{"id":5429,"date":"2014-07-11T08:58:40","date_gmt":"2014-07-11T12:58:40","guid":{"rendered":"https:\/\/blogs.mathworks.com\/pick\/?p=5429"},"modified":"2014-07-11T08:58:40","modified_gmt":"2014-07-11T12:58:40","slug":"c-mex-programming-tutorial-examples","status":"publish","type":"post","link":"https:\/\/blogs.mathworks.com\/pick\/2014\/07\/11\/c-mex-programming-tutorial-examples\/","title":{"rendered":"C-MEX Programming Tutorial Examples"},"content":{"rendered":"
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Sean<\/a>'s pick this week is \"C-MEX Programming Tutorial Examples\"<\/a> by Ilias Konsoulas<\/a>.\r\n <\/p>\r\n <\/introduction>\r\n

\r\n <\/div>\r\n

I spent the last few days at the 2014 SIAM conference in Chicago manning the MathWorks booth with a few of our developers.\r\n We were asked many questions about the products, new features, life at MathWorks, and of course for t-shirts and rubik's\r\n cubes.\r\n <\/p>\r\n

One of the questions I was asked was along the lines of: \"How do I get started with MEX?\". MEX<\/a>, which is short for \"MATLAB Executable\", is compiled C\/C++ or Fortran code with the appropriate MATLAB wrappers on it so\r\n that it can be called at the command line like any other MATLAB function. Personally, I haven't written any productive C\/C++\r\n code since high school about ten years ago. When I need C or C++ code, I develop the algorithm in MATLAB and then use MATLAB Coder<\/a> to automagically generate equivalent C code.\r\n <\/p>\r\n

I had found Ilias' submission a while ago and added it to the \"to experiment with list\". Now, it allowed me to answer this\r\n question while sounding knowledgable and getting the user started on his journey.\r\n <\/p>\r\n

The submission comes with nine heavily commented C files that do simple matrix manipulations like summing and reshaping as\r\n well as a readme file that documents the package. The C files show the MEX syntax, required headers and some good programming\r\n practices like error checking.\r\n <\/p>\r\n

Curious if I could actually write my own hand-written MEX file, I challenged myself to write one which calculates the sum\r\n of the diagonal of a matrix. I started by editing Ilias' transposeM.c<\/tt> which should be a good blueprint.\r\n <\/p>\r\n

After some time, having it fail to compile 20ish times, and getting stuck in an infinite loop only once(!), (I forgot to increment\r\n i<\/i> in the for<\/tt>-loop), it works!\r\n <\/p>\r\n

Here's a snapshot of the file:<\/p>\r\n

<\/p>\r\n

That was an exercise in frustration. How about we just use MATLAB Coder to do this? First, I wrote a MATLAB function to\r\n calculate the sum of the diagonal; there happens to be a function called trace<\/tt> that does this:\r\n <\/p>\r\n

<\/p>\r\n

Now to generate C code, you can use the MATLAB Coder App to generate code interactively, or do it programatically with codegen<\/tt><\/a>. I'll take the latter approach since it's easier to automate.\r\n <\/p>

% Input must be a double precision matrix of size \"up-to-inf\" by \"up-to-inf\"<\/span>\r\ninput_specs = coder.typeof(zeros,inf,inf);\r\ncodegen mytrace<\/span> -args<\/span> {input_specs}<\/span><\/pre>
This generates mytrace_mex<\/tt> which I can call like any other function.\r\n   <\/p>
rng(5) % reproducible<\/span>\r\nX = gallery('randhess'<\/span>,7); % a matrix<\/span>\r\nt = mytrace_mex(X); % use mex file<\/span>\r\ndisp(t)<\/pre>
   -0.1573\r\n<\/pre>
Now let's see if the two C implementations and the MATLAB implementation agree using the MATLAB unit testing framework<\/a>.<\/p>
% Build interactive test object<\/span>\r\nTester = matlab.unittest.TestCase.forInteractiveUse;\r\n\r\n% Assert equality<\/span>\r\nassertEqual(Tester,trace(X),traceM(X)) % My C implementation<\/span>\r\nassertEqual(Tester,trace(X),mytrace_mex(X)) % MATLAB Coder's implementation<\/span><\/pre>
Interactive assertion passed.\r\nInteractive assertion passed.\r\n<\/pre>
Comments<\/a><\/h3>\r\n   
Give it a try and let us know what you think here<\/a> or leave a comment<\/a> for Ilias.\r\n   <\/p>