Using randperm in a loop
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I have a 3x3 cell called VID1. I want to find all possible combinations and store them in a matrix.
Currently Im using the code below. As I will work with HUGE cells later on I need to optimize it:
So what I want is to loop all the combinations in the best way. The code below can select a combination several times unnecessarily.
As an example:
if index=[1 2]
then that combination should no longer be possible
Jan on 14 Apr 2021
This code collects pairs of random numbers until all elements occur in the result. In opposite to this, in the description you mention all possible combinations. The code does something else. If you are looking for the conmbinations, you need the 'rows' flag for ismember().
ismember replies a logical flag already, so you save time, if you omit the " == 1".
The continue statement bends the program flow. Avoid it, if possible. Here I've inserted the not operator ~ to achieve this:
a1 = ;
for oz = 1:999
index = randperm(numel(VID1), 2);
if ~ismember(index, a1, 'rows')
a1 = [a1; index];
Now we have a working start point, which is faster already. But a general problem of such random so called "shotgun appraochs" is, that you cannot guarantee, that all solutions are found in a finite amount of time. In addition it wastes a lot of time with checking already existing solutions. With a larger input, this problem grows exponentially. This term should trigger the alarm bells of programmers, because it means, that the run time explodes to millions of years soon.
Your contains a second exponentially growing time eater: The output a1 is growing iteratively. This consumes a surprising huge amount of resources, because with each new element, Matlab has to reserve a new larger array and copy the former values. An example:
x = ;
for k = 1:1e6
x = rand;
The output x needs 8 MB only (8 bytes per double). But Matlab reserves ways more memory: 1 element in the first iteration, 2 elements in the 2nd iteration, etc. Finally sum(1:1e6)*8 Bytes are allocated in the RAM, cleared by overwriting with zeros and the former values of almost the same size are copied: 4 TeraByte!
This can be avoided easily by a pre-allocation:
x = zeros(1, 1e6);
for k = 1:1e6
x(k) = rand;
Now Matlab reserves 8MB and uses it.
Let's come back to the actual problem: "find all possible combinations and store them in a matrix" and "HUGE" cell.
By the way, avoid terms like "HUGE" in the forum. Some users think, that 200 elements are huge already, because they cannot type their values in manually, others are working with Petabytes of data on a compute cluster and call it "medium sized", because it takes less then a week so process it. Prefer to post absolute numbers instead.
Getting all combinations of large arrays has a severe aspect: The size of the result grows very fast. So before you start, you have to determine the size of the output. For getting 2 indices out of n elements, you get n * (n-1) pairs. Check, if your HUGE * (HUGE-1) * 8 matchs into your RAM at all. If not, you need another solution.
If it does match, think twice: This sounds like a common problem and somebody has solved it already. In you case, there is even a toolbox function:
a1 = nchoosek(1:9, 2)
For HUGE input, this is slow also, because the output is nearly HUGE^2. In the FileExchange you find some faster implementations. Search there for "combination" (if repetiions are wanted as [1,1]) or "permutation" (no repetitions).
You see, that your question opens a wide field and that you can learn a lot from this job.