calculate roughness against lenghscale and Power Spectrum Density (PSD): calculate roughness against length scale (RoughnessByLengthScale), PSD 1D (PSD1DAgainstFrequency) or PSD 2D (PSD2DAgainstFrequency) against frequencies
calculate fractal dimension and scale: use (getFractalDimensions) function
print in 3D (3D print) (exportToSTL) your AFM image
An EC2 instance is available for basic testing at the following address: http://www.afmist.org
Note: To use with a Brucker(TM) Atomic Force Microscope, use nanoscope analysis(TM) software and
Use the "Flatten" function.
Save the flattened image.
Use the "Browse Data Files" windows, right click on image name and then Export the AFM image with the headers and the "Export> ASCII" contextual menu option.
Author(s)
M.Beauvais, J.Landoulsi, I.Liascukiene
References
Gneiting2012, Tilmann Gneiting, Hana Sevcikova and Donald B. Percival 'Estimators of Fractal Dimension: Assessing the Roughness of Time Series and Spatial Data - Statistics in statistical Science, 2012, Vol. 27, No. 2, 247-277'
Olea2006, Ricardo A. Olea "A six-step practical approach to semivariogram modeling", 2006, "Stochastic Environmental Research and Risk Assessment, Volume 20, Issue 5 , pp 307-318"
Sidick2009, Erkin Sidick "Power Spectral Density Specification and Analysis of Large Optical Surfaces", 2009, "Modeling Aspects in Optical Metrology II, Proc. of SPIE Vol. 7390 73900L-1"
See Also
gstat, fractaldim, rgl
Examples
## Not run:
library(AFM)
# Analyse the AFMImageOfRegularPeaks AFM Image from this package
data("AFMImageOfRegularPeaks")
AFMImage<-AFMImageOfRegularPeaks
# exportDirectory="C:/Users/my_windows_login" or exportDirectory="/home/ubuntu"
exportDirectory=tempdir()
AFMImage@fullfilename<-paste(exportDirectory,"AFMImageOfRegularPeaks.txt",sep="/")
# Start to check if your sample is normaly distributed and isotropic.
generateCheckReport(AFMImage)
# If the sample is normaly distributed and isotropic, generate a full report
generateReport(AFMImage)
## End(Not run)