jax.numpy.linalg.slogdet
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jax.numpy.linalg.slogdetΒΆ
- jax.numpy.linalg.slogdet = <jax._src.custom_derivatives.custom_jvp object>[source]ΒΆ
Compute the sign and (natural) logarithm of the determinant of an array.
LAX-backend implementation of
slogdet()
.Original docstring below.
If an array has a very small or very large determinant, then a call to det may overflow or underflow. This routine is more robust against such issues, because it computes the logarithm of the determinant rather than the determinant itself.
- Parameters
a ((..., M, M) array_like) β Input array, has to be a square 2-D array.
- Returns
sign ((β¦) array_like) β A number representing the sign of the determinant. For a real matrix, this is 1, 0, or -1. For a complex matrix, this is a complex number with absolute value 1 (i.e., it is on the unit circle), or else 0.
logdet ((β¦) array_like) β The natural log of the absolute value of the determinant.
If the determinant is zero, then sign will be 0 and logdet will be
-Inf. In all cases, the determinant is equal to
sign * np.exp(logdet)
.