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jpvantassel/pivpostprocess: v1.0.0

Authors: Ghazi Nezami, A.; Johnson, B. A.; Vantassel, J. P.;

jpvantassel/pivpostprocess: v1.0.0

Abstract

Initial release of PIVPostProcess 🎉! This release of PIVPostProcess was used for the paper, "An Open-Source, Physics-Aware, Data-Driven Tool for Automated Particle Image Velocimetry Post-Processing" by Ghazi Nezami, A., Johnson B. A., and Vantassel, J. P. as submitted for peer review. Note if changes are needed to the code as a result of the peer review process a new release will be created. This release includes: ✨ Trained gradient boosted trees (GBT) model. ✨ Implementation of PIV data pre-processing workflow. 📚 No-coding-required examples of using PIVPostProcess on real datasets.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average