Corrspec: Difference between revisions
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===Synopsis=== | ===Synopsis=== | ||
: | :model = corrspec(xspec,yspec,ncomp,''options'') | ||
:[purintx,purinty,purspecx,purspecy,maps] = corrspec(xspec,yspec,idex,options) | :[purintx,purinty,purspecx,purspecy,maps] = corrspec(xspec,yspec,idex,''options'') | ||
:[purintx,purinty,purspecx,purspecy,maps] = corrspec(xspec,yspec,model,options) | :[purintx,purinty,purspecx,purspecy,maps] = corrspec(xspec,yspec,model,''options'') | ||
===Description=== | ===Description=== | ||
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====Inputs==== | ====Inputs==== | ||
:xspec : (2-way array class "double" or "dataset") x-matrix for dispersion matrix. | |||
:yspec : (2-way array class "double" or "dataset") y-matrix for dispersion matrix. | |||
:ncomp : (scalar or ''N''x2 matrix) if (ncomp) is a scalar then CORRSPEC will estimate the first ncomp "purity" components. If (ncomp) is an ''N''x2 matrix, each row indicates the X- and Y-position (i.e., index) to estimate the purity solution. If (ncomp) is empty [ ], the initial matrices will be estimated by CORRSPEC. | |||
=== | ===Options=== | ||
Optional input ''options'' is a structure array with the following fields: | |||
:plots_spectra : [ 'off' |{ 'on'} ] governs level of plotting for spectra. | |||
:plots_maps : [ 'off' | {'on'} ] governs level of plotting for maps. | |||
:offset : noise correction factor. If (offset) is a scalar, it defines the offset for both x and y. If (offset) is a two element vector it defines the offset for for x and y respectively. | |||
inactivate : [ ] logical matrix of indices not to be used in purity calculation. | |||
:dispersion : [1] See (max) (below). | |||
:max : [3] If not given, only weight matrix will be calculated, otherwise select one of the options below: | |||
:: max = 1: standardized, offset corrected | |||
:: max = 2: length sqrt(nrows), offset corrected | |||
:: max = 3: purity about mean, offset corrected | |||
:: max = 4: purity about origin, offset corrected | |||
:: max = 5: asynchronous, offset corrected | |||
====Outputs==== | |||
:purintx : resolved x contributions("concentrations"). | |||
:purinty : resolved y contributions("concentrations"). | |||
:purspecx : resolved x pure component spectra. | |||
:purspecy : resolved y pure component spectra. | |||
:map : cell array with ncomp resolved dispersion matrixes, each with size [size(yspec,2) by size(xspec,2)] | |||
:model : standard model structure, used for prediction (same pure variables on other data set) and add components to the model. The series of correlation maps resulting from the sequential elimination of components are stored in the field (.detail.matrix). See CORRSPECENGINE for detailed description of (matrix). The series of resolved correlation maps is stored in field (.detail.maps). Once a model has been calculated it can be used to predict x spectra from y spectra and vice versa. | |||
===Examples=== | ===Examples=== | ||
Revision as of 15:04, 7 October 2008
Purpose
Resolves correlation spectroscopy maps.
Synopsis
- model = corrspec(xspec,yspec,ncomp,options)
- [purintx,purinty,purspecx,purspecy,maps] = corrspec(xspec,yspec,idex,options)
- [purintx,purinty,purspecx,purspecy,maps] = corrspec(xspec,yspec,model,options)
Description
CORRSPEC resolves a correlation map of two spectroscopies into the maps of individual components, their associated resolved spectra and the contributions ("concentrations") of the components in the original mixture spectra.
Inputs
- xspec : (2-way array class "double" or "dataset") x-matrix for dispersion matrix.
- yspec : (2-way array class "double" or "dataset") y-matrix for dispersion matrix.
- ncomp : (scalar or Nx2 matrix) if (ncomp) is a scalar then CORRSPEC will estimate the first ncomp "purity" components. If (ncomp) is an Nx2 matrix, each row indicates the X- and Y-position (i.e., index) to estimate the purity solution. If (ncomp) is empty [ ], the initial matrices will be estimated by CORRSPEC.
Options
Optional input options is a structure array with the following fields:
- plots_spectra : [ 'off' |{ 'on'} ] governs level of plotting for spectra.
- plots_maps : [ 'off' | {'on'} ] governs level of plotting for maps.
- offset : noise correction factor. If (offset) is a scalar, it defines the offset for both x and y. If (offset) is a two element vector it defines the offset for for x and y respectively.
inactivate : [ ] logical matrix of indices not to be used in purity calculation.
- dispersion : [1] See (max) (below).
- max : [3] If not given, only weight matrix will be calculated, otherwise select one of the options below:
- max = 1: standardized, offset corrected
- max = 2: length sqrt(nrows), offset corrected
- max = 3: purity about mean, offset corrected
- max = 4: purity about origin, offset corrected
- max = 5: asynchronous, offset corrected
Outputs
- purintx : resolved x contributions("concentrations").
- purinty : resolved y contributions("concentrations").
- purspecx : resolved x pure component spectra.
- purspecy : resolved y pure component spectra.
- map : cell array with ncomp resolved dispersion matrixes, each with size [size(yspec,2) by size(xspec,2)]
- model : standard model structure, used for prediction (same pure variables on other data set) and add components to the model. The series of correlation maps resulting from the sequential elimination of components are stored in the field (.detail.matrix). See CORRSPECENGINE for detailed description of (matrix). The series of resolved correlation maps is stored in field (.detail.maps). Once a model has been calculated it can be used to predict x spectra from y spectra and vice versa.
Examples
load data_mid_IR load data_near_IR corrspec(data_mid_IR,data_near_IR,4)