ctdTrim with
method="downcast", although it is almost always best to use plotScan to
investigate the data, and then use the method="index" or method="scan" method based on
visual inspection of the data.
ctdTrim(x, method, removeDepthInversions = FALSE, parameters = NULL, debug = getOption("oceDebug"))ctd object, i.e. one inheriting from ctd-class.method is not provided, "downcast" is
assumed. See “Details”.ctdDecimate will be used, which will remove the inversions.oce functions. Generally, setting debug=0
turns off the printing, while higher values suggest that more information
be printed.ctd-class, with data having been trimmed in some way.
ctdTrim begins by examining the pressure differences between subsequent samples. If
these are all of the same value, then the input ctd object is returned, unaltered.
This handles the case of pressure-binned data. However, if the pressure difference
varies, a variety of approaches are taken to trimming the dataset.method[1] is "downcast" then an attempt is made to only data for
which the CTD is descending. This is done in stages, with variants based on method[2], if
supplied. Step 1. The pressure data are despiked with a smooth() filter with method "3R".
This removes wild spikes that arise from poor instrument connections, etc. Step 2. If no
parameters are given, then any data with negative pressures are deleted. If there is a
parameter named pmin, then that pressure (in decibars) is used instead as the lower limit.
This is a commonly-used setup, e.g. ctdTrim(ctd, parameters=list(pmin=1)) removes the top
decibar (roughly 1m) from the data. Specifying pmin is a simple way to remove near-surface
data, such as a shallow equilibration phase, and if specified will cause ctdTrim to skip
step 4 below. Step 3. The maximum pressure is determined, and data acquired subsequent to
that point are deleted. This removes the upcast and any subsequent data. Step 4. If the
pmin parameter is not specified, an attempt is made to remove an initial equilibrium phase
by a regression of pressure on scan number. There are three variants to this, depending on the
value of the second method element. If it is "A" (or not given), the procedure is to
call nls to fit a piecewise linear model of pressure as a function of scan,
in which pressure is
constant for scan less than a critical value, and then linearly varying for with scan. This is
meant to handle the common situation in which the CTD is held at roughly constant depth (typically
a metre or so) to equilibrate, before it is lowered through the water column.
Case "B" is the same,
except that the pressure in the surface region is taken to be zero (this does not make
much sense, but it might help in some cases). Note that, prior to early 2016, method "B" was
called method "C"; the old "B" method was judged useless and was removed.
method="sbe", a method similar to that described
in the SBE Data Processing manual is used to remove the "soak"
period at the beginning of a cast (see Section 6 under subsection
"Loop Edit"). The method is based on the soak procedure whereby
the instrument sits at a fixed depth for a period of time, after
which it is raised toward the surface before beginning the actual
downcast. This enables equilibration of the sensors while still
permitting reasonably good near-surface data. Parameters for the
method can be passed using the parameters argument, which
include minSoak (the minimum depth for the soak) and
maxSoak the maximum depth of the soak. The method finds
the minimum pressure prior to the maxSoak value being
passed, each of which occuring after the scan in which the
minSoak value was reached. For the method to work, the
pre-cast pressure minimum must be less than the minSoak
value. The default values of minSoak and maxSoak
are 1 and 20 dbar, respectively.
method="index" or "scan", then each column of data is subsetted according to the
value of parameters. If the latter is a logical vector of length matching data column
length, then it is used directly for subsetting. If parameters is a numerical vector with
two elements, then the index or scan values that lie between parameters[1]
and parameters[2] (inclusive) are used for subsetting. The
two-element method is probably the most useful, with the values being determined by visual
inspection of the results of plotScan. While this may take a minute or two, the
analyst should bear in mind that a deep-water CTD profile might take 6 hours, corresponding to
ship-time costs exceeding a week of salary.
method="range" then data are selected based on the value of the column named
parameters$item. This may be by range or by critical value. By range: select values
between parameters$from (the lower limit) and parameters$to (the upper limit) By
critical value: select if the named column exceeds the value. For example, ctd2 <-
ctdTrim(ctd, "range", parameters=list(item="scan", from=5)) starts at scan number 5 and
continues to the end, while
ctdTrim(ctd,"range",parameters=list(item="scan",from=5,to=100)) also starts at scan 5,
but extends only to scan 100.
method is a function, then it must return a vector of logical
values, computed based on two arguments: data (a
list), and parameters as supplied to ctdTrim. Both
inferWaterDepth and removeInversions are ignored in the function case. See
“Examples”.
Seasoft V2: SBE Data Processing, SeaBird Scientific, 05/26/2016
ctd data: [[,ctd-method,
[[<-,ctd-method, as.ctd,
cnvName2oceName, ctd-class,
ctdDecimate, ctdFindProfiles,
ctdRaw, ctd,
handleFlags,ctd-method,
plot,ctd-method, plotProfile,
plotScan, plotTS,
read.ctd.itp, read.ctd.odf,
read.ctd.sbe,
read.ctd.woce.other,
read.ctd.woce, read.ctd,
subset,ctd-method,
summary,ctd-method,
woceNames2oceNames, write.ctd
## Not run:
# library(oce)
# data(ctdRaw)
# plot(ctdRaw) # barely recognizable, due to pre- and post-cast junk
# plot(ctdTrim(ctdRaw)) # looks like a real profile ...
# plot(ctdDecimate(ctdTrim(ctdRaw),method="boxcar")) # ... smoothed
# # Demonstrate use of a function. The scan limits were chosen
# # by using locator(2) on a graph made by plotScan(ctdRaw).
# trimByIndex<-function(data, parameters) {
# parameters[1] < data$scan & data$scan < parameters[2]
# }
# trimmed <- ctdTrim(ctdRaw, trimByIndex, parameters=c(130, 380))
# plot(trimmed)
# ## End(Not run)
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