### Navigation

- index
- modules |
- modules |
- next |
- previous |
- NumPy v1.5 Manual (DRAFT) »
- NumPy Reference »
- Routines »

# Linear algebra (`numpy.linalg`)

## Matrix and vector products

`dot`(a, b) | Dot product of two arrays.
`vdot`(a, b) | Return the dot product of two vectors.
`inner`(a, b) | Inner product of two arrays.
`outer`(a, b) | Compute the outer product of two vectors.
`tensordot`(a, b[, axes]) | Compute tensor dot product along specified axes for arrays >= 1-D.
`linalg.matrix_power`(M, n) | Raise a square matrix to the (integer) power n.
`kron`(a, b) | Kronecker product of two arrays.

## Decompositions

`linalg.cholesky`(a) | Cholesky decomposition.
`linalg.qr`(a[, mode]) | Compute the qr factorization of a matrix.
`linalg.svd`(a[, full_matrices, compute_uv]) | Singular Value Decomposition.

## Matrix eigenvalues

`linalg.eig`(a) | Compute the eigenvalues and right eigenvectors of a square array.
`linalg.eigh`(a[, UPLO]) | Return the eigenvalues and eigenvectors of a Hermitian or symmetric matrix.
`linalg.eigvals`(a) | Compute the eigenvalues of a general matrix.
`linalg.eigvalsh`(a[, UPLO]) | Compute the eigenvalues of a Hermitian or real symmetric matrix.

## Norms and other numbers

`linalg.norm`(x[, ord]) | Matrix or vector norm.
`linalg.cond`(x[, p]) | Compute the condition number of a matrix.
`linalg.det`(a) | Compute the determinant of an array.
`linalg.slogdet`(a) | Compute the sign and (natural) logarithm of the determinant of an array.
`trace`(a[, offset, axis1, axis2, dtype, out]) | Return the sum along diagonals of the array.

## Solving equations and inverting matrices

`linalg.solve`(a, b) | Solve a linear matrix equation, or system of linear scalar equations.
`linalg.tensorsolve`(a, b[, axes]) | Solve the tensor equation `a x = b` for x.
`linalg.lstsq`(a, b[, rcond]) | Return the least-squares solution to a linear matrix equation.
`linalg.inv`(a) | Compute the (multiplicative) inverse of a matrix.
`linalg.pinv`(a[, rcond]) | Compute the (Moore-Penrose) pseudo-inverse of a matrix.
`linalg.tensorinv`(a[, ind]) | Compute the ‘inverse’ of an N-dimensional array.

## Exceptions

`linalg.LinAlgError` | Generic Python-exception-derived object raised by linalg functions.

### Navigation

- index
- modules |
- modules |
- next |
- previous |
- NumPy v1.5 Manual (DRAFT) »
- NumPy Reference »
- Routines »