I have some oceanographic data (time, depth, plankton counts, salinity, temperature, etc.) from the deployment of oceanographic equipment. The deployment consisted of multiple profiles of the water column. I subsetted all downcasts in the data (when the equipment was descending), so that when I plot depth over time, the data look like this: depth over time.
What code or function can I use in R to automatically identify, isolate, and extract the data from each individual downcast into its own object (without having to specifically identify the times of each downcast)? For the data in the plot, it would essentially generate 6 objects. Ideally, the code could easily be applied to other deployments with 1-7 downcasts each.
I've been looking at identifying data break points or structural changes, but nothing has been fruitful. Thank you!!
If the probe only goes down during the downcast, i.e, there is no such case where
depth(i) > depth(i+1)
for cells belonging to the same downcast, then this code works.
It considers that when the depth of a cell is less than the depth of its previous one - see docs for diff(x) - a downcast has ended. So you may want to sanitize your date before using this. I've set a temperature list to demonstrate how to extend the use for other parameters.
## create test data for depth "Z" and temperature "T"
dc1.Z <- seq(10,100,1)
dc1.T <- seq(15, 3, length.out=length(dc1.Z))
dc2.Z <- seq(10,90,1)
dc2.T <- seq(18, 1, length.out=length(dc2.Z))
dc3.Z <- seq(20,80,1)
dc3.T <- seq(10, 2, length.out=length(dc3.Z))
dc4.Z <- seq(10,95,1)
dc4.T <- seq(15, 5, length.out=length(dc4.Z))
## join data as specified
dc.Z <- c(dc1.Z, dc2.Z, dc3.Z, dc4.Z)
dc.T <- c(dc1.T, dc2.T, dc3.T, dc4.T)
## get indexes for points where depth increases
## the 'plus one' is to target the first values of a downcast
## instead of the last ones, so splitAt will work properly
indexes <- which(diff(dc.Z) < 0) + 1
## define function for spliting a list at given indexes and use it
splitAt <- function(x, pos) unname(split(x, cumsum(seq_along(x) %in% pos)))
splited.dc.Z <- splitAt(dc.Z, indexes)
splited.dc.T <- splitAt(dc.T, indexes)
## check if each of the splited values match the original
all(dc1.Z == splited.dc.Z[[1]])
all(dc1.T == splited.dc.T[[1]])
all(dc2.Z == splited.dc.Z[[2]])
all(dc2.T == splited.dc.T[[2]])
all(dc3.Z == splited.dc.Z[[3]])
all(dc3.T == splited.dc.T[[3]])
all(dc4.Z == splited.dc.Z[[4]])
all(dc4.T == splited.dc.T[[4]])
I got the function splitAt from this question