SGI Logo


random_sample_n

Category: algorithms Component type: function

Prototype

Random_sample_n is an overloaded name; there are actually two random_sample_n functions.
template <class ForwardIterator, class OutputIterator, class Distance>
OutputIterator random_sample_n(ForwardIterator first, ForwardIterator last,
                               OutputIterator out, Distance n)

template <class ForwardIterator, class OutputIterator, class Distance,
          class RandomNumberGenerator>
OutputIterator random_sample_n(ForwardIterator first, ForwardIterator last,
                               OutputIterator out, Distance n,
                               RandomNumberGenerator& rand)

Description

Random_sample_n randomly copies a sample of the elements from the range [first, last) into the range [out, out + n). Each element in the input range appears at most once in the output range, and samples are chosen with uniform probability. [1] Elements in the output range appear in the same relative order as their relative order within the input range. [2]

Random_sample copies m elements from [first, last) to [out, out + m), where m is min(last - first, n). The return value is out + m.

The first version uses an internal random number generator, and the second uses a Random Number Generator, a special kind of function object, that is explicitly passed as an argument.

Definition

Defined in the standard header algorithm, and in the nonstandard backward-compatibility header algo.h. This function is an SGI extension; it is not part of the C++ standard.

Requirements on types

For the first version: For the second version:

Preconditions

Complexity

Linear in last - first. At most last - first elements from the input range are examined, and exactly min(n, last - first) elements are copied to the output range.

Example

int main()
{
  const int N = 10;
  int A[] = {1, 2, 3, 4, 5, 6, 7, 8, 9, 10};

  random_sample_n(A, A+N, ostream_iterator<int>(cout, " "), 4);
  // The printed value might be 3 5 6 10,
  //  or any of 209 other possibilities.
}

Notes

[1] This is "Algorithm S" from section 3.4.2 of Knuth (D. E. Knuth, The Art of Computer Programming. Volume 2: Seminumerical Algorithms, second edition. Addison-Wesley, 1981). Knuth credits C. T. Fan, M. E. Muller, and I. Rezucha (1962) and T. G. Jones (1962). Note that there are N! / n! / (N - n)! ways of selecting a sample of n elements from a range of N elements. Random_sample_n yields uniformly distributed results; that is, the probability of selecting any particular element is n / N, and the probability of any particular sampling is n! * (N - n)! / N!.

[2] In contrast, the random_sample algorithm does not preserve relative ordering within the input range. The other major distinction between the two algorithms is that random_sample_n requires its input range to be Forward Iterators and only requires its output range to be Output Iterators, while random_sample only requires its input range to be Input Iterators and requires its output range to be Random Access Iterators.

See also

random_shuffle, random_sample, Random Number Generator


STL Main Page

Contact Us | Site Map | Trademarks | Privacy | Using this site means you accept its Terms of Use
Copyright © 2009 - 2016 Silicon Graphics International. All rights reserved.