Hello,
I am not entirely sure the subject line captures what I am trying to do, but
hopefully this description of the problem will help folks to see my
challenge and hopefully offer constructive assistance.
I have an experimental setup where I measure the decrease in oxygen in small
vials as an organism, such as an oyster, consumes the oxygen. Each vial is
calibrated before the experiment and these calibrations are used to convert
the raw data after the experiment into oxygen values. I end up with two
dataframes. One has the calibration data and for example could look like
this
vial cal0 T0 cal100 T100
1 61 18 28 18
2 60.8 18 27.1 18
3 60.2 18 28.3 18
4 59.8 18 27.2 18
The second is a data file which could look like this
vial phase temp time
1 31 17.5 10
1 31.5 17.4 20
1 32.8 17.5 30
2 29.0 17.5 10
2 29.7 17.5 20
2 30.9 17.5 30
3 27.1 17.4 10
3 27.6 17.4 20
3 28.1 17.5 30
4 31.0 17.6 10
4 33.3 17.6 20
4 35.6 17.6 30
I have a complicated function (included at the bottom) that uses the
calibration values and the raw data to calculate actual oxygen levels. It
works great, but as its currently written it requires that each calibration
be entered individually. I would rather apply the function based upon the
vial number (applying the calibration for vial 1 to all vial 1 data,
calibration for vial 2 to all vial 2 data).
I have managed to do this by combining the two dataframes into one that
looks like this
data
vial phase temp time cal0 T0 cal100 T100
1 31 17.5 10 61 18 28 18
1 31.5 17.4 20 61 18 28 18
1 32.8 17.5 30 61 18 28 18
1 33.6 17.5 40 61 18 28 18
2 29.0 17.5 10 60.8 18 27.1 18
2 29.7 17.5 20 60.8 18 27.1 18
2 30.9 17.5 30 60.8 18 27.1 18
3 27.1 17.4 10 60.2 18 28.3 18
3 27.6 17.4 20 60.2 18 28.3 18
3 28.1 17.5 30 60.2 18 28.3 18
4 31.0 17.6 10 59.8 18 27.2 18
4 33.3 17.6 20 59.8 18 27.2 18
4 35.6 17.6 30 59.8 18 27.2 18
I have then used ddply to apply my function grouped by "vial"
oxygen<-ddply(data,.(vial), function(d) optode(d$cal0, d$T0, d$cal100,
d$T100, d$phase, d$temp))
This works, but I do not like having to put the calibrations into the same
dataframe as the data. Can anyone show me an example of how I could have a
function reference a dataframe (like the calibration data) based upon a
grouping variable (like "vial") and use that data as partial inputs to the
function when it is applied to another dataframe (the actual data)? I don't
necessarily need an example using my sample data or the function I have
included here (as it is rather unwieldly). A simplified example of how to
achieve this type of cross referencing would suffice and I can apply the
principle to my current problem.
Thanks so much,
Nate
optode<-function(cal0,T0,cal100,T100,phase,temp) {
f1=0.801
deltaPsiK=-0.08
deltaKsvK=0.000383
m=22.9
tan0T100=tan(((cal0+deltaPsiK*(T100-T0)))*pi/180)
tan0Tm=tan((cal0+(deltaPsiK*(temp-T0)))*pi/180)
tan100T100=tan(cal100*pi/180)
tanmTm=tan(phase*pi/180)
A=tan100T100/tan0T100*1/m*100^2
B=tan100T100/tan0T100*100+tan100T100/tan0T100*1/m*100-f1*1/m*100-100+f1*100
C=tan100T100/tan0T100-1
KsvT100=(-B+(sqrt(B^2-4*A*C)))/(2*A)
KsvTm=KsvT100+(deltaKsvK*(temp-T100))
a=tanmTm/tan0Tm*1/m*KsvTm^2
b=tanmTm/tan0Tm*KsvTm+tanmTm/tan0Tm*1/m*KsvTm-f1*1/m*KsvTm-KsvTm+f1*KsvTm
c=tanmTm/tan0Tm-1
saturation=(-((tan(phase*pi/180))/(tan((cal0+(deltaPsiK*(temp-T0)))*pi/180))*(KsvT100+(deltaKsvK*(temp-T100)))+(tan(phase*pi/180))/(tan((cal0+(deltaPsiK*(temp-T0)))*pi/180))*1/m*(KsvT100+(deltaKsvK*(temp-T100)))-f1*1/m*(KsvT100+(deltaKsvK*(temp-T100)))-(KsvT100+(deltaKsvK*(temp-T100)))+f1*(KsvT100+(deltaKsvK*(temp-T100))))+(sqrt((((tan(phase*pi/180))/(tan((cal0+(deltaPsiK*(temp-T0)))*pi/180))*(KsvT100+(deltaKsvK*(temp-T100)))+(tan(phase*pi/180))/(tan((cal0+(deltaPsiK*(temp-T0)))*pi/180))*1/m*(KsvT100+(deltaKsvK*(temp-T100)))-f1*1/m*(KsvT100+(deltaKsvK*(temp-T100)))-(KsvT100+(deltaKsvK*(temp-T100)))+f1*(KsvT100+(deltaKsvK*(temp-T100)))))^2-4*((tan(phase*pi/180))/(tan((cal0+(deltaPsiK*(temp-T0)))*pi/180))*1/m*(KsvT100+(deltaKsvK*(temp-T100)))^2)*((tan(phase*pi/180))/(tan((cal0+(deltaPsiK*(temp-T0)))*pi/180))-1))))/(2*((tan(phase*pi/180))/(tan((cal0+(deltaPsiK*(temp-T0)))*pi/180))*1/m*(KsvT100+(deltaKsvK*(temp-T100)))^2))
print(saturation)
}
[[alternative HTML version deleted]]
______________________________________________
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
