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Re: [ferret_users] Extracting frequency from FFTA



HI Dave,
                     As I understand you are looking for a band pass filter which can permit only frequencies near to 4 hours.  The below link where use of Lancoz filter is described may be helpful for you
http://ferret.pmel.noaa.gov/Ferret/documentation/users-guide/appendix-a-external-functions/LANCZOS
with best regards,
Sudheer
On Tue, Apr 5, 2011 at 3:17 PM, David Ogier <david.ogier@xxxxxxxxx> wrote:
I think that I wasn't very clear on the previous help request.

I know the frequency and period that I I intend to use. I do however need to extract that 4 hours signal from the existing data set so that I can have two data sets, one original with all it's various frequencies and the other, only the data that is influenced by the 4 hourly oscillation. That's why I did the FFT first to see where are areas are that have the greatest 4 hourly wave activity, the 4 hour filtered data should correspond roughly to this FFT data.

is this even possible?

many thanks again for your time

dave



On 4 April 2011 18:00, David Ogier <david.ogier@xxxxxxxxx> wrote:
Hi there,

I hope you have some extra experience with Fourier analysis as I'm running out of ideas.
I have a time series (hourly for a month) and I have done a FFTA on it with the following

   let FFT_temp = ffta(temp[l=1:744])     !simple enough

and I now need to isolate the 4 hourly frequency and return only it back to the hourly temperature data (ie I need 744 time steps again 24 hours * 31 days)
I've tried FFT_INVERSE but I don't know how to specify the frequency or period I need,

    let sample_re = FFT_RE(temp[d=1])
    let sample_im = FFT_IM(temp[d=1])
    let invert_ts = FFT_INVERSE(sample_re, sample_im)           ! this returns the full original data set and imposing l limits to the sample_re or sample_im seems to return wrong data

I've also been trying LSL_LOWPASS but I'm not sure on the functioning and is returning strange data that looks incorrect.
Is there something simple that I'm doing wrong?

Many thanks for your time.

Cheers

Dave




--
with best regards

Sudheer

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