BCORR(A, R, (list_of_points) )
Computes and applies a base-line correction to the current data set.
A describe the algorithm used:
- 1 is linear correction
- 2 is cubic spline correction.
- 3 is polynomial (and related) correction
R is the radius around which each pivot point is averaged.
n in 2D is either f1 or f2 (dimension in which correction is applied).
list_of_points is then the list of the pivot points used for the
base-line correction. The list finishes by 0. The content of the
point stack is used for prompting.
Linear correction can use 1 or more pivot points. 1 point
corresponds to correction of a continuous level. Spline corrections
needs at least 3 points.
In any case maximum is 100 pivot points.
This method uses a correction by estimation of the baseline and
subtraction. Words in uppercase are commands.
The four steps are :
- Initial smooth of data : SMOOTH1
- First segmentation (detection of signal) : SEGM1
- Second segmentation (Polynomial approximation may be done on several areas) : SEGM2
- Approximation (the estimated baseline is an approximation of data points that are not signal) : APPROX
If you do not know how to use these corrections the next three
commands should help you :
- BCORRP : Will prompt you for the related parameters, along with the name of the command..
- BCORRP_Q : the current choices are listed.
- BCORRP0 : the default set up is restored.
- BCORRP1 : another set up is activated
see also : smooth median window blciter blocbase bcorrp bcorrp_q bcorrp0 bcorrp1 smooth1 winma levelhyste segm1 blcu blcv sds sdb scs scb dcfactor dciter morphob morphos dcalgo dcdistance segm2 window winsegm2 levelsegm2 approx winma2 degre winlin
NPK Documentation, version 0.995 - 2009-10-14