Using the R “apply” family with oce objects


In the oce package, the various different data formats are stored in consistently structured objects. In this post, I’ll explore a way to access elements of multiple oce objects using the R lapply(), from the apply family of functions.

Example with a ctd object

The objects always contain three fields (or “slots”): metadata, data, and processingLog. The layout of the object can be visualized using the str() command, like:


which produces something like:

Formal class 'ctd' [package "oce"] with 3 slots
  ..@ metadata     :List of 26
  .. ..$ header                  : chr [1:42] "* Sea-Bird SBE 25 Data File:"
  .. ..$ type                    : chr "SBE"
  .. ..$ conductivityUnit        : chr "ratio"
  .. ..$ temperatureUnit         : chr "IPTS-68"
  .. ..$ systemUploadTime        : POSIXct[1:1], format: "2003-10-15 11:38:38"
  .. ..$ station                 : chr "Stn 2"
  .. ..$ date                    : POSIXct[1:1], format: "2003-10-15 11:38:38"
  .. ..$ startTime               : POSIXct[1:1], format: "2003-10-15 11:38:38"
  .. ..$ latitude                : num 44.7
  .. ..$ longitude               : num -63.6
  ..@ data         :List of 9
  .. ..$ scan         : int [1:181] 130 131 132 133 134 135 136 137 138 139 ...
  .. ..$ time         : num [1:181] 129 130 131 132 133 134 135 136 137 138 ...
  .. ..$ pressure     : num [1:181] 1.48 1.67 2.05 2.24 2.62 ...
  .. ..$ depth        : num [1:181] 1.47 1.66 2.04 2.23 2.6 ...
  .. ..$ temperature  : num [1:181] 14.2 14.2 14.2 14.2 14.2 ...
  .. ..$ salinity     : num [1:181] 29.9 29.9 29.9 29.9 29.9 ...
  .. ..$ temperature68: num [1:181] 14.2 14.2 14.2 14.2 14.2 ...
  ..@ processingLog:List of 2
  .. ..$ time : POSIXct[1:5], format: "2015-08-18 19:22:36" "2015-08-18 19:22:36" ...
  .. ..$ value: chr [1:5] "create 'ctd' object" "ctdAddColumn(x = res, column = swSigmaTheta(res@data$salinity,     res@data$temperature, res@data$pressure), name = "sigmaThet"| __truncated__ "read.ctd.sbe(file = file, processingLog = processingLog)" "converted temperature from IPTS-69 to ITS-90" ...

(where I’ve trimmed a few lines out just to make it shorter).

For a single object, there are several ways to access the information contained in the object. The first (and generally recommended) way is to use the [[ accessor — for example if you wanted the temperature values from a ctd object you would do

T <- ctd[['temperature']]

Another way is to access the element directly, by using the slot and list syntax, like:

T <- ctd@data$temperature

The disadvantage to the latter is that it requires knowledge of exactly where the desired field is in the object structure, and is brittle to downstream changes in the oce source.

Working with multiple objects

Frequently, especially with CTD data, it is common to have to work with a number of individual ctd objects — usually representing different casts. One way of organizing such objects, particularly if they share a common instrument, or ship, or experiment etc, is to collect them into a list.

For example, we could loop through a directory of individual cast files (or extract multiple casts from one file using ctdFindProfiles()), and append each one to a list like:

files <- dir(pattern='*.cnv')
casts <- list()
for (ifile in 1:length(files)) {
    casts[[ifile]] <- read.oce(files[ifile])

If we summarize the new casts list, we can see that it’s filled with ctd objects:

str(casts, 1) # the "1" means just go one level deep
List of 5
 $ :Formal class 'ctd' [package "oce"] with 3 slots
 $ :Formal class 'ctd' [package "oce"] with 3 slots
 $ :Formal class 'ctd' [package "oce"] with 3 slots
 $ :Formal class 'ctd' [package "oce"] with 3 slots
 $ :Formal class 'ctd' [package "oce"] with 3 slots

Extracting fields from multiple objects at once

Say we want to extract all the temperature measurements from each object in our new list? How could we do it?

The brute force approach would be to loop through the list elements, and append the temperature field to a vector, maybe something like:

T_all <- NULL
for (i in 1:length(casts)) {
    T_all <- c(T_all, casts[[i]][['temperature']])

But in R, there’s a more elegant way — lapply()!

T_all <- unlist(lapply(casts, function(x) x[['temperature']]))

4 thoughts on “Using the R “apply” family with oce objects

  1. Nerea

    Thanks for your post, it has been very useful for me to start with oce package. I am a beginer with programming and R. I need to work with multiple ctd files and trying to apply your code:

    files <- dir(pattern=’*.cnv’)
    casts <- list()
    for (ifile in 1:length(ifile)) {
    casts[[ifile]] <- read.oce(files[ifile])

    I get an error: object ‘ifile’ not found

    I think that what I need is to create the object ifile, but I don’t know what kind of object is and for what is used to. I would be very greatful if you could help me.

    Thanks in advance,


    1. clarkrichards Post author

      Hi Nerea,

      Thanks for the comment. FYI I have mostly moved my blogging about oce over to, but there are no comments enabled there yet.

      The example I posted above was pseudo-code — meant simply to illustrate generally how you could accomplish a task. In looking closer I see a typo that is perhaps the reason it doesn’t work for your case. Note the 1:length(files) in place of 1:length(ifile)

      files <- dir(pattern=’*.cnv’)
      casts <- list()
      for (ifile in 1:length(files)) {
      casts[[ifile]] <- read.oce(files[ifile])

      However, as I said this is really only a broadly general way of reading data files. I expect that for real science work you will have to spend some time examining (i.e. plotting) your CTD objects, trimming them, cleaning them up, etc. Always plot your data and make sure it makes sense before doing anything with it.


  2. Nerea

    Dear Clark. Thank you for your response. I will definitely visit your new blog.

    I agree with you about the specific work that requires real data. I am just trying to get familiar with Oce and R programming at the same time using my own data as an example.

    Thanks again for your help.



  3. Nerea

    By the way. I tried the correction you wrote above and now it works perfect. I also understand now the function.

    Thanks again.



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