# 3D interpolation with anisotropy

**URL:** https://discourse.paraview.org/t/3d-interpolation-with-anisotropy/1516
**Category:** ParaView Support
**Created:** [March 24, 2019, 2:14am UTC](https://discourse.paraview.org/t/3d-interpolation-with-anisotropy/1516 "2019-03-24T02:14:45Z")
**Posts on this page:** 2
**Page:** 1

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### Author: ![fanfan](https://discourse.paraview.org/letter_avatar_proxy/v4/letter/f/45deac/32.png) [@fanfan](https://discourse.paraview.org/u/fanfan)
#### Post date: [March 24, 2019, 2:14am UTC](https://discourse.paraview.org/t/3d-interpolation-with-anisotropy/1516/1 "2019-03-24T02:14:45Z")

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Hi,

I am developping a 3D model of soil texture and would like to give more weight to the interpolation horizontally than vertically. I have a data set of 300K points of soil texture in mm, with data points at every meter interval and at top of intervals. Dataset is based on borehole information.  
A - what would be the most suited Filter for this, Resample to Image, Gaussian Resampling, structure vs unstructured grid?  
B-how to give more weight horizontally to the interpolation?

 ![image](https://discourse.paraview.org/uploads/default/original/2X/9/9ac538d9f6f92b4f47af792a1b94f6a6ca070119.png)

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### Author: ![Kenneth\_Moreland](https://discourse.paraview.org/user_avatar/discourse.paraview.org/kenneth_moreland/32/15033_2.png) [@Kenneth\_Moreland](https://discourse.paraview.org/u/Kenneth_Moreland)
#### Post date: [March 25, 2019, 5:15pm UTC](https://discourse.paraview.org/t/3d-interpolation-with-anisotropy/1516/2 "2019-03-25T17:15:21Z")

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I think the `Gaussian Resampling` filter is closest to what you want.

`Gaussian Resampling` does support anisotropic splatting kernels, but to only way to orient the kernels is by a normal field, which would be a pain to add to your data. A quick a dirty way to get what you want would be to use the `Transform` filter to squish your data horizontally, then apply `Gaussian Resampling`, and then apply `Transform` again to the result to spread the grid back out to normal size.

So, for example, assuming by “horizontal” you mean along the x-axis and you want the sampling to have twice the spread in that direction, you would first apply the `Transform` filter with a `Scale` of [0.5,1,1]. Then you would apply the `Gaussian Resampling` filter. Then you would apply another `Transform` filter with a `Scale` of [2,1,1].