Baselineds
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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.
- mode: [ 1 ] dimension of data on which to calculate the minima and maxima for scaling. 1 = over rows (each row will have range [0,1]); 2 = over columns (each column will have range [0,1]). Default is 1.
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)