Is there any way to speed this up?
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Gavin
el 23 de Mayo de 2024
Comentada: Gavin
el 24 de Mayo de 2024
I have a large (100x100x100) dataset of very small probabilites for electron locations in the hydrogen atom. I am attempting to create a 3-D heatmap of sorts, which I have done, using isosurface and layering many of them ontop of eachother using this code.
figure()
Psi = importdata("psi.mat");
n = 4;
l = 2;
m = 0;
isovalues1 = 1*10^(-(n+2)):1*10^(-(n+2)):1*10^(-n);
for i=1:length(isovalues1)
isosurface(Psi.^2,isovalues1(i))
alpha(isovalues1(i)*10^(n-2));
end
axis equal
axis vis3d
ax=gca; ax.SortMethod='childorder';
colorbar
title(['N = ',num2str(n),', L = ',num2str(l),', M = ',num2str(m)])
This works. But as you can imagine, making 100 isosurfaces at a time can be quite slow. I was wondering if there was any way to speed up what I have or perhaps another way to make a 3-D heatmap.
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Cris LaPierre
el 23 de Mayo de 2024
Editada: Cris LaPierre
el 24 de Mayo de 2024
My question is if it has to be done with isosurfaces. Here's an approach that uses scatter3. You can adjust the marker size to change how the data is displayed. It does look different, but it seems all the important info is still there.
load("psi.mat",'Psi');
n = 4;
l = 2;
m = 0;
% create (x,y,z) coordinates
[X,Y,Z] = meshgrid(1:size(Psi,2),1:size(Psi,1),1:size(Psi,3));
isovalues1 = 1*10^(-(n+2)):1*10^(-(n+2)):1*10^(-n);
% discretize the data by isovalues
[bin,edges] = discretize(Psi.^2,isovalues1);
% Plot data
idx = bin(:)>0;
scatter3(X(idx),Y(idx),Z(idx),1,isovalues1(bin(idx)),'filled')
alpha(isovalues1(bin(idx)).*10^(n-2))
axis equal
axis vis3d
colorbar('TickLabels',isovalues1)
title(['N = ',num2str(n),', L = ',num2str(l),', M = ',num2str(m)])
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