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Granular Healing - Python module associated to the 2022 GeoMod material benchmark

Cite as:

Rudolf, Michael (2023): Granular Healing - Python module associated to the 2022 GeoMod material benchmark. GFZ Data Services. https://doi.org/10.5880/fidgeo.2023.010

Status

I   N       R   E   V   I   E   W : Rudolf, Michael (2023): Granular Healing - Python module associated to the 2022 GeoMod material benchmark. GFZ Data Services. https://doi.org/10.5880/fidgeo.2023.010

Abstract

The software is provided as an executable python module. The software automatically analyzes the files present in the data publication. The results are saved in the form of the images presented in the main publication. Each figure is implemented as a dedicated function that first loads the necessary data, then does some processing steps, such as curve fitting, and then plots the outputs in the desired layout. A 'main' function calls all figure functions sequentially. However, the packages is modular so that each individual plot has a standalone function which could be used with other, similarly structured data. Several submodules provide additional data for plotting, e.g. the 'groups' submodule that contains naming schemes and the densities for all samples.

Additional Information

License: GNU General Public License, Version 3, 29 June 2007

Copyright © 2023 Michael Rudolf

Granular-Healing is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version. Granular-Healing is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program. If not, see <http://www.gnu.org/licenses/>.

Technical Information

To install the package run:
"python -m pip install git+https://git.gfz-potsdam.de/analab-code/granular-healing.git"
To run the script run:
"python -m granularhealing"

Authors

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Keywords

EPOS, multi-scale laboratories, analogue models of geologic processes, software tools, ring shear tester, science > informatics > data processing system

Files

License: GNU Lesser General Public License (Version 3, 29 June 2007) (C) 2022 Rudolf, Michael (TU Darmstadt, Germany)

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