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.