[SciPy-user] fft numerical precision

Scott Ransom sransom at nrao.edu
Wed Dec 21 13:58:23 CST 2005


Hi Ryan,

Note that 1e-16 is the approximate _fractional_ precision of double 
precision floats.  You can get absolute numbers much smaller than that.

There are a bunch of good references to floating point accuracy etc.  
Some of them are linked here:
http://babbage.cs.qc.edu/courses/cs341/IEEE-754references.html

Note that the FFTW website lists FFT accuracies in both single and 
double precision here:

http://www.fftw.org/accuracy/

Scott

On Wednesday 21 December 2005 02:53 pm, Ryan Krauss wrote:
> I have run into this as well.  1e-16 seems large to me for double
> precision.  Robert can you explain this a bit more please.  Is there
> an IEEE spec or something that specifies how much of the 64bits is
> for exponent and how much is for the mantissa (I think that is the
> right word)?   I was playing with some FORTRAN code and it seems like
> there was a big difference with complex vs. double complex.  It seems
> like 1e-16 was the magnitude floor of complex and double complex was
> better.
>
> Ryan
>
> On 12/21/05, Robert Kern <robert.kern at gmail.com> wrote:
> > Darren Dale wrote:
> > > I am running into problems related, I think, to numerical
> > > precision of fast Fourier transforms. If I Fourier transform a
> > > gaussian distribution:
> > >
> > > absolute(fft(stats.norm.pdf(linspace(-10,10,512), loc=0,
> > > scale=1)))
> > >
> > > I find a floor of about 1e-16. Does anyone know of a way to
> > > improve the precision?
> >
> > 1e-16 is the best you can do with double precision.
> >
> > --
> > Robert Kern
> > robert.kern at gmail.com
> >
> > "In the fields of hell where the grass grows high
> >  Are the graves of dreams allowed to die."
> >   -- Richard Harter
> >
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>
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-- 
Scott M. Ransom            Address:  NRAO
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