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  2. @wjandrea yeah I'm aware that Python 3 range produces a generator. Back when I posted that comment if you tried sample = random.sample(range(1000000000000000000), 10) you could watch the memory of the process grow as it tried to materialize the range before extracting a sample.

  3. Non-repetitive random number in numpy - Stack Overflow

    stackoverflow.com/questions/8505651

    numpy.random.Generator.choice offers a replace argument to sample without replacement: from numpy.random import default_rng rng = default_rng() numbers = rng.choice(20, size=10, replace=False) If you're on a pre-1.17 NumPy, without the Generator API, you can use random.sample() from the standard library:

  4. So you want k distinct random numbers from 0 to n (with k < n). Two possible approaches: Pick k random numbers, as you already did, and store them in a data structure. Everytime you pick a number, check if it is already contained in the structure: if it is, keep picking until you have a "new" random number.

  5. This same protection persists for all numbers, even if you got the same number 5 times in a row. E.g., if the random number generator gave you 0 five times in a row, the results would be: [ 0, 19, 18, 17, 16 ]. You would never get the same number twice.

  6. Lazy random number generation without replacement in R

    stackoverflow.com/questions/64368524

    I want to generate random values from vector 1:n without replacement, just as sample(n) would do. However, instead of saving the permutation in memory, I want to generate the values on demand. similar to a generator in Python. I imagine something like this:

  7. What you do is to generate a random number each time in the loop. There is a chance of course that the next random number may be the same as the previous one. Just add one check that the current random number is not present in the sequence. You can use a while loop like: while (currentRandom not in listNumbers): generateNewRandomNumber

  8. I want to draw random integer pairs without replacement (said another way I don't want any duplicate pairs). This concept sounds simple but I can't think of a quick and simple solution. Imagine, for example, I want to generate random pairs of integers using the sequence of integer 1:4 to populate the elements of the pair. Also assume I want to ...

  9. Using random.sample(xrange(1, 100), 3) - with xrange instead of range - speeds the code a lot, particularly if you have a big range, since it will only generate on-demand the required 3 numbers (or more if the sampling without replacement needs it), but not the whole range.

  10. What I would do: Generate a vector of length N and fill it with values 1,2,...N. Use std::random_shuffle.; If you have say 30 elements and only want 10, use the first 10 out the vector.

  11. Suppose you require only two draws without replacement from a large vector. The shuffle algorithm will be of linear complexity in the size of the vector, whereas the alternative suggestion (drawing and rejecting if already drawn) would be O(1).