def test_set_reactants_list_of_list():
mol = UniqueMolecule(smiles="N#Cc1cccc(NC(=O)c2ccc(F)cc2)c1F")
reactant1 = UniqueMolecule(smiles="N#Cc1cccc(N)c1F")
reactant2 = UniqueMolecule(smiles="O=C(Cl)c1ccc(F)cc1")
rxn = FixedRetroReaction(mol)
rxn.reactants = ((reactant1, reactant2), )
assert rxn.reactants == ((reactant1, reactant2), )
def _parse_tree_dict(self, tree_dict, ncalls=0):
product_node = UniqueMolecule(smiles=tree_dict["smiles"])
self._add_node(
product_node,
depth=2 * ncalls,
transform=ncalls,
hide=tree_dict.get("hide", False),
in_stock=tree_dict["in_stock"],
)
rxn_tree_dict = tree_dict.get("children", [])
if not rxn_tree_dict:
return product_node
rxn_tree_dict = rxn_tree_dict[0]
reaction_node = FixedRetroReaction(
product_node,
smiles=rxn_tree_dict["smiles"],
metadata=rxn_tree_dict.get("metadata", {}),
)
self._add_node(reaction_node,
depth=2 * ncalls + 1,
hide=rxn_tree_dict.get("hide", False))
self.tree.graph.add_edge(product_node, reaction_node)
reactant_nodes = []
for reactant_tree in rxn_tree_dict.get("children", []):
reactant_node = self._parse_tree_dict(reactant_tree, ncalls + 1)
self.tree.graph.add_edge(reaction_node, reactant_node)
reactant_nodes.append(reactant_node)
reaction_node.reactants = reactant_nodes
return product_node
def test_create_fixed_reaction():
smiles = "[C:1](=[O:2])([cH3:3])[N:4][cH3:5]>>Cl[C:1](=[O:2])[cH3:3].[N:4][cH3:5]"
mol = UniqueMolecule(smiles="N#Cc1cccc(NC(=O)c2ccc(F)cc2)c1F")
rxn = FixedRetroReaction(mol, smiles=smiles)
assert rxn.smiles == smiles
def test_scorers_tree_one_node_route(default_config):
tree = ReactionTree()
tree.root = UniqueMolecule(smiles="CCCCOc1ccc(CC(=O)N(C)O)cc1")
tree.graph.add_node(tree.root)
assert pytest.approx(StateScorer(default_config)(tree), abs=1e-3) == 0.0497
assert NumberOfReactionsScorer(default_config)(tree) == 0
assert NumberOfPrecursorsScorer(default_config)(tree) == 1
assert NumberOfPrecursorsInStockScorer(default_config)(tree) == 0
assert PriceSumScorer(default_config)(tree) == 10
assert RouteCostScorer(default_config)(tree) == 10
def _parse_tree_dict(tree_dict, rt_object, reaction_cls):
if tree_dict["type"] == "mol":
node = UniqueMolecule(smiles=tree_dict["smiles"])
if not rt_object.root:
rt_object.root = node
if tree_dict["in_stock"]:
rt_object._stock.append(node)
else:
node = reaction_cls(smiles=tree_dict["smiles"],
metadata=tree_dict.get("metadata", {}))
rt_object.graph.add_node(node)
for child_dict in tree_dict.get("children", []):
child = ReactionTree._parse_tree_dict(child_dict, rt_object,
reaction_cls)
rt_object.graph.add_edge(node, child)
return node