---
id: libhreels
version: "2.3.1"
license: unclear
license_treatment: unclear
maintenance: aging
---

# libhreels — Handling, simulating, and plotting HREELS and Auger spectroscopy data

License: unclear · Maintenance: aging · Downloads: 79.6K/mo

## What it is and what it does

Libhreels is a Python package for handling and analyzing high-resolution electron energy loss spectroscopy (HREELS) data acquired from Delta05 spectrometers running VSI or SPECS software. It provides data reading, plotting, and interactive analysis routines through a HREELS class that exposes spectrum properties (energy, resolution, intensity) and methods for visualization, peak selection, and data extraction. The package also wraps a Fortran90-based calculation engine (via the lambin class) for computing full HREEL spectra from heterostructures, and includes a dielectrics module for modeling material optical properties through oscillator and Drude responses.

The package ships with a graphical data browser (ViewHREELS.py) and command-line tools like showHREELS.py for quick spectrum inspection. Core analysis happens through the HREELS class, which loads spectroscopy files and calculates derived quantities such as elastic peak width and count rate. The Fortran calculation component requires manual compilation on most systems, though binaries are pre-built only for Linux Python 3.8.

Use it for:

- Load and visualize HREELS spectra from Delta05 spectrometer output files with automated property extraction.
- Interactively select and analyze spectral peaks using the graphical data browser or programmatic peak-picking methods.
- Simulate full HREEL spectra for layered materials and heterostructures using Lambin's published calculation method.
- Model dielectric properties and optical responses of materials via oscillator and Drude models.
- Batch process multiple spectroscopy datasets and extract quantitative metrics like resolution and elastic peak intensity.

## Worth the install?

AI-flagged interpretation of the facts above — verify before relying.

Libhreels reads, analyzes, and simulates high-resolution electron energy loss spectroscopy (HREELS) data from Delta05 spectrometers, with tools for plotting, peak selection, and computing full HREEL spectra via Fortran-based calculations.

Yes, if you work with HREELS data from Delta05 spectrometers and can accept the aging maintenance status and unclear license. The package has no runtime dependencies and low install friction for basic use. However, do not install if you need Fortran-based spectrum simulation on Python versions other than 3.8 on Linux, or if you require legal clarity on licensing before use. Verify the license status and repository health with the maintainers before production deployment.

## Install

pip install libhreels
uv add libhreels
poetry add libhreels

## Installing libhreels

Before you install: Low install friction with no runtime dependencies; however, the package is aging (353 days since last release) and advanced features requiring Fortran compilation are only pre-built for Linux Python 3.8, limiting portability.

License in practice: License status is unclear—no SPDX identifier or raw license text is declared—so legal terms for use and redistribution cannot be determined from the package metadata.

Quickstart:

pip install libhreels

from libhreels import HREELS
data = HREELS('filename', datapath='path/to/data')
data.plot()

Advanced Fortran-based spectrum calculation requires local compilation via f2py3; pre-compiled binaries are only provided for Linux with Python 3.8.

Verify before relying:

- Whether the package's Fortran compilation step is documented and maintainable on modern systems beyond Python 3.8.
- Current status of the GitLab repository and whether active maintenance is ongoing.
- Whether the unclear license permits commercial or derivative use.

## Package facts

- License: not declared (unclear)
- Python support: unspecified
- Install friction: low
- Maintenance: aging
- Downloads: 79.6K/month (top 15,000 on PyPI)
- Known vulnerabilities: none known

## Tags

HREELS spectroscopy data analysis, electron energy loss spectrum, surface vibrational spectroscopy, HREEL spectra simulation, spectroscopy data plotting, dielectric properties modeling, Auger spectroscopy data, spectroscopy, fortran-integration, scientific-data

[View on SkillFed](https://skillfed.io/packages/libhreels) · [View on PyPI](https://pypi.org/project/libhreels/)