def test_rescore_collection_for_trees(default_config, setup_linear_reaction_tree):
rt = setup_linear_reaction_tree()
routes = RouteCollection(reaction_trees=[rt])
routes.compute_scores(StateScorer(default_config))
routes.rescore(NumberOfReactionsScorer())
assert routes.scores[0] == 2
assert np.round(routes.all_scores[0]["state score"], 3) == 0.994
assert routes.all_scores[0]["number of reactions"] == 2
def test_clustering_collection_timeout(load_reaction_tree):
collection = RouteCollection(reaction_trees=[
ReactionTree.from_dict(
load_reaction_tree("routes_for_clustering.json", idx))
for idx in range(3)
])
cluster_labels = collection.cluster(n_clusters=1, timeout=0)
assert len(cluster_labels) == 0
assert collection.clusters is None
def test_create_clustering_gui(mocker, load_reaction_tree):
collection = RouteCollection(reaction_trees=[
ReactionTree.from_dict(
load_reaction_tree("routes_for_clustering.json", idx))
for idx in range(3)
])
display_patch = mocker.patch(
"aizynthfinder.interfaces.gui.clustering.display")
ClusteringGui(collection)
display_patch.assert_called()
def test_rescore_collection_for_trees(default_config, mock_stock,
load_reaction_tree):
mock_stock(default_config, "N#Cc1cccc(N)c1F", "O=C(Cl)c1ccc(F)cc1",
"CN1CCC(Cl)CC1", "O")
rt = ReactionTree.from_dict(load_reaction_tree("sample_reaction.json"))
routes = RouteCollection(reaction_trees=[rt])
routes.compute_scores(StateScorer(default_config))
routes.rescore(NumberOfReactionsScorer())
assert routes.scores[0] == 2
assert np.round(routes.all_scores[0]["state score"], 3) == 0.994
assert routes.all_scores[0]["number of reactions"] == 2
def test_compute_new_score_for_trees(default_config, setup_linear_reaction_tree):
rt = setup_linear_reaction_tree()
routes = RouteCollection(reaction_trees=[rt])
assert routes.nodes[0] is None
assert routes.scores[0] is np.nan
assert routes.all_scores[0] == {}
routes.compute_scores(StateScorer(default_config), NumberOfReactionsScorer())
assert routes.scores[0] is np.nan
assert np.round(routes.all_scores[0]["state score"], 3) == 0.994
assert routes.all_scores[0]["number of reactions"] == 2
def test_clustering_collection(load_reaction_tree):
collection = RouteCollection(reaction_trees=[
ReactionTree.from_dict(
load_reaction_tree("routes_for_clustering.json", idx))
for idx in range(3)
])
collection.cluster(n_clusters=1)
assert len(collection.clusters) == 2
assert collection.clusters[0].reaction_trees == collection.reaction_trees[
1:3]
assert collection.clusters[1].reaction_trees == [
collection.reaction_trees[0]
]
def prepare_tree(self) -> None:
"""
Setup the tree for searching
:raises ValueError: if the target molecule was not set
"""
if not self.target_mol:
raise ValueError("No target molecule set")
self.stock.reset_exclusion_list()
if self.config.exclude_target_from_stock and self.target_mol in self.stock:
self.stock.exclude(self.target_mol)
self._logger.debug("Excluding the target compound from the stock")
self._setup_search_tree()
self.analysis = None
self.routes = RouteCollection([])
def test_create_combine_tree_to_visjs(load_reaction_tree, tmpdir):
collection = RouteCollection(
reaction_trees=[
ReactionTree.from_dict(load_reaction_tree("routes_for_clustering.json", 0)),
ReactionTree.from_dict(load_reaction_tree("routes_for_clustering.json", 1)),
ReactionTree.from_dict(load_reaction_tree("routes_for_clustering.json", 2)),
]
)
tar_filename = str(tmpdir / "routes.tar")
combined = collection.combined_reaction_trees()
combined.to_visjs_page(tar_filename)
assert os.path.exists(tar_filename)
with TarFile(tar_filename) as tarobj:
assert "./route.html" in tarobj.getnames()
assert len([name for name in tarobj.getnames() if name.endswith(".png")]) == 8
def test_distance_collection(load_reaction_tree):
collection = RouteCollection(reaction_trees=[
ReactionTree.from_dict(
load_reaction_tree("routes_for_clustering.json", idx))
for idx in range(3)
])
dist_mat1 = collection.distance_matrix()
dist_mat2 = collection.distance_matrix(recreate=True)
assert (dist_mat1 - dist_mat2).sum() == 0
dist_mat3 = collection.distance_matrix(content="molecules")
assert (dist_mat1 - dist_mat3).sum() != 0
assert len(dist_mat3) == 3
assert pytest.approx(dist_mat3[0, 1], abs=1e-2) == 2.6522
assert pytest.approx(dist_mat3[0, 2], abs=1e-2) == 3.0779
assert pytest.approx(dist_mat3[2, 1], abs=1e-2) == 0.7483
def test_create_combine_tree_dict_from_json(load_reaction_tree):
collection = RouteCollection(
reaction_trees=[
ReactionTree.from_dict(load_reaction_tree("routes_for_clustering.json", 0)),
ReactionTree.from_dict(load_reaction_tree("routes_for_clustering.json", 1)),
ReactionTree.from_dict(load_reaction_tree("routes_for_clustering.json", 2)),
]
)
expected = load_reaction_tree("combined_example_tree.json")
combined_dict = collection.combined_reaction_trees().to_dict()
assert len(combined_dict["children"]) == 2
assert combined_dict["children"][0]["is_reaction"]
assert len(combined_dict["children"][0]["children"]) == 2
assert len(combined_dict["children"][1]["children"]) == 2
assert len(combined_dict["children"][1]["children"][1]["children"]) == 2
assert combined_dict["children"][1]["children"][1]["children"][0]["is_reaction"]
assert combined_dict == expected
def __init__(self, configfile: str = None, configdict: StrDict = None) -> None:
self._logger = logger()
if configfile:
self.config = Configuration.from_file(configfile)
elif configdict:
self.config = Configuration.from_dict(configdict)
else:
self.config = Configuration()
self.expansion_policy = self.config.expansion_policy
self.filter_policy = self.config.filter_policy
self.stock = self.config.stock
self.scorers = self.config.scorers
self.tree: Optional[SearchTree] = None
self._target_mol: Optional[Molecule] = None
self.search_stats: StrDict = dict()
self.routes = RouteCollection([])
self.analysis: Optional[TreeAnalysis] = None