比较两个双精度浮点数或两个浮点数最有效的方法是什么?
简单地这样做是不正确的:
bool CompareDoubles1 (double A, double B)
{
return A == B;
}
比如:
bool CompareDoubles2 (double A, double B)
{
diff = A - B;
return (diff < EPSILON) && (-diff < EPSILON);
}
似乎是浪费加工。
有人知道更聪明的浮点比较器吗?
当前回答
这是另一个解:
#include <cmath>
#include <limits>
auto Compare = [](float a, float b, float epsilon = std::numeric_limits<float>::epsilon()){ return (std::fabs(a - b) <= epsilon); };
其他回答
General-purpose comparison of floating-point numbers is generally meaningless. How to compare really depends on a problem at hand. In many problems, numbers are sufficiently discretized to allow comparing them within a given tolerance. Unfortunately, there are just as many problems, where such trick doesn't really work. For one example, consider working with a Heaviside (step) function of a number in question (digital stock options come to mind) when your observations are very close to the barrier. Performing tolerance-based comparison wouldn't do much good, as it would effectively shift the issue from the original barrier to two new ones. Again, there is no general-purpose solution for such problems and the particular solution might require going as far as changing the numerical method in order to achieve stability.
在c++中获取的可移植方法是
#include <limits>
std::numeric_limits<double>::epsilon()
然后比较函数变成
#include <cmath>
#include <limits>
bool AreSame(double a, double b) {
return std::fabs(a - b) < std::numeric_limits<double>::epsilon();
}
我的方法也许不正确，但很有用
将两个浮点数都转换为字符串，然后进行字符串比较
bool IsFlaotEqual(float a, float b, int decimal)
{
TCHAR form[50] = _T("");
_stprintf(form, _T("%%.%df"), decimal);
TCHAR a1[30] = _T(""), a2[30] = _T("");
_stprintf(a1, form, a);
_stprintf(a2, form, b);
if( _tcscmp(a1, a2) == 0 )
return true;
return false;
}
也可以做到操作人员超载
我使用这个代码:
bool AlmostEqual(double v1, double v2)
{
return (std::fabs(v1 - v2) < std::fabs(std::min(v1, v2)) * std::numeric_limits<double>::epsilon());
}
/// testing whether two doubles are almost equal. We consider two doubles
/// equal if the difference is within the range [0, epsilon).
///
/// epsilon: a positive number (supposed to be small)
///
/// if either x or y is 0, then we are comparing the absolute difference to
/// epsilon.
/// if both x and y are non-zero, then we are comparing the relative difference
/// to epsilon.
bool almost_equal(double x, double y, double epsilon)
{
double diff = x - y;
if (x != 0 && y != 0){
diff = diff/y;
}
if (diff < epsilon && -1.0*diff < epsilon){
return true;
}
return false;
}
我在我的小项目中使用了这个函数，它是有效的，但注意以下几点:
双精度误差可以为你制造惊喜。假设epsilon = 1.0e-6，那么根据上面的代码，1.0和1.000001不应该被认为是相等的，但在我的机器上，函数认为它们是相等的，这是因为1.000001不能精确地转换为二进制格式，它可能是1.0000009xxx。我用1.0和1.0000011测试了它，这次我得到了预期的结果。
