Linear Algebra

Wrappers for numpy.linalg.

Matrix and vector products

einsum(dims, *operands[, keep_dims, ...])	Preprocess inputs to call numpy.einsum or numpy.einsum_path.
raw_einsum(subscripts, *operands[, ...])	Wrap numpy.einsum crudely.
einsum_path(dims, *operands[, keep_dims, ...])	Wrap numpy.einsum_path.
matmul(da, db[, dims, out_append])	Wrap numpy.linalg.matmul.
linalg.matrix_transpose(da, dims)	Transpose the underlying matrix without modifying the dimensions.
linalg.matrix_power(da, n[, dims])	Wrap numpy.linalg.matrix_power.

Decompositions

cholesky(da[, dims])	Wrap numpy.linalg.cholesky.
qr(da[, dims, mode, out_append])	Wrap numpy.linalg.qr.
svd(da[, dims, full_matrices, compute_uv, ...])	Wrap numpy.linalg.svd.

Matrix eigenvalues

eig(da[, dims])	Wrap numpy.linalg.eig.
eigh(da[, dims, UPLO])	Wrap numpy.linalg.eigh.
eigvals(da[, dims])	Wrap numpy.linalg.eigvals.
eigvalsh(da[, dims, UPLO])	Wrap numpy.linalg.eigvalsh.

Norms and other numbers

norm(da[, dims, ord])	Wrap numpy.linalg.norm.
cond(da[, dims, p])	Wrap numpy.linalg.cond.
det(da[, dims])	Wrap numpy.linalg.det.
matrix_rank(da[, dims, tol, hermitian])	Wrap numpy.linalg.matrix_rank.
slogdet(da[, dims])	Wrap numpy.linalg.slogdet.
trace(da[, dims, offset, dtype, out])	Wrap numpy.trace.

Solving equations and inverting matrices

solve(da, db[, dims])	Wrap numpy.linalg.solve.
inv(da[, dims])	Wrap numpy.linalg.inv.

Convenience functions

get_default_dims(da1_dims[, d2_dims])

Get the dimensions corresponding to the matrices.