def read_grid(self, spin=0, *args, **kwargs):
""" Read grid contained in the Grid file
Parameters
----------
spin : int or array_like, optional
the spin-index for retrieving one of the components. If a vector
is passed it refers to the fraction per indexed component. I.e.
``[0.5, 0.5]`` will return sum of half the first two components.
Default to the first component.
"""
# Read the sizes
nspin, mesh = _siesta.read_grid_sizes(self.file)
# Read the cell and grid
cell = _siesta.read_grid_cell(self.file)
grid = _siesta.read_grid(self.file, nspin, mesh[0], mesh[1], mesh[2])
if isinstance(spin, Integral):
grid = grid[:, :, :, spin]
else:
if len(spin) > grid.shape[0]:
raise ValueError(self.__class__.__name__ + '.read_grid requires spin to be an integer or '
'an array of length equal to the number of spin components.')
g = grid[:, :, :, 0] * spin[0]
for i, scale in enumerate(spin[1:]):
g += grid[:, :, :, 1+i] * scale
grid = g
cell = np.array(cell.T, np.float64)
cell.shape = (3, 3)
g = Grid(mesh, sc=SuperCell(cell), dtype=np.float32)
g.grid = np.array(grid.swapaxes(0, 2), np.float32) * self.grid_unit
return g
def __init__(self):
bond = 1.42
sq3h = 3.**.5 * 0.5
self.sc = SuperCell(
np.array([[1.5, sq3h, 0.], [1.5, -sq3h, 0.], [0., 0., 10.]],
np.float64) * bond,
nsc=[3, 3, 1])
C = Atom(Z=6, R=[bond * 1.01] * 2)
self.g = Geometry(
np.array([[0., 0., 0.], [1., 0., 0.]], np.float64) * bond,
atoms=C,
sc=self.sc)
self.grid = Grid(0.2, geometry=self.g)
self.grid.grid[:, :, :] = np.random.rand(*self.grid.shape)
self.mol = Geometry([[i, 0, 0] for i in range(10)], sc=[50])
self.grid_mol = Grid(0.2, geometry=self.mol)
self.grid_mol.grid[:, :, :] = np.random.rand(*self.grid_mol.shape)
def sg_g(**kwargs):
kwargs['ret_grid'] = True
if 'grid' not in kwargs:
kwargs['grid'] = self.grid
return sgrid(**kwargs)
self.sg_g = sg_g
def sg_mol(**kwargs):
kwargs['ret_grid'] = True
if 'grid' not in kwargs:
kwargs['grid'] = self.grid_mol
return sgrid(**kwargs)
self.sg_mol = sg_mol
def read_grid(self, name='gridfunc', idx=0, *args, **kwargs):
""" Reads a grid in the current SIESTA.grid.nc file
Enables the reading and processing of the grids created by SIESTA
"""
# Swap as we swap back in the end
sc = self.read_supercell().swapaxes(0, 2)
# Create the grid
nx = len(self._dimension('n1'))
ny = len(self._dimension('n2'))
nz = len(self._dimension('n3'))
if name is None:
v = self._variable('gridfunc')
else:
v = self._variable(name)
# Create the grid, SIESTA uses periodic, always
grid = Grid([nz, ny, nx], bc=Grid.Periodic, sc=sc,
dtype=v.dtype)
if len(v.shape) == 3:
grid.grid[:, :, :] = v[:, :, :]
else:
grid.grid[:, :, :] = v[idx, :, :, :]
# Read the grid, we want the z-axis to be the fastest
# looping direction, hence x,y,z == 0,1,2
return grid.swapaxes(0, 2)
def test_default(sisl_tmp):
f = sisl_tmp('GRID.xsf', _dir)
print(f)
grid = Grid(0.2)
grid.grid = np.random.rand(*grid.shape)
grid.write(f)
assert grid.geometry is None
def test_imaginary(sisl_tmp):
f = sisl_tmp('GRID.xsf', _dir)
geom = Geometry(np.random.rand(10, 3), np.random.randint(1, 70, 10), sc=[10, 10, 10, 45, 60, 90])
grid = Grid(0.2, geometry=geom, dtype=np.complex128)
grid.grid = np.random.rand(*grid.shape) + 1j*np.random.rand(*grid.shape)
grid.write(f)
assert not grid.geometry is None
def read_grid(self):
""" Returns `Grid` object from the CUBE file """
geom = self.read_geom()
# Now seek behind to read grid sizes
self.fh.seek(0)
# Skip headers and origo
self.readline()
self.readline()
na = int(self.readline().split()[0])
ngrid = [0] * 3
for i in [0, 1, 2]:
tmp = self.readline().split()
ngrid[i] = int(tmp[0])
# Read past the atoms
for i in range(na):
self.readline()
grid = Grid(ngrid, dtype=np.float32, geom=geom)
grid.grid = np.loadtxt(self.fh, dtype=grid.dtype)
grid.grid.shape = ngrid
return grid
def read_grid(self):
""" Returns `Grid` object from the CUBE file """
geom = self.read_geom()
# Now seek behind to read grid sizes
self.fh.seek(0)
# Skip headers and origo
self.readline()
self.readline()
na = int(self.readline().split()[0])
ngrid = [0] * 3
for i in [0, 1, 2]:
tmp = self.readline().split()
ngrid[i] = int(tmp[0])
# Read past the atoms
for i in range(na):
self.readline()
grid = Grid(ngrid, dtype=np.float32, geom=geom)
grid.grid = np.loadtxt(self.fh, dtype=grid.dtype)
grid.grid.shape = ngrid
return grid
def test_read_write_grid(self, sisl_tmp, sisl_system, sile):
g = sisl_system.g.rotate(-30, sisl_system.g.cell[2, :])
G = Grid([10, 11, 12])
G[:, :, :] = np.random.rand(10, 11, 12)
f = sisl_tmp("test_read_write_grid.win", _dir)
# Write
try:
with sile(f, mode="w") as s:
s.write_grid(G)
except SileError:
with sile(f, mode="wb") as s:
s.write_grid(G)
# Read 1
try:
with sile(f, mode="r") as s:
g = s.read_grid()
assert np.allclose(g.grid, G.grid, atol=1e-5)
except UnicodeDecodeError as e:
pass
# Read 2
try:
with sile(f, mode='r') as s:
g = Grid.read(s)
assert np.allclose(g.grid, G.grid, atol=1e-5)
except UnicodeDecodeError as e:
pass
def read_grid(self, name='gridfunc', idx=0, *args, **kwargs):
""" Reads a grid in the current SIESTA.grid.nc file
Enables the reading and processing of the grids created by SIESTA
"""
# Swap as we swap back in the end
sc = self.read_sc().swapaxes(0, 2)
# Create the grid
nx = len(self._dimension('n1'))
ny = len(self._dimension('n2'))
nz = len(self._dimension('n3'))
if name is None:
v = self._variable('gridfunc')
else:
v = self._variable(name)
# Create the grid, SIESTA uses periodic, always
grid = Grid([nz, ny, nx], bc=Grid.Periodic, sc=sc,
dtype=v.dtype)
if len(v[:].shape) == 3:
grid.grid = v[:, :, :]
else:
grid.grid = v[idx, :, :, :]
# Read the grid, we want the z-axis to be the fastest
# looping direction, hence x,y,z == 0,1,2
return grid.swapaxes(0, 2)
def setUp(self):
alat = 1.42
sq3h = 3.**.5 * 0.5
self.sc = SuperCell(np.array(
[[1.5, sq3h, 0.], [1.5, -sq3h, 0.], [0., 0., 10.]], np.float64) *
alat,
nsc=[3, 3, 1])
self.g = Grid([10, 10, 100], sc=self.sc)
def test_iadd1(self):
g = Grid([10, 10, 10])
g.fill(1)
old = g.copy()
g += g
g -= old
assert np.allclose(g.grid, 1)
g -= g
assert np.allclose(g.grid, 0)
class t():
def __init__(self):
alat = 1.42
sq3h = 3.**.5 * 0.5
self.sc = SuperCell(np.array([[1.5, sq3h, 0.],
[1.5, -sq3h, 0.],
[0., 0., 10.]], np.float64) * alat, nsc=[3, 3, 1])
self.g = Grid([10, 10, 100], sc=self.sc)
self.g.fill(2.)
def test_wavefunction1():
N = 50
o1 = SphericalOrbital(0, (np.linspace(0, 2, N), np.exp(-np.linspace(0, 100, N))))
G = Geometry([[1] * 3, [2] * 3], Atom(6, o1), sc=[4, 4, 4])
H = Hamiltonian(G)
R, param = [0.1, 1.5], [1., 0.1]
H.construct([R, param])
ES = H.eigenstate(dtype=np.float64)
# Plot in the full thing
grid = Grid(0.1, geometry=H.geom)
grid.fill(0.)
ES.sub(0).wavefunction(grid)
def test_smooth_gaussian(self, setup):
g = Grid(0.1, sc=[[2, 0, 0], [0, 2, 0], [0, 0, 2]])
g[10, 10, 10] = 1
# With a sigma of 0.3 Ang, that single value should be propagated
# to the whole grid
smoothed = g.smooth(r=0.7, truncate=4)
assert not np.any(smoothed.grid == 0)
# With a sigma of 0.2 Ang, borders should be still 0
smoothed = g.smooth(r=0.1, truncate=4)
assert np.any(smoothed.grid == 0)
def test_grid_tile_sc():
grid = Grid([4, 5, 6])
grid2 = grid.tile(2, 2)
assert grid.shape[:2] == grid2.shape[:2]
assert grid.shape[2] == grid2.shape[2] // 2
assert grid.volume * 2 == pytest.approx(grid2.volume)
grid4 = grid2.tile(2, 1)
assert grid.shape[0] == grid4.shape[0]
assert grid.shape[1] == grid4.shape[1] // 2
assert grid.shape[2] == grid4.shape[2] // 2
assert grid.volume * 4 == pytest.approx(grid4.volume)
def test_smooth_uniform(self, setup):
g = Grid(0.1, sc=[[2, 0, 0], [0, 2, 0], [0, 0, 2]])
g[10, 10, 10] = 1
# With a radius of 0.7 Ang, that single value should be propagated
# to the whole grid
smoothed = g.smooth(r=1., method='uniform')
assert not np.any(smoothed.grid == 0)
# With a sigma of 0.1 Ang, borders should still be 0
smoothed = g.smooth(r=0.9, method='uniform')
assert np.any(smoothed.grid == 0)
def test_wavefunction2():
N = 50
o1 = SphericalOrbital(0, (np.linspace(0, 2, N), np.exp(-np.linspace(0, 100, N))))
G = Geometry([[1] * 3, [2] * 3], Atom(6, o1), sc=[4, 4, 4])
H = Hamiltonian(G)
R, param = [0.1, 1.5], [1., 0.1]
H.construct([R, param])
ES = H.eigenstate(dtype=np.float64)
# This is effectively plotting outside where no atoms exists
# (there could however still be psi weight).
grid = Grid(0.1, sc=SuperCell([2, 2, 2], origo=[2] * 3))
grid.fill(0.)
ES.sub(0).wavefunction(grid)
def test_wavefunction_eta():
N = 50
o1 = SphericalOrbital(0, (np.linspace(0, 2, N), np.exp(-np.linspace(0, 100, N))))
G = Geometry([[1] * 3, [2] * 3], Atom(6, o1), sc=[4, 4, 4])
H = Hamiltonian(G, spin=Spin('nc'))
R, param = [0.1, 1.5], [[0., 0., 0.1, -0.1],
[1., 1., 0.1, -0.1]]
H.construct([R, param])
ES = H.eigenstate()
# Plot in the full thing
grid = Grid(0.1, dtype=np.complex128, sc=SuperCell([2, 2, 2], origo=[-1] * 3))
grid.fill(0.)
ES.sub(0).wavefunction(grid, eta=True)
def test_grid_tile_geom():
grid = Grid([4, 5, 6], geometry=Geometry([0] * 3, Atom[4], sc=4.))
grid2 = grid.tile(2, 2)
assert grid.shape[:2] == grid2.shape[:2]
assert grid.shape[2] == grid2.shape[2] // 2
assert grid.volume * 2 == pytest.approx(grid2.volume)
assert grid.geometry.na * 2 == grid2.geometry.na
grid4 = grid2.tile(2, 1)
assert grid.shape[0] == grid4.shape[0]
assert grid.shape[1] == grid4.shape[1] // 2
assert grid.shape[2] == grid4.shape[2] // 2
assert grid.volume * 4 == pytest.approx(grid4.volume)
assert grid.geometry.na * 4 == grid4.geometry.na
def read_grid(self, index=0, dtype=np.float64, *args, **kwargs):
""" Read grid contained in the Grid file
Parameters
----------
index : int or array_like, optional
the spin-index for retrieving one of the components. If a vector
is passed it refers to the fraction per indexed component. I.e.
``[0.5, 0.5]`` will return sum of half the first two components.
Default to the first component.
dtype : numpy.float64, optional
default data-type precision
"""
index = kwargs.get('spin', index)
# Read the sizes and cell
nspin, mesh = self.read_grid_size()
cell = _siesta.read_grid_cell(self.file)
_bin_check(self, 'read_grid', 'could not read grid cell.')
grid = _siesta.read_grid(self.file, nspin, mesh[0], mesh[1], mesh[2])
_bin_check(self, 'read_grid', 'could not read grid.')
if isinstance(index, Integral):
grid = grid[:, :, :, index]
else:
if len(index) > grid.shape[0]:
raise ValueError(
self.__class__.__name__ +
'.read_grid requires spin to be an integer or '
'an array of length equal to the number of spin components.'
)
# It is F-contiguous, hence the last index
g = grid[:, :, :, 0] * index[0]
for i, scale in enumerate(index[1:]):
g += grid[:, :, :, 1 + i] * scale
grid = g
cell = np.array(cell.T, np.float64)
cell.shape = (3, 3)
# Simply create the grid (with no information)
# We will overwrite the actual grid
g = Grid([1, 1, 1], sc=SuperCell(cell))
# NOTE: there is no need to swap-axes since the returned array is in F ordering
# and thus the first axis is the fast (x, y, z) is retained
g.grid = (grid * self.grid_unit).astype(dtype=dtype,
order='C',
copy=False)
return g
def setUp(self):
alat = 1.42
sq3h = 3.**.5 * 0.5
self.sc = SuperCell(np.array([[1.5, sq3h, 0.],
[1.5, -sq3h, 0.],
[0., 0., 10.]], np.float64) * alat, nsc=[3, 3, 1])
self.g = Grid([10, 10, 100], sc=self.sc)
def test_isosurface_non_orthogonal(self, setup):
pytest.importorskip("skimage", reason="scikit-image not available")
# If the grid is non-orthogonal, there should be 20 unique values
# (10 for each (HERE), see test_isosurface_orthogonal)
grid = Grid(0.1, sc=[[1, 0, 0], [0, 1, 0], [0, 2, 1]])
grid.grid = np.tile([1, 2, 3, 4, 5, 4, 3, 2, 1, 0],
100).reshape(10, 10, 10)
verts, *returns = grid.isosurface(2.5)
# we have twice as many since the 3rd lattice vector has components in y
assert np.unique(verts[:, 1]).shape == (20, )
assert np.unique(verts[:, 2]).shape == (2, )
def test_rho2(self, setup):
bond = 1.42
sq3h = 3.**.5 * 0.5
sc = SuperCell(np.array(
[[1.5, sq3h, 0.], [1.5, -sq3h, 0.], [0., 0., 10.]], np.float64) *
bond,
nsc=[3, 3, 1])
n = 60
rf = np.linspace(0, bond * 1.01, n)
rf = (rf, rf)
orb = SphericalOrbital(1, rf, 2.)
C = Atom(6, orb)
g = Geometry(np.array([[0., 0., 0.], [1., 0., 0.]], np.float64) * bond,
atom=C,
sc=sc)
D = DensityMatrix(g)
D.construct([[0.1, bond + 0.01], [1., 0.1]])
grid = Grid(0.2, geometry=D.geom)
D.density(grid)
D = DensityMatrix(g, spin=Spin('P'))
D.construct([[0.1, bond + 0.01], [(1., 0.5), (0.1, 0.1)]])
grid = Grid(0.2, geometry=D.geom)
D.density(grid)
D.density(grid, [1., -1])
D.density(grid, 0)
D.density(grid, 1)
D = DensityMatrix(g, spin=Spin('NC'))
D.construct([[0.1, bond + 0.01],
[(1., 0.5, 0.01, 0.01), (0.1, 0.1, 0.1, 0.1)]])
grid = Grid(0.2, geometry=D.geom)
D.density(grid)
D.density(grid, [[1., 0.], [0., -1]])
D = DensityMatrix(g, spin=Spin('SO'))
D.construct([[0.1, bond + 0.01],
[(1., 0.5, 0.01, 0.01, 0.01, 0.01, 0., 0.),
(0.1, 0.1, 0.1, 0.1, 0., 0., 0., 0.)]])
grid = Grid(0.2, geometry=D.geom)
D.density(grid)
D.density(grid, [[1., 0.], [0., -1]])
D.density(grid, Spin.X)
D.density(grid, Spin.Y)
D.density(grid, Spin.Z)
def read_grid(self, *args, **kwargs):
""" Reads the TranSiesta potential input grid """
# Create the grid
na = len(self._dimension('a'))
nb = len(self._dimension('b'))
nc = len(self._dimension('c'))
v = self._variable('V')
# Create the grid, Siesta uses periodic, always
grid = Grid([nc, nb, na], bc=Grid.PERIODIC, dtype=v.dtype)
grid.grid[:, :, :] = v[:, :, :] / eV2Ry
# Read the grid, we want the z-axis to be the fastest
# looping direction, hence x,y,z == 0,1,2
return grid.swapaxes(0, 2)
def test_isosurface_orthogonal(self, setup):
pytest.importorskip("skimage", reason="scikit-image not available")
# Build an empty grid
grid = Grid(0.1, sc=[[1, 0, 0], [0, 1, 0], [0, 0, 1]])
# Fill it with some values that have a clear isosurface
grid.grid = np.tile([1, 2, 3, 4, 5, 4, 3, 2, 1, 0],
100).reshape(10, 10, 10)
# Calculate the isosurface for the value of 2.5
verts, *returns = grid.isosurface(2.5)
# The third dimension should contain only two coordinates
# [1, 2, (HERE) 3, 4, 5, 4, 3, (HERE) 2, 1, 0]
assert np.unique(verts[:, 1]).shape == (10, )
assert np.unique(verts[:, 2]).shape == (2, )
def read_grid(self, index=0, dtype=np.float64):
""" Reads the charge density from the file and returns with a grid (plus geometry)
Parameters
----------
index : int, optional
the index of the grid to read. For a spin-polarized VASP calculation 0 and 1 are
allowed, UP/DOWN. For non-collinear 0, 1, 2 or 3 is allowed which equals,
TOTAL, x, y, z charge density with the Cartesian directions equal to the charge
magnetization.
dtype : numpy.dtype, optional
grid stored dtype
Returns
-------
Grid : charge density grid with associated geometry
"""
geom = self.read_geometry()
V = geom.sc.volume
# Now we are past the cell and geometry
# We can now read the size of CHGCAR
self.readline()
nx, ny, nz = list(map(int, self.readline().split()))
n = nx * ny * nz
i = 0
vals = []
while i < n * (index + 1):
dat = [float(l) for l in self.readline().split()]
vals.append(dat)
i += len(dat)
vals = np.swapaxes(np.array(vals).reshape(nz, ny, nx), 0, 2)
vals = vals[index * n:(index + 1) * n] / V
# Create the grid with data
# Since we populate the grid data afterwards there
# is no need to create a bigger grid than necessary.
grid = Grid([1, 1, 1], dtype=dtype, geometry=geom)
grid.grid = vals
return grid
def test_read_write_grid(self, sisl_tmp, sisl_system, sile):
g = sisl_system.g.rotatec(-30)
G = Grid([10, 11, 12])
G[:, :, :] = np.random.rand(10, 11, 12)
f = sisl_tmp('test_read_write_grid.win', _dir)
# Write
try:
sile(f, mode='w').write_grid(G)
except SileError:
sile(f, mode='wb').write_grid(G)
# Read 1
try:
g = sile(f, mode='r').read_grid()
assert np.allclose(g.grid, G.grid, atol=1e-5)
except UnicodeDecodeError as e:
pass
# Read 2
try:
g = Grid.read(sile(f, mode='r'))
assert np.allclose(g.grid, G.grid, atol=1e-5)
except UnicodeDecodeError as e:
pass
def test_default_size(sisl_tmp):
f = sisl_tmp('GRID.cube', _dir)
grid = Grid(0.2, sc=2.0)
grid.grid = np.random.rand(*grid.shape)
grid.write(f)
read = grid.read(f)
assert np.allclose(grid.grid, read.grid)
assert grid.geometry is None
assert len(read.geometry) == 1
def test_geometry(sisl_tmp):
f = sisl_tmp('GRID.cube', _dir)
geom = Geometry(np.random.rand(10, 3), np.random.randint(1, 70, 10), sc=[10, 10, 10, 45, 60, 90])
grid = Grid(0.2, geometry=geom)
grid.grid = np.random.rand(*grid.shape)
grid.write(f)
read = grid.read(f)
assert np.allclose(grid.grid, read.grid)
assert not grid.geometry is None
assert not read.geometry is None
assert grid.geometry == read.geometry
def test_rho_fail_nc(self, setup):
bond = 1.42
sq3h = 3.**.5 * 0.5
sc = SuperCell(np.array([[1.5, sq3h, 0.],
[1.5, -sq3h, 0.],
[0., 0., 10.]], np.float64) * bond, nsc=[3, 3, 1])
n = 60
rf = np.linspace(0, bond * 1.01, n)
rf = (rf, rf)
orb = SphericalOrbital(1, rf, 2.)
C = Atom(6, orb)
g = Geometry(np.array([[0., 0., 0.],
[1., 0., 0.]], np.float64) * bond,
atoms=C, sc=sc)
D = DensityMatrix(g, spin=Spin('NC'))
D.construct([[0.1, bond + 0.01], [(1., 0.5, 0.01, 0.01), (0.1, 0.1, 0.1, 0.1)]])
grid = Grid(0.2, geometry=D.geometry)
with pytest.raises(ValueError):
D.density(grid, [1., 0.])
def read_grid(self, name, idx=0):
""" Reads a grid in the current SIESTA.nc file
Enables the reading and processing of the grids created by SIESTA
"""
# Swap as we swap back in the end
geom = self.read_geom().swapaxes(0, 2)
# Shorthand
g = self.groups['GRID']
# Create the grid
nx = len(g.dimensions['nx'])
ny = len(g.dimensions['ny'])
nz = len(g.dimensions['nz'])
# Shorthand variable name
v = g.variables[name]
# Create the grid, SIESTA uses periodic, always
grid = Grid([nz, ny, nx], bc=Grid.Periodic, dtype=v.dtype)
if len(v[:].shape) == 3:
grid.grid = v[:, :, :]
else:
grid.grid = v[idx, :, :, :]
try:
u = v.unit
if u == 'Ry':
# Convert to ev
grid *= Ry2eV
except:
# Simply, we have no units
pass
# Read the grid, we want the z-axis to be the fastest
# looping direction, hence x,y,z == 0,1,2
grid = grid.swapaxes(0, 2)
grid.set_geom(geom)
return grid
def read_grid(self, name, idx=0):
""" Reads a grid in the current SIESTA.nc file
Enables the reading and processing of the grids created by SIESTA
"""
# Swap as we swap back in the end
geom = self.read_geom().swapaxes(0, 2)
# Shorthand
g = self.groups['GRID']
# Create the grid
nx = len(g.dimensions['nx'])
ny = len(g.dimensions['ny'])
nz = len(g.dimensions['nz'])
# Shorthand variable name
v = g.variables[name]
# Create the grid, SIESTA uses periodic, always
grid = Grid([nz, ny, nx], bc=Grid.Periodic, dtype=v.dtype)
if len(v[:].shape) == 3:
grid.grid = v[:, :, :]
else:
grid.grid = v[idx, :, :, :]
try:
u = v.unit
if u == 'Ry':
# Convert to ev
grid *= Ry2eV
except:
# Simply, we have no units
pass
# Read the grid, we want the z-axis to be the fastest
# looping direction, hence x,y,z == 0,1,2
grid = grid.swapaxes(0, 2)
grid.set_geom(geom)
return grid
def read_grid(self, name, spin=0, **kwargs):
""" Reads a grid in the current Siesta.nc file
Enables the reading and processing of the grids created by Siesta
Parameters
----------
name : str
name of the grid variable to read
spin : int or array_like, optional
the spin-index for retrieving one of the components. If a vector
is passed it refers to the fraction per indexed component. I.e.
``[0.5, 0.5]`` will return sum of half the first two components.
Default to the first component.
"""
spin = kwargs.get('index', spin)
geom = self.read_geometry()
# Shorthand
g = self.groups['GRID']
# Create the grid
nx = len(g.dimensions['nx'])
ny = len(g.dimensions['ny'])
nz = len(g.dimensions['nz'])
# Shorthand variable name
v = g.variables[name]
# Create the grid, Siesta uses periodic, always
grid = Grid([nz, ny, nx],
bc=Grid.PERIODIC,
geometry=geom,
dtype=v.dtype)
# Unit-conversion
BohrC2AngC = Bohr2Ang**3
unit = {
'Rho': 1. / BohrC2AngC,
'RhoInit': 1. / BohrC2AngC,
'RhoTot': 1. / BohrC2AngC,
'RhoDelta': 1. / BohrC2AngC,
'RhoXC': 1. / BohrC2AngC,
'RhoBader': 1. / BohrC2AngC,
'Chlocal': 1. / BohrC2AngC,
}.get(name, 1.)
if len(v[:].shape) == 3:
grid.grid = v[:, :, :] * unit
elif isinstance(spin, Integral):
grid.grid = v[spin, :, :, :] * unit
else:
if len(spin) > v.shape[0]:
raise SileError(
self.__class__.__name__ +
'.read_grid requires spin to be an integer or '
'an array of length equal to the number of spin components.'
)
grid.grid[:, :, :] = v[0, :, :, :] * (spin[0] * unit)
for i, scale in enumerate(spin[1:]):
grid.grid[:, :, :] += v[1 + i, :, :, :] * (scale * unit)
try:
if v.unit == 'Ry':
# Convert to ev
grid *= Ry2eV
except:
# Allowed pass due to pythonic reading
pass
# Read the grid, we want the z-axis to be the fastest
# looping direction, hence x,y,z == 0,1,2
grid.grid = np.copy(np.swapaxes(grid.grid, 0, 2), order='C')
return grid
def test_rho_smaller_grid1(self, setup):
D = setup.D.copy()
D.construct(setup.func)
sc = setup.D.geom.cell.copy() / 2
grid = Grid(0.2, geometry=setup.D.geom.copy(), sc=sc)
D.density(grid)
class TestGrid(object):
def setUp(self):
alat = 1.42
sq3h = 3.**.5 * 0.5
self.sc = SuperCell(np.array([[1.5, sq3h, 0.],
[1.5, -sq3h, 0.],
[0., 0., 10.]], np.float64) * alat, nsc=[3, 3, 1])
self.g = Grid([10, 10, 100], sc=self.sc)
def tearDown(self):
del self.sc
del self.g
def test_append(self):
g = self.g.append(self.g, 0)
assert_true(np.allclose(g.grid.shape, [20, 10, 100]))
g = self.g.append(self.g, 1)
assert_true(np.allclose(g.grid.shape, [10, 20, 100]))
g = self.g.append(self.g, 2)
assert_true(np.allclose(g.grid.shape, [10, 10, 200]))
def test_size(self):
assert_true(np.allclose(self.g.grid.shape, [10, 10, 100]))
def test_item(self):
assert_true(np.allclose(self.g[1:2, 1:2, 2:3], self.g.grid[1:2, 1:2, 2:3]))
def test_dcell(self):
assert_true(np.all(self.g.dcell*self.g.cell >= 0))
def test_dvol(self):
assert_true(self.g.dvol > 0)
def test_shape(self):
assert_true(np.all(self.g.shape == self.g.grid.shape))
def test_dtype(self):
assert_true(self.g.dtype == self.g.grid.dtype)
def test_copy(self):
assert_true(self.g.copy() == self.g)
def test_swapaxes(self):
g = self.g.swapaxes(0, 1)
assert_true(np.allclose(self.g.cell[0,:], g.cell[1,:]))
assert_true(np.allclose(self.g.cell[1,:], g.cell[0,:]))
def test_interp(self):
shape = np.array(self.g.shape, np.int32)
g = self.g.interp(shape * 2)
g1 = g.interp(shape)
assert_true(np.allclose(self.g.grid, g1.grid))
def test_index1(self):
mid = np.array(self.g.shape, np.int32) // 2
idx = self.g.index(self.sc.center())
print(mid, idx)
assert_true(np.all(mid == idx))
def test_sum(self):
for i in range(3):
assert_true(self.g.sum(i).shape[i] == 1)
def test_mean(self):
for i in range(3):
assert_true(self.g.mean(i).shape[i] == 1)
def test_cross_section(self):
for i in range(3):
assert_true(self.g.cross_section(1, i).shape[i] == 1)
def test_remove_part(self):
for i in range(3):
assert_true(self.g.remove_part(1, i, above=True).shape[i] == 1)
def test_sub_part(self):
for i in range(3):
assert_true(self.g.sub_part(1, i, above=False).shape[i] == 1)
def test_sub(self):
for i in range(3):
assert_true(self.g.sub(1, i).shape[i] == 1)
for i in range(3):
assert_true(self.g.sub([1,2], i).shape[i] == 2)
def test_remove(self):
for i in range(3):
assert_true(self.g.remove(1, i).shape[i] == self.g.shape[i]-1)
for i in range(3):
assert_true(self.g.remove([1,2], i).shape[i] == self.g.shape[i]-2)
def test_argumentparser(self):
self.g.ArgumentParser()
