# Multi Dimensional Cubic Spline
**URL:** https://discourse.julialang.org/t/multi-dimensional-cubic-spline/71687
**Category:** General Usage
**Tags:** interpolations, splines
**Created:** [November 17, 2021, 10:01pm UTC](https://discourse.julialang.org/t/multi-dimensional-cubic-spline/71687 "2021-11-17T22:01:45Z")
**Posts on this page:** 4
**Page:** 1
### Author:  [@tgautam03](https://discourse.julialang.org/u/tgautam03)
#### Post date: [November 17, 2021, 10:01pm UTC](https://discourse.julialang.org/t/multi-dimensional-cubic-spline/71687/1 "2021-11-17T22:01:45Z")
Hi, I’ve a multi dimensional dataset (3 features and 1 label) and want to interpolate using cubic splines. I have found several documentations on interpolation in 2D but can’t find anything that’ll help with this. Looking forward to any suggestions.
Thanks.
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### Author:  [@stevengj](https://discourse.julialang.org/u/stevengj)
#### Post date: [November 17, 2021, 10:47pm UTC](https://discourse.julialang.org/t/multi-dimensional-cubic-spline/71687/2 "2021-11-17T22:47:23Z")
> [@tgautam03](#):
>
> Hi, I’ve a multi dimensional dataset (3 features and 1 label) and want to interpolate using cubic splines. I have found several documentations on interpolation in 2D but can’t find anything that’ll help with this. Looking forward to any suggestions.
Is the data on a cartesian grid? If so, it should be straightforward to recursively define a 1d spline of 1d splines of 1d splines (by making splines of the coefficients)…
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### Author:  [@tgautam03](https://discourse.julialang.org/u/tgautam03)
#### Post date: [November 18, 2021, 4:08am UTC](https://discourse.julialang.org/t/multi-dimensional-cubic-spline/71687/3 "2021-11-18T04:08:05Z")
Can you mention any resources that’ll help me implement this effectively. My data is structured such that `M*g` is the label. I’m showing a few points but I’ve around 18k of them.
```julia
# a/c a/t phi M*g
0 0.2 0.2 0.162 1.24187
1 0.2 0.2 0.261 1.20996
2 0.2 0.2 0.423 1.18170
3 0.2 0.2 0.581 1.15911
4 0.2 0.2 0.739 1.16206
```
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### Author:  [@dlakelan](https://discourse.julialang.org/u/dlakelan)
#### Post date: [November 18, 2021, 5:20am UTC](https://discourse.julialang.org/t/multi-dimensional-cubic-spline/71687/4 "2021-11-18T05:20:30Z")
Radial Basis Functions are a common way to do multidimensional interpolation or more generally function approximation.
They are also relatively easy to understand usually infinitely smooth, and have nice rapid convergence properties for many cases.