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std::ranges::sample() 算法

// (1)
O sample( I first, S last, O out, std::iter_difference_t<I> n, Gen&& gen );

// (2)
O sample( R&& r, O out, ranges::range_difference_t<R> n, Gen&& gen );

参数类型是泛型的,并具有以下约束

  • I - std::input_iterator
  • S - std::sentinel_for<I>
  • O - std::weakly_incrementable
  • R - std::ranges::input_range
  • Gen - (无)

此外,每个重载都有以下约束

  • (1):
    (forward_iterator<I> || random_access_iterator<O>)
    && indirectly_copyable<I, O>
    && uniform_random_bit_generator<remove_reference_t<Gen>>
  • (2):
    (ranges::forward_range<R> || random_access_iterator<O>)
    && indirectly_copyable<ranges::iterator_t<R>, O>
    && uniform_random_bit_generator<remove_reference_t<Gen>>

(为便于阅读,省略了 std:: 命名空间)

  • (1) 从序列 [first; last) 中选择 M = min(n, last - first) 个元素(不替换),使得每个可能的样本出现概率相等,并将这些选定的元素写入从 out 开始的范围。

    仅当 I 建模 std::forward_iterator 时,算法才稳定(保留选定元素的相对顺序)。

    未定义行为

    行为未定义

    如果 out 在 [first; last) 中。

  • (2)(1) 相同,但使用 r 作为范围,如同使用 ranges::begin(r) 作为 firstranges::end(r) 作为 last

本页描述的函数类实体是niebloids

参数

first
last

从中进行抽样的元素范围(总体)。

r

从中进行抽样的元素范围(总体)。

out

写入样本的输出迭代器。

n

要获取的样本数量。

gen

用作随机性来源的随机数生成器。

返回值

其中 M 定义为 min(n, last - first)

一个等于 out + M 的迭代器,即结果样本范围的末尾。

复杂度

(last - first) 的线性时间复杂度。

异常

(无)

可能的实现

sample(1) 和 sample(2)

struct sample_fn
{
template<std::input_iterator I, std::sentinel_for<I> S,
std::weakly_incrementable O, class Gen>
requires (std::forward_iterator<I> or
std::random_access_iterator<O>) &&
std::indirectly_copyable<I, O> &&
std::uniform_random_bit_generator<std::remove_reference_t<Gen>>
O operator()(I first, S last, O out, std::iter_difference_t<I> n, Gen&& gen) const
{
using diff_t = std::iter_difference_t<I>;
using distrib_t = std::uniform_int_distribution<diff_t>;
using param_t = typename distrib_t::param_type;
distrib_t D {};

if constexpr (std::forward_iterator<I>)
{
// this branch preserves "stability" of the sample elements
auto rest {ranges::distance(first, last)};
for (n = ranges::min(n, rest); n != 0; ++first)
{
if (D(gen, param_t(0, --rest)) < n)
{
*out++ = *first;
--n;
}
}
return out;
}
else
{
// O is a random_access_iterator
diff_t sample_size {};
// copy [first, first + M) elements to "random access" output
for (; first != last && sample_size != n; ++first)
out[sample_size++] = *first;
// overwrite some of the copied elements with randomly selected ones
for (auto pop_size {sample_size}; first != last; ++first, ++pop_size)
{
const auto i {D(gen, param_t{0, pop_size})};
if (i < n)
out[i] = *first;
}
return out + sample_size;
}
}

template<ranges::input_range R, std::weakly_incrementable O, class Gen>
requires (ranges::forward_range<R> or std::random_access_iterator<O>) &&
std::indirectly_copyable<ranges::iterator_t<R>, O> &&
std::uniform_random_bit_generator<std::remove_reference_t<Gen>>
O operator()(R&& r, O out, ranges::range_difference_t<R> n, Gen&& gen) const
{
return (*this)(ranges::begin(r), ranges::end(r), std::move(out), n,
std::forward<Gen>(gen));
}
};

inline constexpr sample_fn sample {};

示例

Main.cpp
#include <algorithm>
#include <iomanip>
#include <iostream>
#include <iterator>
#include <random>
#include <vector>

void print(auto const& rem, auto const& v)
{
std::cout << rem << " = [" << std::size(v) << "] { ";
for (auto const& e : v)
std::cout << e << ' ';
std::cout << "}\n";
}

int main()
{
const auto in = {1, 2, 3, 4, 5, 6};
print("in", in);

std::vector<int> out;
const int max = in.size() + 2;
auto gen = std::mt19937 {std::random_device {}()};

for (int n {}; n != max; ++n)
{
out.clear();
std::ranges::sample(in, std::back_inserter(out), n, gen);
std::cout << "n = " << n;
print(", out", out);
}
}
可能的输出
in = [6] { 1 2 3 4 5 6 }
n = 0, out = [0] { }
n = 1, out = [1] { 5 }
n = 2, out = [2] { 4 5 }
n = 3, out = [3] { 2 3 5 }
n = 4, out = [4] { 2 4 5 6 }
n = 5, out = [5] { 1 2 3 5 6 }
n = 6, out = [6] { 1 2 3 4 5 6 }
n = 7, out = [6] { 1 2 3 4 5 6 }
本文源自 此 CppReference 页面。它可能为了改进或编辑者偏好而进行了修改。点击“编辑此页面”查看本文档的所有更改。
悬停查看原始许可证。

std::ranges::sample() 算法

// (1)
O sample( I first, S last, O out, std::iter_difference_t<I> n, Gen&& gen );

// (2)
O sample( R&& r, O out, ranges::range_difference_t<R> n, Gen&& gen );

参数类型是泛型的,并具有以下约束

  • I - std::input_iterator
  • S - std::sentinel_for<I>
  • O - std::weakly_incrementable
  • R - std::ranges::input_range
  • Gen - (无)

此外,每个重载都有以下约束

  • (1):
    (forward_iterator<I> || random_access_iterator<O>)
    && indirectly_copyable<I, O>
    && uniform_random_bit_generator<remove_reference_t<Gen>>
  • (2):
    (ranges::forward_range<R> || random_access_iterator<O>)
    && indirectly_copyable<ranges::iterator_t<R>, O>
    && uniform_random_bit_generator<remove_reference_t<Gen>>

(为便于阅读,省略了 std:: 命名空间)

  • (1) 从序列 [first; last) 中选择 M = min(n, last - first) 个元素(不替换),使得每个可能的样本出现概率相等,并将这些选定的元素写入从 out 开始的范围。

    仅当 I 建模 std::forward_iterator 时,算法才稳定(保留选定元素的相对顺序)。

    未定义行为

    行为未定义

    如果 out 在 [first; last) 中。

  • (2)(1) 相同,但使用 r 作为范围,如同使用 ranges::begin(r) 作为 firstranges::end(r) 作为 last

本页描述的函数类实体是niebloids

参数

first
last

从中进行抽样的元素范围(总体)。

r

从中进行抽样的元素范围(总体)。

out

写入样本的输出迭代器。

n

要获取的样本数量。

gen

用作随机性来源的随机数生成器。

返回值

其中 M 定义为 min(n, last - first)

一个等于 out + M 的迭代器,即结果样本范围的末尾。

复杂度

(last - first) 的线性时间复杂度。

异常

(无)

可能的实现

sample(1) 和 sample(2)

struct sample_fn
{
template<std::input_iterator I, std::sentinel_for<I> S,
std::weakly_incrementable O, class Gen>
requires (std::forward_iterator<I> or
std::random_access_iterator<O>) &&
std::indirectly_copyable<I, O> &&
std::uniform_random_bit_generator<std::remove_reference_t<Gen>>
O operator()(I first, S last, O out, std::iter_difference_t<I> n, Gen&& gen) const
{
using diff_t = std::iter_difference_t<I>;
using distrib_t = std::uniform_int_distribution<diff_t>;
using param_t = typename distrib_t::param_type;
distrib_t D {};

if constexpr (std::forward_iterator<I>)
{
// this branch preserves "stability" of the sample elements
auto rest {ranges::distance(first, last)};
for (n = ranges::min(n, rest); n != 0; ++first)
{
if (D(gen, param_t(0, --rest)) < n)
{
*out++ = *first;
--n;
}
}
return out;
}
else
{
// O is a random_access_iterator
diff_t sample_size {};
// copy [first, first + M) elements to "random access" output
for (; first != last && sample_size != n; ++first)
out[sample_size++] = *first;
// overwrite some of the copied elements with randomly selected ones
for (auto pop_size {sample_size}; first != last; ++first, ++pop_size)
{
const auto i {D(gen, param_t{0, pop_size})};
if (i < n)
out[i] = *first;
}
return out + sample_size;
}
}

template<ranges::input_range R, std::weakly_incrementable O, class Gen>
requires (ranges::forward_range<R> or std::random_access_iterator<O>) &&
std::indirectly_copyable<ranges::iterator_t<R>, O> &&
std::uniform_random_bit_generator<std::remove_reference_t<Gen>>
O operator()(R&& r, O out, ranges::range_difference_t<R> n, Gen&& gen) const
{
return (*this)(ranges::begin(r), ranges::end(r), std::move(out), n,
std::forward<Gen>(gen));
}
};

inline constexpr sample_fn sample {};

示例

Main.cpp
#include <algorithm>
#include <iomanip>
#include <iostream>
#include <iterator>
#include <random>
#include <vector>

void print(auto const& rem, auto const& v)
{
std::cout << rem << " = [" << std::size(v) << "] { ";
for (auto const& e : v)
std::cout << e << ' ';
std::cout << "}\n";
}

int main()
{
const auto in = {1, 2, 3, 4, 5, 6};
print("in", in);

std::vector<int> out;
const int max = in.size() + 2;
auto gen = std::mt19937 {std::random_device {}()};

for (int n {}; n != max; ++n)
{
out.clear();
std::ranges::sample(in, std::back_inserter(out), n, gen);
std::cout << "n = " << n;
print(", out", out);
}
}
可能的输出
in = [6] { 1 2 3 4 5 6 }
n = 0, out = [0] { }
n = 1, out = [1] { 5 }
n = 2, out = [2] { 4 5 }
n = 3, out = [3] { 2 3 5 }
n = 4, out = [4] { 2 4 5 6 }
n = 5, out = [5] { 1 2 3 5 6 }
n = 6, out = [6] { 1 2 3 4 5 6 }
n = 7, out = [6] { 1 2 3 4 5 6 }
本文源自 此 CppReference 页面。它可能为了改进或编辑者偏好而进行了修改。点击“编辑此页面”查看本文档的所有更改。
悬停查看原始许可证。