# Import lomap
import lomap
import sys
import networkx as nx
    
# Create the molecule database by using .mol2 files
# The DBMolecule class must be created with a valid
# directory name
        
db_mol = lomap.DBMolecules('test/basic/', output=True, display=True)
    
# Generate the strict and loose syimmetric similarity 
# score matrices
          
strict, loose = db_mol.build_matrices()
    
# Convert the matrices in standard numpy matrices

strict_numpy = strict.to_numpy_2D_array()
loose_numpy = loose.to_numpy_2D_array()

    
# Networkx graph generation based on the similarity 
# score matrices
          
nx_graph = db_mol.build_graph() 
#print(nx_graph.edges(data=True))

                
# Calculate the Maximum Common Subgraph (MCS) between 
# the first two molecules in the molecule database
    
#MC = lomap.MCS(db_mol[0].getMolecule(), db_mol[1].getMolecule())

# Output the MCS in a .png file

#MC.draw_mcs()

@@ -230,16 +230,74 @@
 basic/',
+ output=True)%0A%0A# db_mol = lomap.DBMolecules('test/basic/',
  output=
@@ -316,16 +316,17 @@
 y=True)%0A
+%0A
     %0A# G
@@ -356,17 +356,16 @@
 loose sy
-i
 mmetric 

fix example