def mutate(mol, mutation_rate):
if random.random() > mutation_rate:
return mol
Chem.Kekulize(mol, clearAromaticFlags=True)
p = [0.15, 0.14, 0.14, 0.14, 0.14, 0.14, 0.15]
for i in range(10):
rxn_smarts_list = 7 * ['']
rxn_smarts_list[0] = insert_atom()
rxn_smarts_list[1] = change_bond_order()
rxn_smarts_list[2] = delete_cyclic_bond()
rxn_smarts_list[3] = add_ring()
rxn_smarts_list[4] = delete_atom()
rxn_smarts_list[5] = change_atom(mol)
rxn_smarts_list[6] = append_atom()
rxn_smarts = np.random.choice(rxn_smarts_list, p=p)
#print 'mutation',rxn_smarts
rxn = AllChem.ReactionFromSmarts(rxn_smarts)
new_mol_trial = rxn.RunReactants((mol, ))
new_mols = []
for m in new_mol_trial:
m = m[0]
#print Chem.MolToSmiles(mol),mol_OK(mol)
if co.mol_OK(m) and co.ring_OK(m):
new_mols.append(m)
if len(new_mols) > 0:
return random.choice(new_mols)
return None
def crossover(parent_a_mol,parent_b_mol):
parent_a, parent_b = mol2string(parent_a_mol), mol2string(parent_b_mol)
for _ in range(50):
cut_point_a = cut_point(parent_a)
cut_point_b = cut_point(parent_b)
a1 = parent_a[0:cut_point_a]
b2 = parent_b[cut_point_b:len(parent_b)]
child_string = a1 + b2
child_mol = string2mol(child_string)
#print(child_string,Chem.MolToSmiles(child_mol),child_mol,co.mol_OK(child_mol))
if co.mol_OK(child_mol):
return child_mol
return None
def mutate(mol,mutation_rate):
if random.random() > mutation_rate:
return mol
Chem.Kekulize(mol,clearAromaticFlags=True)
child = stco.mol2string(mol)
symbols = get_symbols()
for i in range(50):
random_number = random.random()
mutated_gene = random.randint(0, len(child) - 1)
random_symbol_number = random.randint(0, len(symbols)-1)
new_child = list(child)
random_number = random.random()
new_child[mutated_gene] = symbols[random_symbol_number]
new_child_mol = stco.string2mol(new_child)
#print(child_smiles,Chem.MolToSmiles(child_mol),child_mol,co.mol_OK(child_mol))
if co.mol_OK(new_child_mol):
return new_child_mol
return mol
def reproduce(mating_pool, population_size, mutation_rate):
new_population = []
count = 0
while len(new_population) < population_size:
parent_A = random.choice(mating_pool)
parent_B = random.choice(mating_pool)
#print Chem.MolToSmiles(parent_A),Chem.MolToSmiles(parent_B)
new_child = co.crossover(parent_A, parent_B)
#print new_child
if new_child != None:
new_child = mu.mutate(new_child, mutation_rate)
#print "after mutation",new_child
if new_child != None:
mol = co.mol_OK(new_child)
if mol != True:
count += 1
else:
new_population.append(new_child)
else:
count += 1
else:
count += 1
return new_population, count
