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Pairwise summation is the default summation algorithm in NumPy [9] and the Julia technical-computing language, [10] where in both cases it was found to have comparable speed to naive summation (thanks to the use of a large base case).
In numerical linear algebra, the Arnoldi iteration is an eigenvalue algorithm and an important example of an iterative method.Arnoldi finds an approximation to the eigenvalues and eigenvectors of general (possibly non-Hermitian) matrices by constructing an orthonormal basis of the Krylov subspace, which makes it particularly useful when dealing with large sparse matrices.
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]
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.
These often generalize to multi-dimensional arguments, and more than two arguments. 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. The outer product of multidimensional arrays can be computed using np.multiply.outer.
There is an optimization version of the partition problem, which is to partition the multiset S into two subsets S 1, S 2 such that the difference between the sum of elements in S 1 and the sum of elements in S 2 is minimized. The optimization version is NP-hard, but can be solved efficiently in practice. [4]
Args: histogram (np.ndarray): The histogram of the image as a 1D numpy array, where each element represents the count of pixels at a specific intensity level. minimum_bin_count (int): Minimum count for a bin to be considered in the thresholding process. Bins with counts below this value are ignored, reducing the effect of noise.
Formally, a parity check matrix H of a linear code C is a generator matrix of the dual code, C ⊥.This means that a codeword c is in C if and only if the matrix-vector product Hc ⊤ = 0 (some authors [1] would write this in an equivalent form, cH ⊤ = 0.)