python tips: array computation with numpy II

As previous post shows, for-loop calculation in array computations needs more processing time than vectorized calculation. There are some techniques for fasten calculation over arrays. Sample code shown below is one of them.

>>> from numpy import *
>>> 
>>> A = array([[1,2,3], [4,5,6], [7,8,9]])
>>> 
>>> def somefunc(x):
...     x1 = x
...     x2 = x - 3
...     return where(x < 7, x1, x2)
... 
>>> somefunc(A)
array([[1, 2, 3],
       [4, 5, 6],
       [4, 5, 6]])
>>>