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For data requests that fall between the table's samples, an interpolation algorithm can generate reasonable approximations by averaging nearby samples." [8] In data analysis applications, such as image processing, a lookup table (LUT) can be used to transform the input data into a more desirable output format. For example, a grayscale picture ...
dc: "Desktop Calculator" arbitrary-precision RPN calculator that comes standard on most Unix-like systems. KCalc, Linux based scientific calculator; Maxima: a computer algebra system which bignum integers are directly inherited from its implementation language Common Lisp. In addition, it supports arbitrary-precision floating-point numbers ...
In computer science, a dynamic array, growable array, resizable array, dynamic table, mutable array, or array list is a random access, variable-size list data structure that allows elements to be added or removed. It is supplied with standard libraries in many modern mainstream programming languages.
BER: variable-length big-endian binary representation (up to 2 2 1024 bits); PER Unaligned: a fixed number of bits if the integer type has a finite range; a variable number of bits otherwise; PER Aligned: a fixed number of bits if the integer type has a finite range and the size of the range is less than 65536; a variable number of octets ...
java.util.Collection class and interface hierarchy Java's java.util.Map class and interface hierarchy. The Java collections framework is a set of classes and interfaces that implement commonly reusable collection data structures. [1] Although referred to as a framework, it works in a manner of a library. The collections framework provides both ...
This is most commonly implemented in the underlying object model, like .Net or Cocoa, which includes standard functions that convert the internal data into text. The program can create a complete text representation of any group of objects by calling these methods, which are almost always already implemented in the base associative array class.
The half-precision binary floating-point exponent is encoded using an offset-binary representation, with the zero offset being 15; also known as exponent bias in the IEEE 754 standard. [9] E min = 00001 2 − 01111 2 = −14; E max = 11110 2 − 01111 2 = 15; Exponent bias = 01111 2 = 15
convert a double to a float: d2i 8e 1000 1110 value → result convert a double to an int d2l 8f 1000 1111 value → result convert a double to a long dadd 63 0110 0011 value1, value2 → result add two doubles daload 31 0011 0001 arrayref, index → value load a double from an array dastore 52 0101 0010 arrayref, index, value →