[SciPy-User] Boxcar smoothing of 1D data array...?
Fri Jun 18 09:51:28 CDT 2010
On 18 June 2010 07:22, Sturla Molden <firstname.lastname@example.org> wrote:
> Den 16.06.2010 02:26, skrev David Baddeley:
> Alternatively you could just use scipy.convolve with a tophat kernel ie (for
> a filter of length N & signal y):
> scipy.convolve(y, ones(N)/N)
> see the docs for scipy.convolve for more info (you might want to specify how
> it handles the ends, for example)
> You should not use convolution for boxcar filtering. It can be solved using
> a recursive filter, basically
> y[n] = y[n-1] + x[n] - x[n-m]
> then normalize y by 1/m.
How does the numerical stability of this compare to a FIR
implementation (with or without a Fourier transform)?
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