编译时多个集合的笛卡尔积
Cartesian product for multiple sets at compile time
我正在努力实现笛卡尔积
具有给定 范围 0,...,n-1
.
的多个索引
基本思路是有一个函数:
cartesian_product<std::size_t range, std::size_t sets>()
输出数组包含包含不同产品的元组
[(0,..,0), (0,...,1), (0,...,n-1),...., (n-1, ..., n-1)]
一个简单的例子如下:
auto result = cartesian_product<3, 2>();
输出类型std::array<std::tuple<int, int>, (3^2)>
:
[(0,0), (0,1), (0,2), (1,0), (1,1), (1,2), (2,0), (2,1), (2,2)]
我的主要问题 是我的笛卡尔积版本很慢,如果您选择超过 5 组就会造成堆栈溢出。我相信我的代码有太多的递归和临时变量。
我的实现 (C++17) 可以在这里找到:cartesian_product
#include <stdio.h>
#include <iostream>
#include <tuple>
template<typename T, std::size_t ...is>
constexpr auto flatten_tuple_i(T tuple, std::index_sequence<is...>) {
return std::tuple_cat(std::get<is>(tuple)...);
}
template<typename T>
constexpr auto flatten_tuple(T tuple) {
return flatten_tuple_i(tuple, std::make_index_sequence<std::tuple_size<T>::value>{});
}
template<std::size_t depth, typename T>
constexpr auto recursive_flatten_tuple(T tuple){
if constexpr(depth <= 1){
return tuple;
}else{
return recursive_flatten_tuple<depth-1>(flatten_tuple(tuple));
}
}
template<std::size_t depth, typename T, std::size_t ...is>
constexpr auto wdh(T&& tuple, std::index_sequence<is...>){
if constexpr (depth == 0) {
return tuple;
}else{
//return (wdh<depth-1>(std::tuple_cat(tuple, std::make_tuple(is)),std::make_index_sequence<sizeof...(is)>{})...);
return std::make_tuple(wdh<depth-1>(std::tuple_cat(tuple, std::make_tuple(is)), std::make_index_sequence<sizeof...(is)>{})...);
}
}
template<std::size_t sets, typename T, std::size_t ...is>
constexpr auto to_array(T tuple, std::index_sequence<is...>){
if constexpr (sets == 0){
auto t = (std::make_tuple(std::get<is>(tuple)),...);
std::array<decltype(t), sizeof...(is)> arr = {std::make_tuple(std::get<is>(tuple))...};
//decltype(arr)::foo = 1;
return arr;
}else{
auto t = ((std::get<is>(tuple)),...);
std::array<decltype(t), sizeof...(is)> arr = {std::get<is>(tuple)...};
return arr;
}
}
template<std::size_t sets, std::size_t ...is>
constexpr auto ct_i(std::index_sequence<is...>){
if constexpr (sets == 0){
auto u = std::tuple_cat(wdh<sets>(std::make_tuple(is), std::make_index_sequence<sizeof...(is)>{})...);
auto arr = to_array<sets>(u, std::make_index_sequence<std::tuple_size<decltype(u)>::value>{});
return arr;
}else {
auto u = std::tuple_cat(wdh<sets>(std::make_tuple(is), std::make_index_sequence<sizeof...(is)>{})...);
auto r = recursive_flatten_tuple<sets>(u);
auto d = to_array<sets>(r, std::make_index_sequence<std::tuple_size<decltype(r)>::value>{});
return d;
}
}
template<std::size_t range, std::size_t sets>
constexpr auto cartesian_product(){
static_assert( (range > 0), "lowest input must be cartesian<1,1>" );
static_assert( (sets > 0), "lowest input must be cartesian<1,1>" );
return ct_i<sets-1>(std::make_index_sequence<range>{});
}
int main()
{
constexpr auto crt = cartesian_product<3, 2>();
for(auto&& ele : crt){
std::cout << std::get<0>(ele) << " " << std::get<1>(ele) << std::endl;
}
return 0;
}
您无需递归即可轻松完成此操作。请注意,每个元组都是基数 range
中从 0
到 range ** sets
的数字的数字,因此您可以递增计数器(或应用于 std::index_sequence
)并计算每个值一个接一个。
这是一个实现(returns std::array
of std::array
s,它的工作原理与 std::tuple
s 基本相同,你可以 get<N>
, tuple_size
和 tuple_element<N>
在 std::array
上,但如果你真的想要,你可以将它们转换为 std::tuple
s):
#include <cstddef>
#include <array>
namespace detail {
constexpr std::size_t ipow(std::size_t base, std::size_t exponent) noexcept {
std::size_t p = 1;
while (exponent) {
if (exponent % 2 != 0) {
p *= base;
}
exponent /= 2;
base *= base;
}
return p;
}
}
template<std::size_t range, std::size_t sets>
constexpr std::array<std::array<std::size_t, sets>, detail::ipow(range, sets)>
cartesian_product() noexcept {
constexpr std::size_t size = detail::ipow(range, sets);
std::array<std::array<std::size_t, sets>, size> result{};
for (std::size_t i = 0; i < size; ++i) {
std::size_t place = size;
for (std::size_t j = 0; j < sets; ++j) {
place /= range;
result[i][j] = (i / place) % range;
}
}
return result;
}
这是一个测试link:https://www.onlinegdb.com/By_X9wbrI
请注意,(empty_set)^0
在这里被定义为一个包含空集的集合,但可以通过 ipow(0, 0) == 0
而不是 1
来更改
因为我也在研究一个解决方案,所以我想我也 post 它(尽管与 Artyer 的回答非常相似)。同样的前提,我们用数组替换元组,然后迭代元素,将它们一个接一个地递增。
请注意,power
函数已损坏,因此如果您需要幂值 <0 或非整数类型,则必须修复它。
template <typename It, typename T>
constexpr void setAll(It begin, It end, T value)
{
for (; begin != end; ++begin)
*begin = value;
}
template <typename T, std::size_t I>
constexpr void increment(std::array<T, I>& counter, T max)
{
for (auto idx = I; idx > 0;)
{
--idx;
if (++counter[idx] >= max)
{
setAll(counter.begin() + idx, counter.end(), 0); // because std::fill is not constexpr yet
}
else
{
break;
}
}
}
// std::pow is not constexpr
constexpr auto power = [](auto base, auto power)
{
auto result = base;
while (--power)
result *= base;
return result;
};
template<std::size_t range, std::size_t sets>
constexpr auto cartesian_product()
{
std::array<std::array<int, sets>, power(range, sets)> products{};
std::array<int, sets> currentSet{};
for (auto& product : products)
{
product = currentSet;
increment(currentSet, static_cast<int>(range));
}
return products;
}
int main()
{
constexpr auto crt = cartesian_product<5, 3>();
for (auto&& ele : crt)
{
for (auto val : ele)
std::cout << val << " ";
std::cout << "\n";
}
return 0;
}
我只是为了好玩而尝试,结果我得到了与@Timo 几乎相同的想法,只是 format/style。
#include <iostream>
#include <array>
using namespace std;
template<size_t range, size_t sets>
constexpr auto cartesian_product() {
// how many elements = range^sets
constexpr auto size = []() {
size_t x = range;
size_t n = sets;
while(--n != 0) x *= range;
return x;
}();
auto products = array<array<size_t, sets>, size>();
auto counter = array<size_t, sets>{}; // array of zeroes
for (auto &product : products) {
product = counter;
// counter increment and wrapping/carry over
counter.back()++;
for (size_t i = counter.size()-1; i != 0; i--) {
if (counter[i] == range) {
counter[i] = 0;
counter[i-1]++;
}
else break;
}
}
return products;
}
int main() {
auto prods = cartesian_product<3, 6>();
}
我基本上有一个手动递增的计数器数组,如下所示:
// given cartesian_product<3, 4>
[0, 0, 0, 0]
[0, 0, 0, 1]
[0, 0, 0, 2]
[0, 0, 1, 0] // carry over
...
...
[2, 2, 2, 2]
几乎就是您手工完成的方式。
对于 Boost.Mp11,这是...好吧,它不是单线的,但还算不错:
template <typename... Lists>
using list_product = mp_product<mp_list, Lists...>;
template <typename... Ts>
constexpr auto list_to_tuple(mp_list<Ts...>) {
return std::make_tuple(int(Ts::value)...);
}
template <typename... Ls>
constexpr auto list_to_array(mp_list<Ls...>) {
return std::array{list_to_tuple(Ls{})...};
}
template <size_t R, size_t N>
constexpr auto cartesian_product()
{
using L = mp_repeat_c<mp_list<mp_iota_c<R>>, N>;
return list_to_array(mp_apply<list_product, L>{});
}
使用 C++20,您可以在 cartesian_product
中将两个辅助函数模板声明为 lambda,这样可以更好地阅读(从上到下而不是从下到上)。
根据 cartesian_product<3, 2>
的 OP 示例解释发生了什么:
mp_iota_c<R>
给我们列表 [0, 1, 2]
(但作为整数常量类型)
mp_repeat_c<mp_list<mp_iota_c<R>>, N>
给我们 [[0, 1, 2], [0, 1, 2]]
。我们只是重复列表,但我们想要一个列表列表(因此中间有额外的 mp_list
)。
mp_apply<list_product, L>
执行 mp_product
,这是您传入的所有列表的笛卡尔积...将结果粘贴在 mp_list
中。这给你 [[0, 0], [0, 1], [0, 2], ..., [2, 2]]
,但作为整数常数 mp_list
的 mp_list
。
- 此时困难的部分已经结束,我们只需要将结果转换回元组数组即可。
list_to_tuple
接受整数常数的 mp_list
并将其转换为具有正确值的 tuple<int...>
。 list_to_array
将 mp_list
的 mp_list
整数常数转换为 std::array
的 tuple
。
仅使用单个辅助函数的略有不同的方法:
template <template <typename...> class L,
typename... Ts, typename F>
constexpr auto unpack(L<Ts...>, F f) {
return f(Ts{}...);
}
template <size_t R, size_t N>
constexpr auto cartesian_product()
{
using P = mp_apply_q<
mp_bind_front<mp_product_q, mp_quote<mp_list>>,
mp_repeat_c<mp_list<mp_iota_c<R>>, N>>;
return unpack(P{},
[](auto... lists){
return std::array{
unpack(lists, [](auto... values){
return std::make_tuple(int(values)...);
})...
};
});
}
尽管这种方法更难阅读,但它是相同的算法。
如果你想在编译时使用它,你应该只对编译时数据结构使用编译时评估。正如@Barry 上面指出的那样,使用 Boost.Mp11 极大地促进了它。当然你可以自己用纯C++17重新实现相关的基础函数:
#include <iostream>
template<class T> struct Box {
using type = T;
};
template<class... Types> struct List {};
template<class Car, class Cdr> struct Cons;
template<class Car, class Cdr> using ConsT = typename Cons<Car, Cdr>::type;
template<class Car, class... Cdr> struct Cons<Car, List<Cdr...>>: Box<List<Car, Cdr...>> {};
using Nil = List<>;
template<std::size_t i, class L> struct Nth;
template<std::size_t i, class L> using NthT = typename Nth<i, L>::type;
template<std::size_t i, class... Ts> struct Nth<i, List<Ts...>>: std::tuple_element<i, std::tuple<Ts...>> {};
template<class L> struct Head;
template<class L> using HeadT = typename Head<L>::type;
template<class Car, class... Cdr> struct Head<List<Car, Cdr...>>: Box<Car> {};
template<class L> struct Tail;
template<class L> using TailT = typename Tail<L>::type;
template<class Car, class... Cdr> struct Tail<List<Car, Cdr...>>: Box<List<Cdr...>> {};
template<class... Lists> struct Concat;
template<class... Lists> using ConcatT = typename Concat<Lists...>::type;
template<class T, class... Rest> struct Concat<T, Rest...>: Cons<T, ConcatT<Rest...>> {};
template<class Head, class... Tail, class... Rest> struct Concat<List<Head, Tail...>, Rest...>: Cons<Head, ConcatT<List<Tail...>, Rest...>> {};
template<class... Rest> struct Concat<Nil, Rest...>: Concat<Rest...> {};
template<> struct Concat<>: Box<Nil> {};
template<class T, class Subspace> struct Prepend;
template<class T, class Subspace> using PrependT = typename Prepend<T, Subspace>::type;
template<class T, class... Points> struct Prepend<T, List<Points...>>: Box<List<ConsT<T, Points>...>> {};
template<class T> struct Prepend<T, Nil>: Box<List<List<T>>> {};
template<class Range, class Subspace> struct Product;
template<class Range, class Subspace> using ProductT = typename Product<Range, Subspace>::type;
template<class Range, class Subspace> struct Product: Concat<PrependT<HeadT<Range>, Subspace>, ProductT<TailT<Range>, Subspace>> {};
template<class Subspace> struct Product<Nil, Subspace>: Box<Nil> {};
template<std::size_t i> using IntValue = std::integral_constant<std::size_t, i>;
template<class Seq> struct IntegerSequence;
template<class Seq> using IntegerSequenceT = typename IntegerSequence<Seq>::type;
template<std::size_t... is> struct IntegerSequence<std::index_sequence<is...>>: Box<List<IntValue<is>...>> {};
template<std::size_t n> using Range = IntegerSequenceT<std::make_index_sequence<n>>;
template<std::size_t dimensions, std::size_t range> struct CartesianCube;
template<std::size_t dimensions, std::size_t range> using CartesianCubeT = typename CartesianCube<dimensions, range>::type;
template<std::size_t dimensions, std::size_t range> struct CartesianCube: Product<Range<range>, CartesianCubeT<dimensions - 1, range>> {};
template<std::size_t range> struct CartesianCube<0, range>: Box<Nil> {};
template<std::size_t i> std::ostream &operator<<(std::ostream &s, IntValue<i>) {
return s << '<' << i << '>';
}
template<class... Ts> std::ostream &operator<<(std::ostream &s, List<Ts...>);
namespace detail_ {
template<class L, std::size_t... is> std::ostream &printList(std::ostream &s, L, std::index_sequence<is...>) {
return ((s << (is == 0? "" : ", ") << NthT<is, L>{}), ...), s;
}
}
template<class... Ts> std::ostream &operator<<(std::ostream &s, List<Ts...>) {
return detail_::printList(s << "List{", List<Ts...>{}, std::index_sequence_for<Ts...>{}) << '}';
}
int main() {
std::cout << CartesianCubeT<2, 3>{} << '\n';
}
注意这里的CartesianCubeT
实际上是List
个List
个integral_constant
个。一旦有了这些,将它们转换成 运行 时间值就很简单了。请注意 cartesian_product
甚至不必是函数,因为整个数据集是在编译时评估的,它可以是模板值。
我正在努力实现笛卡尔积
具有给定 范围 0,...,n-1
.
基本思路是有一个函数:
cartesian_product<std::size_t range, std::size_t sets>()
输出数组包含包含不同产品的元组
[(0,..,0), (0,...,1), (0,...,n-1),...., (n-1, ..., n-1)]
一个简单的例子如下:
auto result = cartesian_product<3, 2>();
输出类型std::array<std::tuple<int, int>, (3^2)>
:
[(0,0), (0,1), (0,2), (1,0), (1,1), (1,2), (2,0), (2,1), (2,2)]
我的主要问题 是我的笛卡尔积版本很慢,如果您选择超过 5 组就会造成堆栈溢出。我相信我的代码有太多的递归和临时变量。
我的实现 (C++17) 可以在这里找到:cartesian_product
#include <stdio.h>
#include <iostream>
#include <tuple>
template<typename T, std::size_t ...is>
constexpr auto flatten_tuple_i(T tuple, std::index_sequence<is...>) {
return std::tuple_cat(std::get<is>(tuple)...);
}
template<typename T>
constexpr auto flatten_tuple(T tuple) {
return flatten_tuple_i(tuple, std::make_index_sequence<std::tuple_size<T>::value>{});
}
template<std::size_t depth, typename T>
constexpr auto recursive_flatten_tuple(T tuple){
if constexpr(depth <= 1){
return tuple;
}else{
return recursive_flatten_tuple<depth-1>(flatten_tuple(tuple));
}
}
template<std::size_t depth, typename T, std::size_t ...is>
constexpr auto wdh(T&& tuple, std::index_sequence<is...>){
if constexpr (depth == 0) {
return tuple;
}else{
//return (wdh<depth-1>(std::tuple_cat(tuple, std::make_tuple(is)),std::make_index_sequence<sizeof...(is)>{})...);
return std::make_tuple(wdh<depth-1>(std::tuple_cat(tuple, std::make_tuple(is)), std::make_index_sequence<sizeof...(is)>{})...);
}
}
template<std::size_t sets, typename T, std::size_t ...is>
constexpr auto to_array(T tuple, std::index_sequence<is...>){
if constexpr (sets == 0){
auto t = (std::make_tuple(std::get<is>(tuple)),...);
std::array<decltype(t), sizeof...(is)> arr = {std::make_tuple(std::get<is>(tuple))...};
//decltype(arr)::foo = 1;
return arr;
}else{
auto t = ((std::get<is>(tuple)),...);
std::array<decltype(t), sizeof...(is)> arr = {std::get<is>(tuple)...};
return arr;
}
}
template<std::size_t sets, std::size_t ...is>
constexpr auto ct_i(std::index_sequence<is...>){
if constexpr (sets == 0){
auto u = std::tuple_cat(wdh<sets>(std::make_tuple(is), std::make_index_sequence<sizeof...(is)>{})...);
auto arr = to_array<sets>(u, std::make_index_sequence<std::tuple_size<decltype(u)>::value>{});
return arr;
}else {
auto u = std::tuple_cat(wdh<sets>(std::make_tuple(is), std::make_index_sequence<sizeof...(is)>{})...);
auto r = recursive_flatten_tuple<sets>(u);
auto d = to_array<sets>(r, std::make_index_sequence<std::tuple_size<decltype(r)>::value>{});
return d;
}
}
template<std::size_t range, std::size_t sets>
constexpr auto cartesian_product(){
static_assert( (range > 0), "lowest input must be cartesian<1,1>" );
static_assert( (sets > 0), "lowest input must be cartesian<1,1>" );
return ct_i<sets-1>(std::make_index_sequence<range>{});
}
int main()
{
constexpr auto crt = cartesian_product<3, 2>();
for(auto&& ele : crt){
std::cout << std::get<0>(ele) << " " << std::get<1>(ele) << std::endl;
}
return 0;
}
您无需递归即可轻松完成此操作。请注意,每个元组都是基数 range
中从 0
到 range ** sets
的数字的数字,因此您可以递增计数器(或应用于 std::index_sequence
)并计算每个值一个接一个。
这是一个实现(returns std::array
of std::array
s,它的工作原理与 std::tuple
s 基本相同,你可以 get<N>
, tuple_size
和 tuple_element<N>
在 std::array
上,但如果你真的想要,你可以将它们转换为 std::tuple
s):
#include <cstddef>
#include <array>
namespace detail {
constexpr std::size_t ipow(std::size_t base, std::size_t exponent) noexcept {
std::size_t p = 1;
while (exponent) {
if (exponent % 2 != 0) {
p *= base;
}
exponent /= 2;
base *= base;
}
return p;
}
}
template<std::size_t range, std::size_t sets>
constexpr std::array<std::array<std::size_t, sets>, detail::ipow(range, sets)>
cartesian_product() noexcept {
constexpr std::size_t size = detail::ipow(range, sets);
std::array<std::array<std::size_t, sets>, size> result{};
for (std::size_t i = 0; i < size; ++i) {
std::size_t place = size;
for (std::size_t j = 0; j < sets; ++j) {
place /= range;
result[i][j] = (i / place) % range;
}
}
return result;
}
这是一个测试link:https://www.onlinegdb.com/By_X9wbrI
请注意,(empty_set)^0
在这里被定义为一个包含空集的集合,但可以通过 ipow(0, 0) == 0
而不是 1
因为我也在研究一个解决方案,所以我想我也 post 它(尽管与 Artyer 的回答非常相似)。同样的前提,我们用数组替换元组,然后迭代元素,将它们一个接一个地递增。
请注意,power
函数已损坏,因此如果您需要幂值 <0 或非整数类型,则必须修复它。
template <typename It, typename T>
constexpr void setAll(It begin, It end, T value)
{
for (; begin != end; ++begin)
*begin = value;
}
template <typename T, std::size_t I>
constexpr void increment(std::array<T, I>& counter, T max)
{
for (auto idx = I; idx > 0;)
{
--idx;
if (++counter[idx] >= max)
{
setAll(counter.begin() + idx, counter.end(), 0); // because std::fill is not constexpr yet
}
else
{
break;
}
}
}
// std::pow is not constexpr
constexpr auto power = [](auto base, auto power)
{
auto result = base;
while (--power)
result *= base;
return result;
};
template<std::size_t range, std::size_t sets>
constexpr auto cartesian_product()
{
std::array<std::array<int, sets>, power(range, sets)> products{};
std::array<int, sets> currentSet{};
for (auto& product : products)
{
product = currentSet;
increment(currentSet, static_cast<int>(range));
}
return products;
}
int main()
{
constexpr auto crt = cartesian_product<5, 3>();
for (auto&& ele : crt)
{
for (auto val : ele)
std::cout << val << " ";
std::cout << "\n";
}
return 0;
}
我只是为了好玩而尝试,结果我得到了与@Timo 几乎相同的想法,只是 format/style。
#include <iostream>
#include <array>
using namespace std;
template<size_t range, size_t sets>
constexpr auto cartesian_product() {
// how many elements = range^sets
constexpr auto size = []() {
size_t x = range;
size_t n = sets;
while(--n != 0) x *= range;
return x;
}();
auto products = array<array<size_t, sets>, size>();
auto counter = array<size_t, sets>{}; // array of zeroes
for (auto &product : products) {
product = counter;
// counter increment and wrapping/carry over
counter.back()++;
for (size_t i = counter.size()-1; i != 0; i--) {
if (counter[i] == range) {
counter[i] = 0;
counter[i-1]++;
}
else break;
}
}
return products;
}
int main() {
auto prods = cartesian_product<3, 6>();
}
我基本上有一个手动递增的计数器数组,如下所示:
// given cartesian_product<3, 4>
[0, 0, 0, 0]
[0, 0, 0, 1]
[0, 0, 0, 2]
[0, 0, 1, 0] // carry over
...
...
[2, 2, 2, 2]
几乎就是您手工完成的方式。
对于 Boost.Mp11,这是...好吧,它不是单线的,但还算不错:
template <typename... Lists>
using list_product = mp_product<mp_list, Lists...>;
template <typename... Ts>
constexpr auto list_to_tuple(mp_list<Ts...>) {
return std::make_tuple(int(Ts::value)...);
}
template <typename... Ls>
constexpr auto list_to_array(mp_list<Ls...>) {
return std::array{list_to_tuple(Ls{})...};
}
template <size_t R, size_t N>
constexpr auto cartesian_product()
{
using L = mp_repeat_c<mp_list<mp_iota_c<R>>, N>;
return list_to_array(mp_apply<list_product, L>{});
}
使用 C++20,您可以在 cartesian_product
中将两个辅助函数模板声明为 lambda,这样可以更好地阅读(从上到下而不是从下到上)。
根据 cartesian_product<3, 2>
的 OP 示例解释发生了什么:
mp_iota_c<R>
给我们列表[0, 1, 2]
(但作为整数常量类型)mp_repeat_c<mp_list<mp_iota_c<R>>, N>
给我们[[0, 1, 2], [0, 1, 2]]
。我们只是重复列表,但我们想要一个列表列表(因此中间有额外的mp_list
)。mp_apply<list_product, L>
执行mp_product
,这是您传入的所有列表的笛卡尔积...将结果粘贴在mp_list
中。这给你[[0, 0], [0, 1], [0, 2], ..., [2, 2]]
,但作为整数常数mp_list
的mp_list
。- 此时困难的部分已经结束,我们只需要将结果转换回元组数组即可。
list_to_tuple
接受整数常数的mp_list
并将其转换为具有正确值的tuple<int...>
。list_to_array
将mp_list
的mp_list
整数常数转换为std::array
的tuple
。
仅使用单个辅助函数的略有不同的方法:
template <template <typename...> class L,
typename... Ts, typename F>
constexpr auto unpack(L<Ts...>, F f) {
return f(Ts{}...);
}
template <size_t R, size_t N>
constexpr auto cartesian_product()
{
using P = mp_apply_q<
mp_bind_front<mp_product_q, mp_quote<mp_list>>,
mp_repeat_c<mp_list<mp_iota_c<R>>, N>>;
return unpack(P{},
[](auto... lists){
return std::array{
unpack(lists, [](auto... values){
return std::make_tuple(int(values)...);
})...
};
});
}
尽管这种方法更难阅读,但它是相同的算法。
如果你想在编译时使用它,你应该只对编译时数据结构使用编译时评估。正如@Barry 上面指出的那样,使用 Boost.Mp11 极大地促进了它。当然你可以自己用纯C++17重新实现相关的基础函数:
#include <iostream>
template<class T> struct Box {
using type = T;
};
template<class... Types> struct List {};
template<class Car, class Cdr> struct Cons;
template<class Car, class Cdr> using ConsT = typename Cons<Car, Cdr>::type;
template<class Car, class... Cdr> struct Cons<Car, List<Cdr...>>: Box<List<Car, Cdr...>> {};
using Nil = List<>;
template<std::size_t i, class L> struct Nth;
template<std::size_t i, class L> using NthT = typename Nth<i, L>::type;
template<std::size_t i, class... Ts> struct Nth<i, List<Ts...>>: std::tuple_element<i, std::tuple<Ts...>> {};
template<class L> struct Head;
template<class L> using HeadT = typename Head<L>::type;
template<class Car, class... Cdr> struct Head<List<Car, Cdr...>>: Box<Car> {};
template<class L> struct Tail;
template<class L> using TailT = typename Tail<L>::type;
template<class Car, class... Cdr> struct Tail<List<Car, Cdr...>>: Box<List<Cdr...>> {};
template<class... Lists> struct Concat;
template<class... Lists> using ConcatT = typename Concat<Lists...>::type;
template<class T, class... Rest> struct Concat<T, Rest...>: Cons<T, ConcatT<Rest...>> {};
template<class Head, class... Tail, class... Rest> struct Concat<List<Head, Tail...>, Rest...>: Cons<Head, ConcatT<List<Tail...>, Rest...>> {};
template<class... Rest> struct Concat<Nil, Rest...>: Concat<Rest...> {};
template<> struct Concat<>: Box<Nil> {};
template<class T, class Subspace> struct Prepend;
template<class T, class Subspace> using PrependT = typename Prepend<T, Subspace>::type;
template<class T, class... Points> struct Prepend<T, List<Points...>>: Box<List<ConsT<T, Points>...>> {};
template<class T> struct Prepend<T, Nil>: Box<List<List<T>>> {};
template<class Range, class Subspace> struct Product;
template<class Range, class Subspace> using ProductT = typename Product<Range, Subspace>::type;
template<class Range, class Subspace> struct Product: Concat<PrependT<HeadT<Range>, Subspace>, ProductT<TailT<Range>, Subspace>> {};
template<class Subspace> struct Product<Nil, Subspace>: Box<Nil> {};
template<std::size_t i> using IntValue = std::integral_constant<std::size_t, i>;
template<class Seq> struct IntegerSequence;
template<class Seq> using IntegerSequenceT = typename IntegerSequence<Seq>::type;
template<std::size_t... is> struct IntegerSequence<std::index_sequence<is...>>: Box<List<IntValue<is>...>> {};
template<std::size_t n> using Range = IntegerSequenceT<std::make_index_sequence<n>>;
template<std::size_t dimensions, std::size_t range> struct CartesianCube;
template<std::size_t dimensions, std::size_t range> using CartesianCubeT = typename CartesianCube<dimensions, range>::type;
template<std::size_t dimensions, std::size_t range> struct CartesianCube: Product<Range<range>, CartesianCubeT<dimensions - 1, range>> {};
template<std::size_t range> struct CartesianCube<0, range>: Box<Nil> {};
template<std::size_t i> std::ostream &operator<<(std::ostream &s, IntValue<i>) {
return s << '<' << i << '>';
}
template<class... Ts> std::ostream &operator<<(std::ostream &s, List<Ts...>);
namespace detail_ {
template<class L, std::size_t... is> std::ostream &printList(std::ostream &s, L, std::index_sequence<is...>) {
return ((s << (is == 0? "" : ", ") << NthT<is, L>{}), ...), s;
}
}
template<class... Ts> std::ostream &operator<<(std::ostream &s, List<Ts...>) {
return detail_::printList(s << "List{", List<Ts...>{}, std::index_sequence_for<Ts...>{}) << '}';
}
int main() {
std::cout << CartesianCubeT<2, 3>{} << '\n';
}
注意这里的CartesianCubeT
实际上是List
个List
个integral_constant
个。一旦有了这些,将它们转换成 运行 时间值就很简单了。请注意 cartesian_product
甚至不必是函数,因为整个数据集是在编译时评估的,它可以是模板值。