Visualizing large 3D dataset with scatter plot

Question

I\'m running a simulation in MATLAB in which I have a large 3D dataset that changes each time step. I\'m trying to visualize the data using a 3D scatter plot with points tha

Answer 1

It sounds like the timer function is a good place to try next in order to get a sense of your simulation's progression and then making an AVI once you are satisfied with how things look.

MATLAB's got some great documentation for it with a variety of options for consecutive calls are made and the spacing between them. Check out the ExecutionMode and Period properties.

Answer 2

I'm not sure this will solve all the problem, but as a first step I would suggest taking all calculations out of the loop that is used for drawing. Here is a suggestion how to do it:

load sample_data2
clf
channels_matrix = cat(1, channels{:});
num_channels = length(channels);
channel_lengths = cellfun(@(x) size(x, 1), channels);

figure(1);
for k = 1:num_channels
    g = plot3(channels{k}(:, 1), channels{k}(:, 2), channels{k}(:, 3), 'k');
    set(g, 'LineWidth', 1.5)
    hold on;
    text(channels{k}(1, 1), channels{k}(1, 2), channels{k}(1, 3), num2str(k))
end
caxis([0 1])
colorbar
drawnow

numDivisions = 8;
ptsPerDivision = numel(grid_x)/numDivisions;
T = 1000;
numplotpts = 2E4;

% -> chnages starts here:

% first loop for creating random indices
plot_signal = nan(size(grid_x));
rand_numplotpts =sort(rand(numplotpts,T),1);
rand_inds = zeros(numplotpts,T);
for t = 1:T % one loop for creating random indices
    rand_inds(:,t) = sort(randperm(numel(grid_x),numplotpts));
end
plot_signal(rand_inds(:,t)) = rand_numplotpts(:,t);

% second loop for drawing the first instance:
for k = 1:numDivisions
    temp = plot_signal(dists_idx((k-1)*ptsPerDivision+1:k*ptsPerDivision));
    yplot = grid_y(dists_idx((k-1)*ptsPerDivision+1:k*ptsPerDivision));
    xplot = grid_x(dists_idx((k-1)*ptsPerDivision+1:k*ptsPerDivision));
    zplot = grid_z(dists_idx((k-1)*ptsPerDivision+1:k*ptsPerDivision));
    h(k) = scatter3(yplot(~isnan(temp)), xplot(~isnan(temp)),...
        zplot(~isnan(temp)), 50*temp(~isnan(temp)), temp(~isnan(temp)), ...
        'filled', 'MarkerFaceAlpha', exp(-k)^0.25);
end

% third loop to calculate all timesteps:
[X,Y,Z,S,C] = deal(nan(size(temp,1),numDivisions,T));
for t = 2:T 
    plot_signal(rand_inds(:,t)) = rand_numplotpts(:,t);
    for k = 1:numDivisions
        temp = plot_signal(dists_idx((k-1)*ptsPerDivision+1:k*ptsPerDivision));
        yplot = grid_y(dists_idx((k-1)*ptsPerDivision+1:k*ptsPerDivision));
        xplot = grid_x(dists_idx((k-1)*ptsPerDivision+1:k*ptsPerDivision));
        zplot = grid_z(dists_idx((k-1)*ptsPerDivision+1:k*ptsPerDivision));
        non_nan_inds = ~isnan(temp);
        inds = 1:sum(non_nan_inds);
        X(inds,k,t) = yplot(non_nan_inds);
        Y(inds,k,t) = xplot(non_nan_inds);
        Z(inds,k,t) = zplot(non_nan_inds);
        S(inds,k,t) = 50*temp(non_nan_inds);
        C(inds,k,t) = temp(non_nan_inds);
    end
end

% forth loop to draw all data:
for t = 2:T
    for k = 1:numDivisions
        h(k).XData = Y(:,k,t);
        h(k).YData = X(:,k,t);
        h(k).ZData = Z(:,k,t);
        h(k).SizeData = S(:,k,t);
        h(k).CData = C(:,k,t);
        drawnow
    end
end