# Scattered interpolation
**URL:** https://discourse.julialang.org/t/scattered-interpolation/31733
**Category:** General Usage
**Tags:** interpolations
**Created:** [December 2, 2019, 4:55am UTC](https://discourse.julialang.org/t/scattered-interpolation/31733 "2019-12-02T04:55:04Z")
**Posts on this page:** 6
**Page:** 1
### Author:  [@henry2004y](https://discourse.julialang.org/u/henry2004y)
#### Post date: [December 2, 2019, 4:55am UTC](https://discourse.julialang.org/t/scattered-interpolation/31733/1 "2019-12-02T04:55:05Z")
Hi,
I am kind of struggling with scattered interpolation in Julia for 2D. What I have is a bunch of points (x,y,w), where x and y are coordinates and w is the value. I want to interpolate onto a regular grid. Currently for me this can be achieved by calling Python using linear interpolation:
```julia
using PyPlot
n = 100
X, Y, W = rand(n), rand(n), rand(n)
interval = 0.02
xi = range(minimum(X), stop=maximum(X), step=interval)
yi = range(minimum(Y), stop=maximum(Y), step=interval)
# Perform linear interpolation of the data (x,y) on grid(xi,yi)
triang = matplotlib.tri.Triangulation(X,Y)
interpolator = matplotlib.tri.LinearTriInterpolator(triang, W)
Xi = [y for x in xi, y in yi]
Yi = [x for x in xi, y in yi]
wi = interpolator(Xi, Yi)
```
Similar things can be done in MATLAB with scatteredInterpolant method.
I tried to look at the interpolation packages in Julia, but nothing works so far. Is there a native Julia way of doing this?
Thanks!
---
### Author:  [@Mattriks](https://discourse.julialang.org/u/Mattriks)
#### Post date: [December 2, 2019, 9:15pm UTC](https://discourse.julialang.org/t/scattered-interpolation/31733/2 "2019-12-02T21:15:42Z")
[GitHub - eljungsk/ScatteredInterpolation.jl: Interpolation of scattered data](https://github.com/eljungsk/ScatteredInterpolation.jl) ?
---
### Author:  [@juliohm](https://discourse.julialang.org/u/juliohm)
#### Post date: [December 2, 2019, 10:25pm UTC](https://discourse.julialang.org/t/scattered-interpolation/31733/3 "2019-12-02T22:25:57Z")
Please take a look at [GeoStats.jl](https://github.com/juliohm/GeoStats.jl), it has multiple solvers that you can use for spatial interpolation. There are many other packages that you can use for interpolation in Julia, including [Interpolations.jl](https://github.com/JuliaMath/Interpolations.jl). Your choice depends on your goals.
---
### Author:  [@henry2004y](https://discourse.julialang.org/u/henry2004y)
#### Post date: [December 2, 2019, 11:07pm UTC](https://discourse.julialang.org/t/scattered-interpolation/31733/4 "2019-12-02T23:07:00Z")
I did look at this package, but unfortunately, currently it does not support simple linear interpolation, and with large number of points memory becomes an issue.
---
### Author:  [@henry2004y](https://discourse.julialang.org/u/henry2004y)
#### Post date: [December 2, 2019, 11:15pm UTC](https://discourse.julialang.org/t/scattered-interpolation/31733/5 "2019-12-02T23:15:24Z")
I know there’s the Interpolations.jl package, but my impression is that mostly it contains gridded interpolation schemes but not scattered interpolations. I haven’t looked at the GeoStats.jl package. Will try later. Thanks!
---
### Author:  [@joa-quim](https://discourse.julialang.org/u/joa-quim)
#### Post date: [December 3, 2019, 1:37am UTC](https://discourse.julialang.org/t/scattered-interpolation/31733/6 "2019-12-03T01:37:54Z")
[GMT.jl](https://www.generic-mapping-tools.org/GMT.jl) has several interpolation algorithms
```julia
julia> G = surface(rand(1000,3) * 100, limits=(0,100,0,100), inc=0.5);
julia> imshow(G,title="Minimum curvature",colorbar=true,fmt=:png)
```
or a linear Delaunay triangulation
```julia
julia> G = triangulate(rand(1000,3) * 100, limits=(0,100,0,100), inc=0.5, grid=true);
imshow(G,title="Delaunay Triangulation",colorbar=true,fmt=:png)
```
