Книга: Standard Template Library Programmer
random_sample_n
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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:
• 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. 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