Skip to contents

Mutate traits within a traitdata object.

Source: R/mutate.traitdata.R
mutate.traitdata.Rd

This function allows to transform, factorize, or combine trait measurements into compound measurements or update factor levels into binaries.

Usage

mutate.traitdata(
  .data,
  ...,
  values = "verbatimTraitValue",
  traits = "verbatimTraitName",
  units = "verbatimTraitUnit"
)

Arguments

.data

the traitdata object to transform

...

named parameters giving definitions of new columns.

values

(NOT TESTED) the column name containing the trait values to be used to fill the matrix (default is verbatimTraitValue). Duplicate columns (e.g. traitValue) will be omitted. See notes.

traits

(NOT TESTED) the column name to be kept for parsing into wide-table (default is verbatimTraitName). Note that any duplicate column that contains trait names, e.g. traitName will be omitted.

units

(NOT TESTED) the column name containing the units of numerical values (default is verbatimTraitUnit).

Value

an updated traitdata object with the new trait measures or facts appended to the original table. If the given trait name has been refined, it will be replaced.

Details

The function handles units for numerical traits and returns the new unit of the computed value in column verbatimTraitUnit, if units of input variables were specified according to the units package. Handling of other columns than verbatimTraitName and verbatimTraitValue is not advised at present.

It is advised to mutate traits before applying standardize.traits()! If the mutate function is applied to a standardised dataset, the new trait will not be mapped automatically to the provided thesaurus. (automated re-mapping might be added in later versions of the package.)

Examples


if (FALSE) {
pulldata("arthropodtraits")
dataset3 <- as.traitdata(arthropodtraits,
                         taxa = "SpeciesID",
                         traits = c("Body_Size", "Dispersal_ability",
                            "Feeding_guild","Feeding_guild_short",
                            "Feeding_mode", "Feeding_specialization",
                            "Feeding_tissue", "Feeding_plant_part",
                            "Endophagous_lifestyle", "Stratum_use",
                            "Stratum_use_short"),
                         units = c(Body_Size = "mm", Dispersal_ability = "unitless"),
                         keep = c(measurementRemark = "Remark"),
                         metadata = list(
                            license = "http://creativecommons.org/publicdomain/zero/1.0/"
                            )
)
head(dataset3)

updated <- mutate.traitdata(dataset3, predator = Feeding_guild == "c" )

head(updated[updated$verbatimTraitName == "predator",])

levels(updated$verbatimTraitName)

##

pulldata("heteroptera_raw")
dataset2 <- as.traitdata(heteroptera_raw,
                        traits = c("Body_length", "Body_width", "Body_height", "Thorax_length",
                                  "Thorax_width", "Head_width", "Eye_width", "Antenna_Seg1",
                                   "Antenna_Seg2", "Antenna_Seg3", "Antenna_Seg4", "Antenna_Seg5",
                                   "Front.Tibia_length", "Mid.Tibia_length", "Hind.Tibia_length",
                                   "Front.Femur_length", "Hind.Femur_length", "Front.Femur_width",
                                   "Hind.Femur_width", "Rostrum_length", "Rostrum_width",
                                   "Wing_length", "Wing_width"),
                        taxa = "SpeciesID",
                        occurrences = "ID"
)
updated <- mutate.traitdata(dataset2,
                            Body_shape = Body_length/Body_width,
                            Body_volume = Body_length*Body_width*Body_height,
                            Wingload = Wing_length*Wing_width/Body_volume)

head(updated[updated$verbatimTraitName %in% c( "Body_volume"),])
}