On 23/05/07, Albert Strasheim <[EMAIL PROTECTED]> wrote: > Consider the following example:
First a comment: almost nobody needs to care how the data is stored internally. Try to avoid looking at the flags unless you're interfacing with a C library. The nice feature of numpy is that it hides all that junk - strides, contiguous storage, iteration, what have you - so that you don't have to deal with it. > Is it correct that the F_CONTIGUOUS flag is set in the case of the fancy > indexed x? I'm running NumPy 1.0.3.dev3792 here. Numpy arrays are always stored in contiguous blocks of memory with uniform strides. The "CONTIGUOUS" flag actually means something totally different, which is unfortunate, but in any case, "fancy indexing" can't be done as a simple reindexing operation. It must make a copy of the array. So what you're seeing is the flags of a fresh new array, created from scratch (and numpy always creates arrays in C order internally, though that is an implementation detail you should not rely on). Anne _______________________________________________ Numpy-discussion mailing list [email protected] http://projects.scipy.org/mailman/listinfo/numpy-discussion
