On 06/10/2011 08:10 AM, Sam Albers wrote:
Hello all,
I have been using an instrument that collects a temperature profile of a
water column. The instrument records the temperature and depth any time it
takes a reading. I was sampling many times at discrete depth rather than a
complete profile of the water column (e.g. interested in 5m, 10m and 20m
depth position only). The issue was that these measurement were taken with
the instrument hanging off the side of a boat so a big enough wave moved the
instrument such that it recorded a slightly different depth. For my
purposes, however, this difference is negligible and I wish to consider all
those different readings at close depth as a single depth. So for example:
library(ggplot2)
eg<- read.csv("http://dl.dropbox.com/u/1574243/example_data.csv";,
header=TRUE, sep=",")
## Calculating an average value from all the readings for each depth reading
eg.avg<- ddply(eg, c("site", "depth"), function(df)
return(c(temp=mean(df$temperature),
+
num_samp=length(df$temperature)
+ )))
## An example of my problem
eg.avg[eg.avg$num_samp>10& eg.avg=="Station 3",]
site depth temp num_samp
154 Station 3 1.09000 4.073667 30
159 Station 3 2.49744 3.950972 72
175 Station 3 7.96332 3.903188 69
208 Station 3 19.37708 4.066393 61
209 Station 3 19.54096 4.025385 13
## So here you will notice that record 208 and 209, by my criteria, should
be considered a sample at the same depth and lumped together. Yet I can't
figure out a way to coerce R to calculate a mean value of temperature based
on a threshold range depth (say +/- 0.25). Generally speaking this can be
said to be calculating a mean (temperature) based on a factor (depth) range.
Hi Sam,
I suspect that you have a set of "nominal depths" in which you are
interested. If so, I would suggest using "cut" as Peter suggested, but
specifying the breaks like this:
depth_cat<-cut(depth,breaks=c(0,2.5,7.5,15,30),
labels=c("0","5","10","25"))
So that the values nearest to your "nominal depths" will be aggregated
into the correct categories.
Jim
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