.xyz", rem.labels, rem.coord)
 
-    print("remaining_fragments", [len(rem_frag_list) for rem_frag_list in remaining_fragments])
-    for i, rem_frag_list in enumerate(remaining_fragments):
-        print(i,newcell.refmoleclist[i].formula, [frag.formula for frag in rem_frag_list],\
-              [frag.ref_indices for frag in rem_frag_list])
+    print("all molecules", len(all_molecules), [mol.formula for mol in all_molecules])
+    print("reconstructed_molecules", len(reconstructed_molecules), [mol.formula for mol in reconstructed_molecules])
 
-    
-    # Reconstructing remaining fragments within the whole new cell
-    final_remaining_fragments = []
     if len(all_found) == len(cell_pos):
-        for i, rem_frag_list in enumerate(remaining_fragments):
-            if len(rem_frag_list) > 1:
-                # rem_frag_list = sort_remaining_fragments_list(rem_frag_list)
-                # with open("/Users/ycho/cell2mol/cell2mol/test/ACEYOW/rem_frag_list.pkl", "wb") as fil:
-                    # pickle.dump(rem_frag_list, fil)
-                print(f"target_ref: {newcell.refmoleclist[i].formula}")
-                print(f"Fragments formula {i}: {[rem.formula for rem in rem_frag_list]}")
-                target_ref = newcell.refmoleclist[i].get_parent_indices("reference")
-                list_of_found_molecules, final_remaining = fragments_reconstruct(rem_frag_list, target_ref, cell_vector, debug=0)
-                print(f"{[mol.formula for mol in list_of_found_molecules]=}")
-                print(f"{[frag.formula for frag in final_remaining]=}")
-                if len(list_of_found_molecules) > 0:
-                    reconstructed_molecules.extend(list_of_found_molecules)
-                if len(final_remaining) > 0:
-                    final_remaining_fragments.extend(final_remaining)
-
-            elif len(rem_frag_list) == 1:
-                final_remaining_fragments.extend(rem_frag_list)
-
-        if len(final_remaining_fragments) == 0:
+        num_rem_frags = 0
+        for rem_frag_list in remaining_fragments:
+            num_rem_frags += len(rem_frag_list) 
+        
+        if num_rem_frags == 0 :
+            print("All fragments are reconstructed successfully")
             newcell.is_fragmented = False
             newcell.error_reconstruction = False
-            print("All fragments are reconstructed successfully")
         else:
-            newcell.is_fragmented = True        
-            newcell.error_reconstruction = True
-            print("Final Remaining Fragments")
-        
-            for i, rem in enumerate(final_remaining_fragments):
-                print(rem.formula)
-                writexyz("/Users/ycho/cell2mol/cell2mol/test/ACEYOW",\
-                         f"final_remaining_fragments_{rem.formula}_{i}.xyz", rem.labels, rem.coord)
+            print(f"There are {num_rem_frags} remaining fragments.")
+            final_remaining_fragments, reconstructed_molecules = final_remaining_reconstruction(remaining_fragments, newcell, cell_vector, reconstructed_molecules, debug=0)
+            if len(final_remaining_fragments) == 0:
+                print("All fragments are reconstructed successfully")
+                newcell.is_fragmented = False
+                newcell.error_reconstruction = False
+            else :
+                print("Error in reconstruction!!")
+                newcell.is_fragmented = True
+                newcell.error_reconstruction = True
+                print("final remaining fragments", len(final_remaining_fragments), [mol.formula for mol in final_remaining_fragments])    
     else:
         print("Error in reconstruction!!")
         newcell.is_fragmented = True
-        newcell.error_reconstruction = True
+        newcell.error_reconstruction = True          
+
+    return all_molecules, reconstructed_molecules
+
+######################################################
+
+def final_remaining_reconstruction(remaining_fragments, newcell, cell_vector, reconstructed_molecules, debug: int=0):
+    
+    # Reconstructing remaining fragments within the whole new cell
+    final_remaining_fragments = []
+    for i, rem_frag_list in enumerate(remaining_fragments):
+        if len(rem_frag_list) > 1:
+            print(f"target_ref: {newcell.refmoleclist[i].formula}")
+            print(f"Fragments formula {i}: {[rem.formula for rem in rem_frag_list]}")
+            target_ref = newcell.refmoleclist[i].get_parent_indices("reference")
+            list_of_found_molecules, final_remaining = fragments_reconstruct(rem_frag_list, target_ref, cell_vector, debug=debug)
+            print(f"{[mol.formula for mol in list_of_found_molecules]=}")
+            print(f"{[frag.formula for frag in final_remaining]=}")
+            if len(list_of_found_molecules) > 0:
+                reconstructed_molecules.extend(list_of_found_molecules)
+            if len(final_remaining) > 0:
+                final_remaining_fragments.extend(final_remaining)
+        elif len(rem_frag_list) == 1:
+            final_remaining_fragments.extend(rem_frag_list)
+
+    return final_remaining_fragments, reconstructed_molecules
 
-    return all_molecules, reconstructed_molecules, final_remaining_fragments
 ######################################################
 def get_moleclist (newcell, refcell, all_molecules, debug):
     # Get moleclist for the unit cell
diff --git a/cell2mol/test/Cell_reconstruction_Assign-Copy1.ipynb b/cell2mol/test/Cell_reconstruction_Assign-Copy1.ipynb
index 34be279c..48e12215 100644
--- a/cell2mol/test/Cell_reconstruction_Assign-Copy1.ipynb
+++ b/cell2mol/test/Cell_reconstruction_Assign-Copy1.ipynb
@@ -2,23 +2,10 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 36,
    "id": "da7c39aa-eeb1-4d30-a41a-d33ab8b580ab",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "c72b79d02676407194a53cee22c5ea6f",
-       "version_major": 2,
-       "version_minor": 0
-      },
-      "text/plain": []
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "from scipy import sparse\n",
     "from ase.build import molecule\n",
@@ -34,6 +21,7 @@
     "from cell2mol.read_write import readinfo\n",
     "from cell2mol.cell_operations import frac2cart_fromparam, cart2frac\n",
     "import nglview\n",
+    "from nglview.viewer_control import ViewerControl\n",
     "from ase.build import molecule\n",
     "from ase.neighborlist import NeighborList\n",
     "import matplotlib.pyplot as plt\n",
@@ -41,6 +29,449 @@
     "import pickle"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "33fcc8f6-a260-4d5d-b388-46bcb94eab08",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "name = \"ACEYOW\"\n",
+    "infopath = f\"{name}/{name}.info\"\n",
+    "input_path = f\"{name}/{name}.cif\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "c8707364-33c5-477b-9a39-c18cb417ffd7",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "labels, pos, ref_labels, ref_fracs, cellvec, cell_param = readinfo(infopath)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 59,
+   "id": "245d26c1-9d62-483a-a1b7-f7a2d0594ace",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      " /opt/anaconda3/envs/cell2mol/lib/python3.10/site-packages/ase/spacegroup/spacegroup.py:433: UserWarning: scaled_positions 1 and 10 are equivalent\n",
+      " /opt/anaconda3/envs/cell2mol/lib/python3.10/site-packages/ase/spacegroup/spacegroup.py:433: UserWarning: scaled_positions 2 and 11 are equivalent\n",
+      " /opt/anaconda3/envs/cell2mol/lib/python3.10/site-packages/ase/spacegroup/spacegroup.py:433: UserWarning: scaled_positions 3 and 12 are equivalent\n",
+      " /opt/anaconda3/envs/cell2mol/lib/python3.10/site-packages/ase/spacegroup/spacegroup.py:433: UserWarning: scaled_positions 4 and 13 are equivalent\n",
+      " /opt/anaconda3/envs/cell2mol/lib/python3.10/site-packages/ase/spacegroup/spacegroup.py:433: UserWarning: scaled_positions 5 and 14 are equivalent\n",
+      " /opt/anaconda3/envs/cell2mol/lib/python3.10/site-packages/ase/spacegroup/spacegroup.py:433: UserWarning: scaled_positions 6 and 15 are equivalent\n",
+      " /opt/anaconda3/envs/cell2mol/lib/python3.10/site-packages/ase/spacegroup/spacegroup.py:433: UserWarning: scaled_positions 1 and 16 are equivalent\n",
+      " /opt/anaconda3/envs/cell2mol/lib/python3.10/site-packages/ase/spacegroup/spacegroup.py:433: UserWarning: scaled_positions 2 and 17 are equivalent\n",
+      " /opt/anaconda3/envs/cell2mol/lib/python3.10/site-packages/ase/spacegroup/spacegroup.py:433: UserWarning: scaled_positions 3 and 18 are equivalent\n",
+      " /opt/anaconda3/envs/cell2mol/lib/python3.10/site-packages/ase/spacegroup/spacegroup.py:433: UserWarning: scaled_positions 4 and 19 are equivalent\n",
+      " /opt/anaconda3/envs/cell2mol/lib/python3.10/site-packages/ase/spacegroup/spacegroup.py:433: UserWarning: scaled_positions 5 and 20 are equivalent\n",
+      " /opt/anaconda3/envs/cell2mol/lib/python3.10/site-packages/ase/spacegroup/spacegroup.py:433: UserWarning: scaled_positions 6 and 21 are equivalent\n",
+      " /opt/anaconda3/envs/cell2mol/lib/python3.10/site-packages/ase/spacegroup/spacegroup.py:433: UserWarning: scaled_positions 1 and 22 are equivalent\n",
+      " /opt/anaconda3/envs/cell2mol/lib/python3.10/site-packages/ase/spacegroup/spacegroup.py:433: UserWarning: scaled_positions 2 and 23 are equivalent\n",
+      " /opt/anaconda3/envs/cell2mol/lib/python3.10/site-packages/ase/spacegroup/spacegroup.py:433: UserWarning: scaled_positions 3 and 24 are equivalent\n",
+      " /opt/anaconda3/envs/cell2mol/lib/python3.10/site-packages/ase/spacegroup/spacegroup.py:433: UserWarning: scaled_positions 4 and 25 are equivalent\n",
+      " /opt/anaconda3/envs/cell2mol/lib/python3.10/site-packages/ase/spacegroup/spacegroup.py:433: UserWarning: scaled_positions 5 and 26 are equivalent\n",
+      " /opt/anaconda3/envs/cell2mol/lib/python3.10/site-packages/ase/spacegroup/spacegroup.py:433: UserWarning: scaled_positions 6 and 27 are equivalent\n",
+      " /opt/anaconda3/envs/cell2mol/lib/python3.10/site-packages/ase/spacegroup/spacegroup.py:433: UserWarning: scaled_positions 1 and 28 are equivalent\n",
+      " /opt/anaconda3/envs/cell2mol/lib/python3.10/site-packages/ase/spacegroup/spacegroup.py:433: UserWarning: scaled_positions 2 and 29 are equivalent\n",
+      " /opt/anaconda3/envs/cell2mol/lib/python3.10/site-packages/ase/spacegroup/spacegroup.py:433: UserWarning: scaled_positions 3 and 30 are equivalent\n",
+      " /opt/anaconda3/envs/cell2mol/lib/python3.10/site-packages/ase/spacegroup/spacegroup.py:433: UserWarning: scaled_positions 4 and 31 are equivalent\n",
+      " /opt/anaconda3/envs/cell2mol/lib/python3.10/site-packages/ase/spacegroup/spacegroup.py:433: UserWarning: scaled_positions 5 and 32 are equivalent\n",
+      " /opt/anaconda3/envs/cell2mol/lib/python3.10/site-packages/ase/spacegroup/spacegroup.py:433: UserWarning: scaled_positions 6 and 33 are equivalent\n",
+      " /opt/anaconda3/envs/cell2mol/lib/python3.10/site-packages/ase/spacegroup/spacegroup.py:433: UserWarning: scaled_positions 1 and 34 are equivalent\n",
+      " /opt/anaconda3/envs/cell2mol/lib/python3.10/site-packages/ase/spacegroup/spacegroup.py:433: UserWarning: scaled_positions 2 and 35 are equivalent\n",
+      " /opt/anaconda3/envs/cell2mol/lib/python3.10/site-packages/ase/spacegroup/spacegroup.py:433: UserWarning: scaled_positions 3 and 36 are equivalent\n",
+      " /opt/anaconda3/envs/cell2mol/lib/python3.10/site-packages/ase/spacegroup/spacegroup.py:433: UserWarning: scaled_positions 4 and 37 are equivalent\n",
+      " /opt/anaconda3/envs/cell2mol/lib/python3.10/site-packages/ase/spacegroup/spacegroup.py:433: UserWarning: scaled_positions 5 and 38 are equivalent\n",
+      " /opt/anaconda3/envs/cell2mol/lib/python3.10/site-packages/ase/spacegroup/spacegroup.py:433: UserWarning: scaled_positions 6 and 39 are equivalent\n",
+      " /opt/anaconda3/envs/cell2mol/lib/python3.10/site-packages/ase/spacegroup/spacegroup.py:433: UserWarning: scaled_positions 8 and 40 are equivalent\n",
+      " /opt/anaconda3/envs/cell2mol/lib/python3.10/site-packages/ase/spacegroup/spacegroup.py:433: UserWarning: scaled_positions 8 and 41 are equivalent\n",
+      " /opt/anaconda3/envs/cell2mol/lib/python3.10/site-packages/ase/spacegroup/spacegroup.py:433: UserWarning: scaled_positions 9 and 42 are equivalent\n",
+      " /opt/anaconda3/envs/cell2mol/lib/python3.10/site-packages/ase/spacegroup/spacegroup.py:433: UserWarning: scaled_positions 9 and 43 are equivalent\n"
+     ]
+    }
+   ],
+   "source": [
+    "atoms = read(input_path)\n",
+    "cell_labels = atoms.get_chemical_symbols()\n",
+    "cell_pos = atoms.positions\n",
+    "cell_fracs = atoms.get_scaled_positions()\n",
+    "cell_vector = atoms.cell.array\n",
+    "# cell_parameters = atoms.cell.cellpar()\n",
+    "space_group = atoms.info['spacegroup']\n",
+    "sym_ops = space_group.get_op()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "4d9ed17e-20ce-4acd-bba6-85178edd1805",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Axes: >"
+      ]
+     },
+     "execution_count": 18,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plot_atoms(atoms, rotation='45x,75y,75z')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 87,
+   "id": "4c096eb1-dd9d-4b86-8687-5fec1d3eb080",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Help on method rotate in module nglview.viewer_control:\n",
+      "\n",
+      "rotate(basis) method of nglview.viewer_control.ViewerControl instance\n",
+      "    Parameters\n",
+      "    ----------\n",
+      "    basis : List[float], len=4\n",
+      "        quaternion\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "help(view.control.rotate)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 105,
+   "id": "0bcccf62-28d6-4c10-a9c2-2db9c047b929",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "853b111c7aef43128f669f3dff47244c",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "NGLWidget()"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "view = nglview.show_ase(atoms)\n",
+    "view.add_unitcell()\n",
+    "view.control.rotate([0.2, 0, 0, 1])  \n",
+    "view"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "398156c8-d9d1-4ec6-938a-04add496e259",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ref_molecule = Atoms(symbols=ref_labels, scaled_positions=ref_fracs, cell=cell_vector, pbc=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "id": "dcc2e6db-1242-4283-a76d-5f50c212ac78",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Axes: >"
+      ]
+     },
+     "execution_count": 20,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plot_atoms(ref_molecule, rotation='45x,75y,75z')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 140,
+   "id": "5e21aeec-1c5b-4f0d-876f-c034a7e508f4",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "62180d47969f440f88e5e8c547234365",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "NGLWidget()"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "view = nglview.show_ase(ref_molecule, )\n",
+    "view.add_unitcell()\n",
+    "# view.control.rotate([0, 0, 0, 1])  \n",
+    "view"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "id": "0f27dfa6-198a-4589-b0b3-07c6cb5b8979",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "new_structures = apply_symmetry_operations_reference(ref_molecule, cell_vector, sym_ops, False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "id": "fcb78292-b24e-44de-a039-660aff74dfea",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Axes: >"
+      ]
+     },
+     "execution_count": 23,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plot_atoms(new_structures[0], rotation='45x,75y,75z')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 141,
+   "id": "4001937a-ed3e-4427-98d1-5d359cd68f57",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "be7e8e8ae3c04d19bc18725124d03374",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "NGLWidget()"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "unit_cell = Atoms(cell=cell_vector, pbc=True)\n",
+    "view = nglview.show_ase(unit_cell+new_structures[0])\n",
+    "view.add_unitcell()\n",
+    "view"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 148,
+   "id": "e2b28786-4d14-4ca4-8ae5-c414e50089a4",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "symmtry operation 4: new symmetry atom index 34 N [ 0.90038012  5.00258411 10.37112903] [0.33409967 0.50939933 0.59747033]\n",
+      "\tsame frac [0.33409967 0.50939933 0.59747033] [0.3341  0.5094  0.59747]\n",
+      "symmtry operation 31: new symmetry atom index 34 N [ 0.90038012  5.00258411 10.37112903] [0.33409967 0.50939933 0.59747033]\n",
+      "\tsame frac [0.33409967 0.50939933 0.59747033] [0.3341  0.5094  0.59747]\n"
+     ]
+    }
+   ],
+   "source": [
+    "idx = 12\n",
+    "for jdx, new in enumerate(new_structures):\n",
+    "    new_labels =  new.get_chemical_symbols()\n",
+    "    new_pos = new.get_positions()    \n",
+    "    new_fracs = new.get_scaled_positions()\n",
+    "    for kdx, (l, p, f) in enumerate(zip(new_labels, new_pos, new_fracs)):\n",
+    "        if l == cell_labels[idx] and np.allclose(p, cell_pos[idx]) :\n",
+    "            print(f\"symmtry operation {jdx}:\", f\"new symmetry atom index {kdx}\", l, p, f)\n",
+    "            if np.allclose(f, cell_fracs[idx], atol=1e-5, rtol=1e-3):\n",
+    "                print(f\"\\tsame frac\", f, cell_fracs[idx])\n",
+    "            else:\n",
+    "                print(f\"\\tdifferent frac\", f, cell_fracs[idx])\n",
+    "                \n",
+    "    # if new_labels == cell_labels[idx] :\n",
+    "    #     if np.allclose(cell_pos[idx], ):"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "4be7d95e-824c-4902-bb95-8dcb81cdd35a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ref"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 153,
+   "id": "b6c3371f-12be-4b1c-b120-648c5e5100aa",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "['Fe',\n",
+       " 'N',\n",
+       " 'C',\n",
+       " 'C',\n",
+       " 'H',\n",
+       " 'H',\n",
+       " 'H',\n",
+       " 'Sb',\n",
+       " 'F',\n",
+       " 'F',\n",
+       " 'N',\n",
+       " 'C',\n",
+       " 'C',\n",
+       " 'H',\n",
+       " 'H',\n",
+       " 'H',\n",
+       " 'N',\n",
+       " 'C',\n",
+       " 'C',\n",
+       " 'H',\n",
+       " 'H',\n",
+       " 'H',\n",
+       " 'N',\n",
+       " 'C',\n",
+       " 'C',\n",
+       " 'H',\n",
+       " 'H',\n",
+       " 'H',\n",
+       " 'N',\n",
+       " 'C',\n",
+       " 'C',\n",
+       " 'H',\n",
+       " 'H',\n",
+       " 'H',\n",
+       " 'N',\n",
+       " 'C',\n",
+       " 'C',\n",
+       " 'H',\n",
+       " 'H',\n",
+       " 'H',\n",
+       " 'F',\n",
+       " 'F',\n",
+       " 'F',\n",
+       " 'F']"
+      ]
+     },
+     "execution_count": 153,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "new_structures[15].get_chemical_symbols()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 151,
+   "id": "226333da-8a86-4148-92ef-3ea01b3fc328",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "numpy.ndarray"
+      ]
+     },
+     "execution_count": 151,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "t = np.array([0.6667, 0.3333, 0.3333])\n",
+    "type(t)"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 65,
@@ -502,91 +933,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
-   "id": "33fcc8f6-a260-4d5d-b388-46bcb94eab08",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "name = \"ACEYOW\"\n",
-    "infopath = f\"{name}/{name}.info\"\n",
-    "input_path = f\"{name}/{name}.cif\""
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "id": "c8707364-33c5-477b-9a39-c18cb417ffd7",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "labels, pos, ref_labels, ref_fracs, cellvec, cell_param = readinfo(infopath)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "id": "245d26c1-9d62-483a-a1b7-f7a2d0594ace",
+   "execution_count": 5,
+   "id": "0fc550e4-349a-48f8-aa21-b80d4547b25c",
    "metadata": {
     "scrolled": true
    },
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      " /Users/ycho/miniconda3/envs/cell2mol/lib/python3.10/site-packages/ase/spacegroup/spacegroup.py:433: UserWarning: scaled_positions 1 and 10 are equivalent\n",
-      " /Users/ycho/miniconda3/envs/cell2mol/lib/python3.10/site-packages/ase/spacegroup/spacegroup.py:433: UserWarning: scaled_positions 2 and 11 are equivalent\n",
-      " /Users/ycho/miniconda3/envs/cell2mol/lib/python3.10/site-packages/ase/spacegroup/spacegroup.py:433: UserWarning: scaled_positions 3 and 12 are equivalent\n",
-      " /Users/ycho/miniconda3/envs/cell2mol/lib/python3.10/site-packages/ase/spacegroup/spacegroup.py:433: UserWarning: scaled_positions 4 and 13 are equivalent\n",
-      " /Users/ycho/miniconda3/envs/cell2mol/lib/python3.10/site-packages/ase/spacegroup/spacegroup.py:433: UserWarning: scaled_positions 5 and 14 are equivalent\n",
-      " /Users/ycho/miniconda3/envs/cell2mol/lib/python3.10/site-packages/ase/spacegroup/spacegroup.py:433: UserWarning: scaled_positions 6 and 15 are equivalent\n",
-      " /Users/ycho/miniconda3/envs/cell2mol/lib/python3.10/site-packages/ase/spacegroup/spacegroup.py:433: UserWarning: scaled_positions 1 and 16 are equivalent\n",
-      " /Users/ycho/miniconda3/envs/cell2mol/lib/python3.10/site-packages/ase/spacegroup/spacegroup.py:433: UserWarning: scaled_positions 2 and 17 are equivalent\n",
-      " /Users/ycho/miniconda3/envs/cell2mol/lib/python3.10/site-packages/ase/spacegroup/spacegroup.py:433: UserWarning: scaled_positions 3 and 18 are equivalent\n",
-      " /Users/ycho/miniconda3/envs/cell2mol/lib/python3.10/site-packages/ase/spacegroup/spacegroup.py:433: UserWarning: scaled_positions 4 and 19 are equivalent\n",
-      " /Users/ycho/miniconda3/envs/cell2mol/lib/python3.10/site-packages/ase/spacegroup/spacegroup.py:433: UserWarning: scaled_positions 5 and 20 are equivalent\n",
-      " /Users/ycho/miniconda3/envs/cell2mol/lib/python3.10/site-packages/ase/spacegroup/spacegroup.py:433: UserWarning: scaled_positions 6 and 21 are equivalent\n",
-      " /Users/ycho/miniconda3/envs/cell2mol/lib/python3.10/site-packages/ase/spacegroup/spacegroup.py:433: UserWarning: scaled_positions 1 and 22 are equivalent\n",
-      " /Users/ycho/miniconda3/envs/cell2mol/lib/python3.10/site-packages/ase/spacegroup/spacegroup.py:433: UserWarning: scaled_positions 2 and 23 are equivalent\n",
-      " /Users/ycho/miniconda3/envs/cell2mol/lib/python3.10/site-packages/ase/spacegroup/spacegroup.py:433: UserWarning: scaled_positions 3 and 24 are equivalent\n",
-      " /Users/ycho/miniconda3/envs/cell2mol/lib/python3.10/site-packages/ase/spacegroup/spacegroup.py:433: UserWarning: scaled_positions 4 and 25 are equivalent\n",
-      " /Users/ycho/miniconda3/envs/cell2mol/lib/python3.10/site-packages/ase/spacegroup/spacegroup.py:433: UserWarning: scaled_positions 5 and 26 are equivalent\n",
-      " /Users/ycho/miniconda3/envs/cell2mol/lib/python3.10/site-packages/ase/spacegroup/spacegroup.py:433: UserWarning: scaled_positions 6 and 27 are equivalent\n",
-      " /Users/ycho/miniconda3/envs/cell2mol/lib/python3.10/site-packages/ase/spacegroup/spacegroup.py:433: UserWarning: scaled_positions 1 and 28 are equivalent\n",
-      " /Users/ycho/miniconda3/envs/cell2mol/lib/python3.10/site-packages/ase/spacegroup/spacegroup.py:433: UserWarning: scaled_positions 2 and 29 are equivalent\n",
-      " /Users/ycho/miniconda3/envs/cell2mol/lib/python3.10/site-packages/ase/spacegroup/spacegroup.py:433: UserWarning: scaled_positions 3 and 30 are equivalent\n",
-      " /Users/ycho/miniconda3/envs/cell2mol/lib/python3.10/site-packages/ase/spacegroup/spacegroup.py:433: UserWarning: scaled_positions 4 and 31 are equivalent\n",
-      " /Users/ycho/miniconda3/envs/cell2mol/lib/python3.10/site-packages/ase/spacegroup/spacegroup.py:433: UserWarning: scaled_positions 5 and 32 are equivalent\n",
-      " /Users/ycho/miniconda3/envs/cell2mol/lib/python3.10/site-packages/ase/spacegroup/spacegroup.py:433: UserWarning: scaled_positions 6 and 33 are equivalent\n",
-      " /Users/ycho/miniconda3/envs/cell2mol/lib/python3.10/site-packages/ase/spacegroup/spacegroup.py:433: UserWarning: scaled_positions 1 and 34 are equivalent\n",
-      " /Users/ycho/miniconda3/envs/cell2mol/lib/python3.10/site-packages/ase/spacegroup/spacegroup.py:433: UserWarning: scaled_positions 2 and 35 are equivalent\n",
-      " /Users/ycho/miniconda3/envs/cell2mol/lib/python3.10/site-packages/ase/spacegroup/spacegroup.py:433: UserWarning: scaled_positions 3 and 36 are equivalent\n",
-      " /Users/ycho/miniconda3/envs/cell2mol/lib/python3.10/site-packages/ase/spacegroup/spacegroup.py:433: UserWarning: scaled_positions 4 and 37 are equivalent\n",
-      " /Users/ycho/miniconda3/envs/cell2mol/lib/python3.10/site-packages/ase/spacegroup/spacegroup.py:433: UserWarning: scaled_positions 5 and 38 are equivalent\n",
-      " /Users/ycho/miniconda3/envs/cell2mol/lib/python3.10/site-packages/ase/spacegroup/spacegroup.py:433: UserWarning: scaled_positions 6 and 39 are equivalent\n",
-      " /Users/ycho/miniconda3/envs/cell2mol/lib/python3.10/site-packages/ase/spacegroup/spacegroup.py:433: UserWarning: scaled_positions 8 and 40 are equivalent\n",
-      " /Users/ycho/miniconda3/envs/cell2mol/lib/python3.10/site-packages/ase/spacegroup/spacegroup.py:433: UserWarning: scaled_positions 8 and 41 are equivalent\n",
-      " /Users/ycho/miniconda3/envs/cell2mol/lib/python3.10/site-packages/ase/spacegroup/spacegroup.py:433: UserWarning: scaled_positions 9 and 42 are equivalent\n",
-      " /Users/ycho/miniconda3/envs/cell2mol/lib/python3.10/site-packages/ase/spacegroup/spacegroup.py:433: UserWarning: scaled_positions 9 and 43 are equivalent\n"
-     ]
-    }
-   ],
-   "source": [
-    "atoms = read(input_path)\n",
-    "cell_labels = atoms.get_chemical_symbols()\n",
-    "cell_pos = atoms.positions\n",
-    "cell_fracs = atoms.get_scaled_positions()\n",
-    "cell_vector = atoms.cell.array\n",
-    "# cell_parameters = atoms.cell.cellpar()\n",
-    "space_group = atoms.info['spacegroup']\n",
-    "sym_ops = space_group.get_op()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 5,
-   "id": "0fc550e4-349a-48f8-aa21-b80d4547b25c",
-   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -4510,7 +4861,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "cell2mol",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
    "name": "python3"
   },
diff --git a/cell2mol/test/cif_file_BOFFOS.ipynb b/cell2mol/test/cif_file_BOFFOS.ipynb
index 69758bab..cf82ff85 100644
--- a/cell2mol/test/cif_file_BOFFOS.ipynb
+++ b/cell2mol/test/cif_file_BOFFOS.ipynb
@@ -371,9 +371,7 @@
   {
    "cell_type": "code",
    "execution_count": 10,
-   "metadata": {
-    "scrolled": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -390,6 +388,15 @@
     "unit_cell"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "t = np.array([0.6667, 0.3333, 0.3333])"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 11,