Baselineds

Purpose

Wrapper for baselining functions.

Synopsis

[baselined_data,baselines] = baselineds(spec,options); %Calibrate and apply.

spec = baselineds(baselined_data,baselines); %Undo

Description

Wrapper for baselining functions.

Inputs

• spec = M by N matrix of data to be baslined (class "double" or "dataset").

Options

options = a structure array with the following fields:

• plots : [ {'none'} | 'final' ] governs plotting.

• algorithm : [ {'wlsbaseline'} | 'baseline' | 'whittaker' | 'datafit']

wlsbaseline - Baseline subtraction using iterative asymmetric least squares algorithm.

baseline - Subtracts a polynomial baseline offset from spectra.

whittaker - Baseline subtraction using Whittaker filter.

datafit - Asymmetric least squares baselining.

• order : positive integer for polynomial order {default =1}.

• wlsbaseline_options : see wlsbaseline.m.

• whittaker_options : see wlsbaseline.m.

• baseline_freqs : wavenumber or frequency axis vector, see baseline.m.
• baseline_range : baseline regions, see baseline.m.
• baseline_options : see baseline.m.

• datafit_options : see datafit_engine.m. NOTE: 'lambdas' and 'trbflag' options have defaults updated for baselining.

Outputs

• xcorr = the scaled data (xcorr will be the same class as x)

• mins = vector of minima for each row (or column)

• maxs = vector of maxima for each row (or column)

See Also

normaliz, preprocess, snv