It can happen that even acquiring enough
subscans the spectra is still noisy, due to certain sample presentation
limitations, so we can apply another technique to reduce the noise, the one
called “moving average”. With this technique we select a window size (in this
case 11) and the absorbance average of the 11 data points is given to the
middle one. After we move one data point to the right and continue with the
processing. Is for this reason that, in this case, we truncate the spectrum 5
points at the beginning and 5 points at the end.
See the results following this script:
library(prospectr)
X.movav<-movav(X.noisy,11) plot(colnames(X),X.noisy[1,],type="l",col="red",
+ xlim=c(1100,2500),ylim=c(0.28,0.38),
+ xlab="wavelength",ylab="absorbance")
par(new=TRUE)
plot(colnames(X.movav),X.movav[1,],type="l",lwd=2,
+ xlim=c(1100,2500),ylim=c(0.28,0.38),
+ xlab="wavelength",ylab="absorbance",col="blue")
legend("topleft",legend=c("moving average","raw"),
+ lty=c(1,1),col=1:2)
Follow this tutorial
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