brainunit.linalg module

`brainunit.linalg` module#

`dot`	Compute the dot product of two arrays or quantities.
`multi_dot`	Efficiently compute matrix products between a sequence of arrays.
`vdot`	Perform a conjugate multiplication of two 1D vectors.
`vecdot`	Perform a conjugate multiplication of two batched vectors.
`inner`	Compute the inner product of two arrays or quantities.
`kron`	Compute the Kronecker product of two arrays or quantities.
`matmul`	Compute the matrix product of two arrays or quantities.
`tensordot`	Compute tensor dot product along specified axes.
`matrix_power`	Raise a square matrix to the (integer) power n.
`cross`	Return the cross product of two (arrays of) vectors.
`cholesky`	Compute the Cholesky decomposition of a matrix.
`outer`	Compute the outer product of two vectors or quantities.
`det`	Compute the determinant of a matrix.
`solve`	Solve a linear system of equations.
`tensorsolve`	Solve the tensor equation `a x = b` for `x`.
`lstsq`	Return the least-squares solution to a linear equation.
`inv`	Return the inverse of a square matrix.
`pinv`	Compute the Moore-Penrose pseudo-inverse of a matrix.
`tensorinv`	Compute the tensor inverse of an array.

`qr`	Compute the QR decomposition of a matrix.
`svd`	Singular value decomposition.
`svdvals`	Compute the singular values of a matrix.
`eig`	Compute the eigenvalues and eigenvectors of a square matrix.
`eigh`	Compute eigenvalues and eigenvectors of a Hermitian matrix.
`eigvals`	Compute the eigenvalues of a general matrix.
`eigvalsh`	Compute the eigenvalues of a Hermitian matrix.
`norm`	Compute the norm of a matrix or vector.
`matrix_norm`	Compute the norm of a matrix or stack of matrices.
`vector_norm`	Compute the vector norm of a vector or batch of vectors.
`trace`	Return the sum along diagonals of the array.
`diagonal`	Return specified diagonals.
`matrix_transpose`	Transpose a matrix or stack of matrices.