# Extracting Maximum Positions of Moving Lagrangian Points in a Fixed Eulerian Space

Hello ParaView community,

I am seeking assistance in using ParaView to extract the maximum positions of moving Lagrangian points within a fixed Eulerian space. Specifically, I have a scenario where points are in motion, and I want to extract the highest positions of these points within a certain spatial region defined by two planes or lines.

To provide more context, the Lagrangian points represent moving particles, and the Eulerian space is stationary. For instance, I am interested in extracting points that lie between two planes defined at x=2cm and x=4cm. However, it is essential to note that these points are continuously updating over time. Therefore, some points that were previously between the two planes might have moved out of this spatial region in the next time step.

I am looking to extract and visualize the maximum positions of these points within the specified spatial region for each time step. I need to use the extracted data to create a line plot that describes the variation of the maximum positions of particle points at a fixed location in space over time.

Could you kindly guide me on how to achieve this in ParaView? Any step-by-step instructions or suggestions on using the appropriate filters and settings to accomplish this task would be highly appreciated.

Thank you in advance for your help and insights. Your expertise will be instrumental in solving this challenging problem.

Best regards!

Clip + FindData should do the trick

First of all, I would like to express my sincere gratitude for your guidance and assistance. I have successfully achieved my objective using the “Clip” method you mentioned, although I did not utilize “FindData” as I was unable to locate it within the Filters. My approach involved using the “Clip” method twice to create a Eulerian space, where the particles are continually changing. My focus is solely on the maximum positions of particles within this space. Therefore, I simply added a Filter to the particles within this space, implementing it as follows:
Add Filter → Data Analysis → Plot Data Over Time

However, I have encountered a new challenge. The above implementation only allows me to extract the variation of the maximum values of particles within a specific space over time (for instance, the highest point of waves in a fixed space). Now, I wish to extract other attribute values of the particle corresponding to the maximum value (for example, if the highest point of waves within the fixed space corresponds to a particle that updates continuously, and I have extracted the highest vertical position ‘y’, I now desire the horizontal position ‘x’ of this particle). Could you please guide me on how to achieve this? In simpler terms, within the fixed Eulerian space, my goal is to identify the maximum value of a particular attribute across all particles, use this maximum value to find the particle’s index, and then use this index to access and extract other attribute values of the same particle.

That works.

Find data is not a filter, its a dock widget.

View → FindData.

Thank you very much. I just checked, and the feature is not available in my version 5.8.0 of ParaView. However, fortunately, I found the “FindData” feature in version 5.11.1. I will give it a try first, and if I encounter any issues, I will reach out to you for further discussion. I appreciate your help very much. Have a great day!

in 5.8 its in Tools → FindData.

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In version 5.8.0, I still couldn’t find “FindData,” but I just found “Find Data…” under “Edit” in version 5.8.0. I’m not sure if this is what you referred to as “FindData.”

Yes, it is this one.

Thanks! I’ll try it.

Thank you so much, I think I have achieved my goal. I truly appreciate your help!

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I realize you already found it, but in both versions of ParaView, the `Find Data` feature can also be opened with a button on the toolbar.

I bring it up because it might help you and others find it. I hope that helps.

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This is fantastic; it provides a lot of convenience. Thank you very much.