There is a pull request <https://github.com/numpy/numpy/pull/3220>for work adding linear algebra support as generalized ufuncs. The result is that many of the linear algebra routines can now be applied to stacks of matrices. Another new feature is support for float32 versions of the routines. Some work has also gone into porting the current linalg package to use the new routines. The work isn't finished, the new and old libraries {blas, lapack}_lite libraries should probably be united and the error handling could maybe use more polish, but I'm inclined to put the PR in at this point. Although some things may break, I think it needs to be out there to gather feedback and testing. Thoughts? Chuck
14.04.2013 18:39, Charles R Harris kirjoitti:
There is a pull request <https://github.com/numpy/numpy/pull/3220>for work adding linear algebra support as generalized ufuncs. The result is that many of the linear algebra routines can now be applied to stacks of matrices. Another new feature is support for float32 versions of the routines. Some work has also gone into porting the current linalg package to use the new routines.
The work isn't finished, the new and old libraries {blas, lapack}_lite libraries should probably be united and the error handling could maybe use more polish, but I'm inclined to put the PR in at this point. Although some things may break, I think it needs to be out there to gather feedback and testing.
It's merged:
a = np.array([[[1, 2], [3, 4]], [[1, 2], [2, 1]], [[1, 3], [3, 1]] ]) np.linalg.det(a) array([-2., -3., -8.])
-- Pauli Virtanen
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Pauli Virtanen