BigDFT.InputActions module

Actions to define on the Input parameters.

This module defines some of the most common actions that a BigDFT user might like to perform on the input file. Such module therefore sets some of the keys of the input dictionary to the values needed to perform the operations. Users might also inspire to the actions performed in order to customize the runs in a different way. All the functions of this module have as first argument inp, the dictionary of the input parameters.

Many other actions are available in BigDFT code. This module only regroups the most common. Any of these functionalities might be removed from the input file by the remove() function.

Note

Any of the action of this module, including the remove() function, can be also applied to an instance of the BigDFT.Inputfiles.Inputfile class, by removing the first argument (inp). This adds extra flexibility as the same method may be used to a dictionary instance or to a BigDFT input files. See the example Example.

We now list the available methods, in order of category.

Basic Setup and common functionalities

`set_xc`(inp[, xc])	Set the exchange and correlation approximation
`set_hgrid`(inp[, hgrids])	Set the wavelet grid spacing.
`set_rmult`(inp[, rmult, coarse, fine])	Set the wavelet grid extension by modifying the multiplicative radii.
`set_mesh_sizes`(inp[, ngrids])	Constrain the number of grid points in each direction.
`optimize_geometry`(inp[, method, nsteps, ...])	Optimize the geometry of the system
`spin_polarize`(inp[, mpol])	Add a collinear spin polarization to the system.
`charge`(inp[, charge])	Charge the system
`charge_and_polarize`(inp)	Charge the system by removing one electron. Assume that the original
`set_symmetry`(inp[, yes])	Set the symmetry detection for the charge density and the ionic forces and stressdef set_symmetry(inp,yes=True):
`apply_electric_field`(inp[, elecfield])	Apply an external electric field on the system
`add_empty_scf_orbitals`(inp[, norbs])	Insert `norbs` empty orbitals in the scf procedure
`extract_virtual_states`(inp[, nvirt, ...])	Extract a given number of empty states after the scf cycle.
`set_electronic_temperature`(inp[, kT, T])	Define the electronic temperature, in AU (`kT`) or K (`T`)
`set_implicit_solvent`(inp[, itermax, minres, ...])	Add an implicit solvent around the system with the
`set_dispersion_correction`(inp)	Add Grimme's D3 correction to the energy and the forces

Self-Consistent-Field setup and algorithms

`set_scf_convergence`(inp[, gnrm, rpnrm])	Set the tolerance acceptance level for stopping the self-consistent iterations.
`set_random_inputguess`(inp)	Input orbitals are initialized as random coefficients
`set_linear_scaling`(inp)	Activates the linear scaling mode
`set_scf_method`(inp[, method, mixing_on, ...])	Set the algorithm for scf.
`set_kernel_guess`(inp[, mode])	Method for guessing the kernel at restart.
`set_ntpoly`(inp[, thresh_dens, conv_dens, ...])	In the linear scaling mode, use NTPoly as the solver.
`optimize_kernel`(inp[, method, ...])	Methods for scf of the density kernel.
`optimize_coefficients`(inp[, nit, gnrm])	Methods for scf of the kernel coefficients.
`optimize_support_functions`(inp[, nit, gnrm, ...])	Methods for scf of the Support functions.

Input-Output and restart

`write_orbitals_on_disk`(inp[, format])	Set the code to write the orbitals on disk in the provided format
`read_orbitals_from_disk`(inp[, mode])	Read the orbitals from data directory, if available.
`write_density_on_disk`(inp)	Write the charge density on the disk after the last scf convergence
`change_data_directory`(inp[, name])	Modify the name of the `data-` directory.
`connect_run_data`(inp[, log])	Associate the data of the run of a given logfile to the input by retrieving the data directory name of the logfile.
`write_support_function_matrices`(inp[, format])	Write the matrices of the linear scaling formats.
`write_cubefiles_around_fermi_level`(inp[, nplot])	Writes the `nplot` orbitals around the fermi level in cube format.
`write_support_functions_on_disk`(inp[, format])	Dump the support functions.

Post-Processing and other functionalities

`calculate_dipole`(inp)	Extract the dipole moment from the total charge density.
`calculate_pdos`(inp)	Calculate the Partial Density of states.
`calculate_tddft_coupling_matrix`(inp[, tda, ...])	Perform a Casida TDDFT coupling matrix extraction.
`calculate_multipoles`(inp[, yes])	Calculate the multipoles on the atoms based on SF.
`add_cdft_constraint`(inp[, constraint, ...])	Include a cdft constraint into the SCF cycle.

Setting atomic-based information and other functionalities

`set_atomic_positions`(inp[, posinp])	Insert the atomic positions as a part of the input dictionary
`use_gpu_acceleration`(inp[, flavour])	Employ gpu acceleration when available, for convolutions and Fock operator
`set_orbital_occupancy`(inp[, avg, up, down, ...])	Control the occupation number of the KS orbitals.
`set_external_potential`(inp, mm_pot)	Set the external potential to which the system is submitted outside the QM region
`set_kpt_mesh`(inp, method, *[, ngkpt, kptrlen])	Set the K-point mesh.
`set_psp_directory`(inp[, directory, elements])	Employs all the "psppar.*" files of the given directory as pseudopotentials
`set_psp_file`(inp[, filename, element])	Employ the given PSP file for the provided element
`set_psp_nlcc`(inp[, elements])	Employed the built in Non Linear Core Correction (NLCC) pseudopotentials.
`load`(inp[, profile, profiles])	Load a profile or list of profiles.
`remove`(inp, action)	Remove action from the input dictionary.

Note

Each of the actions here must have default value for the arguments (except the input dictionary inp). This is needed for a good behaviour of the function remove.

We list here the extended documentation in alphabetic order.

remove(inp, action)[source]

Remove action from the input dictionary.

Remove an action from the input file, thereby restoring the default value, as if the action were not specified.

Parameters:

inp (dict) – dictionary to remove the action from.
action (func) – one of the actions of this module. It does not need to be
before (specified) –
effect. (in which case it produces no) –

Example

>>> from Calculators import SystemCalculator as C
>>> code=C()
>>> inp={}
>>> set_xc(inp,'PBE')
>>> write_orbitals_on_disk(inp)
>>> log=code.run(input=inp) # perform calculations
>>> remove(inp, write_orbitals_on_disk) #remove the action
>>> read_orbitals_from_disk(inp)
>>> # this will restart the scf from the previous orbitals
>>> log2=code.run(input=inp)

set_hgrid(inp, hgrids=0.4)[source]

Set the wavelet grid spacing.

Parameters:

hgrid (float,list) – list of the grid spacings in the three directions.
scalar (It might also be a) –
spacing (which implies the same) –

set_scf_convergence(inp, gnrm='default', rpnrm='default')[source]

Set the tolerance acceptance level for stopping the self-consistent iterations. Useful both for LS and CS

Parameters:

gnrm (float) – the tolerance level for the CS inner loop
rpnrm (float) – residue for the density/or potential norm. Useful both for CS and LS

set_rmult(inp, rmult=None, coarse=5.0, fine=8.0)[source]

Set the wavelet grid extension by modifying the multiplicative radii.

Parameters:

rmult (float,list) – list of two values that have to be used for the coarse and the fine resolution grid. It may also be a scalar.
coarse (float) – if the argument rmult is not provided it sets the coarse radius multiplier
fine (float) – if the argument rmult is not provided it sets the fine radius multiplier

set_symmetry(inp, yes=True)[source]

Set the symmetry detection for the charge density and the ionic forces and stressdef set_symmetry(inp,yes=True):

Parameters:: yes (bool) – If False the symmetry detection is disabled

set_linear_scaling(inp)[source]: Activates the linear scaling mode

set_ntpoly(inp, thresh_dens=1e-06, conv_dens=0.0001, thresh_ovlp=1e-07, conv_ovlp=0.0001)[source]

In the linear scaling mode, use NTPoly as the solver.

Parameters:

thresh_dens (float) – the threshold for filtering sparse matrices
density. (when solving for the) –
thresh_ovlp (float) – the threshold for filtering sparse matrices
inverse. (when solving for the overlap) –
conv_dens (float) – the energy value to consider the density converged.
conv_ovlp (float) – the value (in terms of norm) to consider the
converged. (overlap matrix) –
solver (int) – which solver to use; (1) TRS4, (2) TRS2,
eigensolver ((3) Dense) –

set_mesh_sizes(inp, ngrids=64)[source]

Constrain the number of grid points in each direction. This is useful when performing periodic system calculations with variable cells which need to be compared each other. In this way the number of degrees of freedom is kept constant throughout the various simuilations.

Parameters:: ngrids (int,list) – list of the number of mesh points in each direction. Might be a scalar.

spin_polarize(inp, mpol=1)[source]

Add a collinear spin polarization to the system.

Parameters:: mpol (int) – spin polarization in Bohr magneton units.

charge(inp, charge=- 1)[source]

Charge the system

Parameters:: charge (int,float) – value of the charge in units of e (the electron has charge -1). Also accept floating point numbers.

apply_electric_field(inp, elecfield=[0, 0, 0.001])[source]

Apply an external electric field on the system

Parameters:: electric (list, float) – Values of the Electric Field in the three directions. Might also be a scalar.

charge_and_polarize(inp)[source]

Charge the system by removing one electron. Assume that the original: system is closed shell, thus polarize.

set_scf_method(inp, method='dirmin', mixing_on='density', mixing_scheme='Pulay')[source]

Set the algorithm for scf.

Parameters:

method (str) – The algoritm chosen. Might be different for the cubic (CS) or linear scaling (LS) algorithm. * dirmin: Direct minimization approach (only CS) * mixing: Mixing scheme (only CS) * hybrid: outer loop of the LS mode * two_levels: two level of accuracy in the scf
mixing_on (str) – May be "density" or "potential" in the "mixing" case, decide to which quantity the mixing to be performed
mixing_scheme (str) –
May be:
- Pulay : DIIS mixing on the last 7 iterations
- Simple: Simple mixing
- Anderson: Anderson scheme
- Anderson2: Anderson scheme based on the two pervious iterations
- CG: Conjugate Gradient based on the minimum of the energy with
  respect of the potential

Warning

Only the FOE method exhibit asymptotic linear scaling regime.

Todo

Check if the linear scaling case needs another input variable for the mixing of the potential (density)

add_empty_scf_orbitals(inp, norbs=10)[source]

Insert norbs empty orbitals in the scf procedure

Parameters:: norbs (int) – Number of empty orbitals

Warning

In linear scaling case, this is only meaningful for the direct minimization approach.

write_cubefiles_around_fermi_level(inp, nplot=1)[source]

Writes the nplot orbitals around the fermi level in cube format.

Parameters:: nplot (int) – the number of orbitals to print around the fermi level.

Warning

This would work only for the cubic scaling code at present.

write_orbitals_on_disk(inp, format='binary')[source]

Set the code to write the orbitals on disk in the provided format

Parameters:: format (str) – The format to write the orbitals with. Accepts the strings: * ‘binary’ * ‘text’ * ‘etsf’ (requires etsf-io enabled)

Todo

Verify if this option works for a linear scaling calulation.

write_support_functions_on_disk(inp, format='text')[source]

Dump the support functions.

Write the support function which are expressed in wavelet basis in the code as files at the end of the calculation.

Parameters:: format (str) – the format of the data, can be ‘text’, ‘ETSF’ or ‘binary’ or one of the allowed codes of the output_wf key.

write_support_function_matrices(inp, format='text')[source]

Write the matrices of the linear scaling formats.

Parameters:

format (str) –

The format to write the orbitals with. Accepts the strings:

’binary’

’text’

’text_serial’

Todo

Verify if the binary format is available and set the appropriate values

set_atomic_positions(inp, posinp=None)[source]: Insert the atomic positions as a part of the input dictionary

read_orbitals_from_disk(inp, mode='cubic')[source]

Read the orbitals from data directory, if available.

Parameters:: mode (str) – can be ‘cubic’ or ‘linear’. In the first case, orbitals are read as KS objects, whereas in the second kernel (or coeffs) and support functions are expressed.

set_kernel_guess(inp, mode='kernel')[source]

Method for guessing the kernel at restart.

Parameters:: mode (str) – Guessing method. Can be: * kernel * coefficients * random * diag * weight * ao * full_kernel * full_coefficients

set_random_inputguess(inp)[source]: Input orbitals are initialized as random coefficients

set_electronic_temperature(inp, kT=0.001, T=0)[source]: Define the electronic temperature, in AU (kT) or K (T)

optimize_geometry(inp, method='FIRE', nsteps=50, betax=4.0, frac_fluct=1.0, forcemax=0)[source]

Optimize the geometry of the system

Parameters:

nsteps (int) – maximum number of atomic steps.
method (str) –
Geometry optimizer. Available keys:
- SDCG: A combination of Steepest Descent and Conjugate Gradient
- VSSD: Variable Stepsize Steepest Descent method
- LBFGS: Limited-memory BFGS
- BFGS: Broyden-Fletcher-Goldfarb-Shanno
- PBFGS: Same as BFGS with an initial Hessian from a force field
- DIIS: Direct inversion of iterative subspace
- FIRE: Fast Inertial Relaxation Engine, described by Bitzek et al.
- SQNM: Stabilized quasi-Newton minimzer
betax (float) – the step size for the optimization method. This stepsize is system dependent and it has therefore to be determined for each system.
frac_fluct (float) – Fraction of force fluctuations. Stop if fmax < forces_fluct*frac_fluct.
forcemax (float) – Max forces criterion when stop.

set_xc(inp, xc='PBE')[source]

Set the exchange and correlation approximation

Parameters:: xc (str) – the Acronym of the XC approximation

Todo

Insert the XC codes corresponding to libXC conventions

write_density_on_disk(inp)[source]: Write the charge density on the disk after the last scf convergence

use_gpu_acceleration(inp, flavour='CUDA')[source]

Employ gpu acceleration when available, for convolutions and Fock operator

Parameters:: flavour (str) – can be CUDA or OCL. In one case it activates aceleration for the convolutions (useful for dense electronic systems with many k-points). CUDA is an acceleration useful for exact exchange calculations.

set_scf_iterations(inp, nit=[50, 1])[source]

Set the number of the iteration per loop

Parameters:: nit (int,list) – integer of the number of iterations. Might be a scalar or a list, up to length two. The first element of the list contains the number of iterations of the direct minimization loop. if nit is a scalar, only this contribution is taken into account. The second element is the number of subspace iterations where the hamiltonian is diagonalized in the subspace. For a LS calculation, the number of iteration correspond to the levels of the outer loop.

change_data_directory(inp, name='')[source]

Modify the name of the data- directory. Useful to grab the orbitals from another directory than the run name

Parameters:: name (str) – the name of the run

calculate_tddft_coupling_matrix(inp, tda=False, rpa=True, fxc=True)[source]

Perform a Casida TDDFT coupling matrix extraction.

Parameters:

tda (bool) – when True, Tamm-Dancoff approximation is used for the extraction of the coupling matrix
rpa (bool) – when False, the calculation of the RPA term (the linear response of the hartree potential) is switched off
fxc (bool) – when False, the calculation of the fxc term (the linear response of the XC operator) is switched off.

Note

The arguments fxc and rpa should not be simultaneously False.

Warning

Presently the LR-TDDFT casida fxc is only available for LDA functionals in ABINIT flavour.

extract_virtual_states(inp, nvirt=8, davidson=False, norbv=None, itermax_virt=150)[source]

Extract a given number of empty states after the scf cycle.

Parameters:

davidson (bool) – If set to True activates davidson calculation, otherwise Trace Minimization of the Hamiltonian is employed.
norbv (int) – Defines the total size of the virtual subspace, which may be larger than nvirt.

connect_run_data(inp, log=None)[source]

Associate the data of the run of a given logfile to the input by retrieving the data directory name of the logfile.

Parameters:: log (Logfile) – instance of a Logfile class

calculate_dipole(inp)[source]: Extract the dipole moment from the total charge density.

Note

This function is useful for the linear scaling setup as the cubic scaling approach always calculates the charge density multipoles.

set_external_potential(inp, mm_pot)[source]

Set the external potential to which the system is submitted outside the QM region

Parameters:: mm_pot (dict) – dictionary of the external potential which contains the information on the counter-ions

set_kpt_mesh(inp, method, *, ngkpt=None, kptrlen=None)[source]

Set the K-point mesh.

Parameters:

method (str) – K-point sampling method (auto, mpgrid, manual).
ngkpt (list) – list of three integers describing number of Monkhorst-Pack grid points (requires method=mpgrid).
kptrlen (int) – Equivalent length (bohr) of K-space resolution (requires method=auto).

set_implicit_solvent(inp, itermax=20, minres=0.0001, solvent='water')[source]

Add an implicit solvent around the system with the: soft-sphere cavity method

Parameters:

itermax (int) – maximum number of iteration of the Generalized Poisson Solver
minres (float) – minimum residue of the CG method to achieve GPS convergence
solvent (str) – solvent environment. Currently only water, ethanol and
parametrized (mesitylene are available and) –

set_dispersion_correction(inp)[source]: Add Grimme’s D3 correction to the energy and the forces

Warning

Only works with Free Boundary conditions

set_psp_file(inp, filename=None, element=None)[source]

Employ the given PSP file for the provided element

Parameters:

filename (str) – the path of the psp file
element (str) – the element symbol for the PSP. Employs the psp name if absent

set_psp_directory(inp, directory='.', elements=None)[source]

Employs all the “psppar.*” files of the given directory as pseudopotentials

Parameters:

directory (str) – path of the psppar directory
elements (list, dict) – Atomic Species to be included (all if None). If it is a list, only the elements which are listed will be included. If it is a dictionary, the key expresses the element and the value its tag.

set_psp_nlcc(inp, elements=None)[source]

Employed the built in Non Linear Core Correction (NLCC) pseudopotentials.

Parameters:: elements (list, dict) – Atomic Species to be included (all if None). If it is a list, only the elements which are listed will be included. If it is a dictionary, the key expresses the element and the value its tag.

set_psp_krack(inp, functional='PBE', elements=None)[source]

Employed the built in Krack pseudopotentials.

Warning: For certain elements, there are multiple Krack pseudopotentials available with different numbers of electrons. We have choosen the smallest number of electrons as the default behavior. Importantly, the number of electrons when using the LDA or PBE versions may be different.

Parameters:

functional (str) – Either “PBE” or “LDA”.
elements (list, dict) – Atomic Species to be included (all if None). If it is a list, only the elements which are listed are included. If it is a dictionary, the key expresses the element and the value its tag.

load(inp, profile='', profiles=[])[source]

Load a profile or list of profiles.

Parameters:

profile (str) – profile to be loaded, if a single profile is employed.
profiles (list) – profiles list to be loaded in subsequent order.

optimize_kernel(inp, method='DIAG', dynamic_convergence=True, nit=5, rpnrm=1e-10, alphamix=0.5)[source]

Methods for scf of the density kernel.

Strategies for the optimization of the kernel.

Parameters:

dynamic_convergence (bool) – if False, the threshold for the convergence of the kernel are not dynamically adjusted
nit (int) – number of scf iterations
rpnrm (float) – convergence criterion, change in density/potential
method (str) – optimization method (‘DIRMIN’, ‘DIAG’, ‘NTPOLY’, ‘FOE’)
alphamix (float) – mixing parameter

optimize_coefficients(inp, nit=1, gnrm=1e-05)[source]

Methods for scf of the kernel coefficients.

Parameters:

nit (int) – number of scf iterations
gnrm (float) – convergence criterion on the residue

optimize_support_functions(inp, nit=1, gnrm=0.01, diis_history=0)[source]

Methods for scf of the Support functions.

Parameters:

nit (int) – number of scf iterations
gnrm (float) – convergence criterion on the residue

set_orbital_occupancy(inp, avg={}, up={}, down={}, kpoint=1)[source]

Control the occupation number of the KS orbitals.

With this funtionality one can fix the value of the occupation numbers of the KS orbitals.

Parameters:

avg (dict) – dictionary of the form {i: f} where i is an integer stating the non-default value of the occupation number, for spin averaged occupancy
up (dict) – same as avg but for the up spin channel
down (dict) – same as avg but for the down spin channel
kpoint (int) – label of the kpoint associated to the occupancy

set_atomic_occupancy(inp, element=None, iat=None, occupancy={})[source]

Control the occupation number of atomic input guess.

With this funtionality one can fix the value of the occupation numbers of the shells associated to the AO functions employed for the input guess.

Parameters:

element (str) – element to which apply the choice.
iat (int) – atom number in posinp order.
occupancy (dict) – dictionary to define the occupancy. Should follow the guidelines of atomic occupancy.

calculate_pdos(inp)[source]

Calculate the Partial Density of states.

Calculate the data needed for Projected DoS on the set of LCAO input wavefunction in the case of the Cubic-Scaling algorithm and onto the Support Functions in the case of the linear scaling.

calculate_multipoles(inp, yes=True)[source]

Calculate the multipoles on the atoms based on SF.

Parameters:: yes (bool) – switch off the calculation if False.

add_cdft_constraint(inp, constraint=None, homo_per_fragment={})[source]

Include a cdft constraint into the SCF cycle.

Useful for Linear scaling formalism.

Parameters:

constraint (BigDFT.CDFT.CDFTConstraint) – the instantiated constraint
homo_per_fragment (dict) – integer representing the orbital id of the homo of any of the fragments included in the constraint.