For the sake of hardware efficiency, we might want to store arrays in blocking formats, e.g. (i, j) --> (i, j, j4, i4). But from the point of view of user-experience, it's still good to provide look'n'feel of (i, j). Numpy does not allow creating a low-dimensional view into higher-dimensional array but it could be possible if it'd store internal dimensions for sake of all the C extensions, which would know the real strides while presenting 'interface' dimensions to user. Would this kind of trick possible with this libndtypes? Thanks!
For the sake of hardware efficiency, we might want to store arrays in blocking formats, e.g. (i, j) --> (i, j, j4, i4). But from the point of view of user-experience, it's still good to provide look'n'feel of (i, j). Numpy does not allow creating a low-dimensional view into higher-dimensional array but it could be possible if it'd store internal dimensions for sake of all the C extensions, which would know the real strides while presenting 'interface' dimensions to user. Would this kind of trick possible with this libndtypes? Thanks!