Difference between revisions of "Baselineds"

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imported>Scott
(Created page with "===Purpose=== Wrapper for baselining functions. ===Synopsis=== :[baselined_data,baselines] = baselineds(spec,options); %Calibrate and apply. : spec = baselineds(baselined_d...")
 
imported>Scott
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* '''algorithm''' : [ {'wlsbaseline'} | 'baseline' | 'whittaker' | 'datafit']
 
* '''algorithm''' : [ {'wlsbaseline'} | 'baseline' | 'whittaker' | 'datafit']
:: wlsbaseline - Baseline subtraction using iterative asymmetric least squares algorithm.
+
:: [[wlsbaseline]] - Baseline subtraction using iterative asymmetric least squares algorithm.
:: baseline    - Subtracts a polynomial baseline offset from spectra.
+
:: [[baseline]]   - Subtracts a polynomial baseline offset from spectra.
:: whittaker  - Baseline subtraction using Whittaker filter.
+
:: [[wlsbaseline | whittaker]]   - Baseline subtraction using Whittaker filter.
:: datafit    - Asymmetric least squares baselining.
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:: [[datafit_engine | datafit]]     - Asymmetric least squares baselining.
 +
* '''order''' : positive integer for polynomial order {default =1}.
 +
* '''wlsbaseline_options''' : see wlsbaseline.m.
 +
* '''whittaker_options''' : see wlsbaseline.m.
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* '''baseline_freqs''' : wavenumber or frequency axis vector, see baseline.m.
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* '''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.
  
* '''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===
 
===Outputs===
  

Revision as of 15:38, 17 December 2018

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