oce (version 1.2-0)

subset,adp-method: Subset an ADP Object

Description

Subset an adp (acoustic Doppler profile) object, in a manner that is function is somewhat analogous to subset.data.frame().

Usage

# S4 method for adp
subset(x, subset, ...)

Arguments

x

an '>adp object.

subset

A condition to be applied to the data portion of x. See ‘Details’.

...

Ignored.

Value

An '>adp object.

Details

For any data type, subsetting can be by time, ensembleNumber, or distance. These may not be combined, but it is easy to use a string of calls to carry out combined operations, e.g. subset(subset(adp,distance<d0), time<t0)

For the special case of AD2CP data (see read.adp.ad2cp()), it is possible to subset to the "average" data records with subset="average", to the "burst" records with subset="burst", or to the "interleavedBurst" with subset="interleavedBurst"; note that no warning is issued, if this leaves an object with no useful data.

See Also

Other things related to adp data: [[,adp-method, [[<-,adp-method, ad2cpHeaderValue(), adp-class, adpEnsembleAverage(), adp_rdi.000, adp, as.adp(), beamName(), beamToXyzAdpAD2CP(), beamToXyzAdp(), beamToXyzAdv(), beamToXyz(), beamUnspreadAdp(), binmapAdp(), enuToOtherAdp(), enuToOther(), handleFlags,adp-method, is.ad2cp(), plot,adp-method, read.adp.ad2cp(), read.adp.nortek(), read.adp.rdi(), read.adp.sontek.serial(), read.adp.sontek(), read.adp(), read.aquadoppHR(), read.aquadoppProfiler(), read.aquadopp(), rotateAboutZ(), setFlags,adp-method, subtractBottomVelocity(), summary,adp-method, toEnuAdp(), toEnu(), velocityStatistics(), xyzToEnuAdpAD2CP(), xyzToEnuAdp(), xyzToEnu()

Other functions that subset oce objects: subset,adv-method, subset,amsr-method, subset,argo-method, subset,cm-method, subset,coastline-method, subset,ctd-method, subset,echosounder-method, subset,lobo-method, subset,met-method, subset,oce-method, subset,odf-method, subset,rsk-method, subset,sealevel-method, subset,section-method, subset,topo-method, subset,xbt-method

Examples

# NOT RUN {
library(oce)
data(adp)
# 1. Look at first part of time series, organized by time
earlyTime <- subset(adp, time < mean(range(adp[['time']])))
plot(earlyTime)

# 2. Look at first ten ensembles (AKA profiles)
en <- adp[["ensembleNumber"]]
firstTen <- subset(adp, ensembleNumber < en[11])
plot(firstTen)

# }