sisl.io.vasp.locpotSileVASP

class sisl.io.vasp.locpotSileVASP(filename, *args, **kwargs)

Bases: carSileVASP

Electrostatic (or total) potential plus geometry

This file-object handles the electrostatic(total) potential from VASP

Plotting

`plot`	Plotting functions for the `locpotSileVASP` class.
`plot.geometry`([ret_dynamic, ...])	Calls `read_geometry` and creates a `GeometryPlot` from its output.
`plot.grid`([index, dtype, ...])	Calls `read_grid` and creates a `GridPlot` from its output.

Methods

`base_directory`([relative_to])	Retrieve the base directory of the file, relative to the path relative_to
`close`()
`dir_file`([filename, filename_base])	File of the current Sile
`geometry_group`(geometry[, ret_index])	Order atoms in geometry according to species such that all of one specie is consecutive
`read`(args, *kwargs)	Generic read method which should be overloaded in child-classes
`read_geometry`([ret_dynamic])	Returns Geometry object from this Sile
`read_grid`([index, dtype, units])	Reads the potential from the file and returns with a grid (plus geometry)
`read_lattice`()	Returns Lattice object from this Sile
`write`(args, *kwargs)	Generic write method which should be overloaded in child-classes
`write_geometry`(geometry[, dynamic, ...])	Writes the geometry to the contained file

Attributes

`base_file`	File of the current Sile
`file`	File of the current Sile

base_directory(relative_to='.'): Retrieve the base directory of the file, relative to the path relative_to

close()

dir_file(filename=None, filename_base=''): File of the current Sile

static geometry_group(geometry, ret_index=False)

Order atoms in geometry according to species such that all of one specie is consecutive

When creating VASP input files (poscarSileVASP for instance) the equivalent POTCAR file needs to contain the pseudos for each specie as they are provided in blocks.

I.e. for a geometry like this:

[Atom(6), Atom(4), Atom(6)]

the resulting POTCAR needs to contain the pseudo for Carbon twice.

This method will re-order atoms according to the species”

Parameters:

geometry (Geometry) – geometry to be re-ordered
ret_index (bool, optional) – return sorted indices

Returns:

geometry (Geometry) – reordered geometry

plot.geometry(ret_dynamic: bool = False, *, axes: Axes = ['x', 'y', 'z'], atoms: AtomsIndex = None, atoms_style: Sequence[AtomsStyleSpec] = [], atoms_scale: float = 1.0, atoms_colorscale: Colorscale | None = None, drawing_mode: Literal['scatter', 'balls', None] = None, bind_bonds_to_ats: bool = True, points_per_bond: int = 20, bonds_style: StyleSpec = {}, bonds_scale: float = 1.0, bonds_colorscale: Colorscale | None = None, show_atoms: bool = True, show_bonds: bool = True, show_cell: Literal['box', 'axes', False] = 'box', cell_style: StyleSpec = {}, nsc: tuple[int, int, int] = (1, 1, 1), atoms_ndim_scale: tuple[float, float, float] = (16, 16, 1), bonds_ndim_scale: tuple[float, float, float] = (1, 1, 10), dataaxis_1d: np.ndarray | Callable | None = None, arrows: Sequence[AtomArrowSpec] = (), backend='plotly') → GeometryPlot

Calls read_geometry and creates a GeometryPlot from its output.

Parameters:

ret_dynamic (bool, optional) – also return selective dynamics (if present), if not, None will be returned.
axes – The axes to project the geometry to.
atoms – The atoms to plot. If None, all atoms are plotted.
atoms_style – List of style specifications for the atoms. See the showcase notebooks for examples.
atoms_scale – Scaling factor for the size of all atoms.
atoms_colorscale – Colorscale to use for the atoms in case the color attribute is an array of values. If None, the default colorscale is used for each backend.
drawing_mode – The method used to draw the atoms.
bind_bonds_to_ats – Whether to display only bonds between atoms that are being displayed.
points_per_bond – When the points are drawn using points instead of lines (e.g. in some frameworks to draw multicolor bonds), the number of points used per bond.
bonds_style – Style specification for the bonds. See the showcase notebooks for examples.
bonds_scale – Scaling factor for the width of all bonds.
bonds_colorscale – Colorscale to use for the bonds in case the color attribute is an array of values. If None, the default colorscale is used for each backend.
show_atoms – Whether to display the atoms.
show_bonds – Whether to display the bonds.
show_cell – Mode to display the cell. If False, the cell is not displayed.
cell_style – Style specification for the cell. See the showcase notebooks for examples.
nsc – Number of unit cells to display in each direction.
atoms_ndim_scale – Scaling factor for the size of the atoms for different dimensionalities (1D, 2D, 3D).
bonds_ndim_scale – Scaling factor for the width of the bonds for different dimensionalities (1D, 2D, 3D).
dataaxis_1d – Only meaningful for 1D plots. The data to plot on the Y axis.
arrows – List of arrow specifications to display. See the showcase notebooks for examples.
backend – The backend to use to generate the figure.

See also

GeometryPlot: The plot class used to generate the plot.
read_geometry: The method called to get the data.

plot.grid(index=0, dtype=<class 'numpy.float64'>, units: UnitsVar = 'eV', *, data_kwargs={}, axes: Axes = ['z'], represent: Literal['real', 'imag', 'mod', 'phase', 'deg_phase', 'rad_phase'] = 'real', transforms: Sequence[Union[str, Callable]] = (), reduce_method: Literal['average', 'sum'] = 'average', boundary_mode: str = 'grid-wrap', nsc: tuple[int, int, int] = (1, 1, 1), interp: tuple[int, int, int] = (1, 1, 1), isos: Sequence[dict] = [], smooth: bool = False, colorscale: Optional[Colorscale] = None, crange: Optional[tuple[float, float]] = None, cmid: Optional[float] = None, show_cell: Literal['box', 'axes', False] = 'box', cell_style: dict = {}, x_range: Optional[Sequence[float]] = None, y_range: Optional[Sequence[float]] = None, z_range: Optional[Sequence[float]] = None, plot_geom: bool = False, geom_kwargs: dict = {}, backend: str = 'plotly') → GridPlot

Calls read_grid and creates a GridPlot from its output.

Parameters:

index (int or array_like, optional) – the index of the potential 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 total potential with the Cartesian directions equal to the potential for the magnetization directions. For array-like they refer to the fractional contributions for each corresponding index.
dtype (numpy.dtype, optional) – grid stored dtype
units – selects units in the returned data
spin (optional) – same as index argument. spin argument has precedence.
axes – The axes to project the grid to.
represent – The representation of the grid to plot.
transforms – List of transforms to apply to the grid before plotting.
reduce_method – The method used to reduce the grid axes that are not displayed.
boundary_mode – The method used to deal with the boundary conditions. Only used if the grid is to be orthogonalized. See scipy docs for more info on the possible values.
nsc – The number of unit cells to display in each direction.
interp – The interpolation factor to use for each axis to make the grid smoother.
isos – List of isosurfaces or isocontours to plot. See the showcase notebooks for examples.
smooth – Whether to ask the plotting backend to make an attempt at smoothing the grid display.
colorscale – Colorscale to use for the grid display in the 2D representation. If None, the default colorscale is used for each backend.
crange – Min and max values for the colorscale.
cmid – The value at which the colorscale is centered.
show_cell – Method used to display the unit cell. If False, the cell is not displayed.
cell_style – Style specification for the cell. See the showcase notebooks for examples.
x_range – The range of the x axis to take into account. Even if the X axis is not displayed! This is important because the reducing operation will only be applied on this range.
y_range – The range of the y axis to take into account. Even if the Y axis is not displayed! This is important because the reducing operation will only be applied on this range.
z_range – The range of the z axis to take into account. Even if the Z axis is not displayed! This is important because the reducing operation will only be applied on this range.
plot_geom – Whether to plot the associated geometry (if any).
geom_kwargs – Keyword arguments to pass to the geometry plot of the associated geometry.
backend – The backend to use to generate the figure.

See also

GridPlot: The plot class used to generate the plot.
read_grid: The method called to get the data.

read(*args, **kwargs)

Generic read method which should be overloaded in child-classes

Parameters:: kwargs – keyword arguments will try and search for the attribute read_<> and call it with the remaining **kwargs as arguments.

read_geometry(ret_dynamic: bool = False) → Geometry

Returns Geometry object from this Sile

Possibly also return the dynamics (if present).

Parameters:

ret_dynamic (bool, optional) – also return selective dynamics (if present), if not, None will be returned.

Returns:

Geometry – the contained geometry
numpy.ndarray – which Cartesian directions are allowed to move (only if ret_dynamic)

read_grid(index=0, dtype=np.float64, units: sisl.typing.UnitsVar = 'eV', **kwargs) → Grid[source]

Reads the potential from the file and returns with a grid (plus geometry)

Parameters:

index (int or array_like, optional) – the index of the potential 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 total potential with the Cartesian directions equal to the potential for the magnetization directions. For array-like they refer to the fractional contributions for each corresponding index.
dtype (numpy.dtype, optional) – grid stored dtype
units – selects units in the returned data
spin (optional) – same as index argument. spin argument has precedence.

Returns:

Grid – potential with associated geometry

read_lattice() → Lattice: Returns Lattice object from this Sile

write(*args, **kwargs)

Generic write method which should be overloaded in child-classes

Parameters:: **kwargs – keyword arguments will try and search for the attribute write_ and call it with the remaining **kwargs as arguments.

write_geometry(geometry: Geometry, dynamic=True, group_species: bool = False)

Writes the geometry to the contained file

Parameters:

geometry – geometry to be written to the file
dynamic (None, bool or list, optional) – define which atoms are dynamic in the VASP run (default is True, which means all atoms are dynamic). If None, the resulting file will not contain any dynamic flags
group_species – before writing geometry first re-order species to have species in consecutive blocks (see geometry_group)

Examples

>>> car = carSileVASP('POSCAR', 'w')
>>> geom = geom.graphene()
>>> geom.write(car) # regular car without Selective Dynamics
>>> geom.write(car, dynamic=False) # fix all atoms
>>> geom.write(car, dynamic=[False, (True, False, True)]) # fix 1st and y coordinate of 2nd