Hi all, Is there anyone out there using numpy masked arrays, who has an opinion on how empty_like (and its friends ones_like, zeros_like) should handle the mask? Right now apparently if you call np.ma.empty_like on a masked array, you get a new masked array that shares the original array's mask, so modifying one modifies the other. That's almost certainly wrong. This PR: https://github.com/numpy/numpy/pull/3404 makes it so instead the new array has values that are all set to empty/zero/one, and a mask which is set to match the input array's mask (so whenever something was masked in the original array, the empty/zero/one in that place is also masked). We don't know if this is the desired behaviour for these functions, though. Maybe it's more intuitive for the new array to match the original array in shape and dtype, but to always have an empty mask. Or maybe not. None of us really use np.ma, so if you do and have an opinion then please speak up... -n