prospectr (version 0.1.3)

binning: Signal binning

Description

Compute average values of a signal in pre-determined bins (col-wise subsets). The bin size can be determined either directly or by specifying the number of bins. Sometimes called boxcar transformation in signal processing

Usage

binning(X,bins,bin.size)

Arguments

X

numeric data.frame, matrix or vector to process

bins

number of bins

bin.size

desired size of the bins

Value

a matrix or vector with average values per bin

See Also

sgolayfilt, savitzkyGolay, movav, gapDer, continuumRemoval

Examples

data(NIRsoil)
spc <- 1/10^NIRsoil$spc # conversion to reflectance
wav <- as.numeric(colnames(spc))
matplot(wav,t(spc[1:5,]),type='l',xlab='Wavelength /nm',ylab='Reflectance') # 5 first spectra
binned <- binning(spc,bin.size=20)
matpoints(as.numeric(colnames(binned)),t(binned[1:5,]),pch=1:5) # bin means
binned <- binning(spc,bins=20)
dim(binned) # 20 bins
matplot(wav,t(spc[1:5,]),type='l',xlab='Wavelength /nm',ylab='Reflectance') # 5 first spectra
matpoints(as.numeric(colnames(binned)),t(binned[1:5,]),pch=1:5) # bin means