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Unlike the bitset in C++, the Java BitSet does not have a "size" state (it has an effectively infinite size, initialized with 0 bits); a bit can be set or tested at any index. In addition, there is a class EnumSet , which represents a Set of values of an enumerated type internally as a bit vector, as a safer alternative to bit fields.
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 otherwise; OER: 1, 2, or 4 octets (either signed or unsigned) if the integer type has a finite range that fits in that number of octets; a variable number of octets otherwise
In computer programming, a bitwise operation operates on a bit string, a bit array or a binary numeral (considered as a bit string) at the level of its individual bits.It is a fast and simple action, basic to the higher-level arithmetic operations and directly supported by the processor.
A bit field is distinguished from a bit array in that the latter is used to store a large set of bits indexed by integers and is often wider than any integral type supported by the language. [citation needed] Bit fields, on the other hand, typically fit within a machine word, [3] and the denotation of bits is independent of their numerical ...
The Zstandard command-line has an "adaptive" (--adapt) mode that varies compression level depending on I/O conditions, mainly how fast it can write the output. Zstd at its maximum compression level gives a compression ratio close to lzma, lzham, and ppmx, and performs better [vague] than lza or bzip2.
The Hamming weight is named after the American mathematician Richard Hamming, although he did not originate the notion. [5] The Hamming weight of binary numbers was already used in 1899 by James W. L. Glaisher to give a formula for the number of odd binomial coefficients in a single row of Pascal's triangle. [6]
The algorithm essentially divides a large problem (e.g. the full sequence) into a series of smaller problems, and it uses the solutions to the smaller problems to find an optimal solution to the larger problem. [2] It is also sometimes referred to as the optimal matching algorithm and the global alignment technique. The Needleman–Wunsch ...
While BLAST is faster than any Smith-Waterman implementation for most cases, it cannot "guarantee the optimal alignments of the query and database sequences" as Smith-Waterman algorithm does. The Smith-Waterman algorithm was an extension of a previous optimal method, the Needleman–Wunsch algorithm , which was the first sequence alignment ...