elkoa 1.5.1

plot and analyze Elk optics output data

Elk Optics Analyzer (ElkOA)

⚠️ NOTE: You may also try the develop branch via git clone -b develop ...

Description

Elk Optics Analyzer (ElkOA) helps to analyze optics output data from The Elk Code.

Features

Elk Optics Analyzer...

• Gives you quick and painless visual access to many ELK output files
• Comes with an easy to use GUI as well as a python CLI for experts
• Recognizes available tasks / (tensor) fields automatically
• Is easily extendable

Users can...

• Create and save publication-ready pictures via matplotlib's user interface
• Visualize real and imaginary parts of Elk optics output data in various ways
• Cycle through available datasets quickly via Tab and Shift+Tab
• Select tensor elements to plot via dialog Ctrl+T
• Use global tensor elements settings across all available tasks Ctrl+G
• Batch-load parameter studies to visually analyze the impact of different parameter settings Ctrl+B
• Import and plot additional data files on top (e.g. experimental measurements) Ctrl+O
• Write out currently displayed data in different formats Ctrl+S
• Manipulate field data tab-wise, e.g. shift graph(s) to left/right, take square root etc. Ctrl+M
• Convert response functions via Universal Response Relations, e.g. ε ➙ σ Ctrl+C ⚠️ experimental❗
• Convert dielectric tensors computed in the optical limit (q ➙ 0) into ordinary and extra-ordinary refractive indices for arbitrary wavevectors Ctrl+C ⚠️ experimental❗

Possible new features for next releases:

• Most certainly and foremost: Bugfixes
• 3D-plotting of index ellipsoids
• Batch-convert for a set of different q-points
• Sample/geometry-dependent (i.e. thin films) conversions of response functions

Requirements

• Python 3.x
• numpy
• matplotlib
• PyQt5
• pbr
• wrapt
• numexpr

You should use the packages provided by your linux distribution. On recent Debian systems for example, you can get all requirements by running

apt install python3-numpy python3-matplotlib python3-pyqt5 python3-pbr python3-wrapt python3-numexpr

Alternatively, you can get the latest PyPI versions of each package automatically as dependencies by installing ElkOA via pip (see below).

For testing purposes, you additionally need the following packages:

• pytest
• pytest-qt
• pytest-mpl
• nose

Installation

The easiest way to install ElkOA is via pip, either from PyPI directly

pip install elkoa

or, if you want the latest git release,

git clone https://github.com/PandaScience/ElkOpticsAnalyzer.git
cd ElkOpticsAnalyzer
pip install .

This will also install all required but absent python packages automatically from PyPI.

If you like to install ElkOA only for the current user, add the flag --user. If you want to take care of the required python packages yourself (i.e. by using the ones provided by your Linux distribution), add --no-deps. If you like to run a developer installation (no copying of files, instead use git repo files directly), add -e.

Note: On newer systems you possibly encounter error: option --user not recognized during the developer installation. This is due to a bug in pypa/setuptools and can be worked around using the flag --no-build-isolation. However, you then have to take care of all build dependencies yourself.

For example, on my Arch Linux system, I use pip install --user --no-deps --no-build-isolation -e . within the repository's folder.

In any case, after installation you can run the ElkOA GUI from everywhere in a terminal using either elkoa or ElkOpticsAnalyzer.

Another way to install is by cloning the repo as above and instead of installing via pip, put something like

export PATH=$PATH:/path/to/ElkOpticsAnalyzer/elkoa/gui
export PYTHONPATH=$PYTHONPATH:/path/to/ElkOpticsAnalyzer/

to your .bashrc or .bash_profile. Then you can start the ElkOA GUI with ElkOpticsAnalyzer.py.

Tests

Testing is done using the pytest library. Make sure you installed all additional requirements beforehand.

1. Download and extract the sample data
   • TODO
2. Run (--mpl flag is mandatory!)

pytest test_figures.py --mpl

Python CLI

In an Elk output directory containing e.g. the files

EPSILON_TDDFT_11.OUT EPSILON_TDDFT_12.OUT EPSILON_TDDFT_13.OUT 
EPSILON_TDDFT_21.OUT EPSILON_TDDFT_22.OUT EPSILON_TDDFT_23.OUT 
EPSILON_TDDFT_31.OUT EPSILON_TDDFT_32.OUT EPSILON_TDDFT_33.OUT elk.in INFO.OUT 

you can run in a python3 interpreter:

# import helpful submodules from elkoa package
from elkoa.utils import elk, io, convert
# parse Elk input file
elk_input = elk.ElkInput(verbose=True)
eta = elk_input.swidth
# or read specific input parameter directly
eta = elk.readElkInputParameter("swidth")
# read tensorial Elk optics output (ij = dummy for 11, 12, etc.)
freqs, epsilon = io.readTensor("EPSILON_TDDFT_ij.OUT")
# find cartesian representation of q-vector from elk.in
q = elk_input.q_cart
# save crystal lattice vectors in cartesian basis as column-wise matrix
B = elk_input.B
# create converter instance with conventional frequency regularization
converter = convert.Converter(q, B, freqs, eta, reg="conv")
# convert dielectric tensor to optical conductivity
sigma = converter.eps_to_sig(epsilon)
# write out converted tensor
io.writeTensor("sigma_ij_test.dat", freqs, sigma, threeColumn=True)
# write out only 11 and 22 element of converted tensor
io.writeTensor("sigma_ij_test.dat", freqs, sigma, elements=[11, 22])

Misc

• Loading additional data into existing plot: ElkOA supports auto-converting filenames to tex-labels. For this feature to work however, filenames must follow the pattern root+_sub+.ext, which will show up as root_sub. In case root contains a case-insensitive substring like eps, EPSILON, Sig, SIGma etc., corresponding greek letters will be used, i.e. eps_ex.dat ➙ ε_ex.
• The number of additional plots is restricted to 6, but in return we use consistent coloring after consecutively adding more plots.

Extend ElkOA

Users can extend ElkOA easily by modifying the file elkoa/utils/dicts.py, where all GUI-available tasks/output files, parameters and converters are set including naming of axes and tabs.

Usage Examples GUI

Tensor plotting and "on-top-data"

Batch loading for parameter studies

Converter tools for response functions

Manipulating field data and visible frequency range

➙ if images are not shown visit https://github.com/PandaScience/ElkOpticsAnalyzer/