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I have:

  1. Linearly interpolated the dFe_env data every 1 m and create a data frame (This works)
  2. Extracted the 'Depth' (based on sinking rate) in 30 minute intervals (This works)
  3. Created a 'Time' column where it increases every 30 minutes (This works)

How do I:

  1. Merge two dataframes together (Bckgd_env2 and bulk_Fe2). In 'bulk_Fe2' the Depth increases by 1m and in 'Bckgd_env2' the depth increases by 0.8m. Can I get the closest 'Depth' match, extract the dFe_env at that depth and create a new data frame with Depth, Time and dFe_env all together?

    library(dplyr)

Depth    <- c(0, 2, 20, 50, 100, 500, 800, 1000, 1200, 1500)
dFe_env  <- c(0.2, 0.2, 0.3, 0.4, 0.2, 0.1, 0.1, 0.1, 0.1, 0.1)
bulk_Fe <- data.frame(Depth, dFe_env)

summary(bulk_Fe)
is.data.frame(bulk_Fe)

do_interp <- function(dat, Depth = seq(0,1500, by=1)) {
out <- tibble(Depth = Depth)
for (var in c("dFe_env")) {
out[[var]] <- tryCatch(approx(dat$Depth, dat[[var]], Depth)$y, method="ngb", error = function(e) NA_real_)
}
out
}

bulk_Fe2 <- bulk_Fe %>% do(do_interp(.))
bulk_Fe2
summary(bulk_Fe2)

D0 <- 0 #Starting depth 
T0 <- 0 #Starting time of the experiment

r <- 40 #sinking rate per day

r_30min <- r/48 #sinking speed every 30 minutes (There are 48 x 30 minute intervals in 24 hours)


days <- round(1501/(r)) #days 1501 is maximum depth
time <- days * 24 * 60 #minutes

n_steps <- 1501/r_30min

Bckgd_env2 <- data.frame(Depth =seq(from = D0, by= r_30min, length.out = n_steps + 1),
                  Time = seq(from = T0, by= 30, length.out = n_steps + 1))
head(Bckgd_env2)
round(Bckgd_env2, digits = 1)

Bckgd_env3 <- merge(Bckgd_env2, bulk_Fe2)  
Bckgd_env3

plot(Bckgd_env2$dFe_env ~ Bckgd_env2$Depth, ylab="dFe (nmol/L)", xlab="Depth (m)", las=1)
L55
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  • Not sure if I understand the constants correctly. What is 1501? What is 200 second block? 30 mins is 1800 seconds. – Ronak Shah Sep 02 '20 at 05:11
  • 1501 is the maximum depth of a site and I use that to calculate how many days the experiment should run for. For example, at a sinking speed of 40 per day, the experiment should run for 1501/40 = 37.5 days. Rounded to 38 days. I made a mistake - I was trying to do it by 200 second blocks instead of 30 minute blocks (which is what I need) – L55 Sep 02 '20 at 05:18

1 Answers1

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You have already built the mechanism for interpolation which will be useful for the join. But you didn't build it at the right depth values. It is just a matter of reorganizing your code.

Start with buiding Bckgd_env2, and only afterwards compute bulk_Fe2 and bulk_Fe3:

bulk_Fe2 <- bulk_Fe %>% do(do_interp(., Depth=Bckgd_env2$Depth))
Bckgd_env3 <- merge(Bckgd_env2, bulk_Fe2)
Pierre Gramme
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  • I am also merging other data that do not require interpolation (temperature, oxygen etc.). These are raster files and the data is in 1m intervals so I don't have to do any interpolation. Is there a way to merge because some dataframes do not need interpolation? – L55 Sep 02 '20 at 11:29
  • Unless the other dataframes have exactly the same depth values as `Bckgd_env2`, they do need interpolation. What you probably want is constant interpolation (cf `?approx`). You can add method as an argument to your `do_interp()` function. – Pierre Gramme Sep 02 '20 at 12:16
  • By the way, you probably have a typo in your code: `method="ngb"` is not passed to approx (and it wouldn't work) – Pierre Gramme Sep 02 '20 at 12:17