I'm testing out an algorithm and saved a dataset with 100x20 values that I successfully import as a matrix in Matlab and plot it using the surface command. That plot looks like.
Then I do the exact same thing but for a data set with 10 times the values on the y-axis (a 1000x20 matrix). This results in following picture, where the black rectangle are z-values seemingly at 0 rendered:
It's the exact same test so the same values should still exist, for the 0-100 part of the y-axis. The values look like they were imported correctly in the table before plotting but why does the surface plot look completely wrong?
There not much code... All i type is
x=data(1, 2:end)
y=data(2:end, 1)
test=data(2:end, 2:end)
and surface(x,y, test)
where test is the imported matrix using drag and drop to matlab and x, y are just simple vectors with correct dimensions since surface complains otherwhise.
looking through the table, there are no irregularities and using max and min shows nothing strange either:
Related
Hello guys I am trying to export a mesh from MSC Patran and then plot it in Matlab. The mesh can be of arbitrary shape. I have the x, y and z coordinates of all the nodes. So far I have tried many different options and here is why they failed:
Surfc() with meshgrid and griddata:
I generated a grid on x-y plane with meshgrid and then used griddata to obtain the z matrix. But this plot only works when there is only 1 z value corresponding to an x-y pair. In other words, for this to work z must be of type z = f(x,y).
pdegplot() : I found out that matlab can import and plot .stl files. I tried converting my coordinate matrix format and plot it with this function but it doesn't work either. Because apparently in .stl files an edge can not be shared by more than 2 elements. However my FEM files are always (i hope) shell elements. This means 3 or more elements can share the same elements.
Surfc() with 3d meshgrid: I found out that meshgrid() can take 3 inputs (x,y,z) and create a 3d mesh. However this didn't work either. I used a very small mesh with about 1000 nodes and the code was trying to generate 3 matrices with 1000x1000x1000 elements. That means about 3 gb of memory for a 1000 node mesh. Whats more, surfc couldn't plot even that.
Somehow importing other file formats automatically: so far I have been using patran neutral files (.out). I manually read the file and extract x,y,z data from it. Patran can also export to parasolid, iges and step file formats. I looked for direct ways of importing and plotting these in matlab but such functions don't exist as far as I have looked.
Manually generating a grid: Matlab can create 3D objects (like [x,y,z] = sphere()) and Surfc() can plot these despite what I said in (1.) and the x,y,z matrices generated by sphere() are not 3 dimensional like in (3.) so I tried following this and manually generate a 3d grid from my FEM file just for testing. I found that z has repeating columns and in each column (which acts as a layer) there are n values of x and y. When I tried doing the same thing for my mesh manually, surfc() didn't work again. It plotted a really weird shape that I can't even describe.
Finding a 3rd party plotting software: I tried using (light) software like gnuplot and visit but so far I am all wet. I am open to suggestions if you know any (preferably open source) software that can directly plot patran neutral files. But the software has to be capable of contour plotting also. As I am calculating a quantity for each node in Matlab and then plotting its contour on the mesh.
So you can have a tetramesh?
You seem to be working with FEM-stile meshes, thus the standard surface-plotting function wont work. For FEM-meshes of different shape (not tetra) you may need to write your own function...
If you have the grid points and grid cell connectivities in say variables p and c, you can use the external Matlab FEA Toolbox to plot both structured and unstructured grids with for example the plotgrid command
% Cread grid struct.
grid.p = p;
grid.c = c;
grid.a = gridadj(p,c,size(p,1)); % Reconstruct grid cell adjacencies.
grid.b = gridbdr(p,c,grid.a); % Reconstruct boundary information.
grid.s = ones(1,size(c,2)); % Set subdomain numbers to 1 for all grid cells.
% Plot grid.
plotgrid( grid )
I have several dataset matrices x, y, andz, where z contains values at the positions x,y showing shifted (overlapping) parts of the same picture. x and y are rectangularly centered around different center positions for each dataset.
How can I combine the data in one plot using pcolor or similar? Note that it should be a rectangular plot in the end, but that not all data points are given due to the shift.
I now solved my own question by using the command hold on, which makes it possible to plot several times into the same figure. You just have to run it in between two plot commands.
I'm creating a line plot, where the y value of each point is the average value of vector i. The x value of each point is i.
I want to visualise the distribution of numbers in each vector, preferably all on the same graph.
Is there a way I can make a bar graph, where each bar, i, is something like a colorbar, representing the histogram of vector i. So essentially I want to end up with 20 or so bars, each being a histogram.
Or if there is a better way to visualise numerous histograms on a single plot, I'd like to hear it.
I solved the problem using Dan's solution. I took a histogram of each vector (with specific bin intervals), and stored them all in a 2D matrix (Each column is a complete histogram). Then displayed it with image() (Don't have access to imshow).
I did have to mess around with the axis labels though, as the image() function was plotting it according to the coordinates of the 2D matrix, rather than the values in the original vectors. Fixed that up with some calls to set(gca,'YTickLabel/YTick'). Also had to set the YDir back to 'normal' rather than 'reverse'. I think image() was flipping it.
I am trying to get a subset of an image from 4 points. Following the solution given in here I located the points and sorted them in terms of maximum and minimum x,y values. After that I did:
subim = image(x_min:x_max,y_min:y_max,:);
in order to obtain a sub-image formed by the rectangle contained in x_min:x_max,y_min:y_max, but this didn't work.
What am I doing wrong?
Like #Divakar answer you,
matlab image works with row and columns attribute as you can see in figure 1 on this help.
And in figure 2, they show how ( x , y ) axis are define. As you can see, y is the rows axis and x the columns.
So when you are using imshow or imtool to get coordinate on a figure, it's show in (x,y) instead of (row,col). Just by inverting your coordinate, you'll get what you need.
Be aware not all library or langague use the same order, like Numpy in python is same as Matlab but OpenCV is the inverse.
I have a 3D data set of a surface that is not a function graph. The data is just a bunch of points in 3D, and the only thing I could think of was to try scatter3 in Matlab. Surf will not work since the surface is not a function graph.
Using scatter3 gave a not so ideal result since there is no perspective/shading of any sort.
Any thoughts? It does not have to be Matlab, but that is my go-to source for plotting.
To get an idea of the type of surface I have, consider the four images:
The first is a 3D contour plot, the second is a slice in a plane {z = 1.8} of the contour. My goal is to pick up all the red areas. I have a method to do this for each slice {z = k}. This is the 3rd plot, and I like what I see here a lot.
Iterating this over z give will give a surface, which is the 4th plot, which is a bit noisy (though I have ideas to reduce the noise...). If I plot just the black surface using scatter3 without the contour all I get is a black indistinguishable blob, but for every slice I get a smooth curve, and I have noticed that the curves vary pretty smoothly when I adjust z.
Some fine-tuning will give a much better 4th plot, but still, even if I get the 4th plot to have no noise at all, the result using scatter3 will be a black incomprehensible blob when plotted alone and not on top of the 3D contour. I would like to get a nice picture of the full surface that is not plotted on top of the 3D contour plot
In fact, just to compare and show how bad scatter3 is for surfaces, even if you had exact points on a sphere and used scatter3 the result would be a black blob, and wouldn't even look like a sphere
Can POV-Ray handle this? I've never used it...
If you have a triangulation of your points, you could consider using the trisurf function. I have used that before to generate closed surfaces that have no boundary (such as polyhedra and spheres). The downside is that you have to generate a triangulation of your points. This may not be ideal to your needs but it definitely an option.
EDIT: As #High Performance Mark suggests, you could try using delaunay to generate a triangulation in Matlab
just wanted to follow up on this question. A quick nice way to do this in Matlab is the following:
Consider the function d(x, y, z) defined as the minimum distance from (x, y, z) to your data set. Make sure d(x, y, z) is defined on some grid that contains the data set you're trying to plot.
Then use isosurface to plot a (some) countour(s) of d(x, y, z). For me plotting the contour 0.1 of d(x, y ,z) was enough: Matlab will plot a nice looking surface of all points within a distance 0.1 of the data set with good lighting and all.
In povray, a blob object could be used to display a very dense collection of points, if you make them centers of spheres.
http://www.povray.org/documentation/view/3.6.1/71/
If you want to be able to make slices of "space" and have them colored as per your data, then maybe the object pattern (based on a #declared blob object) might do the trick.
Povray also has a way to work with df3 files, which I've never worked with, but this user appears to have done something similar to your visualization.
http://paulbourke.net/miscellaneous/df3/