MOOSEanalyze
MOOSEanalyze is a Python package designed to facilitate advanced analysis and visualization of post-processing of MOOSE simulation's exodus file format. MOOSEanalyze python packageis built on Paraview's PvPython module.
Installation:
To install MOOSEanalyze, run the following command in your terminal:
pip install MOOSEanalyze
Usage:
Here's how to get started with MOOSEanalyze: There are 2 different ways
For windows:
Update windows_run.bat file
cd /d \path\to\Paraview\bin
PvPython \path\to\main_wrapper.py
Double click on the windows_run.bat file
For Linux:
Running from main_wrapper.py
cd path\to\Paraview\bin ---> cd D:/Backup_31_July_2022/Research/Research/MOOSE/ParaView-5.11.0-RC1-Windows-Python3.9-msvc2017-AMD64/ParaView-5.11.0-RC1-Windows-Python3.9-msvc2017-AMD64/bin/
Run in command line -----> ./PvPython path/to/main_wrapper.py
or
Run in command line -----> ./PvPython path/to/MOOSE_post_processsing_paraview.py (This will run in the Default Data Folder)
For comparing between different folders manually
# Specify folder names to process only those folders
folder_names = ['Bare_Zn','MLD_Alucone_eigen_0.5']
for specific_time in specific_times:
compare_folders_at_time(base_directory, specific_times, var_names, folder_names)
For comparing between different folders automatically
# call without specifying folder_names to auto-detect and process all folders
compare_folders_at_time(base_directory, specific_times, var_names)
For comparing the dendrite lengths:
calculate_max_x_coordinate(base_directory, folder_names)
plot_points_vs_time_with_max_w(base_directory, folder_names)
Go to MOOSE_post_processsing_paraview.py and change the following interface/i/aniso, based on interface stress, current density or anisotropy cases, respectively
# Change the following line to define which part of older name to be appeared in the plot legend
aniso_value = folder_name.split('aniso')[-1].strip() #interface/i/aniso
Authors
This Software is developed by Musanna Galib
Citing This Work
If you use this software in your research, please cite the following paper:
@misc{galib2025dendritesuppressionznbatteries,
title={Dendrite Suppression in Zn Batteries Through Hetero-Epitaxial Residual Stresses Shield},
author={Musanna Galib and Amardeep Amardeep and Jian Liu and Mauricio Ponga},
year={2025},
eprint={2502.03841},
archivePrefix={arXiv},
primaryClass={cond-mat.mtrl-sci},
url={https://arxiv.org/abs/2502.03841},
}
Contact, questions, and contributing
If you have questions, please don't hesitate to reach out to galibubc[at]student[dot]ubc[dot]ca
If you find a bug or have a proposal for a feature, please post it in the Issues. If you have a question, topic, or issue that isn't obviously one of those, try our GitHub Disucssions.
If your post is related to the framework/package, please post in the issues/discussion on that repository.
Metadata
Release files for MOOSEanalyze 0.0.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| mooseanalyze-0.0.1.tar.gz | 16.8 kB | Without provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| MOOSEanalyze-0.0.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 33.9 kB
Release files / mooseanalyze-0.0.1.tar.gz
| Download URL | mooseanalyze-0.0.1.tar.gz |
|---|---|
| Size | 16.8 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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No |
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twine/6.1.0 CPython/3.10.12
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Release files / MOOSEanalyze-0.0.1-py3-none-any.whl
| Download URL | MOOSEanalyze-0.0.1-py3-none-any.whl |
|---|---|
| Size | 17.1 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.1.0 CPython/3.10.12
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