plotZOC-methods: Methods for visually assessing results of ZOC procedure

Description Usage Arguments Details Value Methods Author(s) References See Also Examples

Description

Plots for comparing the zero-offset corrected depth from a TDRcalibrate object with the uncorrected data in a TDR object, or the progress in each of the filters during recursive filtering for ZOC (calibrateDepth).

Usage

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## S4 method for signature 'TDR,matrix'
plotZOC(x, y, xlim, ylim, ylab="Depth (m)", ...)
## S4 method for signature 'TDR,TDRcalibrate'
plotZOC(x, y, xlim, ylim, ylab="Depth (m)", ...)

Arguments

x

TDR object.

y

matrix with the same number of rows as there are observations in x, or a TDRcalibrate object.

xlim

POSIXct or numeric vector of length 2, with lower and upper limits of time to be plotted. Defaults to time range of input.

ylim

numeric vector of length 2 (upper, lower) with axis limits. Defaults to range of input.

ylab

character strings to label the corresponding y-axis.

...

Arguments passed to legend.

Details

The TDR,matrix method produces a plot like those shown in Luque and Fried (2011).

The TDR,TDRcalibrate method overlays the corrected depth from the second argument over that from the first.

Value

Nothing; a plot as side effect.

Methods

plotTDR

signature(x="TDR", y="matrix"): This plot helps in finding appropriate parameters for diveMove:::.depthFilter, and consists of three panels. The upper panel shows the original data, the middle panel shows the filters, and the last panel shows the corrected data. method=“visual” in calibrateDepth.

plotTDR

signature(x="TDR", y="TDRcalibrate"): This plots depth from the TDRcalibrate object over the one from the TDR object.

Author(s)

Sebastian P. Luque spluque@gmail.com

References

Luque, S.P. and Fried, R. (2011) Recursive filtering for zero offset correction of diving depth time series. PLoS ONE 6:e15850

See Also

calibrateDepth, .zoc

Examples

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## Using the Example from '?diveStats':

utils::example("diveStats", package="diveMove",
               ask=FALSE, echo=FALSE)

## Plot filters for ZOC
## Work on first phase (trip) subset, to save processing time, since
## there's no drift nor shifts between trips
tdr <- divesTDR[1:15000]
## Try window widths (K), quantiles (P) and bound the search (db)
K <- c(3, 360); P <- c(0.5, 0.02); db <- c(0, 5)
d.filter <- diveMove:::.depthFilter(depth=getDepth(tdr),
                                    k=K, probs=P, depth.bounds=db,
                                    na.rm=TRUE)
old.par <- par(no.readonly=TRUE)
plotZOC(tdr, d.filter, ylim=c(0, 6))
par(old.par)

## Plot corrected and uncorrected depth, regardless of method
## Look at three different scales
xlim1 <- c(getTime(divesTDR)[7100], getTime(divesTDR)[11700])
xlim2 <- c(getTime(divesTDR)[7100], getTime(divesTDR)[7400])
xlim3 <- c(getTime(divesTDR)[7100], getTime(divesTDR)[7200])
par(mar=c(3, 4, 0, 1) + 0.1, cex=1.1, las=1)
layout(seq(3))
plotZOC(divesTDR, dcalib, xlim=xlim1, ylim=c(0, 6))
plotZOC(divesTDR, dcalib, xlim=xlim2, ylim=c(0, 70))
plotZOC(divesTDR, dcalib, xlim=xlim3, ylim=c(0, 70))
par(old.par)

diveMove documentation built on May 2, 2019, 4:47 p.m.