In our explicit conversion test we have to read double indices, write integer indices, and then again read the integer indices during the actual indexing. The second option should be faster, because we only have to read the double indexes once. matlab passes doubles and performs the double->int cast on the fly during the indexing call.matlab converts double indices to uint32 indices explicitly before the indexing call (much like we do in the integer test).Otherwise, we would have seen virtually no difference between the double and integer methods. The runtime difference between the last two methods is unexpected though - it seems Matlab's internals either do not cast the doubles to integers, of perform error-checking on each element before doing the actual indexing. So it would seem that the actual indexing is faster when indexing with integers, but front-to-back, logical indexing performs much better. (double)Įlapsed time is 1.726806 seconds. (logical)Įlapsed time is 1.851225 seconds. Results (angainor): Elapsed time is 1.440018 seconds. (double)Įlapsed time is 3.508009 seconds. (logical)Įlapsed time is 3.233831 seconds. Results (Rody): Elapsed time is 1.945478 seconds. Including the creation of the indices in the test yields very different results however: a = rand(1e7, 1) Unless I am doing something wrong here, integer indexing seems to be the fastest most of the time. (logical)Įlapsed time is 0.296044 seconds. Results for threashold=0.5: Elapsed time is 0.687044 seconds. Index_logical 10000000x1 10000000 logicalįor larger values of the threashold integer indexing is faster. It is interesing, because the index_integer array is almost 4 times larger! index_integer 9198678x1 36794712 uint32 Meaning that the two methods perform almost the same - thats how I chose the example threashold. On my computer the results are Elapsed time is 0.755399 seconds.
Index_integer = uint32(find(index_logical)) % prepare logical and integer indices (note the uint32 cast)
% In this example - small threashold meaning most data in a % This determines the total indexing time - the more data we extract from a, Now I want to find the number of elements greater than 5 and their corresponding indices. % threashold - how much data meets the a>threashold criterion Ask Question Asked 10 years, 8 months ago Modified 10 years, 8 months ago Viewed 41k times 8 I have a matrix A. Quite an important thing I would say, since 'vectorized' MATLAB is mostly about indexing. Motivated by the above discussion with Rody, here is a simple benchmark, which tests speed of integer vs.
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