generates an AFMdata object, which is sometimes useful for testing algorithms or models or to explore AFM data numerically.
AFM.artificialImage(
width = 10,
height = 10,
minZ = 0,
maxZ = 100,
imageWidth = 1000,
imageHeight = 1000,
type = c("random", "gradient", "calibration"),
addNoise = TRUE,
invert = FALSE,
verbose = TRUE
)Arguments
- width
width in pixels
- height
height in pixels
- minZ
minimum z height
- maxZ
maximum z height
- imageWidth
width of image in nm
- imageHeight
height of image in nm
- type
can be random gradient calibration
- addNoise
if
TRUE, add a bit of noise to the data- invert
logical, if
TRUE, top and bottom are inverted- verbose
if
TRUE, output additional information
Value
AFMdata object
Examples
a = AFM.artificialImage(type='calibration')
#> [1] "Instrument: artificial"
plot(a)
#> Graphing: HeightTrace
