IRAF Help page for: PEAKFIND


PEAKFIND (Feb93)              grasp.grtools             PEAKFIND (Feb93)



NAME
    peakfind --  Fit  peaks  in  helioseismic  power  spectra  and  L-Nu
    diagrams.
    
    
USAGE
    peakfind input output table
    
    
PARAMETERS
    
    input
        Input power spectrum image.
    
    output
        Output fit image.
    
    table
        Output Mode-frequency table.
    
    lm_start = INDEF
        Starting L or M value to be fit.
    
    lm_end = INDEF
        Ending L or M value to be fit.
    
    n_start = 1
        Starting N-value to be fit.
    
    n_end = 10
        Ending N-value to be fit.
    
    window = ""
        Window function power spectrum.
    
    fit_background = yes
        Fit the background.
    
    background = ""
        Background image name if not fitting.
    
    restart = 1
        Number of simplex restarts per fit.
    
    nleaks = 0
        Number of leaks to include in the fit.
    
    
DESCRIPTION
    
    PEAKFIND  uses  a  nonlinear,  maximum  likelihood  technique to fit
    lorentz profiles to peaks in helioseismic  power  spectra  (M-Nu  or
    L-Nu  diagrams).  For each ridge in the range lm_start => lm_end and
    n_start => n_end, the task determines the mode frequency,  FWHM  and
    amplitude, of primary mode plus the closest nleaks leakage modes.
    
    If  fit_background  =  yes,  a  linear background is also fit to the
    ridge.  If fit_background = no, a  predetermined  background  image,
    bkg_spectrum may be used.
    
    The input power spectrum is expected to be in GONG format.  The task
    GRTOOLS.SETMWCS may be used to put the required MWCS header into  an
    image  that  was not generated by GRASP.  The type of power spectrum
    is given by the input header keyword DTYPE and may be either LNU  or
    PS for L-Nu diagrams and M-Nu diagrams respectively.
    
    The output image is a 3-d image with band one containing the derived
    limit spectrum, and band  2  containing  the  original  input  power
    spectrum.
    
    Table  is  a  STSDAS  table  containing the results of the fit.  The
    table may be operated upon  by  any  of  the  tasks  of  the  TABLES
    package.  The table columns are:
    
    Column   Data Type  Default Fmt  Plot Label         Comment
    n            I           %2d       ""          n-value
    l            I           %4d       ""          l-value
    m            I           %4d       ""          m-value
    leak         I           %2d       ""          0=primary mode; 1=leak
    nu           R        %10.4f       microHz     frequency
    dnu          R        %10.4f       microHz     frequency error
    fwhm         R         %8.4f       microHz     FWHM
    dpfwhm       R         %8.4f       microHz     FWHM positive error bar
    dmfwhm       R         %8.4f       microHz     FWHM negative error bar
    psamp        R        %10.4f       (cm/s)**2   Power spectrum amplitude
    dppsamp      R        %10.4f       (cm/s)**2   " " " positive error bar
    dmpsamp      R        %10.4f       (cm/s)**2   " " " negative error bar
    tsamp        R        %10.4f       cm/s        Mode amp in time domain
    dptsamp      R        %10.4f       cm/s        " " " positive error bar
    dmtsamp      R        %10.4f       cm/s        " " " negative error bar
    bkg0         R        %10.4f       (cm/s)**2   Background intercept
    dbkg0        R        %10.4f       (cm/s)**2   " " error
    bkg1         R        %10.4f       (cm/s)**2   Background slope
    dbkg1        R        %10.4f       (cm/s)**2   " " error
    merit        D            %8       ""          Merit Function
    
    The  errors  on  the  FWHM  and  Amplitude/Power  are evaluated with
    respect to the logarithm of  those  parameters.   The  quoted  "+/-"
    error  is  with  respect to the log distribution.  The error is then
    translated to the linear distribution resulting in  separate  (i.e.,
    unequal)  "+"  and "-" error bars.  Transformation of power spectrum
    amplitudes to time domain is not yet enabled.
    
    If window = "", the a perfect observing window is assumed.  However,
    window  may be given the name of the observing window power spectrum
    image created by the task PWINDOW, in  which  case  the  non-perfect
    window is taken into account while fitting the modes.
    
    The  maximum  likelihood  function  is  minimized using the Downhill
    Simplex  method.   The  number  of  simplex  restarts  is  given  by 
    restart.   The  fitting  range  extends  to  half  the  distance (in
    frequency) to the next ridge.  The  initial  guesses  for  the  mode
    parameters are determined as follows:
    
    Guess frequencies:
        The  guess frequencies are determined using spline interpolation
        in a sparse table of the South Pole 1987 results.
    
    Guess FWHM
        The guess FWHM are computed from  power-law  graphical  fits  to
        Libbrecht's  curve  as  a function of frequency. Dependence on l
        taken  from  linear  fit  to  Jefferies  et  al.    The   answer 
        constrained to be at least 0.1
    
    Guess Amplitudes
        The  amplitudes  are  determined from the mean (M-Nu) or maximum
        (L-Nu) value of the data within 3 pixels of the guess frequency.
    
    Guess Background intercept and slope
        The guess background parameters are  determined  from  a  linear
        fit  to the mean value of the two groups of 5 pixels at the ends
        of the fitting range.
        
        
        
EXAMPLES
    
    1. To fit all the peaks and background for 5 <= n <=10 and 50  <=  l
    <= 100 using the window function "pwindow":
    
      gr> peakfind inimage outimage outtable lm_s=50 lm_e=100 n_s=5 n_e=10
    
    
    
TIME REQUIREMENTS
    
    On  a  SPARCstation  10, the average time to fit a ridge including 8
    leaks and the  background  with  one  simplex  restart  is  9.5  cpu
    seconds  for the South Pole 1987 data set (1 month resolution plus a
    window function).
    
    
BUGS
    
    No phase information is currently used from the input  or  saved  to
    the output.
    
    This  version  of PEAKFIND only takes into account L-leakage.  Thus,
    it cannot yet be used to fit low-L modes  (l  <=  20)  which  suffer
    from n-leakage as well.
    
    This  version  of  PEAKFIND  is not smart enough to determine that a
    peak is "not there".  Thus, it will result in a fit to noise  spikes
    where peaks do not really exist.
    
    This  version  of PEAKFIND has problems with unresolved leaks (i.e.,
    fitting high frequency and high L modes).
    
    This version of PEAKFIND has not been tested on  M-Nu  diagrams  due
    to a lack of GONG data of sufficient length in time.
    
    Any  suggestions  from  the community on how to deal with any of the
    above problems are most welcome.
    
    
SEE ALSO
    
    pwindow, setmwcs
    
    "Modeling, of, Solar, Oscillation, Power, Spectra"
     Anderson, E.R., Duvall, T.L., Jr., and, Jefferies, S.M.
     Ap.J., December, 1, 1990, (IN, PRESS).


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