![matlab scatter plot matlab scatter plot](https://www.mathworks.com/help/examples/graphics/win64/ScatterSpecifyAxes19bExample_01.png)
Using these, here come the plotting commands: plot(x, avg, Let's make the abscissa just the number of these "measurements", so x <- 1:n. Let's assume you have a vector of "average values" avg and another vector of "standard deviations" sdev, they are of the same length n. This not-so-straightforward idea comes from the R Wiki Tips and is reproduced here as a worked-out example. The trick is to draw arrows (!) but with little horizontal bars instead of arrowheads (!!!). Here is my favourite workaround, the advantage is that you do not need any extra packages.
![matlab scatter plot matlab scatter plot](https://fr.mathworks.com/help/examples/stats/win64/ScatterPlotWithDefaultSettingsExample_01.png)
There are probably more, tools for this and if you think you want to add some, please edit the question freely.įirst of all: it is very unfortunate and surprising that R cannot draw error bars "out of the box". Or if your image is indexed image you may want to use vol3DĪ useful tool if you have "smooth" 3D data is pcolor3, as it fills the 3D volume with semi-transparent surfaces that give the a nice visual 3D perception of "color clouds"ĭisclaimer: I have no relation to any of the toolboxes presented here and I chose them by my own opinion. You can create some surfaces and plot them using isosurface: You may also just want to plot some equipotential surfaces of your data. You can do that using subplot() and imshow(squeeze(:,:, slice)), or by just concatenating all slices together as img=, for example. You may want to use the typical approach of plotting just some of the slices. If you have medical data (or data on a big range) One option is to use the Sliceomatic from FE: Following i will leave you some examples you may want to try. In general have a look to Volumetric data visualization techniques, but there is not just one way of doing this. You'd need to give more information for an specific answer. I guess that you have is a value of C for every X,Y,Z.Īnd it actually depends a lot in what type of data you have.