I need to interpolate scattered data on a model represented by a 3D surface in Matlab. I tried it using "scatteredInterpolant", but the results were quite bad. This function only allows to specify the query points but not the 'ConnectivityList' because internally it performs its own Delaunay triangulation from the specified point set. However, I perfectly know not only the points but also the 'ConnectivityList', so I can create a Matlab 'triangulation representation' using "triangulation".
So my question is the following. Is there any way to give a predefined 'triangulation' to "scatteredInterpolant"? If it is not possible, is there any other Maltab function or class able to perform data interpolation on a previously triangulated 3D surface instead of performing its own triangulation from the query points?
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I have the following coordinate system of (x,y) and attached z value to each coordinate. I need to keep the coordinates the same without using some linear fit function to change it into a grid system of some sort. Is there a way i can create a contour of that data using that data only and not using griddata or something.
x=[0.2,0.2,0.05,1.1,0.8,0.9,1.8,1.9,2.05];
y=[0,1.1,2.1,0.1,1.1,2.2,0.15,1.1,2.05];
z=[0,1,0,0,2,1,0,1,0;];
plot(x,y, 'bo')
The reason is i have another model with 540 thousand coordinate points that is a weird shape and if i start using the other functions it loses its shape and goes rectangular.
One option you have is to use fitto create a fit surface of your data, and then directly plot it. This also has the advantage to give you extra parameters to control the interpolation between your points.
f=fit([x',y'],z','linearinterp')
plot(f,'Style','Contour')
Will create something like:
And
f=fit([x',y'],z','cubicinterp')
plot(f,'Style','Contour')
Will smooth the interpolation into:
Please look here for more information on fit and fit plotting options
https://www.mathworks.com/help/curvefit/fit.html#inputarg_fitType
https://www.mathworks.com/help/curvefit/plot.html
I am trying to use the function inpolyhedron shown here: https://www.mathworks.com/matlabcentral/fileexchange/37856-inpolyhedron-are-points-inside-a-triangulated-volume-
However, I am having trouble creating the polyhedron the way the function wants it defined (a structure with fields 'vertices' and 'faces'). The raw data I have is a matrix of points x y z that are inside the polyhedron. So far, I have been using boundary() and trisurf() to plot the polyhedron.
Dependant on what kind of polyhedron you want, you can use alphashape, delaunay triangulation or convhull. So for example:
shp=alphaShape(x,y,z);
h=plot(shp);
You can access faces and vertices then like:
h.Vertices
h.Faces
It works the same way for trisurf:
tri=delaunay(x,y,z)
t=trisurf(tri,x,y,z)
To see which information is stored, you can use get(t).
For faces and vertices it is the same thing as before:
t.Vertices
t.Faces
Can anyone tell me how to generate a 3D surface model like CAD in Matlab ?
1.Input: Input is a collection of points with (x,y,z) where surface is present for an object(I'm using this for a 3D scanner where my inputs are (x,y,z) of surface)
2.Points should be displayed as a surface using some smooth interpolation.
3.More like surface generation from data points.
Thanks you.
In order to plot surfaces, you can use patch function. However, you need along with the points the faces information. In patch a surface consists of polygons that is specified using 3 point, which is the face information.
1
Since it seems like you will be inputting discrete points located on the surface of the object, you will first want to create a Nonconvex Polygon based on the data using Matlab's boundary function.
https://www.mathworks.com/help/matlab/ref/boundary.html
You can then use the trimesh function to create the figure
This question shows the input data and what was produced using this method: How do I create a 3D polygon/mesh over data points?
I am working with structured 2.5D and unstructured 3D data, which generally is available in (X,Y,Z) coordinates, i.e. point clouds. Now I want to impose a regular voxel grid onto the data. This is not meant for visualization purposes, but rather for "cleaning" or fusing the data. I imagine cases, where e.g. 3 points fall within the volume of one voxel. Then I would aim at either just setting this voxel to "activated" and discarding the 3 original points or alternatively I would like to calculate the euclidian mean of the points and return the thus "cleaned" point cloud as an irregularly structured one again.
I hope I could make my intentions clear enough: It's not about visualization and not necessarily about using volumetric cubes instead of points. It's only about manipulating possibily irregular point clouds in a structured way.
I was thinking about kd-tree or octree based solutions in this context, but can anybody point me in the proper direction? Hinting at existing MATLAB implementations would be most appreciated.
If the data is irregularly spaced, what you want to use is something which both smooths and interpolates your data points. A very good method for doing so is Gaussian process regression. Here's an example for the same problem but in 2D.
I have a formula that depends on theta and phi (spherical coordinates 0<=theta<=2*pi and 0<=phi<=pi). By inserting each engle, I obtained a quantity. Now I have a set of data for different angles and I need to plot the surface. My data is a 180*360 matrix, so I am not sure if I can use SURF or MESH or PLOT3. The figure should be a surface that include all data and the axes should be in terms of the quantity, not the quantity versus the angles. How can I plot such a surface?
I see no reason why you cannot use mesh or surf to plot such data. Another option I tend to use is that of density plots. You basically display the dependent variable (quantity) as an image and include the independent variables (angles) along the axis, much like you would with the aforementioned 3D plotting functions. This can be done with imagesc.
Typically you would want your axes to be the dependent variables. Could you elaborate more on this point?
If I understand you correctly you have calculated a function f(theta,phi) and now you want to plot the surface containing all the points with the polar coordinated (r,theta,phi) where r=f(theta,phi).
If this is what you want to do, the 2D version of such a plot is included in MATLAB under the name polar. Unfortunately, as you pointed out, polar3 on MatlabCentral is not the generalization you are looking for.
I have been able to plot a sphere with the following code, using constant r=1. You can give it a try with your function:
phi1=0:1/(3*pi):pi; %# this would be your 180 points
theta1=-pi:1/(3*pi):pi; % your 360 points
r=ones(numel(theta1),numel(phi1));
[phi,theta]=meshgrid(phi1,theta1);
x=r.*sin(theta).*cos(phi);
y=r.*sin(theta).*sin(phi);
z=r.*cos(theta);
tri=delaunay(x(:),y(:),z(:));
trisurf(tri,x,y,z);
From my tests it seems that delaunay also includes a lot of triangles which go through the volume of my sphere, so it seems this is not optimal. So maybe you can have a look at fill3 and construct the triangles it draws itself: as a first approximation, you could have the points [x(n,m) x(n+1,m) x(n,m+1)] combined into one triangle, and [x(n+1,m) x(n+1,m+1) x(n+1,m+1)] into another...?