I would like to know which programming languages can be called by matlab.
for example I am quiet sure that matlab can use C function and maybe java.
I need this stuff for an industrial project so I need something that works well.
For example I have found some tutorial to call python function in matlab but they look to me not very good and stable solution.
I am not an expert of the field and my knowledge of matlab is very limited. So please be patience with the answer.
This project is related to machine learning and the software will probably run on a cluster.
EDIT according to this post Embedding Python in MATLAB seems that there are problem when importing numpy using python.
The only reason to use python in this environment is the numpy library.
Without that it is almost useless to me.
Do you think that I will encounter similar problem using java or c calling some mathematics libraries?
Most interfaces are listed here:
http://www.mathworks.de/de/help/matlab/external-interfaces.html
For Python I see different solutions:
COM on Windows platforms. This requires to register an application, check if this is possible and allowed on the cluster.
XMLRPC or SOAP. You may need to use Java-Classes in Matlab, but as you already realised this is very simple. Verify that the cluster has a Java VM available, many run matlab without java.
You can embed python code into c, which allows you to write mex functions which run c code: http://docs.python.org/2/extending/embedding.html
Use the command line interface for python.
Besides the documented limitations, I don't see any problem with these solution. If you are familiar with C or Matlab, I would choose the second or third option. This allows you to write a wrapper to access python with a very fundamental knowledge of matlab.
There are two main methods to achieve this:
Write MEX functions, which is basically C/C++ or Fortran methods, which use Matlab-specific API. You can then call these methods like you would any function written in M-language file. This is described here.
Call external libraries written in Java, .Net, C/C++, and COM servers. This is described here.
Both methods require good understanding of what you are doing, although I would argue that writing MEX function is much harder then referencing an existing library.
I'm not sure about programming language but You can do it by EXE file by running run('C:\someCompiledProgram.exe')
And if you need result you can use:
[status, result] = system('command')
You can read about it here:
http://nf.nci.org.au/facilities/software/Matlab/techdoc/ref/system.html
Related
I need to rewrite the linkage function in matlab. Now, as I examine it, I realized there is a method called linkagemex inside of it. But I simply cannot step into this method to see its code. Can anyone help me out with this strange situastion?
function Z= linkage (Y, method, pdistArg, varargin)
Z=linkagemex(Y,method);
PS. I think I am pretty good at learning, but matlab is not so easy to learn. If you have good references to learn it well, feel free to let me know. Thanks very much for your time and attention.
As #m.s. mentions, you've found a call to a MEX function. MEX functions are implemented as C code that is compiled into a function callable by MATLAB.
As you've found, you can't step into this method (as it is compiled C code, not MATLAB code), and you don't have access to the C source code, as it's not supplied with MATLAB.
Normally, you would be at kind of a dead end here. Fortunately, that's not quite the case with linkagemex. You'll notice on line 240 of linkage.m that it actually does a test to see whether linkagemex is present. If it isn't, it instead calls a local subfunction linkageold.
I think you can assume that linkageold does at least roughly the same thing as linkagemex. You may like to test them out with a few suitable input arguments to see if they give the same results. If so, then you should be able to rewrite linkage using the code from linkageold rather than linkagemex.
I'm going to comment more generally, related to your PS. Over the last few days I've been answering a few of your questions - and you do seem like a fast learner. But it's not really that MATLAB is hard to learn - you should realize that what you're attempting (rewriting the clustering behaviour of phytree) is not an easy thing to do for even a very advanced user.
MathWorks write their stuff in a way that makes it (hopefully) easy to use - but not necessarily in a way that makes it easy for users to extend or modify. Sometimes they do things for performance reasons that make it impossible for you to modify, as you've found with linkagemex. In addition, phytree is implemented using an old style of OO programming that is no longer properly documented, so even if you have the code, it's difficult to work out what it even does, unless you happen to have been working with MATLAB for years and remember how the old style worked.
My advice would be that you might find it easier to just implement your own clustering method from scratch, rather than trying to build on top of phytree. There will be a lot of further headaches for you down the road you're on, and mostly what you'll learn is that phytree is implemented in an obscure old-fashioned way. If you take the opportunity to implement your own from scratch, you could instead be learning how to implement things using more modern OO methods, which would be more useful for you in the future.
Your call though, that's just my thoughts. Happy to continue trying to answer questions when I can, if you choose to continue with the phytree route.
You came across a MEX function, which "are dynamically linked subroutines that the MATLAB interpreter loads and executes". Since these subroutines are natively compiled, you cannot step into them. See also the MATLAB documentation about MEX functions.
I'm looking for a function in Julia to estimate coefficients for an ARMA process.
For example using the Prediction Error Model as pem and armax in Matlab (part of system identification toolbox) do. pem documentation and armax documentation.
I've looked at the following packages, but can't see that they do what I'm looking for:
TimeSeries.jl
TimeModels.jl
One solution is of course to use Matlab.jl and use the Matlab functions, but I was hoping to do it all in Julia.
If there isn't anything right now, does anyone know of if there are any good Julia functions for multidimensional numerical minimisation (like Newton-Raphson), that can be used for implementing a PEM function?
UPDATE: I've just pushed a module to github called RARIMA.jl. This module can be used to estimate, forecast, and simulate ARIMA models (of which ARMA is a special case). Some of the functions are implemented in Julia, others (particularly estimation) call equivalent R functions using the RCall package which you will need to install and verify it works prior to using RARIMA. The package isn't officially registered (yet), so Pkg.add("RARIMA") won't work for now. If you want to use RARIMA, instead try Pkg.clone("https://github.com/colintbowers/RARIMA.jl"). If this fails, you can file an issue on the repository github page, but be sure to check RCall is installed and working before doing this. Cheers, I'll come back and update here if/when the package is officially registered.
ORIGINAL ANSWER: I just had a glance at the source, and TimeModels does not appear to have any functionality for estimating ARIMA models, although does have one function for simulating them. Given time though, I suspect this will be the package that deals with ARIMA modelling. The TimeSeries package is more about building the object type TimeSeries rather than implementing time series models, so I would be surprised if ARIMA modelling is ever merged into that package.
As near as I can tell, at this point if you want a fully functioning ARIMA package you'll need to use Matlab or R. The R one is very good (see the forecast package written by Rob Hyndman - it is very nice) and is probably easier to interface with from Julia than the Matlab option. Of course, the other option is to start it yourself and merge the code with the TimeModels package :-)
In terms of optimization procedures, Julia has a fair few that are written in Julia, and can be found under the JuliaOpt umbrella. The Optim package in particular is quite popular and well developed. However, most of the people I know who are really into this stuff use NLOpt which is a free open source library callable from many languages (including Julia). I have heard nothing but good things about this library from people who tend to work with this stuff 24/7.
I would like to write some pieces of code in Scala . It is important for me that this code can be called from matlab. AFAIK java code can easily be integrated with matlab. http://www.mathworks.co.uk/help/matlab/ref/javamethod.html
Is this valid also for scala code?
It is also valid for Scala code. Just pretend that you're doing Java interop (e.g. a method called + would actually be $plus) and make sure scala-library.jar is in Matlab's classpath (e.g. using javaaddpath).
Incidentally, I've done Java/Matlab interop before, and it's not as "easily integrated" as one might hope. Passing data is kind of awkward and you tend to trip on classloader and/or classpath issues every now and then.
I'd be wary of planning a big project with lots of tightly-connected interop. In my experience it usually works better using the Unix mindset: make independent tools that do their own thing well, and chain them together to get what you want. For instance, I routinely have Scala write Matlab code and call Matlab to run it, or have Matlab use system to fire up a Scala program to process a subset of the data.
So--calling Scala from Matlab is completely possible, and for simple interfaces looks just like Java. Just try to keep the interface simple.
You could encapsulate your Scala code in another language that's easily called by Matlab, such as Java of C. Since you seem to know about Java, you could use these examples to learn to encapsulate your Scala methods inside Jave methods that you can call from Matlab. A number of other methods are available to you with different languages (MEX-files, loadlibrary, etc...)
A friend of mine needs to implement some statistical calculations in hardware.
She wants it to be accomplished using VHDL.
(cross my heart, I haven't written a line of code in VHDL and know nothing about its subtleties)
In particular, she needs a direct analogue of MATLAB's betainc function.
Is there a good package around for doing this?
Any hints on the implementation are also highly appreciated.
If it's not a good idea at all, please tell me about it as well.
Thanks a lot!
There isn't a core available that performs an incomplete beta function in the Xilinx toolset. I can't speak for the other toolsets available, although I would doubt that there is such a thing.
What Xilinx does offer is a set of signal processing blocks, like multipliers, adders and RAM Blocks (amongst other things, filters, FFTs), that can be used together to implement various custom signal transforms.
In order for this to be done, there needs to be a complete understanding of the inner workings of the transform to be applied.
A good first step is to implement the function "manually" in matlab as a proof of concept:
Instead of using the built-in function in matlab, your friend can try to implement the function just using fundamental operators like multipliers and adders.
The results can be compared with those produced by the built-in function for verification.
The concept can then be moved to VHDL using the building blocks that are provided.
Doing this for the incomplete beta function isn't something for the faint-hearted, but it can be done.
As far as I know there is no tool which allow interface of VHDL and matlab.
But interface of VHDL and C is fairly easy, so if you can implement your code(MATLAB's betainc function) in C then it can be done easily with FLI(foreign language interface).
If you are using modelsim below link can be helpful.
link
First of all a word of warning, if you haven't done any VHDL/FPGA work before, this is probably not the best place to start. With VHDL (and other HDL languages) you are basically describing hardware, rather than a sequential line of commands to execute on a processor (as you are with C/C++, etc.). You thus need a completely different skill- and mind-set when doing FPGA-development. Just because something can be written in VHDL, it doesn't mean that it actually can work in an FPGA chip (that it is synthesizable).
With that said, Xilinx (one of the major manufacturers of FPGA chips and development tools) does provide the System Generator package, which interfaces with Matlab and can automatically generate code for FPGA chips from this. I haven't used it myself, so I'm not at all sure if it's usable in your friend's case - but it's probably a good place to start.
The System Generator User guide (link is on the previously linked page) also provides a short introduction to FPGA chips in general, and in the context of using it with Matlab.
You COULD write it yourself. However, the incomplete beta function is an integral. For many values of the parameters (as long as both are greater than 1) it is fairly well behaved. However, when either parameter is less than 1, a singularity arises at an endpoint, making the problem a bit nasty. The point is, don't write it yourself unless you have a solid background in numerical analysis.
Anyway, there are surely many versions in C available. Netlib must have something, or look in Numerical Recipes. Or compile it from MATLAB. Then link it in as nav_jan suggests.
As an alternative to VHDL, you could use MyHDL to write and test your beta function - that can produce synthesisable (ie. can go into an FPGA chip) VHDL (or Verilog as you wish) out of the back end.
MyHDL is an extra set of modules on top of Python which allow hardware to be modelled, verified and generated. Python will be a much more familiar environment to write validation code in than VHDL (which is missing many of the abstract data types you might take for granted in a programming language).
The code under test will still have to be written with a "hardware mindset", but that is usually a smaller piece of code than the test environment, so in some ways less hassle than figuring out how to work around the verification limitations of VHDL.
I would like to call a matlab function from mathematica. How best to do that?
I have found an ancient post on Wolfram site describing a way to do this, is this still the way to connect the two?
You can try NETLink for this at least under Windows:
In[1]:= Needs["NETLink`"]
matlab = CreateCOMObject["matlab.application"]
Out[2]= «NETObject[COMInterface[MLApp.DIMLApp]]»
And then you can invoke Matlab functions:
In[4]:= matlab#Execute["version"]
Out[4]= "
ans =
7.9.0.529 (R2009b)
"
In[5]:= matlab#Execute["a=2"]
matlab#Execute["a*2"]
Out[5]= "
a =
2
"
Out[6]= "
ans =
4
"
HTH
You can use mEngine. The precompiled Windows MathLink executable works with Mathematica 8. On Windows you may need to add MATLAB to the system path.
The advantage of this compared to the NETLink method is that transferring variables between Mathematica and MATLAB will be as easy as mGet["x"] or mPut["x"]. Although this might be possible with NETLink too, the advantage of mEngine is that you don't need to implement it yourself (which is great if like me you don't know anything about COM or .NET)
I would imagine that this is a difficult problem in general, but can be easily solved with a little programming for a particular case. I'll demonstrate with C#.
I would build a string of calls, like so.
Mathematica calls a C# program, through MathLink. This is near trivial to setup, and Mathematica has a sample project in Mathematica\8.0\SystemFiles\Links\NETLink directory.
C# program calls Matlab. There are several ways to make this call, and this handy link describes how to do it and offers sample code.
C# program returns Matlab results.
All in all I could do this in less than 50 lines of C# code, for a specific problem. Not too much work, in other words. Possible problems are data conversion, but if you want to send back and forth arrays of data, MathLink offers a lot out of the box. Similarly Mathematica can be linked to MATLAB through Java, though I haven't done that myself.
Perhaps the easiest connection could be made through Python. Mathematica offers an installable MathLink python library, located at Mathematica\8.0\SystemFiles\Links\NETLink, and Matlab has an addon library called PyMat, which can be downloaded here, but this package hasn't been maintained for a long time and supports only the most ancient of Matlabs.
Alternatively you can forgo Matlab altogether in favor of SAGE and/or numpy.
There is now a new package for this --- MATLink. It is the most complete such package I am aware of. (Disclaimer: I'm one of the developers of MATLink.)
MATLink lets you ...
seamlessly call MATLAB functions form Mathematica
transfer data between the two systems
Most MATLAB data types are supported, including sparse arrays, structs and cells.
A more complete description is available here. For detailed examples, see the website.