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[3] the predecessor of numpy, numeric, was originally created by jim hugunin with contributions from several other developers A list comprehension is a syntactic construct available in some programming languages for creating a list based on existing lists This comparison of programming languages (array) compares the features of array data structures or matrix processing for various computer programming languages.
In computer science, an array is a data structure consisting of a collection of elements (values or variables), of same memory size, each identified by at least one array index or key, a collection of which may be a tuple, known as an index tuple The outer product of multidimensional arrays can be computed using np.multiply.outer. In general, an array is a mutable and linear collection of elements with the same data type.
In computer science, array is a data type that represents a collection of elements (values or variables), each selected by one or more indices (identifying keys) that can be computed at run time during program execution
Such a collection is usually called an array variable or array value [1] by analogy with the mathematical concepts vector and matrix, array types with one and two indices are. The term list is also used for several concrete data structures that can be used to implement abstract lists, especially linked lists and arrays In some contexts, such as in lisp programming, the term list may refer specifically to a linked list rather than an array.
The logical size and capacity of the final array are shown In computer science, array programming refers to solutions that allow the application of operations to an entire set of values at once Such solutions are commonly used in scientific and engineering settings. The difference between the orders lies in which elements of an array are contiguous in memory.
In the python library numpy, the outer product can be computed with function np.outer()
[8] in contrast, np.kron results in a flat array
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