 # 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.  Elements in the output range appear in the same relative order as their relative order within the input range. 

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:
• ForwardIterator is a model of Forward Iterator
• OutputIterator is a model of Output Iterator
• ForwardIterator's value type is convertible to a type in OutputIterator's set of value types.
• Distance is an integral type that is large enough to represent the value last - first.
For the second version:
• ForwardIterator is a model of Forward Iterator
• OutputIterator is a model of Output Iterator
• RandomNumberGenerator is a model of Random Number Generator
• Distance is an integral type that is large enough to represent the value last - first.
• ForwardIterator's value type is convertible to a type in OutputIterator's set of value types.
• Distance is convertible to RandomNumberGenerator's argument type.

### Preconditions

• [first, last) is a valid range.
• n is nonnegative.
• [first, last) and [out, out + n) do not overlap.
• There is enough space to hold all of the elements being copied. More formally, the requirement is that [out, out + min(n, last - first)) is a valid range.
• last - first is less than rand's maximum value.

### 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

 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!.

 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  Copyright © 1999 Silicon Graphics, Inc. All Rights Reserved. TrademarkInformation