def test_parsimonious_scissors_tanimotos(self):
"""
Test default Tanimoto approximation using parsimonious overlap
values.
"""
basis = np.random.randint(self.n_mols, size=200)
bb_ip = self.data['tanimotos'][basis][:, basis]
bb_ip = SCISSORS.get_inner_products_from_tanimotos(bb_ip)
lb_ip = self.data['tanimotos'][:, basis]
lb_ip = SCISSORS.get_inner_products_from_tanimotos(lb_ip)
s = SCISSORS(bb_ip)
tanimotos = s.get_tanimotos(lb_ip, max_dim=100)
assert_scissors(tanimotos, self.data['tanimotos'])
def test_parsimonious_scissors_tanimotos_with_overlaps(self):
"""
Test Tanimoto approximation using parsimonious overlap values and
precalculated self-overlap values.
"""
basis = np.random.randint(self.n_mols, size=200)
bb_ip = self.data['tanimotos'][basis][:, basis]
bb_ip = SCISSORS.get_inner_products_from_tanimotos(bb_ip)
lb_ip = self.data['tanimotos'][:, basis]
lb_ip = SCISSORS.get_inner_products_from_tanimotos(lb_ip)
s = SCISSORS(bb_ip)
tanimotos = s.get_tanimotos(lb_ip, self_overlap=np.ones(lb_ip.shape[0],
dtype=float),
max_dim=100)
assert_scissors(tanimotos, self.data['tanimotos'])
def load(filename, overlap):
"""
Load ROCS data from HDF5.
Parameters
----------
filename : str
File containing ROCS overlay results.
overlap : bool
Whether to use actual pairwise overlaps as inner products. If
False, use overlaps calculated under the parsimonious assumption
of unity molecular self-overlap values.
"""
with h5py.File(filename) as f:
if overlap:
shape_ip = f['shape_overlap'][:]
color_ip = f['color_overlap'][:]
else:
shape_ip = SCISSORS.get_inner_products_from_tanimotos(
f['shape_tanimoto'][:])
color_ip = SCISSORS.get_inner_products_from_tanimotos(
f['color_tanimoto'][:])
return shape_ip, color_ip
