def test_vector_types_duplicate():
fname = datadir+"/smalldup.types"
teste = molgrid.ExampleProvider(molgrid.GninaVectorTyper(),shuffle=False, duplicate_first=True,data_root=datadir+"/structs")
teste.populate(fname)
batch_size = 1
gmaker = molgrid.GridMaker()
dims = gmaker.grid_dimensions(molgrid.GninaVectorTyper().num_types()*4)
tensor_shape = (batch_size,)+dims
input_tensor_1 = torch.zeros(tensor_shape, dtype=torch.float32, device='cuda')
batch_1 = teste.next_batch(batch_size)
gmaker.forward(batch_1, input_tensor_1,random_translation=0.0, random_rotation=False)
input_tensor_2 = torch.zeros(tensor_shape, dtype=torch.float32, device='cpu')
gmaker.forward(batch_1, input_tensor_2,random_translation=0.0, random_rotation=False)
np.testing.assert_allclose(input_tensor_1.cpu().detach().numpy(),input_tensor_2.detach().numpy(),atol=1e-4)
assert input_tensor_1.cpu().detach().numpy().max() < 75
def test_gninavector_typing():
m = pybel.readstring('smi', 'C')
m.addh()
t = molgrid.GninaVectorTyper()
typs = [t.get_atom_type_vector(a.OBAtom) for a in m.atoms]
names = list(t.get_type_names())
assert len(names) == 26
assert names[-1] == 'OB_partialcharge'
for tvec, r in typs:
if r < 1: #hydrogen
assert r == approx(0.37)
assert tvec[0] == 1
assert np.sum(tvec[:17]) == 1
else: #carbon
assert r == approx(1.9)
assert tvec[1] == 1
assert np.sum(tvec[:17]) == 1
assert names[20] == "XS_hydrophobe"
assert tvec[20] == 1