The Reaction Network Viewer (ReNView) generates a graphic representation of the reaction fluxes within the system essential for identifying dominant reaction pathways and mechanism reduction.
See our documentation page for examples, and equations used.
Udit Gupta (ugupta@udel.edu)
- Python3
- Numpy : Used for vector and matrix operations
- Pandas: Used to import data from input files and process headers
- Graphviz: Used to generate visualizations from text files
- Install using pip::
pip install ReNView
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species_comp.out - A species composition file specifying species name, phase, and the elemental composition of the molecule. In case of heterogeneous systems, surface coverages can also be provided for node coloring.
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reaction_rates.out - A reactions file specifying the forward, reverse, net rate, partial equilibrium index, and reaction string. The reaction string should contain species names as mentioned in the species_comp.out file.
- Network Visualization
- Species Visualization
- Legend generation
This project is licensed under the GNU LGPL License - see the LICENSE.md file for details
- Gupta, U.; Vlachos, D. G. Reaction Network Viewer (ReNView): An Open-Source Framework for Reaction Path Visualization of Chemical Reaction Systems. SoftwareX 2020, 11, 100442. https://doi.org/10.1016/J.SOFTX.2020.100442.
If you have a suggestion or find a bug, please post to our Issues page with the enhancement or bug tag respectively.
Finally, if you would like to add to the body of code, please:
- fork the development branch
- make the desired changes
- write the appropriate unit tests
- submit a pull request.
If you are having issues, please post to our Issues page with the help wanted or question tag. We will do our best to assist.
This material is based upon work supported by the Department of Energy's Office of Energy Efficient and Renewable Energy's Advanced Manufacturing Office under Award Number DE-EE0007888-9.5.
- Dr. Jeffrey Frey (capsule compatibility)
- Gerhard Wittreich (testing)
- Hilal Ezgi Toraman (testing)
- Jonathan Lym (testing)
- Jaynell Keely (Logo design)