Wlsbaseline
Purpose
Weighted least squares baseline function.
Synopsis
- [bldata,wts] = wlsbaseline(data,baseline,options)
- [bldata,wts] = wlsbaseline(data,order,options)
Description
Subtracts a baseline (or other signal) from a spectrum with the constraint that residuals below zero be weighted more heavily than those above zero. This achieves a robust "non-negaitve" residual fit when residuals of significant amplitude (e.g. signals on a background) are present. Inputs are data the spectral data, baseline the reference spectrum/spectra to use for baseline OR an integer value representing the order of polynomial baselining to use and options an optional options structure. Outputs are the baselined data bldata and the weightings wts indicating the amount of baseline which was removed from each spectrum in data. (i.e. bldata = data - wts\*baseline) Polynomial baseline Option: If a positive scalar value is given instead of the input baseline, then a polynomial baseline of that order will be used. In this mode, any row of the output wts can be used with the polyval function to obtain the baseline removed from the corresponding row of data.
Options
- plots : [{'none'} | 'debug' | 'intermediate' | 'final'] governs plots
- weightmode : [ {1} | 2 ] flag indicating which weighting mode to use.
- Mode 1 = Power method. Negative residuals are weighted up by the power of 10.\^(option.negw). All residuals are then raised to the power of (option.power)
- Mode 2 = T squared method. Negative residuals are weighted up by the extent to which the surpass an estimate of the noise limit and the approximate t-limit defined by (option.tsqlim)
- trbflag : [ 'bottom' | 'top' ] baseline to top or bottom of data
- negw : {1} deweighting scale of negative values (10\^negw) (used only for weightmode = 1),
- power : {2} exponential amplification of residuals (used only for weightmode = 1),
- tsqlim : [0.99] t-test confidence limit for significant negative residuals which need to be up-weighted. (used only for weightmode = 2),
- nonneg : ['no'|{'yes'}] flag to force non-negative baseline weighting, most often used when "real" spectra are used for baslineing and they should not be "flipped" by a negative weighting. Using nonneg = 'yes', WLSBASELINE an be used as a partial CLS prediction to estimate the concentration of a species when not all species' pure component spectra are known,
- delta : [1e-4] change-of-fit convergence criterion,
- maxiter : [100] maximum iterations allowed per spectrum,
- maxtime : [600] maximum time (in seconds) permitted for baselining of all data.
Examples
To swap 4 BYTES in a 32 bit number: