Fernando Perez schrieb:

Nils Wagner wrote:

...

Hi all,

Finally, I have installed IPython via cvs.

Again, the question comes up, how to measure the CPU-time which is required to solve the eigenvalue problem.

A small example is appreciated

from scipy import *

w, vr = linalg.eig(A,B)

In [10]: size=100

In [11]: A=RA.random((size,size))

In [12]: B=RA.random((size,size))

In [13]: timing(1,linalg.eig,A,B) Out[13]: 0.10742200000000002

In [14]: size=500

In [15]: A=RA.random((size,size))

In [16]: B=RA.random((size,size))

In [17]: timing(1,linalg.eig,A,B) Out[17]: 23.265625

From the docstring:

In [18]: timing? Type: function Base Class: <type 'function'> String Form: <function timing at 0x81c37d4> Namespace: Interactive File: /usr/local/home/fperez/code/python/IPython/genutils.py Definition: timing(reps, func, *args, **kw) Docstring: timing(reps,func,*args,**kw) -> t_total

Execute a function reps times, the elapsed total CPU time in seconds. This is just the first value in timings_out().

You'll need to import timing and friends first, they live in IPython.genutils.

Best,

f.

But, what can I do to obtain the CPU-time of a whole sequence of different functions, i.e. t_0= ? while t < tend: several function calls t_1= ? \Delta t = t_1-t_0 I am interested in \Delta t Nils

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