Linear algebra (numpy.linalg)¶
Matrix and vector products¶
| dot | |
| vdot | |
| inner | |
| outer | |
| tensordot | |
| einsum | |
| linalg.matrix_power(M, n) | Raise a square matrix to the (integer) power n. |
| kron |
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 |
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. |
