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  2. Rounding - Wikipedia

    en.wikipedia.org/wiki/Rounding

    Some programming languages (such as Java and Python) use "half up" to refer to round half away from zero rather than round half toward positive infinity. [4] [5] This method only requires checking one digit to determine rounding direction in two's complement and similar representations.

  3. Round-off error - Wikipedia

    en.wikipedia.org/wiki/Round-off_error

    There are two common rounding rules, round-by-chop and round-to-nearest. The IEEE standard uses round-to-nearest. Round-by-chop: The base-expansion of is truncated after the ()-th digit. This rounding rule is biased because it always moves the result toward zero.

  4. Floating-point arithmetic - Wikipedia

    en.wikipedia.org/wiki/Floating-point_arithmetic

    For example, the decimal number 123456789 cannot be exactly represented if only eight decimal digits of precision are available (it would be rounded to one of the two straddling representable values, 12345678 × 10 1 or 12345679 × 10 1), the same applies to non-terminating digits (. 5 to be rounded to either .55555555 or .55555556).

  5. Machine epsilon - Wikipedia

    en.wikipedia.org/wiki/Machine_epsilon

    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.

  6. IEEE 754 - Wikipedia

    en.wikipedia.org/wiki/IEEE_754

    Two different bit-level encodings are defined, and interchange is complicated by the fact that some external indicator of the encoding in use may be required. The two options allow the significand to be encoded as a compressed sequence of decimal digits using densely packed decimal or, alternatively, as a binary integer. The former is more ...

  7. Half-precision floating-point format - Wikipedia

    en.wikipedia.org/wiki/Half-precision_floating...

    In computing, half precision (sometimes called FP16 or float16) is a binary floating-point computer number format that occupies 16 bits (two bytes in modern computers) in computer memory. It is intended for storage of floating-point values in applications where higher precision is not essential, in particular image processing and neural networks .

  8. Kahan summation algorithm - Wikipedia

    en.wikipedia.org/wiki/Kahan_summation_algorithm

    The first result, after rounding, would be 10003.1. The second result would be 10005.81828 before rounding and 10005.8 after rounding. This is not correct. However, with compensated summation, we get the correctly rounded result of 10005.9. Assume that c has the initial value zero. Trailing zeros shown where they are significant for the six ...

  9. Python (programming language) - Wikipedia

    en.wikipedia.org/wiki/Python_(programming_language)

    Since 7 October 2024, Python 3.13 is the latest stable release, and it and, for few more months, 3.12 are the only releases with active support including for bug fixes (as opposed to just for security) and Python 3.9, [55] is the oldest supported version of Python (albeit in the 'security support' phase), due to Python 3.8 reaching end-of-life.