Travis, I am whole-heartedly in favor of your efforts to end the Numeric/numarray split by combining the best of both. I am encouraged by the progress you have made, and by the depth and clarity of the accompanying technical discussions. Thank you! I am a long-time Matlab user in Physical Oceanography, and I have been trying to find a practical way to phase out Matlab. One key is matplotlib, which is coming along wonderfully. A second is the availability of a Num* (or scipy.base) module that provides the functionality and ease-of-use I presently get from Matlab. This leads to a request which I suspect and hope is consistent with your present plans: efficient handling of NaNs and/or masked arrays. In Physical Oceanography, and I suspect in many other fields, data sets are almost always full of holes. Matlab's ability to use NaN as a bad value flag provides a wonderfully simple and efficient way of dealing with missing or bad data values. A similar ease and transparency would be good in scipy.base. In addition, or as a way of implementing NaN-handling internally, it might be best to have masked arrays incorporated at the C level--with the functionality available by default--rather than bolted on as a pure-python package. I hope that inclusion of __array_mask__ in the protocol means that this is part of the plan. Eric