pyEELSMODEL

pyEELSMODEL is a electron energy loss spectroscopy software based on the former c++ software. This software uses the model-based approach to quantify EEL spectra.

See https://pyeelsmodel.readthedocs.io/ for more information.

Installing

At this point, pyEELSMODEL is installed by cloning this repository to your computer via:

git clone https://github.com/joverbee/pyEELSMODEL.git

The next step is to navigate to the pyEELMODEL directory and type following into the command line:

pip install .

If you want to create an editable install one needs to do following:

pip install -e .

In the future, the package will be published on PyPI simplifying the installation procedure.

After installation, the generalized oscillator strengths (GOS) tables should be imported. The GOS tables are necessary to perform EEL quantification since they are used to calculate the atomic cross sections. Two different GOS tables can be used for quantification:

The GOS calculated by Zhang Z. et al. which can be found at doi:10.5281/zenodo.7729585.
The GOS calculated by Segger L. et al. which can be found at doi:10.5281/zenodo.7645765.

To know in which directory your pyEELSMODEL package is installed following command can be run in a python console:

import pyEELSMODEL
print(pyEELSMODEL.__path__)

This information is necessary for the proper use of the GOS tables.

GOS tables from Zhang Z.

Following steps explain on how the properly setup the GOS array of Zhang Z.

Download the Dirac_GOS_database.zip file
Unzip the file
Copy the *.hdf5 files in the folder to .pyEELSMODEL\database\Zhang folder which is found in the pyEELSMODEL folder

GOS tables from Segger L.

Following steps explain on how the properly setup the GOS array of Segger L.

Download the Segger_Guzzinati_Kohl_1.5.0.gosh (depends on version) file
Copy the .gosh file to .pyEELSMODEL\database\Segger_Guzzinati_Kohl folder which is found in the pyEELSMODEL folder

The GOS tables are used in the quantification workflows so they are necessary to run the example notebooks.

Using

import pyEELSMODEL.api as em
import numpy as np

size=1024
offset = 100 #[eV]
dispersion = 0.5 #[eV]

specshape = em.Spectrumshape(dispersion, offset, size)
data_array = np.random.random(size)

s = em.Spectrum(specshape, data=data_array)
s.plot()

For more examples on how to use pyEELSMODEL, check the ./examples folder.
This folder has many examples on how to use the pyEELSMODEL package.

License

The project is licensed under the GPL-3.0 license

joverbee / pyEELSMODEL