[SciPy-User] Order of numpy orperations is not equal to logic (and also octave)?

Oz Nahum Tiram nahumoz@gmail....
Sun Oct 31 15:30:14 CDT 2010

Continuing this subject, I have a feeling that numpy behaves in very
un-intuitive way for me.
Here is an example that someone gave me in Stackoverflow.com:

>>> import numpy as np
>>> a=np.array([1,0])
>>> b=np.array([-1,1])

>>> np.sum(a)/np.sum(b)
>>> np.sum(a)/b
array([-1,  1])
>>> np.sum(a)/0

Octave warns when dividing by zero:
octave:1> a=[1,0]
a =

   1   0

octave:2> b=[-1,1]
b =

  -1   1

octave:3> sum(a)/sum(b)
warning: division by zero
ans = Inf
octave:4> sum(a)./sum(b)
warning: division by zero
ans = Inf
octave:5> sum(a)./b
ans =

  -1   1

I think this is very important that these differences are broad-casted to
new comers from matlab/octave to python and numpy.
I work interchangeably with both, and this is quite tricky...

Oz Nahum
Graduate Student
Zentrum für Angewandte Geologie
Universität Tübingen


Imagine there's no countries
it isn't hard to do
Nothing to kill or die for
And no religion too
Imagine all the people
Living life in peace
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