def test_z4_z2_u1_compute(self):
ndim = 10
sign_array = np.random.randint(0, 2, ndim)
sign_map = {0: "+", 1: "-"}
pattern = "".join([sign_map[ix] for ix in sign_array])
na = np.random.randint(0, 10, ndim)
z4arrs = [Z4(n) for n in na]
z4out = Z4._compute(pattern, z4arrs)
z2arrs = [Z2(n) for n in na]
z2out = Z2._compute(pattern, z2arrs)
u1arrs = [U1(n) for n in na]
u1out = U1._compute(pattern, u1arrs)
z4outn = 0
z2outn = 0
u1outn = 0
for p, n in zip(sign_array, na):
if p == 0:
z4outn += n
z2outn += n
u1outn += n
else:
z4outn -= n
z2outn -= n
u1outn -= n
assert z4out.n == z4outn % 4
assert z2out.n == z2outn % 2
assert u1out.n == u1outn
def setUp(self):
bond = BondInfo({Z2(0):5, Z2(1):7})
self.bond = bond
self.T = rand((bond,)*4, pattern="++--", dq=Z2(1))
self.symmetry = Z2
self.skeleton_test_dq = Z2(1)
self.contract_test_dq = (Z2(0),Z2(1))
self.svd_dq_iterator = [Z2(0), Z2(1)]
self.shift = Z2(0)
self.T1 = rand((bond,)*4, pattern="++--", dq=Z2(0))
def test_z4_z2_u1_flat(self):
for z in range(-10, 10):
z4a = Z4(z)
z4b = Z4.from_flat(z4a.to_flat())
assert z4a == z4b
z2a = Z2(z)
z2b = Z2.from_flat(z2a.to_flat())
assert z2a == z2b
u1a = U1(z)
u1b = U1.from_flat(u1a.to_flat())
assert u1a == u1b
def test_z4_z2_u1_numerics(self):
for za in range(-10, 10):
z4a = Z4(za)
z2a = Z2(za)
u1a = U1(za)
for zb in range(-5, 5):
z4b = Z4(zb)
z2b = Z2(zb)
u1b = U1(zb)
z4_add = z4a + z4b
z2_add = z2a + z2b
u1_add = u1a + u1b
assert z4_add.n == (za + zb) % 4
assert z2_add.n == (za + zb) % 2
assert u1_add.n == (za + zb)
z4_sub = z4a - z4b
z2_sub = z2a - z2b
u1_sub = u1a - u1b
assert z4_sub.n == (za - zb) % 4
assert z2_sub.n == (za - zb) % 2
assert u1_sub.n == (za - zb)
def test_z4_z2_compute_flat(self):
nblks = 30
ndim = 5
sign_array = np.random.randint(0, 2, ndim)
sign_map = {0: "+", 1: "-"}
pattern = "".join([sign_map[ix] for ix in sign_array])
na = np.random.randint(0, 10, nblks * ndim).reshape(nblks, ndim)
z4lsts = [[Z4(na[nb, nd]) for nd in range(ndim)]
for nb in range(nblks)]
z4arrs = [[z4lsts[nb][nd].to_flat() for nd in range(ndim)]
for nb in range(nblks)]
z4arrs = np.asarray(z4arrs, dtype=int)
z4out = Z4._compute(pattern, z4arrs)
z4neg = Z4._compute(pattern, z4arrs, offset=("+", Z4(3)), neg=True)
z2lsts = [[Z2(na[nb, nd]) for nd in range(ndim)]
for nb in range(nblks)]
z2arrs = [[z2lsts[nb][nd].to_flat() for nd in range(ndim)]
for nb in range(nblks)]
z2arrs = np.asarray(z2arrs, dtype=int)
z2out = Z2._compute(pattern, z2arrs)
z2neg = Z2._compute(pattern, z2arrs, offset=("-", Z2(1)), neg=True)
u1lsts = [[U1(na[nb, nd]) for nd in range(ndim)]
for nb in range(nblks)]
u1arrs = [[u1lsts[nb][nd].to_flat() for nd in range(ndim)]
for nb in range(nblks)]
u1arrs = np.asarray(u1arrs, dtype=int)
u1out = U1._compute(pattern, u1arrs)
u1neg = U1._compute(pattern, u1arrs, offset=("-", U1(1)), neg=True)
for i in range(nblks):
z4outa = Z4._compute(pattern, z4lsts[i])
z4outb = Z4.from_flat(z4out[i])
assert z4outa == z4outb
assert -(z4outa + Z4(3)) == Z4.from_flat(z4neg[i])
z2outa = Z2._compute(pattern, z2lsts[i])
z2outb = Z2.from_flat(z2out[i])
assert z2outa == z2outb
assert -(z2outa - Z2(1)) == Z2.from_flat(z2neg[i])
u1outa = U1._compute(pattern, u1lsts[i])
u1outb = U1.from_flat(u1out[i])
assert u1outa == u1outb
assert -(u1outa - U1(1)) == U1.from_flat(u1neg[i])
def setUp(self):
self.t = 2
self.U = 4
self.tau = 0.1
self.mu = 0.2
self.symmetry = Z2
states = np.zeros([2, 2])
states[0, 0] = .5 ** .5
blocks = [SubTensor(reduced=states, q_labels=(Z2(0), Z2(1))), # 0+
SubTensor(reduced=states, q_labels=(Z2(1), Z2(0)))] # +0, eigenstate of hopping
self.hop_psi = SparseFermionTensor(blocks=blocks, pattern="++")
blocks = []
states = np.zeros([2, 2])
states[1, 0] = .5
blocks = [SubTensor(reduced=states, q_labels=(Z2(0), Z2(0))),
SubTensor(reduced=states.T, q_labels=(Z2(0), Z2(0))),
SubTensor(reduced=-states.T, q_labels=(Z2(1), Z2(1))),
SubTensor(reduced=states, q_labels=(Z2(1), Z2(1)))]
self.hop_exp_psi = SparseFermionTensor(blocks=blocks, pattern="++")
psi0 = SparseFermionTensor(blocks=[SubTensor(reduced=np.asarray([1,0]), q_labels=(Z2(0),))], pattern="+")
psi1 = SparseFermionTensor(blocks=[SubTensor(reduced=np.asarray([1,0]), q_labels=(Z2(1),))], pattern="+")
psi2 = SparseFermionTensor(blocks=[SubTensor(reduced=np.asarray([0,1]), q_labels=(Z2(1),))], pattern="+")
psi3 = SparseFermionTensor(blocks=[SubTensor(reduced=np.asarray([0,1]), q_labels=(Z2(0),))], pattern="+")
self.psi_array = [psi0, psi1, psi2, psi3]
self.sz_array = [0,1,-1,0]
self.pn_array = [0,1,1,2]
bond = BondInfo({Z2(0):2, Z2(1):2})
self.psi = SparseFermionTensor.random((bond,)*2, pattern="++", dq=Z2(0))
self.fac = (0.5, 0.3)