Linear algebra | NumPower

📄️ NDArray::cholesky

Calculates the Cholesky decomposition of a positive-definite array, decomposing

Computes the condition number of an array.

Computes the determinant of a square array, which represents the scaling factor of the volume

The dot function performs the dot product of two arrays. The behaviour of the function

Computes the eigenvalues and eigenvectors of a square array.

Calculates the inner product of two arrays. This operation involves multiplying corresponding

Compute the inverse of a matrix, such that $a * nd::identity($a->shape()).

Performs the least-squares solution to a linear matrix equation Ax = b,

Computes the LU factorization of a matrix

Performs matrix multiplication between two arrays and returns the result as a new array.

Calculates the numerical rank of a matrix, number of singular values of the array that are greater than tol.

Calculates different norms (e.g., L1 norm, L2 norm) of an array,

Computes the outer product of two vectors, which results in a higher-dimensional array with dimensions

Calculates the QR decomposition of an array, which expresses it as the product of an orthogonal matrix (Q)

Solves a linear system of equations for x, where Ax = b, and A and b are given arrays.

Calculates the Singular Value Decomposition (SVD) of an array, which decomposes the array

Computes the sum of the diagonal elements of a square array, also known as the trace of the array.