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An example of the printf function. printf is a C standard library function that formats text and writes it to standard output.. The name, printf is short for print formatted where print refers to output to a printer although the functions are not limited to printer output.
All integers with seven or fewer decimal digits, and any 2 n for a whole number −149 ≤ n ≤ 127, can be converted exactly into an IEEE 754 single-precision floating-point value. In the IEEE 754 standard, the 32-bit base-2 format is officially referred to as binary32; it was called single in IEEE 754-1985.
For the next range, from 2 53 to 2 54, everything is multiplied by 2, so the representable numbers are the even ones, etc. Conversely, for the previous range from 2 51 to 2 52, the spacing is 0.5, etc. The spacing as a fraction of the numbers in the range from 2 n to 2 n+1 is 2 n−52.
Starting with Python 2.4, Python's standard library includes a Decimal class in the module decimal. [2] Ruby's standard library includes a BigDecimal class in the module bigdecimal. Java's standard library includes a java.math.BigDecimal class. In Objective-C, the Cocoa and GNUstep APIs provide an NSDecimalNumber class and an NSDecimal C data ...
The binary format with the same bit-size, binary32, has an approximate range from subnormal-minimum ±1 × 10 ^ −45 over normal-minimum with full 24-bit precision: ±1.175 494 4 × 10 ^ −38 to maximum ±3.402 823 5 × 10 ^ 38.
This gives from 33 to 36 significant decimal digits precision. If a decimal string with at most 33 significant digits is converted to the IEEE 754 quadruple-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.
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.
To approximate the greater range and precision of real numbers, we have to abandon signed integers and fixed-point numbers and go to a "floating-point" format. In the decimal system, we are familiar with floating-point numbers of the form (scientific notation): 1.1030402 × 10 5 = 1.1030402 × 100000 = 110304.02. or, more compactly: 1.1030402E5