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This rather neat tweet demonstrates an approach of using a 3D rotation matrix to project 3D points onto a 2D plane to aggregate with datashader. This approach is promising in that it doesn't require rendering an entire volumetric stack and directly produces a visible image, which can also be stitched together into an animation.
The library that was used to achieve the 3D -> 2D projection is Pyrr. It may be nice to either wrap or reproduce some of the functionality in Pyrr to make this easier.
There are considerable differences with this approach compared to volumetric rendering, which we should definitely consider and think about. Unlike volumetric rendering datashader will ensure that all datapoints are adequately aggregated so that nothing is obscured. If we wanted to make it more like a volumetric rendering we could also play with implementing 1/r^2 distance weighted sum aggregation.
The text was updated successfully, but these errors were encountered:
This rather neat tweet demonstrates an approach of using a 3D rotation matrix to project 3D points onto a 2D plane to aggregate with datashader. This approach is promising in that it doesn't require rendering an entire volumetric stack and directly produces a visible image, which can also be stitched together into an animation.
The library that was used to achieve the 3D -> 2D projection is Pyrr. It may be nice to either wrap or reproduce some of the functionality in Pyrr to make this easier.
There are considerable differences with this approach compared to volumetric rendering, which we should definitely consider and think about. Unlike volumetric rendering datashader will ensure that all datapoints are adequately aggregated so that nothing is obscured. If we wanted to make it more like a volumetric rendering we could also play with implementing
1/r^2
distance weighted sum aggregation.The text was updated successfully, but these errors were encountered: