std::numeric_limits<T>::tinyness_before (3) - Linux Manuals
std::numeric_limits<T>::tinyness_before: std::numeric_limits<T>::tinyness_before
NAME
std::numeric_limits<T>::tinyness_before - std::numeric_limits<T>::tinyness_before
Synopsis
static const bool tinyness_before; (until C++11)
static constexpr bool tinyness_before; (since C++11)
The value of std::numeric_limits<T>::tinyness_before is true for all floating-point types T that test results of floating-point expressions for underflow before rounding.
Standard specializations
T value of std::numeric_limits<T>::tinyness_before
/* non-specialized */ false
bool false
char false
signed char false
unsigned char false
wchar_t false
char8_t false
char16_t false
char32_t false
short false
unsigned short false
int false
unsigned int false
long false
unsigned long false
long long false
unsigned long long false
float implementation-defined
double implementation-defined
long double implementation-defined
Notes
Standard-compliant IEEE 754 floating-point implementations are required to detect the floating-point underflow, and have two alternative situations where this can be done
1) Underflow occurs (and FE_UNDERFLOW may be raised) if a computation produces a result whose absolute value, computed as though both the exponent range and the precision were unbounded, is smaller than std::numeric_limits<T>::min(). Such implementation detects tinyness before rounding (e.g. UltraSparc, POWER).
2) Underflow occurs (and FE_UNDERFLOW may be raised) if after the rounding of the result to the target floating-point type (that is, rounding to std::numeric_limits<T>::digits bits), the result's absolute value is smaller than std::numeric_limits<T>::min(). Formally, the absolute value of a nonzero result computed as though the exponent range were unbounded is smaller than std::numeric_limits<T>::min(). Such implementation detects tinyness after rounding (e.g. SuperSparc)
Example
Multiplication of the largest subnormal number by the number one machine epsilon greater than 1.0 gives the tiny value 0x0.fffffffffffff8p-1022 before rounding, but normal value 1p-1022 after rounding. The implementation used to execute this test (IBM Power7) detects tinyness before rounding.
// Run this code
Possible output:
See also
has_denorm_loss identifies the floating-point types that detect loss of precision as denormalization loss rather than inexact result
[static]
has_denorm identifies the denormalization style used by the floating-point type
[static]