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larger of two floating-point values fmin: smaller of two floating-point values fdim: positive difference of two floating-point values nan nanf nanl: returns a NaN (not-a-number) Exponential functions exp: returns e raised to the given power exp2: returns 2 raised to the given power expm1: returns e raised to the given power, minus one log
When there is a tie, the floating-point number whose last stored digit is even (also, the last digit, in binary form, is equal to 0) is used. For IEEE standard where the base β {\displaystyle \beta } is 2 {\displaystyle 2} , this means when there is a tie it is rounded so that the last digit is equal to 0 {\displaystyle 0} .
Here we start with 0 in single precision (binary32) and repeatedly add 1 until the operation does not change the value. Since the significand for a single-precision number contains 24 bits, the first integer that is not exactly representable is 2 24 +1, and this value rounds to 2 24 in round to nearest, ties to even.
This alternative definition is significantly more widespread: machine epsilon is the difference between 1 and the next larger floating point number.This definition is used in language constants in Ada, C, C++, Fortran, MATLAB, Mathematica, Octave, Pascal, Python and Rust etc., and defined in textbooks like «Numerical Recipes» by Press et al.
[2] In C++, the C++20 revision adds the spaceship operator <=>, which returns a value that encodes whether the 2 values are equal, less, greater, or unordered and can return different types depending on the strictness of the comparison. [3] The name's origin is due to it reminding Randal L. Schwartz of the spaceship in an HP BASIC Star Trek ...
An implementation can choose the representation of float, double, and long double to be the same as the decimal floating types. [2] Despite that, the radix has historically been binary (base 2), meaning numbers like 1/2 or 1/4 are exact, but not 1/10, 1/100 or 1/3. With decimal floating point all the same numbers are exact plus numbers like 1/ ...
For numbers with a base-2 exponent part of 0, i.e. numbers with an absolute value higher than or equal to 1 but lower than 2, an ULP is exactly 2 −23 or about 10 −7 in single precision, and exactly 2 −53 or about 10 −16 in double precision. The mandated behavior of IEEE-compliant hardware is that the result be within one-half of a ULP.
Double-precision floating-point format (sometimes called FP64 or float64) is a floating-point number format, usually occupying 64 bits in computer memory; it represents a wide range of numeric values by using a floating radix point. Double precision may be chosen when the range or precision of single precision would be insufficient. In the IEEE ...