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.

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
`write`(args, *kwargs)	Generic write method which should be overloaded in child-classes
`base_file`	File of the current Sile
`file`	File of the current Sile
`plot`	Handles all plotting possibilities for a class
`read_force`
`read_geometry`
`read_moment`
`read_scf`
`read_stress`

__init__(filename, mode='r', *args, **kwargs): Just to pass away the args and kwargs

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

property base_file: File of the current Sile

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

property file: File of the current Sile

plot: Handles all plotting possibilities for a class

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:

At the start of the file there are some initatom output specifying which species in the calculation.
Reading the <basis_specs> entries for the masses
Reading the PAO.Basis block output for orbital information

Return type:: Atoms

read_charge(name, iscf=<Opt.ANY: 2>, imd=<Opt.ANY: 2>, key_scf='scf', as_dataframe=False)[source]

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

Siesta enables many different modes of writing out charges.

NOTE: currently Mulliken charges are not implemented.

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

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 Mulliken is not implemented, any help in reading this would be very welcome.

Parameters:

name ({"voronoi", "hirshfeld"}) – 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 (str, optional) – the key lookup for the scf iterations (a “:” will automatically be appended)
as_dataframe (boolean, optional) – 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 one both 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)[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
Return type:: dictionary like lookup table ionic energies are stored in a nested PropertyDict at the key ion (all energies in eV)

read_force = <sisl.io._multiple.SileBound object>[source]

Parameters:

total (bool)
max (bool)
key (str)

read_geometry = <sisl.io._multiple.SileBound object>[source]

Parameters:: skip_input (bool)
Return type:: Geometry

read_moment = <sisl.io._multiple.SileBound object>[source]

Return type:: ndarray

read_scf = <sisl.io._multiple.SileBound object>[source]

Parameters:

key (str)
iscf (int | None)
as_dataframe (bool)
ret_header (bool)

read_stress = <sisl.io._multiple.SileBound object>[source]

Parameters:

key (str)
skip_final (bool)

Return type:

ndarray

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.