continuous representation (image generation) of discrete data set

I have a discrete data set which contains x and y position and velocity. I usually use patch plot to represent this. Is there a continuous way to represent the data? Something that looks like this : https://quickersim.com/flow-porous-media-matlab-quic

Answer 1

[Image Analyst]

It looks like there is a whole toolbox at that site. Did you look it over for functions that might do that? Otherwise, see my attached scatteredInterpolant demo.

[AAS]

Those functions do not work sadly :(.

I am interested however in the scattered interpolant. I am using it wrong howveer. Can you please let me know where I am going wrong.

F=scatteredInterpolant(x,y,v);

[x, z] = meshgrid( 1:1000,1:1000)

x2=imresize(x,2,'bilinear');

z2=imresize(z,2,'bilinear');

V=F(x2,z2);

I would like to output an array V whichare interpolated values at (x2,z2) from v at points (x,z)

Thank you~

[Image Analyst]

What does resizem() do?

[AAS]

Sorry, it should be imresize()

[Image Analyst]

The demo works. Here is the main part:

%================================ MAIN PART RIGHT HERE ==============================================
% Create the scattered interpolant. x, y, and gray levels must be column vectors so use (:) to make them column vectors.
% And grayLevels must be double or else an error gets thrown.
F = scatteredInterpolant(xAll(:), yAll(:), double(grayLevelsAll(:)))
% The above line creates an interpolant that fits a surface of the form v = F(x,y).
% Vectors x and y specify the (x,y) coordinates of the sample points.
% v is a vector that contains the sample values associated with the points (x,y).

% Get a grid of points at every pixel location in the RGB image.
[xGrid, yGrid] = meshgrid(1:columns, 1:rows);
xq = xGrid(:);
yq = yGrid(:);

% Evaluate the interpolant at query locations (xq,yq).
vq = F(xq, yq);
fittedImage = reshape(vq, rows, columns);
%================================ END OF MAIN PART ==============================================

You need xq and yq to be vectors, not images like you had. Also you forgot to do reshape to turn it back into an image.

V=F(x2(:),z2(:));
fittedImage = reshape(V, 1000, 1000);

Answer 2

[Matt J]

You can use griddedInterpolant() if your x,y are gridded sample locations, or else scatteredInterpolant().