def test_dual_basis_element():
de = DualBasisElement()
de_2 = DualBasisElement()
db_0 = de + de_2
assert isinstance(db_0, DualBasis)
db_1 = db_0 + db_0
assert isinstance(db_1, DualBasis)
dim = 2
opdm = np.random.random((dim, dim))
opdm = (opdm.T + opdm) / 2
opdm = Tensor(tensor=opdm, name='opdm')
rdm = MultiTensor([opdm])
def generate_dual_basis_element(i, j):
element = DualBasisElement(tensor_names=["opdm"],
tensor_elements=[(i, j)],
tensor_coeffs=[-1.0],
bias=1 if i == j else 0,
scalar=0)
return element
opdm_to_oqdm_map = DualBasis()
for _, idx in opdm.all_iterator():
i, j = idx
opdm_to_oqdm_map += generate_dual_basis_element(i, j)
rdm.dual_basis = opdm_to_oqdm_map
A, b, _ = rdm.synthesize_dual_basis()
Adense = A.todense()
opdm_flat = opdm.data.reshape((-1, 1))
oqdm = Adense.dot(opdm_flat)
test_oqdm = oqdm + b.todense()
assert np.allclose(test_oqdm.reshape((dim, dim)), np.eye(dim) - opdm.data)
def test_add_dualelement():
a = np.random.random((5, 5, 5, 5))
b = np.random.random((4, 4, 4))
c = np.random.random((3, 3))
at = Tensor(tensor=a, name='a')
bt = Tensor(tensor=b, name='b')
ct = Tensor(tensor=c, name='c')
mt = MultiTensor([at, bt, ct])
assert isinstance(mt.dual_basis, DualBasis)
dbe = DualBasisElement()
dbe.add_element('a', (0, 1, 2, 3), 4)
mt.add_dual_elements(dbe)
assert len(mt.dual_basis) == 1
def test_d2_to_g2():
# this should test for correctness
filename = os.path.join(DATA_DIRECTORY, "H1-Li1_sto-3g_singlet_1.45.hdf5")
molecule = MolecularData(filename=filename)
molecule.load()
opdm = molecule.fci_one_rdm
tpdm = molecule.fci_two_rdm
phdm = map_two_pdm_to_particle_hole_dm(tpdm, opdm)
db = tpdm_to_phdm_mapping(molecule.n_qubits)
topdm = Tensor(tensor=opdm, name='ck')
ttpdm = Tensor(tensor=np.einsum('ijlk', tpdm), name='cckk')
tphdm = Tensor(tensor=np.einsum('ijlk', phdm), name='ckck')
mt = MultiTensor(tensors=[topdm, ttpdm, tphdm], dual_basis=db)
A, _, b = mt.synthesize_dual_basis()
vec_rdms = mt.vectorize_tensors()
assert np.isclose(np.linalg.norm(A.dot(vec_rdms) - b), 0)
def test_multitensor_init():
"""
Testing the generation of a multitensor object with random tensors
"""
a = np.random.random((5, 5))
b = np.random.random((4, 4))
c = np.random.random((3, 3))
at = Tensor(tensor=a, name='a')
bt = Tensor(tensor=b, name='b')
ct = Tensor(tensor=c, name='c')
mt = MultiTensor([at, bt, ct])
with pytest.raises(TypeError):
_ = MultiTensor((at, bt))
assert len(mt.dual_basis) == 0
assert np.isclose(mt.vec_dim, 5**2 + 4**2 + 3**2)
def test_multitensor_offsetmap():
a = np.random.random((5, 5, 5, 5))
b = np.random.random((4, 4, 4))
c = np.random.random((3, 3))
at = Tensor(tensor=a, name='a')
bt = Tensor(tensor=b, name='b')
ct = Tensor(tensor=c, name='c')
mt = MultiTensor([at, bt, ct])
assert mt.off_set_map == {'a': 0, 'b': 5**4, 'c': 5**4 + 4**3}
def test_synthesis_dualbasis():
a = np.random.random((5, 5))
b = np.random.random((4, 4))
c = np.random.random((3, 3))
at = Tensor(tensor=a, name='a')
bt = Tensor(tensor=b, name='b')
ct = Tensor(tensor=c, name='c')
dbe = DualBasisElement()
dbe.add_element('a', (0, 1), 4)
dbe.add_element('a', (1, 0), 4)
mt = MultiTensor([at, bt, ct], DualBasis(elements=[dbe]))
A, c, b = mt.synthesize_dual_basis()
assert isinstance(A, sp.sparse.csr_matrix)
assert isinstance(c, sp.sparse.csr_matrix)
assert isinstance(b, sp.sparse.csr_matrix)
assert A.shape == (1, 50)
assert b.shape == (1, 1)
assert c.shape == (1, 1)
def test_synthesis_element():
a = np.random.random((5, 5))
b = np.random.random((4, 4))
c = np.random.random((3, 3))
at = Tensor(tensor=a, name='a')
bt = Tensor(tensor=b, name='b')
ct = Tensor(tensor=c, name='c')
mt = MultiTensor([at, bt, ct])
dbe = DualBasisElement()
dbe.add_element('a', (0, 1), 4)
dbe.add_element('a', (1, 0), 4)
with pytest.raises(TypeError):
dbe.add_element(5)
with pytest.raises(TypeError):
mt.add_dual_elements(5)
mt.add_dual_elements(dbe)
colidx, data_vals = mt.synthesize_element(dbe)
assert data_vals == [4, 4]
assert colidx == [1, 5]
assert [at.data[0, 1], at.data[1, 0]] == [at(0, 1), at(1, 0)]
def test_vectorize_test():
a = np.random.random((5, 5))
b = np.random.random((4, 4))
c = np.random.random((3, 3))
at = Tensor(tensor=a, name='a')
bt = Tensor(tensor=b, name='b')
ct = Tensor(tensor=c, name='c')
mt = MultiTensor([at, bt, ct])
vec = np.vstack((at.vectorize(), bt.vectorize()))
vec = np.vstack((vec, ct.vectorize()))
assert np.allclose(vec, mt.vectorize_tensors())
a = np.random.random((5, 5, 5, 5))
b = np.random.random((4, 4, 4))
c = np.random.random((3, 3))
at = Tensor(tensor=a, name='a')
bt = Tensor(tensor=b, name='b')
ct = Tensor(tensor=c, name='c')
mt = MultiTensor([at, bt, ct])
vec = np.vstack((at.vectorize(), bt.vectorize()))
vec = np.vstack((vec, ct.vectorize()))
assert np.allclose(vec, mt.vectorize_tensors())
def test_cover_make_offset_dict():
a = np.random.random((5, 5))
b = np.random.random((4, 4))
c = np.random.random((3, 3))
with pytest.raises(TypeError):
_ = MultiTensor.make_offset_dict([a, b, c])