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This is another way to pre-treat aspectra set with the SNV math-treatment
(Standard Normal Variate). You can see the other one in the post : < o:p>
In this post, I use the R function “sweep“.< o:p>
library(ChemometricsWithR)< o:p>
#in a first step I calculate the average value< o:p>
#of all the data points for every spectrum and< o:p>
#subtract it to every data point of the < o:p>
#spectrum using the function “colMeans” < o:p>
#from the package “ChemometricsWhithR”< o:p>
#the mean value for every spectrum is now cero.< o:p>
NIR.1<-sweep(gasoline$NIR,MARGIN=1,< o:p>
+colMeans(t(gasoline$NIR)),FUN=”-“)< o:p>
#sd function calculates the SD for all the data < o:p>
#points of every #spectrum.< o:p>
#We divide now the value of every data point< o:p>
#by the SD of all the values of that spectrum.< o:p>
NIR.2<-sweep(NIR.1,MARGIN=1,< o:p>
+sd(t(gasoline$NIR)),FUN=”/”)< o:p>
#Now the spectrum has a mean of cero and a SD of 1.
#Use matplot to plot the spectra.
#Use matplot to plot the spectra.
matplot(wavelengths,t(NIR.2),type=”l”,lty=1,< o:p>
+xlab=”nm”,ylab=”log 1/R”,< o:p>
+main=”SNV Gasoline Spectra”,col=”blue”)< o:p>
< o:p>We have to take consider that in the Gasoline matrix, the rows are the < o:p>
samples and the columns the wavelengths, so we have to transpose the matrix < o:p>
for some calculations.< o:p>
Gasoline is a data set included in the “pls” package. Is not a set to see the benefits< o:p>
of the SNV math treatment (not enough scatter), but you can try < o:p>
with other data sets as “yarn”.< o:p>
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