Griddata - extrapolation beyond the Delaunay triangulation

Question

Andrey Melnikov 2023-12-19

0
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此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/2062057-griddata-extrapolation-beyond-the-delaunay-triangulation

评论： Mathieu NOE 2023-12-20

采纳的回答： Mathieu NOE

在 MATLAB Online 中打开

Hi all!

I have an array (for example):

A = [1114.74,419.09,139.578;
49,442.43,139.188;
19,433.00,138.894;
47,414.38,139.072;
44,408.88,138.810;
03,369.45,138.715;
25,392.28,138.941;
77,374.79,139.178];

And wrote a code

[griNodN,griNodE] = meshgrid(min(A(:,1)):0.1:max(A(:,1)),min(A(:,2)):0.1:max(A(:,2)));
valGridDef = griddata(A(:,2),A(:,1),A(:,3)',griNodE,griNodN,'linear');
isolin=(min(A(:,3)):0.05:max(A(:,3)));
clim([min(isolin) max(isolin)]);
contourf(griNodE,griNodN,valGridDef,isolin);
colorbar
plot(A(:,2),A(:,1),'rs','MarkerSize',10,'LineWidth',3)

the result looks as expected

In documentation is noted "For all interpolation methods other than 'v4', the output vq contains NaN values for query points outside the convex hull of the sample data. The 'v4' method performs the same calculation for all points regardless of location."

But v4 gives irrelevant result.

Is there another way to at least approximately extrapolate the surface beyond the Delaunay triangulation?