Learn R Programming

diveMove (version 1.5.4)

diveModel-class: Class "diveModel" for representing a model for identifying dive phases

Description

Details of model used to identify the different phases of a dive.

Arguments

Objects from the Class

Objects can be created by calls of the form new("diveModel", ...).

‘diveModel’ objects contain all relevant details of the process to identify phases of a dive. Objects of this class are typically generated during depth calibration, using calibrateDepth, more specifically .cutDive.

Slots

label.matrix:

Object of class "matrix". A 2-column character matrix with row numbers matching each observation to the full TDR object, and a vector labelling the phases of each dive.

model:

Object of class "character". A string identifying the specific model fit to dives for the purpose of dive phase identification. It should be one of ‘smooth.spline’ or ‘unimodal’.

dive.spline:

Object of class "smooth.spline". Details of cubic smoothing spline fit (see smooth.spline).

spline.deriv:

Object of class "list". A list with the first derivative of the smoothing spline (see predict.smooth.spline).

descent.crit:

Object of class "numeric". The index of the observation at which the descent was deemed to have ended (from initial surface observation).

ascent.crit:

Object of class "numeric". the index of the observation at which the ascent was deemed to have ended (from initial surface observation).

descent.crit.rate:

Object of class "numeric". The rate of descent corresponding to the critical quantile used.

ascent.crit.rate:

Object of class "numeric". The rate of ascent corresponding to the critical quantile used.

See Also

getDiveDeriv, plotDiveModel

Examples

Run this code
# NOT RUN {
showClass("diveModel")

# }
# NOT RUN {
## Too long for checks
## Continuing the Example from '?calibrateDepth':
utils::example("calibrateDepth", package="diveMove",
               ask=FALSE, echo=FALSE, run.donttest=TRUE)
dcalib		# the 'TDRcalibrate' that was created

## Compare dive models for dive phase detection
diveNo <- 255
diveX <- as.data.frame(extractDive(dcalib, diveNo=diveNo))
diveX.m <- cbind(as.numeric(row.names(diveX[-c(1, nrow(diveX)), ])),
                 diveX$depth[-c(1, nrow(diveX))],
                 diveX$time[-c(1, nrow(diveX))])

## calibrateDepth() default unimodal regression. Number of inner knots is
## either 10 or the number of samples in the dive, whichever is larger.
(phases.uni <- diveMove:::.cutDive(diveX.m, smooth.par=0.2, knot.factor=20,
                                   dive.model="unimodal",
                                   descent.crit.q=0.01, ascent.crit.q=0))
## Smoothing spline model, using default smoothing parameter.
(phases.spl <- diveMove:::.cutDive(diveX.m, smooth.par=0.2, knot.factor=20,
                                   dive.model="smooth.spline",
                                   descent.crit.q=0.01, ascent.crit.q=0))
plotDiveModel(phases.spl,
              diveNo=paste(diveNo, ", smooth.par=", 0.2, sep=""))
plotDiveModel(phases.uni, diveNo=paste(diveNo))

# }
# NOT RUN {
# }

Run the code above in your browser using DataLab