C++中double/float类型的二进制序列化的可移植性

2021-12-21 00:00:00 serialization portability ieee-754 double c++

C++ 标准不讨论 float 和 double 类型的底层布局，只讨论它们应该表示的值范围.(对于有符号类型也是如此，是两个的恭维还是别的什么)

The C++ standard does not discuss the underlying layout of float and double types, only the range of values they should represent. (This is also true for signed types, is it two's compliment or something else)

我的问题是:用于以可移植方式序列化/反序列化诸如 double 和 float 之类的 POD 类型的技术有哪些?目前看来，唯一的方法是将值按字面表示(如123.456")，double 的 ieee754 布局并不是所有架构的标准.

My question is: What the are techniques used to serialize/deserialize POD types such as double and float in a portable manner? At the moment it seems the only way to do this is to have the value represented literally(as in "123.456"), The ieee754 layout for double is not standard on all architectures.

推荐答案

Brian "Beej Jorgensen" Hall 在他的 网络编程指南 一些将float(对应double)打包到uint32_t 的代码code> (resp. uint64_t) 能够安全地通过网络在两台机器之间传输它，这台机器可能不同意他们的表示.它有一些限制，主要是不支持 NaN 和无穷大.

Brian "Beej Jorgensen" Hall gives in his Guide to Network Programming some code to pack float (resp. double) to uint32_t (resp. uint64_t) to be able to safely transmit it over the network between two machine that may not both agree to their representation. It has some limitation, mainly it does not support NaN and infinity.

这是他的打包函数:

#define pack754_32(f) (pack754((f), 32, 8))
#define pack754_64(f) (pack754((f), 64, 11))

uint64_t pack754(long double f, unsigned bits, unsigned expbits)
{
    long double fnorm;
    int shift;
    long long sign, exp, significand;
    unsigned significandbits = bits - expbits - 1; // -1 for sign bit

    if (f == 0.0) return 0; // get this special case out of the way

    // check sign and begin normalization
    if (f < 0) { sign = 1; fnorm = -f; }
    else { sign = 0; fnorm = f; }

    // get the normalized form of f and track the exponent
    shift = 0;
    while(fnorm >= 2.0) { fnorm /= 2.0; shift++; }
    while(fnorm < 1.0) { fnorm *= 2.0; shift--; }
    fnorm = fnorm - 1.0;

    // calculate the binary form (non-float) of the significand data
    significand = fnorm * ((1LL<<significandbits) + 0.5f);

    // get the biased exponent
    exp = shift + ((1<<(expbits-1)) - 1); // shift + bias

    // return the final answer
    return (sign<<(bits-1)) | (exp<<(bits-expbits-1)) | significand;
}

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