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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.
Existing Eiffel software uses the string classes (such as STRING_8) from the Eiffel libraries, but Eiffel software written for .NET must use the .NET string class (System.String) in many cases, for example when calling .NET methods which expect items of the .NET type to be passed as arguments. So, the conversion of these types back and forth ...
If a decimal string with at most 6 significant digits is converted to the IEEE 754 single-precision format, giving a normal number, and then converted back to a decimal string with the same number of digits, the final result should match the original string. If an IEEE 754 single-precision number is converted to a decimal string with at least 9 ...
C source code to convert between IEEE double, single, and half precision can be found here; Java source code for half-precision floating-point conversion; Half precision floating point for one of the extended GCC features
C99 for code examples demonstrating access and use of IEEE 754 features; Floating-point arithmetic, for history, design rationale and example usage of IEEE 754 features; Fixed-point arithmetic, for an alternative approach at computation with rational numbers (especially beneficial when the exponent range is known, fixed, or bound at compile time)
Since, in practice, encoded NaNs have a sign, a quiet/signaling bit and optional 'diagnostic information' (sometimes called a payload), these will occasionally be found in string representations of NaNs, too. Some examples are: For the C and C++ languages, the sign bit is always shown by the standard-library functions (e.g. -nan) when present.
The bfloat16 (brain floating point) [1] [2] floating-point format is a computer number format occupying 16 bits in computer memory; it represents a wide dynamic range of numeric values by using a floating radix point.
Base64 encoding can be helpful when fairly lengthy identifying information is used in an HTTP environment. For example, a database persistence framework for Java objects might use Base64 encoding to encode a relatively large unique id (generally 128-bit UUIDs) into a string for use as an HTTP parameter in HTTP forms or HTTP GET URLs. Also, many ...