2012/2/11 Stéfan van der Walt email@example.com
On Fri, Feb 10, 2012 at 10:58 AM, Emmanuelle Gouillart firstname.lastname@example.org wrote:
isn't it possible to test which version of numpy is used, and remove float16 from the list if numpy.__version__ < 1.6? It looks like a small cost in order to be be able to support numpy 1.5. I can do the change if there is no opposition to this.
If we can stay compatible with 1.5 with minor changes, that's probably worth it. Can you also check the dtype conversion code to make sure it all works? (Running the unit tests should be enough of an indication)
I'd be in favor of supporting numpy 1.5. Just note that the `convert` function uses `np.promote_types`, which is also new to numpy 1.6.
As I see things, it would be great if people could use skimage with the
dependencies provided by a recent version of Ubuntu, say the most recent LTS, or the latest release of Ubuntu. We will lose many users if they have to install a new numpy (which also means that they will have to install non-packaged matplolib, and scipy). If you disagree with this philosophy, please tell me :-).
I understand the challenges of running on an older platform, but I also wonder: if a user can recompile scikits-image, what's stopping them from also building the latest (stable) numpy? I certainly have the expectation that software should run with the available stable versions of dependencies on the date of release. That said, any benefit we can get with little effort is worth it, and there's no reason to purposefully make it harder for users than need be. So please, keep the PRs coming for backwards compatibility, as long as they are not too disruptive.