corrspec
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 n x 2 matrix) if ncomp = scalar
then function will calculate first n resolved pure purity components. If ncomp
= n x 2 matrix, each row indicates the x and y position (index) to calculate
the purity solution. If empty, the initial matrices will be calculated.
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 with ncomp resolved dispersion matrixes, each with
size:
size(yspec,2)*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 is
stored in the field detail.matrix. See function 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.
Options
plots_spectra : ['off'|{'on'}] governs level of
plotting for spectra.
plots_maps : ['off'|{'on'}] governs level of plotting
for maps.
offset : noise correction factor. One element
defines offset for both x and y, two elements separately for x and y.
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:
1:
standardized, offset corrected
2:
length sqrt(nrows), offset corrected
3:
purity about mean, offset corrected
4:
purity about origin, offset corrected
5:
asynchronous, offset corrected
Examples
load data_mid_IR
load data_near_IR
corrspec(data_mid_IR,data_near_IR,4)
See Also
corrspecengine, dispmat
