On Tue, Mar 30, 2010 at 2:21 PM, G B <[email protected]> wrote:
> Hi--
>
> I'm trying to figure out how to use RealDistributions to model noise.
> For example, I would like to model a signal+noise and tried using this
> construct:
>
> T=RealDistribution('gaussian',1)
> f(x)=sin(x)+T.get_random_element()
> plot(f(x),(x,0,2*pi))
>
> Unfortunately, that only calls get_random_element() once, at the
> definition of f(x) and results in a perfect sinusoid offset by a
> random value.
def f(x):
return sin(x) + T.get_random_element()
or
f = lambda x : sin(x) + T.get_random_element()
William
>
> How do I write this so that get_random_element() is called each time
> f(x) is evaluated? I would like to see a noisy sinusoid.
>
> Thanks--
> Greg
>
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--
William Stein
Associate Professor of Mathematics
University of Washington
http://wstein.org
--
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