Dear all,
I am encountering problems with the application of ddply within the body of a
self-defined function.
The script is the following:
moncostcarmoto <- function(costtype){
costaux_result <- data.frame()
for (purp in PURPcount){for (per in PERcount){
costcarin =
paste(c("CS_",costtype,"CAR"),collapse="")
costmotoin =
paste(c("CS_",costtype,"MOTO"),collapse="")
browser()
COSTaux_AVCAR <-
ddply(CARaux,c("SC","YEAR"),summarize,costcsolo = sum(CARaux[[costcarin]]))
COSTaux_AVMOTO <-
ddply(CARaux,c("SC","YEAR"),summarize,costmoto= sum(CARaux[[costmotoin]] ))
COSTaux <-
join(COSTaux_AVCAR,COSTaux_AVMOTO,by=c("SC","YEAR"))
COSTaux[ ,"PURP"] <- as.factor(purp)
COSTaux[ ,"PER"] <- as.factor(per)
costaux_result <- rbind(costaux_result,COSTaux)
}}
return(costaux_result)
}
Summarizing what it is supposed to do:
* In previous step of our analysis, we have constructed a dataframe,
CARaux. CARaux represents different cost categories (fuel prices, taxes,
maintenance) etc for cars and motorcycles. The costs are differentiated
according to the projection year ("YEAR") considered, the policy scenario
considered ("SC") and the car type considered.
* The function moncostcarmoto takes as only argument one of four
possible aggregate cost types: "MONCOST_EXCLTAX", "TAX",""FUELCOST" and
"MONCOST_INCLTAX"".
* The output of the function is a summary of the costs per YEAR and
SCENARIO, represented for all possible trip purposes (enumerated in PURPcount)
and period of the day (enumerated in PERcount). Note that these costs do not
depend on PURP and PER in the base scenario, but this is something I may want
to modify in the future (and which explains why I iterate over these
categories).
The function fails in the following line:
COSTaux_AVCAR <- ddply(CARaux,c("SC","YEAR"),summarize,costcsolo =
sum(CARaux[[costcarin]]))
With the following error message:
Error in (function(x, i, exact) if (is.matrix(i)) as.matrix(x)[[i]] else
.subset2(x, :
object 'costcarin' not found
When I debugged the function, I found the following:
Browse[1]> costcarin
[1] "CS_MONCOST_EXCLTAXCAR"
Browse[1]> summary(CARaux[[costcarin]])
Min. 1st Qu. Median Mean 3rd Qu. Max.
0.0000000 0.0000000 0.0001605 0.0166700 0.0048570 0.1633000
Browse[1]> COSTaux_AVCAR <-
ddply(CARaux,c("SC","YEAR"),summarize,costcsolo =
sum(CARaux[["CS_MONCOST_EXCLTAXCAR"]]))
Browse[1]> summary(COSTaux_AVCAR)
SC YEAR costcsolo
BAU:31 Min. :2000 Min. :6.202
1st Qu.:2008 1st Qu.:6.202
Median :2015 Median :6.202
Mean :2015 Mean :6.202
3rd Qu.:2022 3rd Qu.:6.202
Max. :2030 Max. :6.202
Browse[1]> COSTaux_AVCAR <-
ddply(CARaux,c("SC","YEAR"),summarize,costcsolo = sum(CARaux[[costcarin]]))
Error in (function(x, i, exact) if (is.matrix(i)) as.matrix(x)[[i]] else
.subset2(x, :
object 'costcarin' not found
Thus, providing CARaux[["CS_MONCOST_EXCLTAXCAR"]] as an argument to ddply()
works, but CARaux[[costcarin]] does not, although costcarin =
"CS_MONCOST_EXCLTAXCAR".
Best regards
Laurent
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