问题描述
我需要获得任意精度的值的哈希值(来自 Boost.Multiprecision);我使用 cpp_int
后端.我想出了以下代码:
I need to get the hash of a value with arbitrary precision (from Boost.Multiprecision); I use the cpp_int
backend. I came up with the following code:
boost::multiprecision::cpp_int x0 = 1;
const auto seed = std::hash<std::string>{}(x0.str());
我不需要代码尽可能快,但我发现散列字符串表示非常笨拙.
I don't need the code to be as fast as possible, but I find it very clumsy to hash the string representation.
所以我的问题是双重的:
So my question is twofold:
- 保持任意精度,我可以更有效地散列值吗?
- 也许我不应该坚持保持任意精度,我应该转换为一个
double
,我可以很容易地散列(但是我仍然会使用任意精度值对哈希表进行所需的比较)?
- Keeping the arbitrary precision, can I hash the value more efficiently?
- Maybe I should not insisting on keeping the arbitrary precision and I should convert to a
double
which I could hash easily (I would still however make the comparison needed for the hash table using the arbitrary precision value)?
推荐答案
您可以(ab)使用序列化支持:
You can (ab)use the serialization support:
对序列化的支持有两种形式:类 number
、debug_adaptor
、logged_adaptor
和 rational_adaptor
具有直通"序列化支持,这需要底层后端可序列化.
Support for serialization comes in two forms: Classes
number
,debug_adaptor
,logged_adaptor
andrational_adaptor
have "pass through" serialization support which requires the underlying backend to be serializable.
后端cpp_int
、cpp_bin_float
、cpp_dec_float
和float128
完全支持Boost.Serialization.
Backends cpp_int
, cpp_bin_float
, cpp_dec_float
and float128
have full support for Boost.Serialization.
所以,让我拼凑一些适用于 boost 和 std 无序容器的东西:
So, let me cobble something together that works with boost and std unordered containers:
template <typename Map>
void test(Map const& map) {
std::cout << "
" << __PRETTY_FUNCTION__ << "
";
for(auto& p : map)
std::cout << p.second << " " << p.first << "
";
}
int main() {
using boost::multiprecision::cpp_int;
test(std::unordered_map<cpp_int, std::string> {
{ cpp_int(1) << 111, "one" },
{ cpp_int(2) << 222, "two" },
{ cpp_int(3) << 333, "three" },
});
test(boost::unordered_map<cpp_int, std::string> {
{ cpp_int(1) << 111, "one" },
{ cpp_int(2) << 222, "two" },
{ cpp_int(3) << 333, "three" },
});
}
让我们将相关的 hash<>
实现转发到我们自己的使用多精度 和 序列化的 hash_impl
专业化:
Let's forward the relevant hash<>
implementations to our own hash_impl
specialization that uses Multiprecision and Serialization:
namespace std {
template <typename backend>
struct hash<boost::multiprecision::number<backend> >
: mp_hashing::hash_impl<boost::multiprecision::number<backend> >
{};
}
namespace boost {
template <typename backend>
struct hash<multiprecision::number<backend> >
: mp_hashing::hash_impl<multiprecision::number<backend> >
{};
}
当然,这就引出了一个问题,hash_impl
是如何实现的?
Now, of course, this begs the question, how is hash_impl
implemented?
template <typename T> struct hash_impl {
size_t operator()(T const& v) const {
using namespace boost;
size_t seed = 0;
{
iostreams::stream<hash_sink> os(seed);
archive::binary_oarchive oa(os, archive::no_header | archive::no_codecvt);
oa << v;
}
return seed;
}
};
这看起来很简单.那是因为 Boost 很棒,编写一个 hash_sink
设备用于 Boost Iostreams 只是以下简单的练习:
This looks pretty simple. That's because Boost is awesome, and writing a hash_sink
device for use with Boost Iostreams is just the following straightforward exercise:
namespace io = boost::iostreams;
struct hash_sink {
hash_sink(size_t& seed_ref) : _ptr(&seed_ref) {}
typedef char char_type;
typedef io::sink_tag category;
std::streamsize write(const char* s, std::streamsize n) {
boost::hash_combine(*_ptr, boost::hash_range(s, s+n));
return n;
}
private:
size_t* _ptr;
};
完整演示:
生活在 Coliru
#include <iostream>
#include <iomanip>
#include <boost/archive/binary_oarchive.hpp>
#include <boost/multiprecision/cpp_int.hpp>
#include <boost/multiprecision/cpp_int/serialize.hpp>
#include <boost/iostreams/device/back_inserter.hpp>
#include <boost/iostreams/stream_buffer.hpp>
#include <boost/iostreams/stream.hpp>
#include <boost/functional/hash.hpp>
namespace mp_hashing {
namespace io = boost::iostreams;
struct hash_sink {
hash_sink(size_t& seed_ref) : _ptr(&seed_ref) {}
typedef char char_type;
typedef io::sink_tag category;
std::streamsize write(const char* s, std::streamsize n) {
boost::hash_combine(*_ptr, boost::hash_range(s, s+n));
return n;
}
private:
size_t* _ptr;
};
template <typename T> struct hash_impl {
size_t operator()(T const& v) const {
using namespace boost;
size_t seed = 0;
{
iostreams::stream<hash_sink> os(seed);
archive::binary_oarchive oa(os, archive::no_header | archive::no_codecvt);
oa << v;
}
return seed;
}
};
}
#include <unordered_map>
#include <boost/unordered_map.hpp>
namespace std {
template <typename backend>
struct hash<boost::multiprecision::number<backend> >
: mp_hashing::hash_impl<boost::multiprecision::number<backend> >
{};
}
namespace boost {
template <typename backend>
struct hash<multiprecision::number<backend> >
: mp_hashing::hash_impl<multiprecision::number<backend> >
{};
}
template <typename Map>
void test(Map const& map) {
std::cout << "
" << __PRETTY_FUNCTION__ << "
";
for(auto& p : map)
std::cout << p.second << " " << p.first << "
";
}
int main() {
using boost::multiprecision::cpp_int;
test(std::unordered_map<cpp_int, std::string> {
{ cpp_int(1) << 111, "one" },
{ cpp_int(2) << 222, "two" },
{ cpp_int(3) << 333, "three" },
});
test(boost::unordered_map<cpp_int, std::string> {
{ cpp_int(1) << 111, "one" },
{ cpp_int(2) << 222, "two" },
{ cpp_int(3) << 333, "three" },
});
}
印刷品
void test(const Map&) [with Map = std::unordered_map<boost::multiprecision::number<boost::multiprecision::backends::cpp_int_backend<> >, std::basic_string<char> >]
one 2596148429267413814265248164610048
three 52494017394792286184940053450822912768476066341437098474218494553838871980785022157364316248553291776
two 13479973333575319897333507543509815336818572211270286240551805124608
void test(const Map&) [with Map = boost::unordered::unordered_map<boost::multiprecision::number<boost::multiprecision::backends::cpp_int_backend<> >, std::basic_string<char> >]
three 52494017394792286184940053450822912768476066341437098474218494553838871980785022157364316248553291776
two 13479973333575319897333507543509815336818572211270286240551805124608
one 2596148429267413814265248164610048
如您所见,Boost 和标准库的 unordered_map
在实现上的差异表现在相同散列的不同排序中.
As you can see, the difference in implementation between Boost's and the standard library's unordered_map
show up in the different orderings for identical hashes.
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