Thanks. You mean actually when numpy handle masked array, it will first
treat all the base data, and then apply the mask after the treatment.
and normally the base data of maksed elements will very likely to intrigure
these errors, and you will see a lot errory warning or print in the process,
and will make it impossible to see the error information your want to see
for those elements that are not masked but still can intriguer the error
you would like to see or check. I didn't realize this. It's a good to
overwrite the error setting.
thanks for your explanation.
Chao
On Fri, Dec 14, 2012 at 3:15 PM, Robert Kern robert.k...@gmail.com wrote:
On Fri, Dec 14, 2012 at 1:57 PM, Chao YUE chaoyue...@gmail.com wrote:
Dear all,
I tried to capture the zero divide error when I divide a masked array by
another. It seems that np.seterr is not working for masked array?
when I do np.divide on two masked array, it directly put the zero divides
part as being masked. The np.seterr works if the two arrays for dividing
are
not masked arrays.
could anyone explain? thanks!!
numpy.ma uses np.seterr(divide='ignore', invalid='ignore') for most of
its operations, so it is overriding your settings. This is usually
desirable since many of the masked values will be trip these errors
spuriously even though they will be masked out in the result.
--
Robert Kern
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Chao YUE
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