xorbits.numpy.linalg.det#

xorbits.numpy.linalg.det(a)#

Compute the determinant of an array.

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(numpy.linalg).

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.])

Warning

This method has not been implemented yet. Xorbits will try to execute it with numpy.linalg.

This docstring was copied from numpy.linalg.