jax.numpy.linalg.eigvals#
- jax.numpy.linalg.eigvals(a)[source]#
Compute the eigenvalues of a general matrix.
JAX implementation of
numpy.linalg.eigvals()
.- Parameters:
a (ArrayLike) – array of shape
(..., M, M)
for which to compute the eigenvalues.- Returns:
An array of shape
(..., M)
containing the eigenvalues.- Return type:
See also
jax.numpy.linalg.eig()
: computes eigenvalues eigenvectors of a general matrix.jax.numpy.linalg.eigh()
: computes eigenvalues eigenvectors of a Hermitian matrix.
Notes
This differs from
numpy.linalg.eigvals()
in that the return type ofjax.numpy.linalg.eigvals()
is always complex64 for 32-bit input, and complex128 for 64-bit input.At present, non-symmetric eigendecomposition is only implemented on the CPU backend.
Examples
>>> a = jnp.array([[1., 2.], ... [2., 1.]]) >>> w = jnp.linalg.eigvals(a) >>> with jnp.printoptions(precision=2): ... w Array([ 3.+0.j, -1.+0.j], dtype=complex64)