On 11/28/12 1:47 PM, Bartosz wrote:
Hi,
I try to update values in a single field of numpy record array based on a condition defined in another array. I found that that the result depends on the order in which I apply the boolean indices/field names.
For example:
cond = np.zeros(5, dtype=np.bool) cond[2:] = True X = np.rec.fromarrays([np.arange(5)], names='a') X[cond]['a'] = -1 print X
returns: [(0,) (1,) (2,) (3,) (4,)] (the values were not updated)
X['a'][cond] = -1 print X
returns: [(0,) (1,) (-1,) (-1,) (-1,)] (it worked this time).
I find this behaviour very confusing. Is it expected?
Yes, it is. In the first idiom, X[cond] is a fancy indexing operation and the result is not a view, so what you are doing is basically modifying the temporary object that results from the indexing. In the second idiom, X['a'] is returning a *view* of the original object, so this is why it works.
Would it be possible to emit a warning message in the case of "faulty" assignments?
The only solution that I can see for this is that the fancy indexing would return a view, and not a different object, but NumPy containers are not prepared for this. -- Francesc Alted