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Slice semantics potentially differ per object; new semantics can be introduced when operator overloading the indexing operator. With Python standard lists (which are dynamic arrays), every slice is a copy. Slices of NumPy arrays, by contrast, are views onto the same underlying buffer.
The following list contains syntax examples of how a range of element of an array can be accessed. In the following table: first – the index of the first element in the slice; last – the index of the last element in the slice; end – one more than the index of last element in the slice; len – the length of the slice (= end - first)
Thus, an array of numbers with 5 rows and 4 columns, hence 20 elements, is said to have dimension 2 in computing contexts, but represents a matrix that is said to be 4×5-dimensional. Also, the computer science meaning of "rank" conflicts with the notion of tensor rank, which is a generalization of the linear algebra concept of rank of a matrix.)
One method of copying an object is the shallow copy.In that case a new object B is created, and the fields values of A are copied over to B. [3] [4] [5] This is also known as a field-by-field copy, [6] [7] [8] field-for-field copy, or field copy. [9]
Similarly, slice( sum = sum + i + w, i) only contains "for(i = 1; i < N; ++i) {" and slice( sum = sum + i + w, w) only contains the statement "int w = 7". When we union all of those statements, we do not have executable code, so to make the slice an executable slice we merely add the end brace for the for loop and the declaration of i.
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