PeakFilling | R Documentation |
This functions detects which samples (after grouping) are missing from every peak group and reanalyses the raw data to verify whether this peak is actually non-existent for this sample
PeakFilling( Y.grouped, Y.spec, max.index.shift = 10, window.width = "small", nCPU = -1, FilMethod = "new" )
Y.grouped |
Peaks groups (output from the 'PeakGrouper' function). |
Y.spec |
The raw NMR spectra in matrix format. |
max.index.shift |
Maximal shift in index between a filled peak and the group it belongs to. |
window.width |
The width of the detection window for the wavelets. Because of the Fourier transform lengths of 512 ( window.width = 'small') of 1024 ( window.width = 'large') are preferable. |
nCPU |
The amount of cpu's to be used for peak detection. If set to '-1' all available cores minus 1 will be used. |
FilMethod |
A more robust method for peak filling has been implemented. This is now the default. The former method can be used by specifying FilMethod == "old" however this will be deprecated. |
Returns a data frame with grouped peaks and possibly extra peaks obtained from the raw data (these peaks have SNR = NA).
Charlie Beirnaert, charlie.beirnaert@uantwerpen.be
subset <- GetWinedata.subset() # to reduce the example time we only select spectra 1 & 2 subset.spectra = as.matrix(subset$Spectra)[1:2,] subset.ppm = as.numeric(subset$PPM) test.peaks <- getWaveletPeaks(Y.spec=subset.spectra, X.ppm=subset.ppm, nCPU = 1) # nCPU set to 1 for the vignette build test.grouped <- PeakGrouper(Y.peaks = test.peaks) test.filled <- PeakFilling(Y.grouped = test.grouped, Y.spec = subset.spectra, nCPU = 1) # nCPU set to 1 for the vignette build
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