Linear algebra (numpy.linalg)¶
Matrix and vector products¶
| dot () | |
| vdot (a, b) | Return the dot product of two vectors. |
| inner (a, b) | Inner product of two arrays. |
| outer (a, b) | Returns the outer product of two vectors. |
| tensordot (a, b[, axes]) | Returns the tensor dot product for (ndim >= 1) arrays along an axes. |
| 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 QR decomposition of a matrix. |
| linalg.svd (a[, full_matrices, compute_uv]) | Singular Value Decomposition. |
Matrix eigenvalues¶
| linalg.eig (a) | Compute eigenvalues and right eigenvectors of an array. |
| linalg.eigh (a[, UPLO]) | Eigenvalues and eigenvectors of a Hermitian or real symmetric matrix. |
| linalg.eigvals (a) | Compute the eigenvalues of a general matrix. |
| linalg.eigvalsh (a[, UPLO]) | Compute the eigenvalues of a Hermitean 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. |
| trace (a[, offset, axis1, axis2, ...]) | Return the sum along diagonals of the array. |
Solving equations and inverting matrices¶
| linalg.solve (a, b) | Solve the equation a x = b for x. |
| 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 an equation. |
| linalg.inv (a) | Compute the inverse of a matrix. |
| linalg.pinv (a[, rcond]) | Compute the (Moore-Penrose) pseudo-inverse of a matrix. |
| linalg.tensorinv (a[, ind]) | Find the ‘inverse’ of a N-d array |
Exceptions¶
| linalg.LinAlgError | # Error object |
