Background

The rapid evolution of data science has opened new possibilities for advanced analysis in measurement science, particularly within the field of rheology. Despite these advancements, a gap remains between generalized data processing techniques and the specific requirements of rheological data analysis. This often leaves researchers searching for specialized tools tailored to their unique data challenges.

To address this need, we introduce the hermes Python package. Building on the abstraction provided by the piblin library, hermes offers a comprehensive suite of specialized transforms and analytical tools explicitly designed for rheological data. The package enhances research workflows by enabling precise reading, visualization, processing, and export of rheological datasets, all within a flexible framework.

Key features of hermes include the ability to analyze novel rheological methods such as the Optimal Windowed Chirp (OWChirp) technique and the automated, data-driven creation of rheological mastercurves. Additionally, hermes provides an ideal infrastructure for implementing and exploring new analytical rheological techniques. These capabilities position hermes as a powerful tool for advancing research in rheology, bridging the gap between data science and rheological measurement needs.

Citing

Publication of this work is forthcoming. For now, if you use this software, please cite it using:
DOI

Installation

  • hermes is in the Python Package Index! You can now quickly install it using pip.

$ pip install hermes-rheo

You can also use pip to download updates:

$ pip install hermes-rheo --upgrade

Contributing

Questions, comments, or suggestions can be raised as issues on GitHub or emailed directly to aperego[at]mmm.com.