# continuous representation (image generation) of discrete data set

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AAS on 12 Sep 2020
Edited: AAS on 18 Sep 2020
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

Image Analyst on 12 Sep 2020
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.

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Image Analyst on 18 Sep 2020
What does resizem() do?
AAS on 18 Sep 2020
Sorry, it should be imresize()
Image Analyst on 18 Sep 2020
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);

Matt J on 12 Sep 2020
You can use griddedInterpolant() if your x,y are gridded sample locations, or else scatteredInterpolant().

R2018a

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