Create a section based on columnar data, or a set of oce objects that can be coerced to a section. There are three cases.
Usage
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.
See also
Other things related to section data:
[[,section-method,
[[<-,section-method,
handleFlags,section-method,
initializeFlagScheme,section-method,
plot,section-method,
read.section(),
section,
section-class,
sectionAddStation(),
sectionGrid(),
sectionSmooth(),
sectionSort(),
subset,section-method,
summary,section-method
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 Time
#> 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
#>
#> - 2024-11-15 18:57:35 UTC: `create 'section' object`
#> - 2024-11-15 18:57:35 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 Time
#> 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
#>
#> - 2024-11-15 18:57:35 UTC: `create 'section' object`
#> - 2024-11-15 18:57:35 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 Time
#> 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
#>
#> - 2024-11-15 18:57:35 UTC: `create 'section' object`
#> - 2024-11-15 18:57:35 UTC: `as.section(salinity = subset(argo, profile < 5))`