def test_bloch_H_same(nx, ny, nz, dtype):
H = get_H()
b = Bloch([nx, ny, nz])
if dtype == np.complex64:
atol = 1e-6
else:
atol = 1e-8
HB = H.tile(nx, 0).tile(ny, 1).tile(nz, 2)
KX = [0, 0.1, 0.4358923]
KY = [0, 0.128359, -0.340925]
KZ = [0, 0.445]
for kx, ky, kz in product(KX, KY, KZ):
K = [kx, ky, kz]
k_unfold = b.unfold_points(K)
HK = [H.Hk(k, format='array', dtype=dtype) for k in k_unfold]
H_unfold = b.unfold(HK, k_unfold)
H_big = HB.Hk(K, format='array', dtype=dtype)
assert np.allclose(H_big, H_big.T.conj(), atol=atol)
assert np.allclose(H_unfold, H_unfold.T.conj(), atol=atol)
assert np.allclose(H_unfold, H_big, atol=atol)
def test_bloch_call():
b = Bloch([2] * 3)
H = get_H()
# Manual
k_unfold = b.unfold_points([0] * 3)
m = b.unfold([H.Hk(k, format='array') for k in k_unfold], k_unfold)
assert np.allclose(m, b(H.Hk, [0] * 3, format='array'))
def test_bloch_one_direction(nx, ny, nz):
H = get_H()
b = Bloch([nx, ny, nz])
HB = H.tile(nx, 0).tile(ny, 1).tile(nz, 2)
KX = [0, 0.1, 0.4358923]
KY = [0, 0.128359, -0.340925]
KZ = [0, 0.445]
for kx, ky, kz in product(KX, KY, KZ):
K = [kx, ky, kz]
k_unfold = b.unfold_points(K)
HK = [H.Hk(k, format='array') for k in k_unfold]
H_unfold = b.unfold(HK, k_unfold)
H_big = HB.Hk(K, format='array')
assert np.allclose(H_unfold, H_big)
def test_bloch_one_direction(nx, ny, nz, dtype):
H = get_H()
b = Bloch([nx, ny, nz])
if dtype == np.complex64:
atol = 1e-6
else:
atol = 1e-8
HB = H.tile(nx, 0).tile(ny, 1).tile(nz, 2)
KX = [0, 0.1, 0.4358923]
KY = [0, 0.128359, -0.340925]
KZ = [0, 0.445]
for kx, ky, kz in product(KX, KY, KZ):
K = [kx, ky, kz]
k_unfold = b.unfold_points(K)
HK = [H.Hk(k, format='array', dtype=dtype) for k in k_unfold]
H_unfold = b.unfold(np.stack(HK), k_unfold)
H_big = HB.Hk(K, format='array', dtype=dtype)
print(np.amax(np.absolute(H_unfold - H_big)))
assert np.allclose(H_unfold, H_big, atol=atol)
def test_sancho_bloch_zero_off_diag(setup):
# check whether the bloch-expansion with 0 transverse
# connections returns a block-diagonal matrix
H = setup.H.copy()
# disconnect transverse directions
H.set_nsc(b=1)
no = len(H)
SE = RecursiveSI(H, '+A')
for nb in [2, 4, 5]:
bloch = Bloch(1, nb, 1)
for E in [-0.1, 0.2, 0.4, -0.5]:
se = bloch(SE.self_energy, [0.2, 0.2, 0.2], E=E)
for b in range(1, nb):
off = b*no
assert np.allclose(se[:no, :no], se[off:off+no, off:off+no])
se[off:off+no, off:off+no] = 0.
se[:no, :no] = 0.
assert np.allclose(se, 0.)
def test_bloch_method():
b = Bloch([1] * 3)
assert 'Bloch' in str(b)
def test_bloch_create(nx, ny, nz):
b = Bloch([nx, ny, nz])
assert len(b) == nx * ny * nz
assert len(b.unfold_points([0] * 3)) == nx * ny * nz