Creating figures for publication - artefacts in export - matlab

Now I am already trying for hours to get a satisfying vectorized output from a 3D matlab plot. I illustrated the artefacts of the resulting pdf exports in the following image (created with export_fig -> -r2000). I know that this problem is somehow related to the pdf viewer, but is there no solution to get a compatible output for all viewers?
In addition I have tried libs like plot2svg and matlab2tikz, but they seem to have problems with some of my surface plots resulting in completely different problems.
If there are no other ways to create vectorized outputs of the figures, do you have any tips for high quality bitmap figures (especially regarding to the font blurring)?

From my experience, exporting matlab figures results with less than satisfying results.
Personally, I prefer to export the data to other programs and create the plots there.
Excel does pretty good job with many types of figures. You may also try gnuplot.
I know this is not exactly the answer you are looking for but sometime instead of fighting Matlab, it is best to leave this jobs to better suited software.

Related

MATLAB Motion Tracking and Data

I'm very new to coding, and need some help with a project of sorts. I have segments of video, and I need to be able to track the motion of an object(s) through these segments, and get data like a mapped path, average and instantaneous velocities, etc. I'm trying to do this in MATLAB, and have the 2016a version installed. Any help is greatly appreciated.
Without knowing exactly what project you're working on, I can guess that Matlab is the wrong tool for this job.
I've been using Matlab near-daily for about four years now, but when I want to track an object in a video, I use Tracker.
Matlab is a good language for a beginning programmer because you can start doing numerical calculations, and plotting the results, very quickly. More advanced programmers tend to use Matlab to process data (Mathworks has many useful libraries for things like Fourier Transforms); to do linear algebra; to do quick numerical analyses; and to build scientific models. These applications are mainly in math, science, and engineering.
If you want to learn Matlab, I recommend you find a project which plays to Matlab's strengths.
If you want to analyse images and videos, I recommend that you learn a language which is used professionally for this purpose, such as Python or Java.

Matlab Image Histogram Analysis: how do I test for an underlying bimodal distribution?

I am working with image processing in MATLAB. I have two different images whose histogram plots are as shown below.
Image 1:
and
Image 2:
I have multiple images like those and the only distinguishing(separating) features is that some have single peak and others have two peaks.
In other words some can be thresholded (to generate good results) while others cannot. Is there any way I can separate the two images? Are there any functions that do so in MATLAB or any reference code that will help?
The function used is imhist()
If you mean "distinguish" by "separate", then yes: The property you describe is called bimodality, i.e. you have 2 peaks that can be seperated by one threshold. So your question is actually "how do I test for an underlying bimodal distribution?"
One option to do this programmatically is Binning. This is not the most robust method but the easiest. It might work, it might not.
Kernel Smoothing is probably the more robust solution. You basically shift and scale a certain function (e.g. Gaussian) to fit the data. This can be done with histfit in matlab.
There's more solutions for this problem which you can research for yourself since you now know the terms needed. Be aware though that your problem is not a trivial one if you want to do it properly.

How to export a saved fig file to eps using command?

Suppose I have a matlab figure s1.fig. I want to save it as a eps file. I can do this manually (file>export setup>export............). Is there any way to do this using command only without touching the file s1.fig.
You have a couple of ways. One is to use export_fig from Matlab FEX (which is the solution I favour more). However, you can also do:
figure()
...
saveas(gcf,'filename.ext')
Using saveas
In my experience, export_fig gives nicer plots, with antialiasing, and some other nice features. However, if you are using Matlab 2014b, the figure engine has changed and should give you good quality plots also.

Efficiently visualise large quantities of points with matlab.

I have a set of 3D points which numbers up around 1 million points. I am looking to visualise these with matlab.
I have tried the following functions:
plot3
scatter3
But they are both very sluggish. Is there a more efficient way to visualise this level of points in matlab? Maybe a way to mesh the points?
If not can anyone suggest a plug-in or even a different program for visualising 3D points?
You're going to run into efficiency issues no matter what plugin/program you use if you want all million+ points to show up in a plot. My suggestion would be to downsample. Use the plot3 or scatter3 function on every other point, or every nth point, until you get a figure that is not sluggish. As long as the variance in your data isn't astronomical, downsampling a little bit shouldn't affect the overall distribution of points (given that you have a million+ points). And any software that is able to display that much data without being sluggish is most likely downsampling/binning or using some interpolation technique to do so (so you might as well have control over it).
fscatter3 from the file exchange, does what you like.
Is there a specific reason to actually have it display that many points?
I Googled around a bit and found some people who have had similar issues (someone suggested Avizo as an alternate program but I've never used it):
http://www.mathworks.com/matlabcentral/newsreader/view_thread/308948
mathworks.com/matlabcentral/newsreader/view_thread/134022 (not clickable because I don't have enough rep to post more than two links)
An alternate solution would be to generate a histogram if you're more interested in the density of the data:
http://blogs.mathworks.com/videos/2010/01/22/advanced-making-a-2d-or-3d-histogram-to-visualize-data-density/
I you know beforehand roughly the coordinates of the feature you are looking for, try passing the cloud through a simple pass-through-filter, which essentially crops your point cloud. I.e. if you know that the feature is at a x-coordinate > 5, remove all points with x-coordinate < 5.
This filter could for the first coordinated be realized as
data = data(data(1,:) > 5,:);
Provided that your 3d data is stored in an n by 3 matrix.
This, together with downsampling, could help you out. If you still find the performance lagging, consider using something like the PCD viewer in PointCloudLibrary, check half way down the page at
http://pointclouds.org/documentation/overview/visualization.php
It is a stand alone app you could launch from matlab. I find it's performance far better than the sluggish matlab plotting tools.
For anyone who is interested I ended up finding a Point cloud visualiser called Cloud Compare. It is extremely fast and allows selection and segmentation as well as filtering on point clouds.

Matlab versus simulation products such as ANSYS and COMSOL

This may be the wrong place to ask this, but I can't find a better place on the SE network.
I've briefly worked with both Matlab and Ansys, and from what I have learnt/can gather, Matlab is a programming environment that has functions that perform common math, visualization and analysis operations. You primarily write programs in a textual fashion (.m files) or use Simulink to generate flow graphs (model-based development). Ansys on the other hand is primary a simulation environment where quite a lot can be done simply with the GUI (3D models, physics domains, configuration, display settings), and you can add equations at various points in the simulation engine in order to modify the simulation flow.
Whatever I understand is cursory and only serves as an overview. Can anyone give me a suitable real-world comparison between Matlab and Ansys (or any other simulation product such as COMSOL) that would allow us to understand when to use which, and the weaknesses of each system.
I haven't used Ansys, but Ansys is often compared with Comsol, and I've used Comsol and Matlab for years.
Matlab:
Programming language and environment that runs it. Which means it can do anything (that any other programming language can do). What are its highlights, compared to other languages?
Hundreds of built-in functions to work with Matrices. For example, in one project I needed to do simple matrix algebra (add, multiply, scale matrices), and also needed singular value decomposition. SVD is not something you could write in 50 lines of code, so I needed a ready-made library. At the time I used a library for Java, and wrote my own code for representing matrices and doing matrix algebra on them. That's a few hundreds of lines of code. Had I used Matlab, it would have been about ten lines of code, because all of it is there. I would have needed only to type help svd to find out how to use it. However, if you don't need any of that, stay away from Matlab at all costs! There are much better languages that are free.
Great to use as a calculator that is always open on the desktop, and can do back-of-the-envelope style calculations.
Plotting graphs. Many academics recommend Matlab as the tool of choice for producing publication-quality graphics. These can be exported as PDF and imported into Inkscape for further editing. The best thing is that commands for plotting a graph could be put into a script file, and then parts of it can be changed later as needed, which can save a lot of work compared to manually drawing a graph (imagine you wanted to change the axes or symbols used to present the data points).
Personally, I also use it for curve-fitting. It has many toolboxes, one of which is a neat tool that allows me to find equations that model a set of data points.
Comsol:
Specialised tool for solving partial differential equations (PDEs) on complicated domains using the finite element method (FEM). This might sound obscure, but many real-world engineering needs reduce to this. Such things as:
Finding loads, stresses and strains in civil engineering structures with complicated real-world geometry (what happens when there is gusty wind blowing onto a building or bridge?)
How do currents flow in particular conductive objects?
Chemical reactions in various industrial reactors.
What is the power efficiency of a generator (magnet spinning in coil) design?
How to place aircon outlets in a nontrivially-shaped room to achieve both good temperature distribution and good efficiency?
Comsol, as any other FEM tool that can work with arbitrary equations, can do multiphysics, which means, for example, that one could solve for chemistry of a battery, as well as the temperature and pressure, and how that feeds back into the chemical reaction (speeds up or slows down). Compared with a tool where you need to provide the equations, in Comsol, most of the things that would be needed to solve most problems are already there, and just need to be selected and applied to the geometry, which is also built inside Comsol. Also, equations of arbitrary description can be introduced.
The physical descriptions of how these physical substances behave are called PDEs.
Once Comsol has finished solving a problem, the data could be exported for post-processing into Matlab, which has much more versatile tools for manipulating data and making various plots.