def test_params(lib, lattice, device, dtype):
gf = gauge(lattice, dtype=dtype, device=device)
dirac = gf.Dirac()
params = dirac.quda_params
assert dirac.precision == gf.precision
assert params.type == dirac.quda_type
assert params.kappa == dirac.kappa
assert params.m5 == dirac.m5
assert params.Ls == dirac.Ls
assert params.mu == dirac.mu
assert params.epsilon == dirac.epsilon
def test_zero(lib, lattice, device, gamma, dtype=None):
gf = gauge(lattice, dtype=dtype, device=device)
gf.gaussian()
dirac = gf.Dirac(kappa=0.01)
rhs = spinor(lattice, dtype=dtype, device=device, gamma_basis=gamma)
rhs.uniform()
mat = dirac.M
out = mat.solve(rhs)
res = mat(out)
res.field -= rhs.field
res = res.norm() / rhs.norm()
assert res < 1e-9
def test_zero(lib, lattice, device, dtype):
gf = gauge(lattice, dtype=dtype, device=device)
gf.zero()
assert (gf.field == 0).all()
assert gf.plaquette() == (0, 0, 0)
assert gf.topological_charge() == (0, (0, 0, 0))
assert gf.norm1() == 0
assert gf.norm2() == 0
assert gf.abs_max() == 0
assert gf.abs_min() == 0
assert gf.project() == 4 * np.prod(lattice)
gf.zero()
def test_unity(lib, lattice, procs, device, dtype):
comm = get_cart(procs)
gf = gauge(lattice, dtype=dtype, device=device, comm=comm)
gf.unity()
assert gf.norm1() == 3 * 4 * np.prod(lattice) * np.prod(procs)
assert gf.norm2() == 3 * 4 * np.prod(lattice) * np.prod(procs)
assert gf.abs_max() == 1
assert gf.abs_min() == 0
assert gf.project() == 0
assert gf.plaquette() == (1, 1, 1)
topo = gf.topological_charge()
assert np.isclose(topo[0], -3 / 4 / np.pi ** 2 * np.prod(lattice) * np.prod(procs))
assert topo[1] == (0, 0, 0)
def test_matrix(lib, lattice, device, dtype):
gf = gauge(lattice, dtype=dtype, device=device)
dirac = gf.Dirac()
matrix = dirac.M
assert matrix.key == "M"
assert "Wilson" in matrix.name
assert matrix.shift == 0
assert matrix.precision == get_precision(dtype)
assert matrix.flops == 0
assert matrix.hermitian == False
assert matrix.is_wilson == True
assert matrix.is_staggered == False
assert matrix.is_dwf == False
assert matrix.is_coarse == False
def test_unity(lib, lattice, device, dtype):
gf = gauge(lattice, dtype=dtype, device=device)
gf.unity()
assert gf.plaquette() == (1, 1, 1)
topo = gf.topological_charge()
assert np.isclose(topo[0], -3 / 4 / np.pi**2 * np.prod(lattice))
assert topo[1] == (0, 0, 0)
assert gf.norm1() == 3 * 4 * np.prod(lattice)
assert gf.norm2() == 3 * 4 * np.prod(lattice)
assert gf.norm1() == 3 * 4 * np.prod(lattice)
assert gf.norm2() == 3 * 4 * np.prod(lattice)
assert gf.abs_max() == 1
assert gf.abs_min() == 0
assert gf.project() == 0
assert np.allclose(gf.plaquette_field().trace(), 3)
assert np.allclose(gf.rectangle_field().trace(), 3)
def test_params(lib, lattice, device, dtype):
gf = gauge(lattice, dtype=dtype, device=device)
params = gf.quda_params
assert gf.is_native()
assert params.nColor == 3
assert params.nFace == 0
assert params.reconstruct == gf.quda_reconstruct
assert params.location == gf.quda_location
assert params.order == gf.quda_order
assert params.t_boundary == gf.quda_t_boundary
assert params.link_type == gf.quda_link_type
assert params.geometry == gf.quda_geometry
assert addressof(params.gauge) == gf.ptr
assert params.Precision() == gf.quda_precision
assert params.nDim == gf.ndims
assert tuple(params.x)[:gf.ndims] == gf.dims
assert params.pad == gf.pad
assert params.ghostExchange == gf.quda_ghost_exchange
def test_zero(lib, lattice, device, gamma, dtype=None):
gf = gauge(lattice, dtype=dtype, device=device)
gf.zero()
sf = spinor(lattice, dtype=dtype, device=device, gamma_basis=gamma)
sf.uniform()
kappa = random()
dirac = gf.Dirac(kappa=kappa)
assert (dirac.M(sf).field == sf.field).all()
assert (dirac.Mdag(sf).field == sf.field).all()
assert (dirac.MdagM(sf).field == sf.field).all()
assert (dirac.MMdag(sf).field == sf.field).all()
mu = random()
dirac = gf.Dirac(kappa=kappa, mu=mu)
sfmu = (2 * kappa * mu) * 1j * sf.gamma5().field
assert np.allclose(dirac.M(sf).field, sf.field + sfmu)
assert np.allclose(dirac.Mdag(sf).field, sf.field - sfmu)
assert np.allclose(
dirac.MdagM(sf).field, (1 + (2 * kappa * mu)**2) * sf.field)
assert np.allclose(
dirac.MMdag(sf).field, (1 + (2 * kappa * mu)**2) * sf.field)
def test_random(lib, lattice, device, dtype):
gf = gauge(lattice, dtype=dtype, device=device)
gf.gaussian()
assert np.allclose(gf.plaquette()[0],
gf.plaquette_field().trace().mean() / 3)
def test_default(lattice):
gf = gauge(lattice)
assert gf.location == "CUDA"
assert gf.reconstruct == "NO"
assert gf.geometry == "VECTOR"
