# `linalg`¶

Linear algebra functions.

numpy.linalg for more linear algebra functions. Note that although scipy.linalg imports most of them, identically named functions from scipy.linalg may offer more or slightly differing functionality.

### Basics¶

 `inv` `solve` `solve_banded` `solveh_banded` `solve_circulant` `solve_triangular` `solve_toeplitz` `det` `norm` `lstsq` `pinv` `pinv2` `pinvh` `kron` `tril` `triu` `orthogonal_procrustes` `matrix_balance` `subspace_angles` `LinAlgError`

### Eigenvalue Problems¶

 `eig` `eigvals` `eigh` `eigvalsh` `eig_banded` `eigvals_banded` `eigh_tridiagonal` `eigvalsh_tridiagonal`

### Decompositions¶

 `lu` `lu_factor` `lu_solve` `svd` `svdvals` `diagsvd` `orth` `cholesky` `cholesky_banded` `cho_factor` `cho_solve` `cho_solve_banded` `polar` `qr` `qr_multiply` `qr_update` `qr_delete` `qr_insert` `rq` `qz` `ordqz` `schur` `rsf2csf` `hessenberg`

scipy.linalg.interpolative – Interpolative matrix decompositions

### Matrix Functions¶

 `expm` `logm` `cosm` `sinm` `tanm` `coshm` `sinhm` `tanhm` `signm` `sqrtm` `funm` `expm_frechet` `expm_cond` `fractional_matrix_power`

### Matrix Equation Solvers¶

 `solve_sylvester` `solve_continuous_are` `solve_discrete_are` `solve_continuous_lyapunov` `solve_discrete_lyapunov`

### Sketches and Random Projections¶

 `clarkson_woodruff_transform`

### Special Matrices¶

 `block_diag` `circulant` `companion` `dft` `hadamard` `hankel` `helmert` `hilbert` `invhilbert` `leslie` `pascal` `invpascal` `toeplitz` `tri`

### Low-level routines¶

 `get_blas_funcs` `get_lapack_funcs` `find_best_blas_type`