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An array data structure can be mathematically modeled as an abstract data structure (an abstract array) with two operations get(A, I): the data stored in the element of the array A whose indices are the integer tuple I. set(A, I, V): the array that results by setting the value of that element to V. These operations are required to satisfy the ...
NumPy (pronounced / ˈ n ʌ m p aɪ / NUM-py) is a library for the Python programming language, adding support for large, multi-dimensional arrays and matrices, along with a large collection of high-level mathematical functions to operate on these arrays. [3]
Support for multi-dimensional arrays may also be provided by external libraries, which may even support arbitrary orderings, where each dimension has a stride value, and row-major or column-major are just two possible resulting interpretations. Row-major order is the default in NumPy [19] (for Python).
In array languages, operations are generalized to apply to both scalars and arrays. Thus, a+b expresses the sum of two scalars if a and b are scalars, or the sum of two arrays if they are arrays. An array language simplifies programming but possibly at a cost known as the abstraction penalty.
In C, enumerations assign related names to a set of integer values. In Swift, enumerations are much more flexible and need not provide a value for each case of the enumeration. If a value (termed a raw value) is provided for each enumeration case, the value can be a string, a character, or a value of any integer or floating-point type.
For every type T, except void and function types, there exist the types "array of N elements of type T". An array is a collection of values, all of the same type, stored contiguously in memory. An array of size N is indexed by integers from 0 up to and including N−1. Here is a brief example:
CuPy is an open source library for GPU-accelerated computing with Python programming language, providing support for multi-dimensional arrays, sparse matrices, and a variety of numerical algorithms implemented on top of them. [3] CuPy shares the same API set as NumPy and SciPy, allowing it to be a drop-in replacement to run NumPy/SciPy code on GPU.
In C/C++, it is possible to declare the parameter of a function or method as constant. This is a guarantee that this parameter cannot be inadvertently modified after its initialization by the caller. If the parameter is a pre-defined (built-in) type, it is called by value and cannot be modified.