Undocumented MEX API in MATLAB

by Pavel Holoborodko on July 19, 2013

It is not a secret that MATLAB has many undocumented (or deliberately hidden) features and commands. There are even excellent website & book devoted specifically to this topic: Undocumented Matlab

However most of the findings are related to MATLAB language itself and investigations on undocumented MEX API seems to be missing (or scarce at least).

During development of our toolbox we have found lots of hidden functions which can be helpful for creating speed-efficient extensions for MATLAB using native languages.

Here we want to explain some of them in details and provide complete list of undocumented MEX API functions.

Please note that there is a risk in using the functions – MathWorks can change / remove some of them in next versions. It is additional burden for developer to stay tuned and update their toolboxes on time.

Reduced OOP capabilities of MATLAB

Starting from version 2008b MATLAB allows user to introduce custom-type classes by classdef keyword. MATLAB was late on adding object oriented features – I can only image how hard it was for developers at MathWorks to add OOP constructs to purely procedural language which follows entirely different philosophy. (Yes, objects could be created using structs and special folder structure in earlier version of MATLAB – but that was just ugly design, MathWorks will not support it in future).

They still don’t have full support for OOP features though. The most important missing features are:

  • It is prohibited to have destructor for custom non-handle classes.
  • It is not possible to overload assignment-without-subscripts operator (e.g. A = B).

I don’t know the reasons why these fundamental OOP paradigms are not implemented in MATLAB – but this disables creating powerful virtual machine-type of toolboxes.

In that case MATLAB objects would have only one property field – ‘id’, identifier of variable stored in MEX module – virtual machine (e.g. pointer to C++/C object). MEX module would only need to know ‘id’ of objects and what operation to conduct with them (+, -, *, etc.) – all processing would be done in MEX. Heavy data exchange between MATLAB and MEX libraries would be completely unnecessary. MATLAB would act as just an interpreter in such scenario. Moreover MEX API could be simplified to several functions only.

Deep-Copy access to object properties from MEX library (Official)

Unfortunately we are restricted to current architecture – where all the data are allocated / stored on MATLAB side and we have to transfer it from MATLAB to MEX library in order to work with it.

Official MEX API provides two functions to access object properties from within MEX library: mxGetProperty and mxSetProperty.

Both functions share the same major problem – they create deep copy of the data!

Imagine the situation when your object is a huge matrix with high-precision elements and it occupies 800MB of RAM. If we want to access it in MEX library (e.g. transpose) we would call mxGetProperty which will do ENTIRE COPY of your object’s property – wasting another 800MB!

Obviously this cannot be accepted, not speaking of totally reduced performance (copying could take a while for such amount too).

Copy-Free access to object properties from MEX library (Undocumented)

In search for remedy we found similar (but) undocumented functions we can use to get shared access to objects properties (32-bit):

extern mxArray* mxGetPropertyShared(const mxArray* pa, 
                                    unsigned int index, 
                                    const char * propname);
extern void mxSetPropertyShared(mxArray* pa, 
                                unsigned int index, 
                                const char * propname, 
                                const mxArray* value);

Functions can be used as one-to-one replacement for official functions. mxGetPropertyShared just returns pointer to existing property without any copying. mxDestroyArray can still be called on returned pointer (Thanks to James Tursa for correction).

Full list of MEX API functions

We have extracted full list of usable MEX functions from libmx.dll and libmex.dll (MATLAB 2012b 32-bit) – two main MEX API dynamic libraries. It includes functions from official API as well as undocumented ones:

The distinctive feature of the list – it provides de-mangled C++ names of functions, with type of arguments and return value (not published before to the knowledge of author). This makes usage of undocumented functions much easier.

Take a look on function list – there are a lot of interesting ones, like mxEye, mxIsInf, mxFastZeros, mxGetReferenceCount and many others.

Moreover it is possible to see high level C++ classes MathWorks developers use for work. For example, now it is clear that fundamental type mxArray_tag – is not a plain-old-struct anymore, it has member-functions and behaves more like a class. It even has custom new/delete heap management functions and overloaded assignment operator=. Reverse-engineering of these functions might reveal the exact & complete data structure of mxArray_tag.

Actually with some effort internal mxArray_tag class from MathWorks might be used in third-party MEX files now. How much more easier this would be instead of clumsy mx**** functions!

Please feel free to leave your requests or comments below.

{ 2 comments… read them below or add one }

Brad Stiritz July 25, 2013 at 1:25 am

Hi Pavel,

Thanks for your very interesting article. I didn’t follow the exact logic of how the two missing OOP features you listed enable the “virtual machine” functionality? Perhaps you could please add a footnote here or a URL if explained elsewhere? I would really like to understand via a code example how this would work. Thanks for your consideration, Brad


Pavel Holoborodko July 25, 2013 at 2:14 am

Hi Brad,

Thank you for your comment.

My conclusion was the opposite – absence of these two features disable us from creating “virtual machine” – type of toolboxes. Sorry for my unclear statement, my Engrish needs improvement.

I spent few days debugging & doing reverse-engineering of MATLAB’s core in attempts to find undocumented functions to implement these features manually – without any luck unfortunately.


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