python tips: array computation with numpy

I compared performance of array computations. Listed below are results and codes of some experiments which introduced in the book named 'Python Scripting for Computational Science (3rd edition)'.

>>> from numpy import *
>>> import time
>>> 
>>> a = linspace(0, 1, 1E+07)
>>> t0 = time.clock()
>>> b = 3*a - 1
>>> 
>>> t1 = time.clock()
>>> 
>>> for i in xrange(a.size):
...     b[i] = 3*a[i] -1
... 
>>> t2 = time.clock()
>>> 
>>> print '3*a-1: %g sec, loop: %g sec' %(t1-t0, t2-t1)
3*a-1: 0.05 sec, loop: 15.46 sec