Difference between revisions of "Contspacing.m"

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       [all_conts,pos_conts,neg_conts]=contspacing(smax,smin,delta,k,signs,ncont)
 
       [all_conts,pos_conts,neg_conts]=contspacing(smax,smin,delta,k,signs,ncont)
  
==Arguments==
+
==Parameters==
  
 
     smax      - global maximum intensity in the spectrum
 
     smax      - global maximum intensity in the spectrum

Revision as of 18:47, 5 June 2026

Non-linear adaptive contour spacing. Useful for NMR data where small cross-peaks must be adequately contoured next to large diagonal peaks.

Syntax

     [all_conts,pos_conts,neg_conts]=contspacing(smax,smin,delta,k,signs,ncont)

Parameters

    smax      - global maximum intensity in the spectrum

    smin      - global minimum intensity in the spectrum

    delta     - minimum and maximum elevation (as a fraction of the
                total intensity) of the contours above the baseline.
                A good starting value is [0.02 0.2 0.02 0.2]. The
                first pair of numbers refers to the positive conto-
                urs and the second pair to the negative ones.

    k    - a coefficient that controls the curvature of the contour
           spacing function: k=1 corresponds to linear spacing and
           k>1 bends the spacing curve to increase the sampling den-
           sity near the baseline. A reasonable value is 2.

    signs   - can be set to 'positive', 'negative' or 'both' - this
              will cause the corresponding contours to be returned.

    ncont   - the number of contours, a reasonable value is 20

Outputs

    all_conts - all contour levels, a row vector

    pos_conts - positive contour levels, a row vector

    neg_conts - negative contour levels, a row vector

Notes

The following functions are used to get contour levels

 pos_conts=delta(2)*smax*linspace(0,1,ncont).^k+smax*delta(1);
 neg_conts=delta(2)*smin*linspace(0,1,ncont).^k+smin*delta(1);

See also

Data analysis and plotting

Version 2.9, authors: Ilya Kuprov