def test_canonize_cyclic(self, dtype, block):
k = MPS_rand_state(40, 10, dtype=dtype, cyclic=True)
b = k.H
k.add_tag('KET')
b.add_tag('BRA')
kb = (b | k)
assert not np.allclose(k[block].H @ k[block], 1.0)
assert not np.allclose(b[block].H @ b[block], 1.0)
k.canonize_cyclic(block, bra=b)
assert_allclose(k[block].H @ k[block], 1.0, rtol=2e-4)
assert_allclose(b[block].H @ b[block], 1.0, rtol=2e-4)
ii = kb.select(block, which='!any') ^ all
if isinstance(block, slice):
start, stop = block.start, block.stop
else:
start, stop = block, block + 1
assert len(kb.select_tensors(block, 'any')) == 2 * (stop - start)
ul, = bonds(kb[k.site_tag(start - 1), 'BRA'], kb[k.site_tag(start),
'BRA'])
ur, = bonds(kb[k.site_tag(stop - 1), 'BRA'], kb[k.site_tag(stop),
'BRA'])
ll, = bonds(kb[k.site_tag(start - 1), 'KET'], kb[k.site_tag(start),
'KET'])
lr, = bonds(kb[k.site_tag(stop - 1), 'KET'], kb[k.site_tag(stop),
'KET'])
ii = ii.to_dense((ul, ur), (ll, lr))
assert_allclose(ii, np.eye(ii.shape[0]), rtol=0.001, atol=0.001)
def test_replace_with_svd_using_linear_operator(self, dtype, method):
k = MPS_rand_state(100, 10, dtype=dtype, cyclic=True)
b = k.H
b.expand_bond_dimension(11)
k.add_tag('_KET')
b.add_tag('_BRA')
tn = b & k
x1 = tn ^ ...
ul, = tn['_KET', 'I1'].bonds(tn['_KET', 'I2'])
ll, = tn['_BRA', 'I1'].bonds(tn['_BRA', 'I2'])
where = ['I{}'.format(i) for i in range(2, 40)]
tn.replace_with_svd(where,
left_inds=(ul, ll),
eps=1e-3,
method=method,
inplace=True,
ltags='_U',
rtags='_V')
tn.structure = None
x2 = tn ^ ...
# check ltags and rtags have gone in
assert isinstance(tn['_U'], Tensor)
assert isinstance(tn['_V'], Tensor)
assert_allclose(x1, x2, rtol=1e-4)
def test_can_change_data_using_subnetwork(self):
p = MPS_rand_state(3, 10)
pH = p.H
p.add_tag('__ket__')
pH.add_tag('__bra__')
tn = p | pH
assert_allclose((tn ^ ...), 1)
assert_allclose(tn[('__ket__', 'I1')].data,
tn[('__bra__', 'I1')].data.conj())
p[1].modify(data=np.random.randn(10, 10, 2))
assert abs((tn ^ ...) - 1) > 1e-13
assert not np.allclose(tn[('__ket__', 'I1')].data,
tn[('__bra__', 'I1')].data.conj())
def test_partition(self):
k = MPS_rand_state(10, 7, site_tag_id='Q{}', structure_bsz=4)
where = ['Q{}'.format(i) for i in range(10) if i % 2 == 1]
k.add_tag('odd', where=where, which='any')
tn_even, tn_odd = k.partition('odd')
assert len(tn_even.tensors) == len(tn_odd.tensors) == 5
assert tn_even.structure == 'Q{}'
assert tn_even.structure_bsz == 4
assert tn_odd.structure == 'Q{}'
assert tn_odd.structure_bsz == 4
assert (tn_even & tn_odd).sites == range(10)