I'm writing a toy vector graphics editor in Racket (as a way of learning both Racket and the math behind Bezier curves) and I'm wondering: is it possible to make Racket read input coming from a graphics tablet (stylus pressure, tilt) or any other pointer device recognized by xinput under Linux for that matter?
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I'm trying to make a program to enhance an image in LabVIEW. I have already program in matlab codes, but its some built-in functions are not working in LabVIEW since it is not present in LabVIEW mathscript module. The algorithm used to enhance the image is written below
input image in RGB
Contrast stretching of the model
RGB to HSI
contrast stretching of S&I
display the RGB image
So please help to implement this algorithm in LabVIEW
MATLAB can make a dll from your m file (including all of your built-in functions) and then you can call that dll from your Labview. To do so, you need to install MATLAB Compiler Runtime (MCR) on your machine (You don't need that, if you have already installed MATLAB).
If you want to have standalone dll file (not using matlab runtime), you need to use MATLAB Coder (which probably you need to buy it).
I recommend to use MCR first because it is easier to start with and more flexible in using MATLAB features.
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.
I am looking for a library to plot large data sets with a feature set similar to professional plotting tools (e.g. Matlab, Mathematica), but 3D accelareted. In particular I value
can be scripted like the professional tools above (flexible usage)
has a feature at least as big as these
fast (well, that's what the title says)
I can imagine (actually, I have very much in mind) something like this might exist for python - say, NumPy, SciPy. But I am not well-versed with these libraries yet. It would be great if I could convince people to abandon matlab.
Check out Mayavi, a 3d visualization package for Python that wraps around VTK. It's very flexible, has decent documentation, and hardware-accelerated rendering.
MathGL is cross-platform GPL library written in C/C++ which can plot huge data set (including 2- and 3-ranged data). Its list of graphics types is the same or larger than ones in Matlab and in Mathematica. MathGL have its own scripting language (MGL) and have interfaces to Python (including numpy), Fortran, Octave, Forth, Pascal and so on.
I am writing programs that are based on robots navigating through mazes (would involve stochastic programming).
Since it will involve heavy matrix handling (plus point for MATLAB) and simulating a robot (plus point for Prolog), I am in a dilemma between the choice of MATLAB and Prolog.
Note: I do have MATLAB at my work environment, hence cost is not an issue.
As mentioned previously, I am not sure if you are looking for comparisons between MATLAB and Python or MATLAB and Prolog. I can speak to the former, at least: MATLAB provides fast linear algebraic computation and a great IDE... and that's about it. Python will cost you much fewer headaches (and dollars), and you can manage "heavy matrix handling" nearly as easily if you tack on Numpy in particular, or SciPy in general.
Also, VPython (Visual Python) is a great 3D visualization tool that uses Numpy under the hood. I developed a robot simulator using VPython; you can see screenshots and example code (for simple wall-following maze navigation) that you can check out in a recent blog post.
Is there anything I can do with code in MATLAB for digital image processing that I can't do with Simulink's digital image processing toolbox or vice versa?
What difference is there between the two?
At the code level, there's not much difference between MATLAB and Simulink. Simulink provides an environment for constructing programs at a higher level of abstraction than text; the relationships that hold between code blocks is represented as arrows that pass between flowchart objects. You can then visualize the system as it operates at runtime, as data objects are passed visibly between the flowchart blocks. Simulink also lets you alter a part of the program in real time, so that you can see the effects of the local change without having to stop everything else.
Given how much image processing work is done in block-level dataflow languages such as LabVIEW, I would recommend starting with Simulink. Most industrial or creative image processing (like Apple's Shake) is done via a node-based interface. That's not to say that you couldn't use MATLAB code as well; it's just a bit more obtuse (this is a good example of a powerful library that was made with MATLAB code).