Den 07.07.2011 14:10, skrev Jens Jørgen Mortensen: > So, this means I can't count on new arrays being C-contiguous any more. > I guess there is a good reason for this.
Work with linear algebra (LAPACK) caused excessive and redundant array transpositions. Arrays would be transposed from C to Fortran order before they were passed to LAPACK, and returned arrays were transposed from Fortran to C order when used in Python. Signal and image processing in SciPy (FFTPACK) suffered from the same issue, as did certain optimization (MINPACK). Computer graphics with OpenGL was similarly impaired. The OpenGL library has a C frontent, but requires that all buffers and matrices are stored in Fortran order. The old behaviour of NumPy was very annoying. Now we can rely on NumPy to always use the most efficient memory layout, unless we request one in particular. Yeah, and it also made NumPy look bad compared to Matlab, which always uses Fortran order for this reason ;-) Sturla _______________________________________________ NumPy-Discussion mailing list [email protected] http://mail.scipy.org/mailman/listinfo/numpy-discussion
