On Tue, Aug 12, 2014 at 9:24 PM, Sturla Molden <sturla.mol...@gmail.com> wrote:
> Charles R Harris <charlesr.har...@gmail.com> wrote: > > > - Move _dotblas down into multiarray > > 1. When there is cblas, add cblas implementations of decr->f->dot. > > 2. Reimplement API matrixproduct2 > > 3. Make ndarray.dot a first class method and use it for numpy.dot. > > - Implement matmul > > 1. Add matrixmultiply (matmul?) to the numpy API > > 2. Implement __matmul__ method. > > 3. Add functions to linalg for stacked vectors. > > 4. Make sure __matmul__ works with __numpy_ufunc__ > > - Consider using blas_lite instead of cblas, but that is now > independent > > of the previous steps. > > We could consider to have a linalg._linalg module that just stores BLAS and > LAPACK function pointer values as read-only integer attributes. This way we > could move _dotblas into the core without actually having linalg in the > core. linalg._linalg would just sit there and own BLAS and LAPACK, and no > other part of NumPy would need build dependencies on these libraries. Note that those dependencies are optional now. > When _dotblas is imported it just imports linalg._linalg and reads whatever > function pointer value it needs. It would also make it possible to remove > BLAS and LAPACK build dependencies from SciPy, as long as we export most or > all of BLAS and LAPACK. > That's not possible. The only way you can do that is move the hard dependency on BLAS & LAPACK to numpy, which we don't want to do. Ralf
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