Feb. 14, 2010
12:22 p.m.
On Feb 13, 2010, at 10:04 PM, David Carmean wrote:
I'm just starting to work with masked arrays and I've found some behavior that definitely does not follow the Principle of Least Surprise:
A fuzzy concept ;)
I've generated a 2-d array from a list of lists, where the elements are floats with a good number of NaNs. Inspections shows the expected numbers for ma.count() and ma.count_masked().
However, as soon as I run np.nanmin() or np.nanmax() over it, all of the mask elements are reset to False.
I'm sorry, I can't follow you. Can you post a simpler self-contained example I can play with ? Why using np.nanmin/max ? These functions are designed for ndarrays, to avoid using a masked array: can't you just use min/max on the masked array ?