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Eigen is a high-level C++ library of template headers for linear algebra, matrix and vector operations, geometrical transformations, numerical solvers and related algorithms. . Eigen is open-source software licensed under the Mozilla Public License 2.0 since version 3.1
Vectors allow random access; that is, an element of a vector may be referenced in the same manner as elements of arrays (by array indices). Linked-lists and sets , on the other hand, do not support random access or pointer arithmetic.
Apache C++ Standard Library (The starting point for this library was the 2005 version of the Rogue Wave standard library [15]) Libstdc++ uses code derived from SGI STL for the algorithms and containers defined in C++03. Dinkum STL library by P.J. Plauger; The Microsoft STL which ships with Visual C++ is a licensed derivative of Dinkum's STL.
C++ programmers expect the latter on every major implementation of C++; it includes aggregate types (vectors, lists, maps, sets, queues, stacks, arrays, tuples), algorithms (find, for_each, binary_search, random_shuffle, etc.), input/output facilities (iostream, for reading from and writing to the console and files), filesystem library ...
Consider a library representing vectors and operations on them. One common mathematical operation is to add two vectors u and v, element-wise, to produce a new vector.The obvious C++ implementation of this operation would be an overloaded operator+ that returns a new vector object:
Vector (C++), a type in the C++ Standard Template Library; Euclidean vector, a geometric object with a direction and magnitude Vector graphics, images defined by geometric primitives as opposed to bitmaps; Vector monitor, a display device used for early computers; Vector game, any video game that uses a vector graphics display
In computer graphics, swizzles are a class of operations that transform vectors by rearranging components. [1] Swizzles can also project from a vector of one dimensionality to a vector of another dimensionality, such as taking a three-dimensional vector and creating a two-dimensional or five-dimensional vector using components from the original vector. [2]
Intrinsic functions are often used to explicitly implement vectorization and parallelization in languages which do not address such constructs. Some application programming interfaces (API), for example, AltiVec and OpenMP, use intrinsic functions to declare, respectively, vectorizable and multiprocessing-aware operations during compiling.