read: Read in Diet Matrix

In pkuhnert/diet: Performs an analysis of diet data using univariate trees

Read in Diet Matrix

Description

Read in diet compositional data in one of two formats. Data stored as a compositional matrix can be read in using the read.dm function. Data stored in a predator-prey format can be read in using the read.pp function.

Usage

read.dm(object = NULL, filenm = NULL, labels = list(DateL = "Date",
  FullnessL = "Fullness"), Datef = "%d/%m/%Y", diet.ind.start,
  p = 0.01, sp2omit = NULL, predsp = NULL)

read.pp(object = NULL, filenm = NULL, labels = list(PredatorL =
  "PredID", TripSetL = "TripSetNo", SpeciesL = "Species", FullnessL =
  "Fullness", DateL = "Date", WeightL = "Weight", PreyGrpL = "PreyGrp"),
  Datef = "%d/%m/%Y", p = 0.01, Xvars, sp2omit = NULL)

Arguments

object	matrix. A compositional data matrix containing covariate information and diet composition for each predator (optional).
filenm	file name. A file name specifying the location of a comma delimited file that contains the covariate information and diet composition for each predator (optional).
labels	a list containing the following: DateL Date column name: default label is "Date". FullnessL Fullness column name used to identify full stomachs for analysis: default label is "Fullness". PredatorL Predator column name: default label is "PredID". TripSetL Sampling column name: default label is "TripSetNo". SpeciesL Species column name: default label is "Species". This may have the same label as PreyGrpL. WeightL Weight column name: default label is "Weight". This may represent weights, frequencies or binary data. PreyGrpL Prey group column name: default label is "PreyGrp". This may have the same label as SpeciesL.
Datef	date format. See strptime for format options.
diet.ind.start	integer. Column number where the diet composition data begins.
p	numeric. Proportion of prey to omit. If the composition is represented as a wet weight, then p represents the proportion of prey contributing to the wet weight consumption of a predator. If the composition is represented as a frequency or binary outcome, then p represents the proportion of prey found in a predator. (default: 0.01)
sp2omit	a vector of prey names to omit from the analysis (default: NULL)
predsp	Predator species names to extract from the data.
Xvars	a vector of covariate names that will be used in the analysis.

Details

The most common format for storing compositional data is matrix format. The read.dm function can then be used to read in the data. Occasionally data will be stored in predator-prey format. In this instance read.pp can be used to read in the data. In either function, either an R object or file name is required to read in the data.

Value

a matrix where each row represents data for a separate predator-prey combination.

References

Kuhnert, P.M., Duffy, L. M and Olson, R.J. (2012) The Analysis of Predator Diet and Stable Isotope Data, Journal of Statistical Software, In Prep.

Examples

# Reading in a diet matrix
#data(yftDMraw)
#write.csv(yftDMraw, file = "yftDMraw.csv", row.names = FALSE)
#yftpp1 <- read.dm(filenm = "yftDMraw.csv", 
#                   labels = list(FullnessL = "Fullness", DateL = "Date"),
#                                     Datef = "\%m/\%d/\%Y", diet.ind.start = 12, p = 0.01)
#data(PreyTaxonSort)
#val <- apc(x = yftpp1, preyfile = PreyTaxonSort, check = TRUE)
#node.colsY <- val$cols
#dietPP <- val$x   # updated diet matrix with "Group" assigned prey taxa codes
#head(dietPP)

# Reading in a predator-prey matrix
#data(yftPPraw)
#write.csv(yftPPraw, file = "yftPPraw.csv", row.names = FALSE)
#yftpp2 <- read.pp(filenm = "yftPPraw.csv",
#                   labels = list(PredatorL = "TripSetPredNo", TripSetL = "TripSetNo",
#                               SpeciesL = "Family", FullnessL = "Fullness", 
#                                DateL = "Date", WeightL = "PropW", PreyGrpL = "Family"), 
#                                 Datef = "\%m/\%d/\%Y", p = 0.01,
#                               Xvars = c("Lat", "Lon", "Year", "Quarter", "Length", "SST"))
#data(PreyTaxonSort)
#pal <- c(topo.colors(10)[1:2], heat.colors(10)[1:2], terrain.colors(25)[1:8])
#val <- apc(x = yftpp2, preyfile = PreyTaxonSort, palette = pal, check = TRUE)
#node.colsY <- val$cols
#dietPP <- val$x   # updated diet matrix with prey taxa codes
#head(dietPP)

pkuhnert/diet documentation built on June 10, 2025, 2:59 a.m.