Multiple griddata calls into a single one (same grid)

3 次查看（过去 30 天）
Albert
Albert 2021-4-16
评论： Bruno Luong 2021-4-16
Hi,
I'm using griddata to regrid points (xpoint, ypoint, pointval) into a regular grid (xgrid, ygrid). I used to do this in 2D as follows:
x = linspace(-1,1,200);
y = linspace(200,600,200);
[xgrid,ygrid] = meshgrid(x,y);
gridded = griddata(xpoint,ypoint,pointval,xgrid,ygrid,'v4');
But now I have expanded my analysis and I have different sets of points. All have the same (xpoint,ypoint) coordinates but different pointval. The straight way of doing this would be:
gridded = arrayfun(@(nn)griddata(xpoint,ypoint,pointval(:,nn),xgrid,ygrid,'v4'),1:npoints,'uniformoutput',false)
However this is effectively similar to a for loop and takes some time. Do you think there is a smarter way of calling griddata only once?
Thanks!

请先登录，再回答此问题。

回答（3 个）

Star Strider
Star Strider 2021-4-16
The arrayfun function is significantly slower than an explicit loop, at least in my experience.
I would just do something like this:
for nn = 1:npoints
gridded{k} = griddata(xpoint,ypoint,pointval(:,nn),xgrid,ygrid,'v4');
end
I am sure there are applications where arrayfun is useful (perhaps with small arrays in anonymous functions), however llikely not here.
Also, the original arguments were (xpoint,xpoint). I changed them here to (xpoint,ypoint) since that also appears, so check that to be certain it is correct.
  4 个评论
显示 2更早的评论
Albert
Albert 2021-4-16
No problem, maybe it depends on the type of operation inside
Bruno Luong
Bruno Luong 2021-4-16
IMO arrayfun is always slower than for-loop. It is just more visible when the unitary loop operation is fast. Here the interpolation is not fast so using arrayfun or for-loop doesn't matter speedwise.

请先登录，再进行评论。

Bruno Luong
Bruno Luong 2021-4-16
If you are ready to trade 'v4' method for something else, you can use scatteredInterpolant
% example of fake data
x = -3 + 6*rand(50,1);
y = -3 + 6*rand(50,1);
v = sin(x).^4 .* cos(y);
pointval = v + (0:10);
% fake grid
[xgrid,ygrid] = meshgrid(-3:0.1:3);
F = scatteredInterpolant(x,y,pointval(:,1));
F.Method = 'natural';
nv = size(pointval,2);
gridded = zeros([size(xgrid),nv]);
for k=1:size(pointval,2)
F.Values = pointval(:,k);
gridded(:,:,k) = F(xgrid,ygrid);
end
  1 个评论
Albert
Albert 2021-4-16
I always had the impression that v4 performed best but takes more time. I can also use the former griddata function with the 'cubic' method and that's superfast too. Thanks!

请先登录，再进行评论。

Bruno Luong
Bruno Luong 2021-4-16
For nearest/linear/cubic method you can build the matrix https://www.mathworks.com/matlabcentral/fileexchange/85939-mat-op-ex, followed up from this thread
The output is simply matrix x vector of values, so you can multiply by many input vectors in one shot.

类别

在 Help Center 和 File Exchange 中查找有关 Resizing and Reshaping Matrices 的更多信息

标签

产品


版本

R2021a

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by