On Tue, May 6, 2008 at 9:45 AM, Anne Archibald <[EMAIL PROTECTED]> wrote: > In fact, if you want to use empty() down the road, it may > make sense to initialize your array to zeros()/0., so that if you ever > use the values, the NaNs will propagate and become obvious.
Numpy has ones and zeros. Could we add a nans? I often initialize using x = nan * ones((n ,m)). But if it's in a loop, I'll avoid one copy by doing x = np.ones((n, m)) x *= np.nan To many on the list using nans for missing values is like chewing gum you found on the sidewalk. But I use it all the time so I'd use a nans. _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
