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
backwardcompatibility 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
[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.
AddisonWesley, 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
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