Baselineds

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Revision as of 15:38, 17 December 2018 by imported>Scott
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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