Welcome to pytraction paper Discussions!

[rg314]

👋 Welcome!

We’re using Discussions as a place to connect with other members of our community. We hope that you:

• Ask questions you’re wondering about.
• Share ideas.
• Engage with other community members.
• Welcome others and are open-minded. Remember that this is a community we
  build together 💪.

To get started, comment below with an introduction of yourself and tell us about what you do with this community.

[rg314]

@AkiStubb, @andimi, @wolframponisch if you could post papers here that would be great :)

[AndreaDimitracopoulos]

Thanks for opening this @rg314!

I would like to add to this discussion a few points that came up yesterday, which mainly relate to clarifying the steps of the algorithm used in pytraction:

• How does pytraction choose the best window size for the iterative PIV, and what should the user consider when explicitly setting it?
• What algorithm is used for the Baysian estimation of the regularisation parameter?
• Difference between estimating one regularisation parameter for the whole stack/dataset vs a single frame?
• What part of the image is used from the frame(s) when the ROI is not specified, and which one when it is specified?

I think there were more points related to the algorithm, simulations, and experimental data that we can add here if @rg314 you think it's useful?