Command FSUM
Parameters Defaults
FSUM windows
/
DISPLAY
CONDITIONS
LOOP
GRAPHIC
NET
TOTAL
FWHM
CONFIDENCE(co) 0.683
STORE(st)
Purpose
Compute sum and moments.
Function
Compute sum and moments of raw (input) or net (input minus fit) data.
Output results on terminal, current picture or global parameter.
Example
FSUM a,b,c / NET FWHM STORE( p(3,1) )
Compute the moments of the net data (2nd moment expressed as FWHM)
in the three display windows A,B,C.
Results are stored in global parameter array p().
p(3,1), p(3,2), ... receive moments of window A,
p(4,1), p(4,2), ... receive moments of window B, and
p(5,1), p(5,2), ... receive moments of window C.
Parameter WINDOWS(wdws)
List of windows, interpreted as follows:
window item = number: condition,
window item = letter: display window,
window item = #: temporary window
window item = *: all fit windows.
Parameter DISPLAY
All display windows are integrated
Parameter CONDITIONS
All conditions are integrated
Parameter LOOP
Windows are prompted in a loop. See also command FWINDOWS
Parameter GRAPHIC
Write results into current picture
Parameter NET
Sum and moments of the net data are calculated, i.e. the values of the fit function
are subtracted from the input data.
Parameter TOTAL
Sum and moments of the input data are calculated.
Parameter FWHM
The variance (second moment) is converted into an FWHM value according to
FWHM = sqrt( 8*log(2) * n / (n-1) ) * variance,
where n is the number of data points.
The skewness (third moment) is expressed in terms of the square root of the variance.
Parameter CONFIDENCE(co)
For 0 < co < 1 the evaluated function errors correspond to confidence limit co.
Usually co = 0.683 corresponds to the propagated error bars of the fitted input data.
Parameter STORE(p)
Name of a floating point global parameter array to receive the calculated moments.
Storing starts at the specified index, or, if the index is omitted,
at the first element. If the array is 1-dimensional only sums are returned,
otherwise the data are stored columnwise, containing the following items
per row (sufficient bounds provided):
x-limits, sum, error, mean, variance (or FWHM), skewness.