[Numpy-discussion] numpy.mean problems
aronne.merrelli at gmail.com
Sat Dec 10 12:41:29 EST 2011
On Sat, Dec 10, 2011 at 5:47 AM, ferreirafm <ferreirafm at lim12.fm.usp.br>wrote:
> Hi Stéfan,
> Thanks for your replay. Have a look in the arrays at:
I can recreate this error if tab is a structured ndarray - what is the
dtype of tab?
If that is correct, I think you could fix this by simplifying things. Since
tab is already an ndarray, you should not need to convert it back into a
python list. By converting the ndarray back to a list you are making an
extra level of "wrapping" as a python object, which is ultimately why you
get that error about adding numpy.void.
Unfortunately you cannot take directly take a mean of a struct dtype;
structs are generic so they could have fields with strings, or objects,
etc, that would be invalid for a mean calculation. However the following
code fragment should work pretty efficiently. It will make a 1-element
array of the same dtype as tab, and then populate it with the mean value of
all elements where the length is >= 15. Note that dtype.fields.keys() gives
you a nice way to iterate over the fields in the struct dtype:
length_mask = tab['length'] >= 15
tab_means = np.zeros(1, dtype=tab.dtype)
for k in tab.dtype.fields.keys():
tab_means[k] = np.mean( tab[k][mask] )
In general this would not work if tab has a field that is not a simple
numeric type, such as a str, object, ... But it looks like your arrays are
all numeric from your example above.
Hope that helps,
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