Hey, since I am working on the indexing. I was wondering about a few smaller things: * 0-d boolean array, `np.array(0)[True]` (will work now) would give np.array([0]) as a copy, instead of the original array. I guess I could add a FutureWarning or so, but I am not sure and overall the chance of creating bugs seems low. (The boolean index should always add 1 dimension and here, remove 0 dimensions -> 1-d result.) * All index operations return a view; never the object. This means that `v = arr[...]` is slightly slower. But since it does not affect `arr[...] = vals`, I think the speed implications are negligible. * Does anyone have an idea if there is a way to change the subclass logic that view based item setting is implemented as: np.asarray(subclass[index]) = vals I somewhat think the subclass should rather implement `__setitem__` instead of relying on numpy calling its `__getitem__`, but I don't see how it can be changed. * Still thinking a bit about implementing a keepdims keyword or function, to handle matrix type logic mostly in the C-code. And most importantly, is there any behaviour thing in the index machinery that is bugging you, which I may have forgotten until now? - Sebastian