How do I plot a multivariate distribution?
3 ビュー (過去 30 日間)
古いコメントを表示
I have the efficiency map of an electric drive, in wich I plottet the operating points (torque at rpm) during a driving cycle.
Now I somehow want to display in wich areas the system is operating the most. So a multivariate distributional plot with peaks at the areas where the density of points is higher would be my wish.
Please find the attached file as an example (x-Axis is rpm, y-Axis is torque)
Thanks in advance -Fabian
採用された回答
Pawel Jastrzebski
2018 年 8 月 6 日
Consider the following example:
NoOfPoints = 1000;
% Generate 'x' and 'y'
x = rand(NoOfPoints,1);
y = rand(NoOfPoints,1);
% 2d plot of the data
hFig(1) = figure;
hAx(1) = gca();
p(1) = scatter(...
hAx(1),...
x,...
y,...
'ro');
grid on
% generate histogram of the data
% this will give you the density of the points
hFig(2) = figure;
hAx(2) = gca();
NoOfBins = 10;
p(2) = histogram2(hAx(2),...
x,...
y,...
NoOfBins);
% extract peak value of every bin as well as it's
% 'x' and 'y' location
BinCenterX = p(2).XBinEdges(1:end-1) + diff(p(2).XBinEdges)/2;
BinCenterY = p(2).YBinEdges(1:end-1) + diff(p(2).YBinEdges)/2;
BinPeaks = p(2).Values;
% plot values from histogram as surface plot
hFig(3) = figure;
hAx(3) = gca();
p(3) = surface(hAx(3),...
BinCenterX,...
BinCenterY,...
BinPeaks,...
'EdgeAlpha',0.3,...
'FaceAlpha',0.4);
hold on
p(3) = scatter3(...
hAx(3),...
x,...
y,...
zeros(size(x)),...
'ro');
colorbar;
view(3)
grid on;
% use interpolation function to make the surface
% plot smoother
[meshX, meshY] = meshgrid(linspace(0,1,50));
BinPeaksInterp = interp2(...
BinCenterX,...
BinCenterY,...
BinPeaks,...
meshX,meshY,...
'cubic');
hFig(4) = figure;
hAx(4) = gca();
p(4) = surface(hAx(4) ,...
meshX,...
meshY,...
BinPeaksInterp,...
'EdgeAlpha',0.3,...
'FaceAlpha',0.4);
hold on
p(5) = scatter3(hAx(4),...
x,...
y,...
zeros(size(x)),...
'ro');
colorbar;
view(3)
grid on;
0 件のコメント
その他の回答 (0 件)
参考
カテゴリ
Help Center および File Exchange で Data Distribution Plots についてさらに検索
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!