How to create a ones array in mex ?

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Gauraang Khurana 2016-1-5

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https://ww2.mathworks.cn/matlabcentral/answers/262727-how-to-create-a-ones-array-in-mex

编辑： James Tursa 2016-1-7

I am coding in c++ with mex interface. I need to create an array of ones of size 5 * 1. I am trying to use the mexCallMATLAB function but it gives me an error. Can someone please help me with this ?

Code : mexCallMATLAB(1,Ones,1,createOnes,"ones"); I was hoping that the output array will be displayed in Ones and the createOnes array is an array of size 5 * 1.

Error : Error using ones Size vector should be a row vector with real elements.

Please guide me. Thanks in advance

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James Tursa 2016-1-6

在 MATLAB Online 中打开

I agree with Stephen and Adam and others ... your proposed approach of using mexCallMATLAB is not the way to go. Adding A+B at the m-file level is without question going to be faster than passing A and B into a mex routine and then using mexCallMATLAB to call the "plus" function. If speed is an issue, the general advice is to avoid mexCallMATLAB if at all possible (e.g., hand-code your own C/C++ loops to do specific calculations).

Matrix transposing is a separate issue. If the transpose is involved in a matrix multiply and that is the only time you need the transpose, then including the transposing with the matrix multiply is the way to go because MATLAB will not physically do the transpose but will call the BLAS routines with appropriate flags, and the transpose will be accomplished with internal indexing changes. E.g., at the m-file level, with A and B being 2D matrices,

C = A'*B; % <-- A' is not physically formed. A flag is passed to BLAS routine

is better than

At = A'; % <-- A' is physically formed.
C = At*B;

But if you need the transpose for some other reason, then calling "transpose" or "ctranspose" (depending on your needs) will be pretty fast. There are ways to beat MATLAB's transpose functions for speed sometimes by using certain memory blocking schemes in a C/C++ mex routine, but I will not offer up that code here since I doubt this is where your real speed bottleneck is.

Walter Roberson 2016-1-7

I didn't know that the transpose would not actually be done in that case... interesting. Does the trick also work with A.'*B ?

James Tursa 2016-1-7

编辑：James Tursa 2016-1-7

在 MATLAB Online 中打开

Yes. The BLAS matrix multiply routines include character flag arguments for both A and B, 'N' for No transpose, 'T' for Transpose, and 'C' for Conjugate transpose. The MATLAB parser is smart enough to recognize this syntax at the m-file level and pass the flag instead of doing the physical transpose. Of course, I don't have access to MATLAB parser code, but this can easily be concluded based on timing results compared to equivalent mex code calling BLAS routines. Having said all that, I would remind you that MATLAB complex variables store the real part and imaginary part separately in memory, whereas the BLAS complex routines expect that data to be interleaved (ala Fortran). So rather than copy all the memory over to an interleaved state, call the complex matrix multiply, then copy the result to separated states, the multiply is accomplished with a series of real BLAS matrix multiply calls instead with appropriate factors for adding/subtracting the intermediate results. The factor (any real number) is an argument to the BLAS routine.

For LAPACK calls where one needs to call the complex routine, the memory copies into and out of an interleaved state must be done.

I don't know whether the MATLAB parser has gotten smart enough to recognize naked conjugates, however. E.g., something like this:

C = A * conj(B);

can be done at the BLAS calling level by simply passing a -1.0 as the factor argument to apply on the 2nd matrix imaginary part instead of a 1.0. I haven't checked lately to see if the MATLAB parser has gotten smart enough to do this or not. It used to physically do the conjugate and maybe still does.

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