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Conversely, precision can be lost when converting representations from integer to floating-point, since a floating-point type may be unable to exactly represent all possible values of some integer type. For example, float might be an IEEE 754 single precision type, which cannot represent the integer 16777217 exactly, while a 32-bit integer type ...
In Pascal, copying a real to an integer converts it to the truncated value. This method would translate the binary value of the floating-point number into whatever it is as a long integer (32 bit), which will not be the same and may be incompatible with the long integer value on some systems.
Information about the actual properties, such as size, of the basic arithmetic types, is provided via macro constants in two headers: <limits.h> header (climits header in C++) defines macros for integer types and <float.h> header (cfloat header in C++) defines macros for floating-point types. The actual values depend on the implementation.
Go: the standard library package math/big implements arbitrary-precision integers (Int type), rational numbers (Rat type), and floating-point numbers (Float type) Guile: the built-in exact numbers are of arbitrary precision. Example: (expt 10 100) produces the expected (large) result. Exact numbers also include rationals, so (/ 3 4) produces 3/4.
A floating-point variable can represent a wider range of numbers than a fixed-point variable of the same bit width at the cost of precision. A signed 32-bit integer variable has a maximum value of 2 31 − 1 = 2,147,483,647, whereas an IEEE 754 32-bit base-2 floating-point variable has a maximum value of (2 − 2 −23) × 2 127 ≈ 3.4028235 ...
The C programming language, for instance, supplies types such as Booleans, integers, floating-point numbers, etc., but the precise bit representations of these types are implementation-defined. The only C type with a precise machine representation is the char type that represents a byte.
In the floating-point case, a variable exponent would represent the power of ten to which the mantissa of the number is multiplied. Languages that support a rational data type usually allow the construction of such a value from two integers, instead of a base-2 floating-point number, due to the loss of exactness the latter would cause.
Unums (universal numbers [1]) are a family of number formats and arithmetic for implementing real numbers on a computer, proposed by John L. Gustafson in 2015. [2] They are designed as an alternative to the ubiquitous IEEE 754 floating-point standard. The latest version is known as posits. [3]