Matlab has a variety of internal helper functions which are used by the main (documented) functions. Some of these helper functions are undocumented and unsupported, but may be helpful in their own right – not just as internal support functions.
In this post I want to present Matlab’s built-in ismembc helper function. This function is used within the stock Matlab ismember and setxor functions for fast processing of the core ismember functionality in “regular” cases: arrays of sorted, non-sparse, non-NaN data in which we’re only interested in the logical membership information (not the index locations of the found members). In such cases, ismembc can be used directly, saving ismember‘s sanity-checks overhead. ismembc uses the same interface (two inputs, single logical output) as ismember and can be a drop-in replacement for ismember for these “regular” cases.
The performance improvement may be significant: In a recent post, MathWorks’ Loren Shure presented different approaches for fast data retrieval, highlighting the ismember function. Let’s compare:
>> % Initial setup >> n=2e6; a=ceil(n*rand(n,1)); b=ceil(n*rand(n,1)); >> % Run ismember several times, to rule-out JIT compilation overheads >> tic;ismember(a,b);toc; Elapsed time is 2.882907 seconds. >> tic;ismember(a,b);toc; Elapsed time is 2.818318 seconds. >> tic;ismember(a,b);toc; Elapsed time is 3.005967 seconds. >> % Now use ismembc: >> tic;ismembc(a,b);toc; Elapsed time is 0.162108 seconds. >> tic;ismembc(a,b);toc; Elapsed time is 0.204108 seconds. >> tic;ismembc(a,b);toc; Elapsed time is 0.156963 seconds.
ismembc is actually a MEX file (%matlabroot%\toolbox\matlab\ops\ismembc.mexw32). Its source code is included in the same folder (%matlabroot%\toolbox\matlab\ops\ismembc.cpp) and is actually very readable. From the source code comments we learn that the comment in setxor about ismembc usage is misleading: that comment stated that the inputs must be real, but the source-code indicates that imaginary numbers are also accepted and that only the real-part should be sorted.
ismembc should not be used carelessly: as noted, its inputs must be sorted non-sparse non-NaN values. In the general case we should either ensure this programmatically (as done in setxor) or use ismember, which handles this for us.
The nice thing about ismembc is that its source code (ismembc.cpp) is included, so even if future Matlab releases stop using this function, you can always mex-compile the source code and use it.
Readers interested in ismembc might also be interested in its sibling help function, ismembc2, which is also a mex file located (with source-code) in the same folder as ismembc. Whereas ismembc returns an array of logical values, ismembc2 returns the index locations of the found members.
[…] This question reminded me of a similar case that I answered exactly two years ago, of improving the performance of the built-in ismember function. In both cases, the solution to the performance question can be found by simply using Matlab’s built-in profiler in order to extract just the core processing functionality. […]
interestingly, it appears that the variable “a” does not have to be sorted for using ismembc(), but the algorithm runs much more quickly if it is.