def test_parser_roundtrip_via_indices(self):
# TODO: cheating a bit here, reconstruction does fail for some smiles
# chirality gets inverted sometimes, so need to run the loop twice to reconstruct the original
g = HypergraphGrammar()
g.delete_cache()
actions = g.strings_to_actions(smiles)
re_smiles = g.decode_from_actions(actions)
re_actions = g.strings_to_actions(re_smiles)
rere_smiles = g.decode_from_actions(re_actions)
for old, new in zip(smiles, rere_smiles):
old_fix = old #.replace('@@', '@')#.replace('/','\\')
new_fix = new #.replace('@@', '@')#.replace('/','\\').replace('\\','')
assert old_fix == new_fix
def test_mask_gen(self):
g = HypergraphGrammar()
g.strings_to_actions(
smiles) # that initializes g with the rules from these molecules
g.calc_terminal_distance()
batch_size = 10
max_rules = 50
all_actions = []
next_action = [None for _ in range(batch_size)]
mask_gen = HypergraphMaskGenerator(max_rules, g)
while True:
try:
next_masks = mask_gen(next_action)
next_action = []
for mask in next_masks:
inds = np.nonzero(mask)[0]
next_act = random.choice(inds)
next_action.append(next_act)
all_actions.append(next_action)
except StopIteration:
break
all_actions = np.array(all_actions).T
# the test is that we get that far, producing valid molecules
all_smiles = g.decode_from_actions(all_actions)
for smile in all_smiles:
print(smile)
f.close()
fn = "rule_hypergraphs.pickle"
max_rules = 50
if os.path.isfile(fn):
rm = HypergraphGrammar.load(fn)
else:
rm = HypergraphGrammar(cache_file=fn)
bad_smiles = []
for num, smile in enumerate(L[:100]):
try:
smile = MolToSmiles(MolFromSmiles(smile))
print(smile)
mol = MolFromSmiles(smile)
actions = rm.strings_to_actions([smile])
re_smile = rm.decode_from_actions(actions)[0]
mol = MolFromSmiles(smile)
if re_smile != smile:
print("SMILES reconstruction wasn't perfect for " + smile)
print(re_smile)
except Exception as e:
print(e)
bad_smiles.append(smile)
rm.calc_terminal_distance()
# now let's write a basic for-loop to create molecules
batch_size = 10
all_actions = []
next_action = [None for _ in range(batch_size)]