Newbie Questions about speeding up some Numpy calculations

Hi All,

I am pretty new to Cython, so please bare with me. I am at the moment trying to speed up some code that I use a lot
in calculations, so  thought this might be a good idea to learn how to use Cython when I have already some
working Numpy code. 

After searching the tutorials I came up with the attached solution, however compared with the original
Numpy code this is getting slightly slower rather than faster, so obviously I am doing something very
wrong. Could somebody please give me some pointers where I can find examples that are closer to what I am
trying to speed up than what I can find in the tutorials?

Attached are the original numpy code, as well as the Cython code I have tried to develop. If I run this on my
machine, I get:

Python 2.7.2 |EPD 7.2-2 (32-bit)| (default, Sep  7 2011, 09:16:50) 
Type "copyright", "credits" or "license" for more information.

IPython 0.12 -- An enhanced Interactive Python.
?         -> Introduction and overview of IPython's features.
%quickref -> Quick reference.
help      -> Python's own help system.
object?   -> Details about 'object', use 'object??' for extra details.

In [1]: import be

In [2]: timeit be.referencecase(samples=250000)
1 loops, best of 3: 2.12 s per loop

In [3]: import be1

In [4]: timeit be1.referencecase(samples=250000)
1 loops, best of 3: 1.82 s per loop

Many thanks,
Hanno