jax.numpy.linalg.det¶

jax.numpy.linalg.det = <jax.custom_derivatives.custom_jvp object>[source]¶

Compute the determinant of an array.

LAX-backend implementation of det(). Original docstring below.

Parameters: a ((.., M, M) array_like) – Input array to compute determinants for.
Returns: det – Determinant of a.
Return type: (..) array_like

See also

slogdet: Another way to represent the determinant, more suitable for large matrices where underflow/overflow may occur.
scipy.linalg.det: Similar function in SciPy.

Notes

New in version 1.8.0.

Broadcasting rules apply, see the numpy.linalg documentation for details.

The determinant is computed via LU factorization using the LAPACK routine z/dgetrf.

Examples

The determinant of a 2-D array [[a, b], [c, d]] is ad - bc:

>>> a = np.array([[1, 2], [3, 4]])
>>> np.linalg.det(a)
-2.0 # may vary

Computing determinants for a stack of matrices:

>>> a = np.array([ [[1, 2], [3, 4]], [[1, 2], [2, 1]], [[1, 3], [3, 1]] ])
>>> a.shape
(3, 2, 2)
>>> np.linalg.det(a)
array([-2., -3., -8.])