sisl.io.siesta.stdoutSileSiesta

class sisl.io.siesta.stdoutSileSiesta(filename, *args, **kwargs)

Bases: SileSiesta

Output file from Siesta

This enables reading the output quantities from the Siesta output.

Plotting

plot

Plotting functions for the stdoutSileSiesta class.

plot.geometry([skip_input, ...])

Calls read_geometry and creates a GeometryPlot from its output.

Methods

base_directory([relative_to])

Retrieve the base directory of the file, relative to the path relative_to

close()

completed()

True if the full file has been read and "Job completed" was found.

dir_file([filename, filename_base])

File of the current Sile

read(*args, **kwargs)

Generic read method which should be overloaded in child-classes

read_basis()

Reads the basis as found in the output file

read_charge(name[, iscf, imd, key_scf, ...])

Read charges calculated in SCF loop or MD loop (or both)

read_data(*args, **kwargs)

Read specific content in the Siesta out file

read_energy()

Reads the final energy distribution

read_force([total, max, key, skip_final])

Reads the forces from the Siesta output file

read_geometry([skip_input])

Reads the geometry from the Siesta output file

read_moment([orbitals, quantity])

Reads the moments from the Siesta output file

read_scf([key, iscf, as_dataframe, ret_header])

Parse SCF information and return a table of SCF information depending on what is requested

read_stress([key, skip_final])

Reads the stresses from the Siesta output file

write(*args, **kwargs)

Generic write method which should be overloaded in child-classes

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()
completed()[source]

True if the full file has been read and “Job completed” was found.

dir_file(filename=None, filename_base='')

File of the current Sile

plot.geometry(skip_input: bool = True, *, 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:

  • skip_input – the input geometry may be contained as a print-out. This is not part of an MD calculation, and hence is by default not 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.

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_basis() → Atoms[source]

Reads the basis as found in the output file

This parses 3 things:

  1. At the start of the file there are some initatom output specifying which species in the calculation.

  2. Reading the <basis_specs> entries for the masses

  3. Reading the PAO.Basis block output for orbital information

read_charge(name: Literal['voronoi', 'hirshfeld', 'mulliken', 'mulliken:<5.2'], iscf=Opt.ANY, imd=Opt.ANY, key_scf: str = 'scf', as_dataframe: bool = False)[source]

Read charges calculated in SCF loop or MD loop (or both)

Siesta enables many different modes of writing out charges.

The below table shows a list of different cases that may be encountered, the letters are referred to in the return section to indicate what is returned.

Case

A

B

C

D

E

Charge

MD

SCF

MD+SCF

Final

Orbital resolved

Voronoi

Hirshfeld
Mulliken

(>=5.2)
Mulliken

<5.2

(+)

Notes

Errors will be raised if one requests information not present. I.e. passing an integer or Opt.ALL for iscf will raise an error if the SCF charges are not present. For Opt.ANY it will return the most information, effectively SCF will be returned if present.

Currently orbitally-resolved Mulliken is not implemented, any help in reading this would be very welcome.

Parameters:

  • name – the name of the charges that you want to read

  • iscf (int or Opt, optional) – index (0-based) of the scf iteration you want the charges for. If the enum specifier Opt.ANY or Opt.ALL are used, then the returned quantities depend on what is present. If None/Opt.NONE it will not return any SCF charges. If both imd and iscf are None then only the final charges will be returned.

  • imd (int or Opt, optional) – index (0-based) of the md step you want the charges for. If the enum specifier Opt.ANY or Opt.ALL are used, then the returned quantities depend on what is present. If None/Opt.NONE it will not return any MD charges. If both imd and iscf are None then only the final charges will be returned.

  • key_scf – the key lookup for the scf iterations (a “:” will automatically be appended)

  • as_dataframe – whether charges should be returned as a pandas dataframe.

Returns:

  • numpy.ndarray – if a specific MD+SCF index is requested (or special cases where output is not complete)

  • list of numpy.ndarray – if iscf or imd is different from None/Opt.NONE.

  • pandas.DataFrame – if as_dataframe is requested. The dataframe will have multi-indices if multiple SCF or MD steps are requested.

read_data(*args, **kwargs) → Any[source]

Read specific content in the Siesta out file

The currently implemented things are denoted in the parameters list. Note that the returned quantities are in the order of keywords, so:

>>> read_data(geometry=True, force=True)
<geometry>, <force>
>>> read_data(force=True, geometry=True)
<force>, <geometry>
Parameters:

  • geometry (bool, optional) – read geometry, args are passed to read_geometry

  • force (bool, optional) – read force, args are passed to read_force

  • stress (bool, optional) – read stress, args are passed to read_stress

  • moment (bool, optional) – read moment, args are passed to read_moment (only for spin-orbit calculations)

  • energy (bool, optional) – read final energies, args are passed to read_energy

read_energy() → PropertyDict[source]

Reads the final energy distribution

Currently the energies translated are:

band

band structure energy

kinetic

electronic kinetic energy

hartree

electronic electrostatic Hartree energy

dftu

DFT+U energy

spin_orbit

spin-orbit energy

extE

external field energy

xc

exchange-correlation energy

exchange

exchange energy

correlation

correlation energy

bulkV

bulk-bias correction energy

total

total energy

negf

NEGF energy

fermi

Fermi energy

ion.electron

ion-electron interaction energy

ion.ion

ion-ion interaction energy

ion.kinetic

kinetic ion energy

basis.enthalpy

enthalpy of basis sets, Free + p_basis*V_orbitals

Any unrecognized key gets added as is.

Examples

>>> energies = sisl.get_sile("RUN.out").read_energy()
>>> ion_energies = energies.ion
>>> ion_energies.ion # ion-ion interaction energy
>>> ion_energies.kinetic # ion kinetic energy
>>> energies.fermi # fermi energy
Returns:

PropertyDict (dictionary like lookup table ionic energies are stored in a nested `PropertyDict at the key ion (all energies in eV)`)

read_force(total: bool = False, max: bool = False, key: Literal['siesta', 'ts'] = 'siesta', skip_final: bool | None = None)[source]

Reads the forces from the Siesta output file

Parameters:

  • total – return the total forces instead of the atomic forces.

  • max – whether only the maximum atomic force should be returned for each step.

    Setting it to True is equivalent to max(outSile.read_force()) in case atomic forces are written in the output file (WriteForces .true. in the fdf file)

    Note that this is not the same as doing max(outSile.read_force(total=True)) since the forces returned in that case are averages on each axis.

  • key – Specifies the indicator string for the forces that are to be read. The function will look for a line containing f'{key}: Atomic forces' to start reading forces.

  • skip_final – the final output of the forces is duplicated when the final output is written. By default, this method will return the final forces, but only if no other forces are found. If forces from dynamics are found, then the final forces will not be returned, unless explicitly requested through this flag.

Returns:

numpy.ndarray or None – returns None if the forces are not found in the output, otherwise forces will be returned

The shape of the array will be different depending on the type of forces requested:

  • atomic (default): (nMDsteps, nAtoms, 3)

  • total: (nMDsteps, 3)

  • max: (nMDsteps, )

If total and max are both True, they are returned separately as a tuple: (total, max)

Notes

This method defaults to return the first item(s).

This method enables slicing for handling multiple values (see [...|default]).

This is an optional handler enabling returning multiple elements if read_force[...|0] allows this.

>>> single = obj.read_force() # returns the default entry of read_force[...|0]

To retrieve the first two elements that read_force will return

>>> first_two = obj.read_force[:2]()

Retrieving the last two is done equivalently:

>>> last_two = obj.read_force[-2:]()

While one can store the sliced function tmp = obj.read_force[:] one will loose the slice after each call.

read_geometry(skip_input: bool = True) → Geometry[source]

Reads the geometry from the Siesta output file

Parameters:

skip_input – the input geometry may be contained as a print-out. This is not part of an MD calculation, and hence is by default not returned.

Returns:

geometries (list or Geometry or None) – if all is False only one geometry will be returned (or None). Otherwise a list of geometries corresponding to the MD-runs.

Notes

This method defaults to return the first item(s).

This method enables slicing for handling multiple values (see [...|default]).

This is an optional handler enabling returning multiple elements if read_geometry[...|0] allows this.

>>> single = obj.read_geometry() # returns the default entry of read_geometry[...|0]

To retrieve the first two elements that read_geometry will return

>>> first_two = obj.read_geometry[:2]()

Retrieving the last two is done equivalently:

>>> last_two = obj.read_geometry[-2:]()

While one can store the sliced function tmp = obj.read_geometry[:] one will loose the slice after each call.

read_moment(orbitals: bool = False, quantity: Literal['S', 'L'] = 'S') → ndarray[source]

Reads the moments from the Siesta output file

These will only be present in case of spin-orbit coupling.

Parameters:

  • orbitals – return a table with orbitally resolved moments.

  • quantity – return the spin-moments or the L moments

Notes

This method defaults to return the first item(s).

This method enables slicing for handling multiple values (see [...|default]).

This is an optional handler enabling returning multiple elements if read_moment[...|0] allows this.

>>> single = obj.read_moment() # returns the default entry of read_moment[...|0]

To retrieve the first two elements that read_moment will return

>>> first_two = obj.read_moment[:2]()

Retrieving the last two is done equivalently:

>>> last_two = obj.read_moment[-2:]()

While one can store the sliced function tmp = obj.read_moment[:] one will loose the slice after each call.

read_scf(key: str = 'scf', iscf: int | None = -1, as_dataframe: bool = False, ret_header: bool = False)[source]

Parse SCF information and return a table of SCF information depending on what is requested

Parameters:

  • key ({'scf', 'ts-scf'}) – parse SCF information from Siesta SCF or TranSiesta SCF

  • iscf – which SCF cycle should be stored. If -1 only the final SCF step is stored, for None all SCF cycles are returned. When iscf values queried are not found they will be truncated to the nearest SCF step.

  • as_dataframe – whether the information should be returned as a pandas.DataFrame. The advantage of this format is that everything is indexed and therefore you know what each value means.You can also perform operations very easily on a dataframe.

  • ret_header – whether to also return the headers that define each value in the returned array, will have no effect if as_dataframe is true.

Notes

This method defaults to return the last item(s).

This method enables slicing for handling multiple values (see [...|default]).

This is an optional handler enabling returning multiple elements if read_scf[...|-1] allows this.

>>> single = obj.read_scf() # returns the default entry of read_scf[...|-1]

To retrieve the first two elements that read_scf will return

>>> first_two = obj.read_scf[:2]()

Retrieving the last two is done equivalently:

>>> last_two = obj.read_scf[-2:]()

While one can store the sliced function tmp = obj.read_scf[:] one will loose the slice after each call.

read_stress(key: Literal['static', 'total', 'Voigt'] = 'static', skip_final: bool | None = None) → ndarray[source]

Reads the stresses from the Siesta output file

Parameters:

  • key – which stress to read from the output.

  • skip_final – the final output of the stress is duplicated when the final output is written. By default, this method will return the final stress, but only if no other stresses are found. If stresses from dynamics are found, then the final stress will not be returned, unless explicitly requested through this flag.

Returns:

numpy.ndarray or None – returns None if the stresses are not found in the output, otherwise stresses will be returned

Notes

This method defaults to return the first item(s).

This method enables slicing for handling multiple values (see [...|default]).

This is an optional handler enabling returning multiple elements if read_stress[...|0] allows this.

>>> single = obj.read_stress() # returns the default entry of read_stress[...|0]

To retrieve the first two elements that read_stress will return

>>> first_two = obj.read_stress[:2]()

Retrieving the last two is done equivalently:

>>> last_two = obj.read_stress[-2:]()

While one can store the sliced function tmp = obj.read_stress[:] one will loose the slice after each call.

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.

property base_file

File of the current Sile

property file

File of the current Sile

plot

Plotting functions for the stdoutSileSiesta class.