This function is very similar to transform
but it executes the
transformations iteratively so that later transformations can use the
columns created by earlier transformations. Like transform, unnamed
components are silently dropped.
Either the spectra, and/or the attributes (if the .data
inherits from
the SpectraDataFrame
class) can be affected:
To
affect the spectra, one should use the nir
placeholder, eg nir
= log(1/nir)
To affect the attributes of the object, the definitions
of new columns are simply given using attributes names, newAttribute =
1/sqrt(attribute)
Both spectra and attrbutes can be transformed in one command.
# S4 method for Spectra
mutate(.data, ...)
an object inheriting from the Spectra
class
named parameters giving definitions of new columns
Hadley Wickham (2011). The Split-Apply-Combine Strategy for Data Analysis. Journal of Statistical Software, 40(1), 1-29. URL http://www.jstatsoft.org/v40/i01/.
# NOT RUN {
# Loading example data
data(australia)
spectra(australia) <- sr_no ~ ... ~ 350:2500
# Modifying spectra
m <- mutate(australia, nir = log1p(1/nir))
plot(m)
# Modifying and creating attributes
m <- mutate(
australia,
sqrt_carbon = sqrt(carbon),
foo = clay + ph,
nir = log1p(1/nir)
)
plot(m)
# }
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