Multiple griddata calls into a single one (same grid)

4 Ansichten (letzte 30 Tage)
Albert am 16 Apr. 2021
Kommentiert: Bruno Luong am 16 Apr. 2021
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?

Antworten (3)

Star Strider
Star Strider am 16 Apr. 2021
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');
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 Kommentare
Bruno Luong
Bruno Luong am 16 Apr. 2021
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.

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Bruno Luong
Bruno Luong am 16 Apr. 2021
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);
  1 Kommentar
Albert am 16 Apr. 2021
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!

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Bruno Luong
Bruno Luong am 16 Apr. 2021
For nearest/linear/cubic method you can build the matrix, 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.


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