Author: Vladislav Ivanistsev

Bayesian Error Estimation (BEE) for RPBE

The Beyesian Error Estimation (BEE) is implemented in GPAW only for PBE, BEEF-vdW, and mBEEF-vdW.

Here is a trick for making the BEE with the RPBE functional. Just edit the lines in ASE and GPAW codes by adding RPBE as an exception.

To find the needed files, run

find ./ -name "bee.py"

In ase/dft/bee.py change one line:

class BEEFEnsemble:



            if self.xc in ['BEEF-vdW', 'BEEF', 'PBE', 'RPBE']: # add RPBE
                self.beef_type = 'beefvdw'

In gpaw/xc/bee.py add two lines:

class BEEFEnsemble:
    """BEEF ensemble error estimation."""
    def __init__(self, calc):



        # determine functional and read parameters
        self.xc = self.calc.get_xc_functional()
        if self.xc == 'BEEF-vdW':
            self.bee_type = 1
        elif self.xc == 'RPBE': # catch the RPBE exchange functional
            self.bee_type = 1   # assign BEEF coefficients the RBPE

Below we use BEEF-vdW, RPBE, and PBE dimensionless density (n) with gradient (s) and apply BEEF coefficients (E₀, ΔEᵢ) to evaluate the BEE as the standard deviation for the ensemble total energies with the variable enhancement factor (F(s,θᵢ)).


from ase import Atoms
from ase.dft.bee import BEEFEnsemble
from ase.parallel import parprint
from gpaw import GPAW
import time

for xc in ['BEEF-vdW','RPBE','PBE']:
    start_time = time.time()

    h2 = Atoms('H2',[[0.,0.,0.],[0.,0.,0.741]]) #exp. bond length
    h2.center(vacuum=3)
    cell = h2.get_cell()

    calc = GPAW(xc=xc,txt='H2_{0}.txt'.format(xc))
    h2.calc = calc
    e_h2 = h2.get_potential_energy()
    ens = BEEFEnsemble(calc)
    de_h2 = ens.get_ensemble_energies()
    del h2, calc, ens

    h = Atoms('H')
    h.set_cell(cell)
    h.center()
    calc = GPAW(xc=xc,txt='H_{0}.txt'.format(xc), hund=True)
    h.calc = calc
    e_h = h.get_potential_energy()
    ens = BEEFEnsemble(calc)
    de_h = ens.get_ensemble_energies()
    del h, calc, ens

    E_bind = 2*e_h - e_h2
    dE_bind = 2*de_h[:] - de_h2[:]
    dE_bind = dE_bind.std()
    
    parpting('{0} functional'.format(xc))
    parprint('Time: {0} s'.format(round(time.time()-start_time,0)))
    parprint('E_bind: {0} eV'.format(round(E_bind,4)))
    parprint('Error bar {0} eV'.format(round(dE_bind,4)))

TS09 and D4 corrections with ASE

TS09 and D4 are atomic-charge dependent dispersion corrections (see TS09 PRL paper and D4 homepage for the refs). The D4 code is available at github. According to GPAW documentation, TS09 and D4 show for the S26 test set smaller mean deviation than vdW-DF. Herewith, D4 correction does not depend on the actual calculation as it is added to the calculated energy.

Here is how D4 correction can be added with ASE (see Readme) after installing it (for example, as conda install -c conda-forge dftd4 dftd4-python):

from ase.build import molecule 
from ase.calculators.mixing import SumCalculator 
from ase.optimize import BFGS
from dftd4.ase import DFTD4 
from gpaw import GPAW 

atoms = molecule('H2O') 
atoms.center(vacuum=4)

gpaw = GPAW(mode='fd',txt='H2O_D4.txt',xc='PBE') 
atoms.calc = SumCalculator([DFTD4(method='PBE'), gpaw])

#atoms.get_potential_energy()
opt = BFGS(atoms,trajectory='H2O_D4.traj', logfile='H2O_D4.log')
opt.run(fmax=0.05)

Let me stress that before choosing TS09 or D4 one should consider all pro and contra. TS09 method used Hirshfeld charges while D4 uses the electronegativity equilibration method to obtain charges. The former naturally accounts for the interfacial charge transfer while the latter does not. The TS09 correction requires vdW radii and is implemented for a limited set on functionals (see ASE code), like PBE, RPBE, and BLYP. The D4 correction supports much more functionals (see parameters). Regarding the vdW radii values for TS09 bare in mind that there are four data sources – one in GPAW, two in ASE and one more in ASE.

Here is how TS09 correction can be added with ASE and GPAW:

from ase.build import molecule
from ase.calculators.vdwcorrection import vdWTkatchenko09prl
from ase.data.vdw_alvarez import vdw_radii
from ase.optimize import BFGS
from gpaw.analyse.hirshfeld import HirshfeldPartitioning
from gpaw.analyse.vdwradii import vdWradii
from gpaw import GPAW

atoms = molecule('H2O')
atoms.center(vacuum=4)

gpaw = GPAW(mode='fd',txt='H2O_TS.txt',xc='PBE')
atoms.calc = vdWTkatchenko09prl(HirshfeldPartitioning(gpaw), vdWradii(atoms.get_chemical_symbols(), 'PBE'))

#atoms.get_potential_energy()
opt = BFGS(atoms,trajectory='H2O_TS.traj', logfile='H2O_TS.log')
opt.run(fmax=0.05)

N.B! Note that the TS09 and D4 energies are no outputted to the H2O.txt. They are written to the log-file.

Synchronizing calendars

This post describes ways of pushing MS outlook and Google calendars to Nextcloud.

My main working calendar is the Nextcloud app because I can easily sync it is my Sailfish phone. I also use Google calendar (for sharing family events) and MS outlook calendar (for work). Today I decided to merge all these calendars into a single one that I can sync on all my devices. Here is how.

MS to Nextcloud

Use outlookcaldavsynchronizer as recommended in the Nextcloud blog.

Google to Nextcould

  • Get the iCal link from Google Calendar as follows:
  • In the left calendar list menu of Google Calendar, go to the ⋮ menu of the calendar to be shared
  • Click on “Settings and sharing”
  • On the Calendar settings page, scroll down to “Secret address in iCal format”
  • In Nextcloud Calendar’s left menu, click on “+New Calendar” > “New subscription from link (read-only)”
  • Insert the “Secret address in iCal format”
  • Your new calendar subscription will appear in the list; you can change its name or color in the menu of your calendar

“Resurrections”

I have not been writing to the blog for approximately 2.5 years. That period overlaps with the birth of my second child, pandemic, and absence of research funding – all the reasons for prioritizing family and grant writing above the blog writing. At the moment, there are no barriers to blogging, as I have the MSCA fellowship, some vaccine protection, and my adapted to a nursery.

I am now returning to that blog for several reasons. First, it is the right place for summarising research activity. Foremost for myself and close colleagues. Second, I feel the need to communicate science-related thoughts and emotions, especially in changing the working environment (from Tartu Univ. to Copenhagen Univ.). So, I am back!

Mascot again

A long time ago a student told me that I am a mascot of the chemistry olympiad. Since then I have graduated, made a post-doc, and after that returned to the olympiad business. It is very touching that the Estonian team named its mascot “Vlad”. Apparently, I am a mascot again.

Mascot Vlad and Hanna-Riia.

Erasmus

A group of students and tutors from Paris 13 visited Chemicum. Aurélie and Chris on the left and David with sunglasses in the middle. Georgi (on the right) made a nice excursion. Next year two Erastus students from Paris 13 will be studying in Tartu!

Installation of LibXC 4.0.0 trunk + GPAW1.3.0 + ASE

Assume that all the requirements are fulfilled:

  • Python 2.7-3.5
  • NumPy 1.6.1 or later (base N-dimensional array package)
  • ASE 3.15.0 or later (atomic simulation environment)
  • a C-compiler
  • LibXC 2.0.1 or later
  • BLAS and LAPACK libraries

Optional, but highly recommended:

  • SciPy 0.7 or later (library for scientific computing, requirered for some features)
  • an MPI library (required for parallel calculations)
  • FFTW (for increased performance)
  • BLACS and ScaLAPACK

LibXC compilation:

svn co http://www.tddft.org/svn/libxc/trunk/ libxc
cd libxc
autoreconf -i
./configure --enable-shared --prefix=/home/USER/xc
make -j N
make install

The LibXC compilation might not work, and GPAW would complain, so configure as follows:

./configure CFLAGS="-O2 -fPIC" --prefix=/home/USER/xc

After compiling LibXC add these lines to your .bashrc:

export C_INCLUDE_PATH=/home/USER/xc/include
export LIBRARY_PATH=/home/USER/xc/lib
export LD_LIBRARY_PATH=/home/USER/xc/lib

Let’s install ASE using pip, because it is easy.

pip install --upgrade --user ase

Get the GPAW source code and remove in libxc.c in c/xc/ line xc_mgga_x_tb09_set_params(self->functional[0], c);. Them compile GPAW with python setup.py install --user. You might want to add the .local/bin to the path.

Use either Python or Python3, and be consistent with that.

The official guideline also recommends adding these lines to your .bashrc:

export PYTHONPATH=/home/USER/gpaw:$PYTHONPATH
export PATH=/home/USER/tools:$PATH

Don’t forget to get setups. E.g. execute gpaw install-data DIR. After that run the tests.