On Thu, Dec 4, 2008 at 2:40 PM, Jarrod Millman wrote:

On Thu, Dec 4, 2008 at 11:14 AM, Pierre GM wrote:

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Raise a ValueError (even in 2.5, therefore risking to break something)

+1

+1 I'm not yet a serious user of numpy/scipy, but when debugging the discrete distributions, it took me a while to figure out that some mysteriously appearing zeros were nans that were silently converted during casting to int. In matlab, I encode different types of missing values (in the data) by numbers that I know are not in my dataset, e.g -2**20, -2**21,... but that depends on the dataset. (hand made nan handling, before data is cleaned). When I see then a "weird" number, I know that there is a problem, if it the nan is zero, I wouldn't know if it's a missing value or really a zero. Josef

josef.pktd@gmail.com wrote:

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Raise a ValueError (even in 2.5, therefore risking to break something)

+1 as well

it took me a while to figure out that some mysteriously appearing zeros were nans that were silently converted during casting to int.

and this is why -- a zero is a perfectly valid and useful number, NaN should never get cast to a zero (or any other valid number) unless the user explicitly asks it to be. I think the right choice was made for python 2.6 here. -Chris -- Christopher Barker, Ph.D. Oceanographer Emergency Response Division NOAA/NOS/OR&R (206) 526-6959 voice 7600 Sand Point Way NE (206) 526-6329 fax Seattle, WA 98115 (206) 526-6317 main reception Chris.Barker@noaa.gov