Create a section based on columnar data, or a set of oce objects that can be coerced to a section. There are three cases.

as.section(
salinity,
temperature,
pressure,
longitude,
latitude,
station,
sectionId = "",
debug = getOption("oceDebug")
)

## Arguments

salinity

This may be a numerical vector, in which case it is interpreted as the salinity, and the other arguments are used for the other components of ctd objects. Alternatively, it may be one of a variety of other objects from which the CTD objects can be inferred, in which case the other arguments are ignored; see ‘Details’.

temperature

Temperature, in a vector holding values for all stations.

pressure

Pressure, in a vector holding values for all stations.

longitude

Longitude, in a vector holding values for all stations.

latitude

Latitude, in a vector holding values for all stations.

station

Station identifiers, in a vector holding values for all stations.

sectionId

Section identifier.

debug

an integer value that controls whether as.section() prints information during its work. The function works quietly if this is 0 and prints out some information if it is positive.

## Value

An object of section.

## Details

Case 1. If the first argument is a numerical vector, then it is taken to be the salinity, and factor() is applied to station to break the data up into chunks that are assembled into ctd objects with as.ctd() and combined to make a section object to be returned. This mode of operation is provided as a convenience for datasets that are already partly processed; if original CTD data are available, the next mode is preferred, because it permits the storage of much more data and metadata in the CTD object.

Case 2. If the first argument is a list containing oce objects, then those objects are taken as profiles of something. A requirement for this to work is that every element of the list contains both longitude and latitude in either the metadata or data slot (in the latter case, the mean value is recorded in the section object) and that every element also contains pressure in its data slot.

Case 3. If the first argument is a argo object, then the profiles it contains are turned into ctd objects, and these are assembled into a section to be returned.

Other things related to section data: [[,section-method, [[<-,section-method, handleFlags,section-method, initializeFlagScheme,section-method, plot,section-method, read.section(), section-class, sectionAddStation(), sectionGrid(), sectionSmooth(), sectionSort(), section, subset,section-method, summary,section-method

Dan Kelley

## Examples

library(oce)
data(ctd)
## vector of names of CTD objects
fake <- ctd
fake[["temperature"]] <- ctd[["temperature"]] + 0.5
fake[["salinity"]] <- ctd[["salinity"]] + 0.1
fake[["longitude"]] <- ctd[["longitude"]] + 0.01
fake[["station"]] <- "fake"
sec1 <- as.section(c("ctd", "fake"))
summary(sec1)
#> Section Summary
#> ---------------
#>
#> * Source: ""
#> * ID:     ""
#> * Overview of stations
#> Index    ID      Lon      Lat  Levels Depth        StartTime
#>     1 Stn 2 -63.6439  44.6843     181    NA 2003-10-15 15:38
#>     2  fake -63.6339  44.6843     181    NA 2003-10-15 15:38
#> * Processing Log
#>
#>     - 2022-08-18 15:44:12 UTC: create 'section' object
#>     - 2022-08-18 15:44:12 UTC: as.section(salinity = c("ctd", "fake"))
## vector of CTD objects
ctds <- vector("list", 2)
ctds[[1]] <- ctd
ctds[[2]] <- fake
sec2 <- as.section(ctds)
#> Warning: estimated waterDepth as max(pressure) for CTDs numbered 1:2
summary(sec2)
#> Section Summary
#> ---------------
#>
#> * Source: ""
#> * ID:     ""
#> * Overview of stations
#> Index    ID      Lon      Lat  Levels Depth        StartTime
#>     1 Stn 2 -63.6439  44.6843     181    44 2003-10-15 15:38
#>     2  fake -63.6339  44.6843     181    44 2003-10-15 15:38
#> * Processing Log
#>
#>     - 2022-08-18 15:44:12 UTC: create 'section' object
#>     - 2022-08-18 15:44:12 UTC: as.section(salinity = ctds)
## argo data (a subset)
data(argo)
sec3 <- as.section(subset(argo, profile<5))
summary(sec3)
#> Section Summary
#> ---------------
#>
#> * Source: ""
#> * ID:     ""
#> * Overview of stations
#> Index    ID      Lon      Lat  Levels Depth        StartTime
#>     1     1 -21.3850  60.9640      56    NA 2005-10-29 13:57
#>     2     2 -21.8880  60.8480      56    NA 2005-11-08 13:53
#>     3     3 -22.2570  61.1060      56    NA 2005-11-18 13:49
#>     4     4 -22.4160  61.2520      56    NA 2005-11-28 14:12
#> * Processing Log
#>
#>     - 2022-08-18 15:44:12 UTC: create 'section' object
#>     - 2022-08-18 15:44:12 UTC: as.section(salinity = subset(argo, profile < 5))