The annotation attribute in Julia Plots seems to only take tuples of x,y coordinates and a label according to the documentation. Is there any way to do this on a 3D plot? For example:
tvec=0:0.1:4*pi
plot(sin, tvec)
annotate!(pi/2,1.0,"max")
annotate!(3*pi/2,-1.0,"min")
produces
but how do you add something to
tvec=0:0.1:4*pi
plot(tvec, sin(tvec), cos(tvec))
Using the same type of annotate! command seems to annotate onto a superimposed 2D coordinate.
According to the Julia Plots (Plots.jl) docs found here, GR, PyPlot, and Plotly(JS) all support 3D plots in some form. It is worth diving into some examples here to explore how these different backends support 3D plots.
Seems like it's not available yet https://github.com/JuliaPlots/Plots.jl/issues/362
Related
I'm plotting a very simple triangle using trimesh in matlab, but I struggle to find a property that could fill the triangle color.
Is there a specific one I'm missing?
The doc page doesn't say much:
https://uk.mathworks.com/help/matlab/ref/trimesh.html
I'm not a big matlab expert, but I'm pretty sure there's a property for this.
You want a mesh? Use trimesh!
You want a surface? Use trisurf!
Basically, I have been trying to create a jet colored scatter plot in MATLAB.
Ref: Clayson et al. 2013
I have no z-value. Colormap is also not working. How exactly to do it? Thanks
What you are looking for is called a density scatter plot. You don't need a third dimension in order to create it, so don't worry for your missing z. The coloring algorithm is based on the density of the points.
Such plotting function is not included in the default Matlab packages and toolboxes, but after a quick search I probably found exactly what you are looking for. Take a look at this File Exchange release. It contains a full working function for creating density scatters together with a few illustrated usage examples:
I have a 3 dimensional data set which I intend to analyse. After analysing the data set, basically running an algorithm to find a range of points, I this range of points to have a specific colour so that when someone sees the surface plot, they know which are the points of interest. How can this be achieved?
I have tried to find some help in the mathworks forums, but so far I am not able to find a satisfactory solution.
If you are using the surface function, you can use the 4 parameter version surf(x,y,z,c) where c lets you specify colour based on the currently used colour map. See this link at the mathworks site for more detail http://www.mathworks.co.uk/help/matlab/ref/surf.html
I'm currently working with DICOM-RT files (which contain DICOM along with dose delivery data and structure set files). I'm mainly interested in the "structure set" file (i.e. RTSS.dcm), which contains the set of contour points for an ROI of interest. In particular, the contour points surround a tumor volume. For instance, a tumor would have a set of 5 contours, each contour being a set of points that encircle that slice of the tumor.
I'm trying to use MatLab to use these contour points to construct a tumor volume in a binary 3D matrix (0 = nontumor, 1=tumor), and need help.
One possible approach is to fill each contour set as a binary slice, then interpolate the volume between slices. So far I've used the fill or patch function to create binary cross-sections of each contour slice, but I'm having difficulty figuring out how to interpolate these binary slices into a 3D volume. None of the built-in functions appear to apply to this particular problem (although maybe I'm just using them wrong?). A simple linear interpolation doesn't seem appropriate either, since the edges of one contour should blend into the adjacent contour in all directions.
Another option would be to take the points and tesselate them (without making slices first). However, I don't know how to make MatLab only tesselate the surface of the tumor and not intersecting the tumor volume. Currently it seems to find triangles within the tumor. If I could get it into just a surface, I'm not sure how to take that and convert it into a binary 3D matrix volume either.
Does anyone have experience with either 3D slice interpolation OR tesselation techniques that might apply here? Or perhaps any relevant toolkits that exist? I'm stuck... :(
I'm open to approaches in other languages as well: I'm somewhat familiar with C# and Python, although I assumed MatLab would handle the matrix operations a little easier.
Thanks in advance!
I'm not sure from what program you're exporting your dicom-rt structure files, but I believe I found a more elegant solution for you, already described in an open-source software (GDCM, CMake, ITK) in an Insight journal article.
I was discussing a similar problem with one of our physicists, and we saw your solution. It's fine if whatever structure you're attempting to binarize has no concavities, but if so, they'll be rendered inaccurately.
This method is verified for dicom-rt structure sets from Eclipse and Masterplan. Hope it helps.
http://www.midasjournal.org/download/viewpdf/701/4
I think I found an answer in another post (here). Rather than trying to interpolate the "missing slices" between the defined contours, treating the contour points as a point cloud and finding the convex hull might be a more efficient way of doing it. This method created the binary 3D volume that I was after.
Here is the code I used, hope it might be helpful to those who need to work with DICOM-RT files:
function mask = DicomRT2BinaryVol(file)
points = abs(getContourPoints(file));
%%NOTE: The getContourPoints function simply reads the file using
%%'dicominfo' method and organizes the contour points into an n-by-3
%%matrix, each column being the X,Y,Z coordinates.
DT = DelaunayTri(points);
[X,Y,Z] = meshgrid(1:50,1:50,1:50);
simplexIndex = pointLocation(DT, X(:), Y(:), Z(:));
mask = ~isnan(simplexIndex);
mask = reshape(mask,size(X));
end
This method is a slightly modified version of the method posted by #gnovice in the link above.
iTk is an excellent library for this sort of thing: http://www.itk.org/
HTH
Is there any subroutine, in MATLAB, that takes in a list of points, and return me a good mesh that I can use to show to my colleagues, such as this?
Actually, all I need is just a simple 2D mesh generator that takes in a series of X, Y coordinates (that defines the boundary of the area), and give me back a list of elements that can mesh that area well. I can do the rest by using MATLAB command to interpolate the Z value.
Edit : I am not interested to use MATLAB to produce the above looking plot. I am interested in using a MATLAB library to obtain a list of elements so that when I plot those element myself (not in MATLAB itself; but in my own C# program), I can obtain this meshed surface.
PS: I know there is this DistMesh, but I am looking for something simpler - something built-in direct in MATLAB perhaps. And no, meshgrid is not mesh generation.
It sounds like you want to create a finite element mesh, starting with a set of points defining a boundary of a region and then generating a triangular mesh that creates more points within that region. I don't think there's a "simple" solution for this problem.
The closest "built-in" solution would probably be the Partial Differential Equation Toolbox, specifically some of the Geometry Algorithms like INITMESH and REFINEMESH.
The link you gave to DistMesh appears to be another good solution. There are also a few submissions on the MathWorks File Exchange that you could take a look at:
MESH2D by Darren Engwirda
Finite Element Toolbox 2.1 by Rasmus Anthin
That picture looks exactly like the one from the griddata documentation. The example in there looks like what you want.
SFTOOL will easily make the picture that you show.
A thin-plate spline, e.g., TPAPS, should also do the job.
I think the user-created 'gridfit' is the best I've come across for a single surface, much better/prettier than griddata.
Mesh generation as in Delaunay Triangulation + Steiner Points? There is a builtin Delaunay function in MATLAB.
If your surface is the z=f(x,y) form you can use:
http://www.advancedmcode.org/how-to-plot-a-coloured-surface-from-3d-scatter.html
If your surface is concave look for surface reconstruction on the same website.