Arrays bounds using NumPy

NumPy is load by default when calling ipython -pylab. If not, it's always possible to import all the module by from numpy import *  or import numpy as N (then you need to start any numpy function with N.).
To easy create arrays, just use:

a=r_[1:10]

It will create an array from 1 to... 9 !!! It is actually a kind of shortcut for:

a=arange(1,10)

which also provides an array of 9 elements, from 1 to 9.
The step can be specified:
a=r_[1:10:.1] or a=arange(1,10,.1).
In this case, the array latest element is 9.9, not 10.
It is also possible to give the number of elements, for this a "j" is added to the 3rd parameter:
b=r_[1:10:100j] or b=linspace(1,10,100).
BUT in these latest two equivalent cases, the latest element is actually 10!...
Another way to say this:
a=r_[1:10:.1] and b=r_[1:9.9:90j] are equivalent. Not obvious for me...
BTW, the same philosophy apply when selecting part of an array:
In [71]: a=r_[1:10]
In [72]: a
Out[72]: array([1, 2, 3, 4, 5, 6, 7, 8, 9])
In [73]: a[0:2]
Out[73]: array([1, 2])
I certainly would expect the answer to be a 3 elements sub-array. I'm sure this will be a big source of bug in my future Python codes ;-) 
I found something quite powefull: accessing the latest elements of an array:
In [77]: a[-1]
Out[77]: 9
In [78]: a[-5:-1]
Out[78]: array([5, 6, 7, 8])
In [79]: a[-5::]
Out[79]: array([5, 6, 7, 8, 9])

I also saw that the indexing of arrays can be quite sophisticated: http://docs.scipy.org/doc/numpy/reference/arrays.indexing.html