I'm using mayavi in python to visualize some data. I have a surface in 3D space and I want to map an image to it. I have looked at mayavi documentation and all I could find was this, which really doesn't help me much. Has anybody done something like this before?
I found that the mesh function actually does take a scalars argument, which then colors the corresponding point on the surface in accordance to the chosen colormap. I still however don't know how to map an arbitrary RGB image to the surface.
I guess you didn't saw the chapter "Python scripting for 3D plotting". There is a collection of the mayavi commands which can be used inside python. For example the section "3D Plotting functions for numpy arrays". If you follow the links you find some description about the functions and a small example for each of them.
For your case you should take mesh or surf. Both functions are kind of equal, but are different. For example the surf function is more a subfunction of mesh, which is my opinion. You don't really have to define x and y-coordinates, you just need the z-coordinates in a 2D array. If you want to use mesh you have to pass all three coordinates (x,y,z) as 2D arrays.
I would suggest to check the examples.
Is this an answer to your question? Maybe you should be more specific about what you want to do.
Have a nice day and Happy Holidays.
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I am working in my graduation project and one of the tasks I am required to draw a 3D shape(for example an ellipsoid using vtkSampleFunction), this represents the heart for example. I need to change the color of certain areas in that shape and make color gradients using 2 colors for example. How can this be achieved? All I could find is that cant be done without having polydata(points) and I dont know how to access specific points on the outline of my shape. Any help would be appreciated
I tried millions of ways to access points on the outline of my shape but I cant find anyway to do it.
I am new to VTK so please try to simply any answer. Thank You
If you are looking for a way to extract all the points inside a surface, you can use the vtkSelectEnclosedPoints method. For example, if you want to find out which all points in pointsPolydata lie inside the surface surfacePolydata, you can use the below example.
select = vtkSelectEnclosedPoints()
select.CheckSurfaceOn ()
select.SetTolerance(0.001)
select.SetInputData(pointsPolydata)
select.SetSurfaceData(surfacePolydata)
select.Update()
outPut=select.GetOutput()
The outPut polydata will have an array named "SelectedPoints", with 0 for point outside the surface and 1 for points inside the surface.
For more details, refer vtkSelectEnclosedPoints
I have a triangle mesh and look for a way to get programmatically for a given (x,z) 2D point all y coordinates which are represented by the mesh (x,y1,z),(x,y2,z) ..., preferable in python. I have the mesh stored in one of the common file formats (.stl , .obj ...)
The problem behind this question is that i convert a 2D face image into a 3D mesh of the face (using the marvelous https://github.com/sicxu/Deep3DFaceRecon_pytorch project) and then want to map the depth information of the 3D model back to the 2d image (to build something fancy in blender ...)
I finally found a solution for the problem which is both slow and inelegant but does the job for me for now.
I use section_multiplane function of the trimesh python library for that. Basically i use this function to intersect the mesh with 2d planes parallel to the y,z-plane and calculate the depth values by analyzing the resultant 2D Path. The library is very fast in calculating the intersections but the part i wrote - extracting the depth information from the 2D Paths - is painfully slow right now. (which doesnt matter in my particular application)
The code for that I have now is deeply interwoven in my particular application so it doesn't make sense to share it but if someone is interested in this approach there is a very helpful example included in the trimesh library which covers the crucial points: section_multiplane example
I am sure there are much more elegant solutions for this problem available but I wanted to share this approach in case somebody struggles finding a better approach too ...
Heatmap displaying the extracted depth information:
depth info:
Since some years ago I use matlab for my plots (mostly density plots), but now I want to change to matplotlib. I have a problem trying to figure out how to get analogous plots in matplotlib. I have to represent a 2D array. In matlab I used to use the surf function, and then change to view(2) (az=0 and el=90). An example:
surf(X,Y,log10(z),'FaceColor','interp','EdgeColor','none')
view(2)
In matplotlib I have tried some functions, but I have not got the same feeling. m3plot is a computationally expensive toolkit and it is not the same as using surf. imshow does not allow to use log functions in his arguments (like the example), and log values is something mandatory for me. Then it is pcolor, but I can not find a 'FaceColor'-like option to smooth the edges. I would like to know if someone knows what is the best equivalent in matplotlib.
Thank you for your time!
Try installing mayavi which has the surf function (mayavi is a fully-blown 3D visualisation library using hardware acceleration)
Finally, the solution that suits me is to use the routine pcolormesh(). This combined with the option shading='gouraud' interpolates the data and smooth the edges. In addition, it works pretty well with large arrays in comparision with pcolor.
I want to draw 3D primitives like spheres, cylinders and planes (patches) in a 3D plot and I would like to be able to interactively rotate, translate and zoom the scene. I want to do that in Python. I'm use to use Matplotlib for 2d graphs but I never worked with 3D graphics with Python.
Any suggestions?
Any link to tutorials?
Any ideas?
If you're used to matplotlib, then mplot3d is probably a good option if it meets your requirements.
Alternatively there is VPython. This allows you greater freedom to create arbitrary objects and manipulate them, but, of course, more to learn.
As far as I am aware there is no inbuilt polygon functionality for Python. I want to create a 3D map and figured that polygons would be the best way to go about it.
Not wanting to reinvent the wheel I did some googling and found that there's a lot of Python stuff out there, but I couldn't find what I wanted. Thus before I reinvent the wheel (or invent it a whole), does anybody know of a Polygon system for Python?
Note that it does need to be 3D (I found quite a few 2D ones). Note also that I am not interested in the displaying of them but in storing them and the datastructure within Python.
Thanks
One of the most complete geography/mapping systems available for Python that I know about is GeoDjango. This works on top of the Django, an MVC framework. With it comes a large collection of polygon, line and distance calculation tools that can even take into account the curvature of the earth's surface if need be.
With that said, the quickest way I can think of to produce a 3D map is using a height map. Create a two dimensional list of tuples containing (x, y, z) coordinates. Each tuple represents an evenly spaced point on a grid, mapped out by the dimensions of the array. This creates a simple plane along the X and Z axes; the ground plane. The polygons that make up the plane are quads, a polygon with four sides.
Next, to produce the three dimensional height, simply give each point a Y value. This will create peaks and valleys in your ground plane.
How you render this will be up to you, and converting your grid of points into a polygon format that something like OpenGL can understand may take some work, but have a look at Visual Python, its the simplest 3D library I've seen for Python.
I think you mean Polyhedron, not Polygon .. and you might wanna look at vpython
CGAL is a C++ geometry library which, amongst other things, models Polyhedra (3D flat-surfaced shapes)
It has Python bindings available. The documentation for the Polygon3 class is here:
http://cgal-python.gforge.inria.fr/Manual/CGAL.Polyhedron.html#Polyhedron_3