Can wwt consider to support network data display in "Rectangular" coordinate system?

I try to visualize the co-citted data from Nature:
data_link:https://www.nature.com/immersive/d41586-019-03165-4/dat/data.zip
Nature 150 Interactive:https://www.nature.com/immersive/d41586-019-03165-4/index.html

The data has given Nodes’ XYZ coordinate and the key points of links in Network. But WWT seems not support the Linestring() method in "Rectangular" coordinate system which is in "SandBox"。So the key points can’t link together. The Linestring() method is available in “Spherical” coordinate system.

I try to fill in points between key points, but it seems over 10 billion rows data need to shown in wwt. This is unfriendly to most of computer in school, and cost lots of time. So we may need to develop this method. :smile:

I have done part of it.

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The full version with time series and links. It’s cool to show the history of science dynamically in WWT~ :star_struck:

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This is so cool! Do you have a layer or tour file to share?

Yes~ I will upload it in July. Now it’s confidential, because I need to use it to participate in a competition. :smile: :smile: :smile:

Fair enough! Looking forward to it!

Long time no see! I win the first prize and made an acceptance speech to introduce pywwt to Chinese WWT tour maker~

The layer’s .wwtl file and source data from Nature is here.

The file is too big to upload,so I put it into Onedrive and this is link:

https://asdjbi-my.sharepoint.com/:f:/g/personal/miohniui_asdjbi_onmicrosoft_com/EnxXNa8K3R1GvZ8PGjuSQIMB5DX30NWAXnUTPl6qiLbBRw?e=7dBWXO

password:dfgdh1kn4j7is0-nf

It will expire at 1st Sep.

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This is fantastic and congratulations! You used pywwt to assemble the layers?

Yes I use python to create lines and pywwt.windows to transfer it into WWT Windows Client. I make a tour name The Endless Frontier with 2GB data visualization. So I need 24GB RAM to open the tour’s source file :rofl: . But the visual effect is fantastic !

May be WWT could modify it’s 3d engine to improve the render performance and reduce the cost of RAM.

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