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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 ...
The word cast, on the other hand, refers to explicitly changing the interpretation of the bit pattern representing a value from one type to another. For example, 32 contiguous bits may be treated as an array of 32 Booleans, a 4-byte string, an unsigned 32-bit integer or an IEEE single precision floating point value.
The C language provides basic arithmetic types, such as integer and real number types, and syntax to build array and compound types. Headers for the C standard library , to be used via include directives , contain definitions of support types, that have additional properties, such as providing storage with an exact size, independent of 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] The predecessor of NumPy, Numeric, was originally created by Jim Hugunin with ...
The reinterpret cast technique from C/C++ also works in Pascal. This can be useful, when eg. reading dwords from a byte stream, and we want to treat them as float. Here is a working example, where we reinterpret-cast a dword to a float:
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.
Matrix multiplication is an example of a 2-rank function, because it operates on 2-dimensional objects (matrices). Collapse operators reduce the dimensionality of an input data array by one or more dimensions. For example, summing over elements collapses the input array by 1 dimension.
If the array abstraction does not support true negative indices (as for example the arrays of Ada and Pascal do), then negative indices for the bounds of the slice for a given dimension are sometimes used to specify an offset from the end of the array in that dimension. In 1-based schemes, -1 generally would indicate the second-to-last item ...