On Mon, 2013-12-02 at 18:15 -0500, Jim Bosch wrote: > > If your arrays are contiguous, you don't really need the strides > (use the itemsize instead). How is ndarray broken by this? > > ndarray is broken by this change because it expects the stride to be a > multiple of the itemsize (I think; I'm just looking at code here, as I > haven't had time to build NumPy 1.8 yet to test this); it has a > slightly more restricted model for what data can look like than NumPy > has, and it's easier to always just look at the stride for all sizes > rather than special-case for size=1. I think that means the bug is > ndarray's (indeed, it's probably the kind of bug this new behavior was > intended to catch, as I should be handling the case of > non-itemsize-multiple strides more gracefully even when size > 1), and > I'm working on a fix for it there now. > Most bugs I saw were just simply assuming:
arr.strides[-1] == arr.itemsize when the array is C-contiguous, and could be fixed by just using arr.itemsize... Unless you need to calculate contiguous flags which are compatible to NumPy with NPY_RELAXED_STRIDES_CHECKING (i.e. cython had this problem since its memoryview would reject numpy's contiguous arrays as not contiguous), you should not need to special case anything. - Sebastian > > Thanks, Neil, for bringing this to my attention, and to all the NumPy > dev's for help in explaining what's going on. > > > > Jim > > > > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@scipy.org > http://mail.scipy.org/mailman/listinfo/numpy-discussion _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
